Automation

Automation and productivity

Skills and education

Reactions to rapid technological change

The future impact of automation

BIBLIOGRAPHY

Periods of acceleration in the rate of technological change and the resulting improvements in the productivity of the labor force have generally coincided with re-examinations of the impact of technology upon the economy. During the 1950s and 1960s new techniques in production—referred to as automation—have rekindled interest in the relation between technological change and the characteristics of the labor force. The questions asked currently are no different from those asked during previous periods of rapid technological progress: Is the rapid increase in productivity predominantly due to the new techniques? Do the new techniques place different demands upon workers, affect working conditions drastically, require different skills and education, etc.? In this light, the impact of automation on the U.S. labor force may be an interesting case study of the adaptation of workers and the economy to change.

A description of automation. In popular literature any form of mechanization that improves the productivity of labor has been tagged automation. The introduction of the mechanical cotton picker, the big combine, the forklift, and many other machines that displace labor are all described as automation. The assembly line—first used in the automobile industry in 1913—has also been frequently cited as an example of automation.

Technical writers try to distinguish automation from other changes in production techniques by defining it as a special case of technological change and limiting the term to two kinds of production processes: those which utilize the automatic, or feedback, principle, in which a control mechanism triggers the operation after taking into account what has happened before; and those in which a number of discrete production steps are consolidated into a single process through the use of machinery—a technique also known as “Detroit automation.” Unlike the old-fashioned assemblyline technique, in which a part was moved from one manned work station to another, Detroit automation consists of moving parts from one machine to another, while automatic adjustments are made in the positioning of the tools that shape them. For instance, a precast aluminum block is inserted into one end of the machine, and a finished automobile engine is spewed out on the other. Some who have examined the organization of production processes in detail have classified as automation any production technique more advanced than that generally used in a particular industry at a particular time.

Confusion about the character of automation arises when technologies that have some, but not all, of the characteristics of the automatic process are called automation. For instance, machinedirectors, which activate and control the movement of machine tools and permit the shaping of complicated parts without human assistance, have often been cited as examples of automation. If such operations are to be classed as automation, is there any reason to exclude a screw-making machine from this category, just because it produces a less complicated shape?

The most careful attempt at defining automation was made by James R. Bright (1958), who gave up and instead divided technology in the production process into 17 levels of sophistication. The simplest technologies, according to Bright, involve the use of human labor only or human labor and hand tools; the more complicated do not require human interference in the selection and identification of the appropriate action; the most sophisticated correct performance during the operation or after the operation is completed, or they even anticipate required action and automatically make adjustments to provide for it (Bright 1958, pp. 41–46).

Most manufacturing operations—even those dubbed automation—consist of series of work stations, where mechanization has progressed to different levels of sophistication. For instance, a seamless-pipe mill described by Walker (1957) as an example of the automatic factory consisted of a series of analog, pneumatic, and mechanical devices ingeniously combined to speed the movement of steel through the pipe-making process. The new production line cut the requirements for workers from 20 men to 9 men and increased output four times.

The ultimate in automation is the closed-loop process, a method of operation that requires no human interference from the time the raw material is inserted into the machine to the time the finished product is stored or stacked at the end of the production line (for a lucid general discussion, see Macmillan 1956). In the middle 1960s few closed-loop processes were in operation. Even in the case of oil refineries, which have been heavily instrumented and automated since the 1950s, the rhythm of the process is under human control in most refineries. An attempt to schedule the refinery process by computer is still in the experimental stage.

Since the end of World War II considerable changes in techniques of production have taken place. Most plants acquired more efficient and faster machines; these changes could very well be classified as more intensive mechanization. Other plants substantially changed the method of organization of production; these changes may be put under the heading of automation. The innovations generally fell into five categories: assembly of parts, generally through automatic insertion of one part into another; material movement from one location to another, especially between machines; consolidation of control activities into one panel; mechanization of testing and inspection; and data processing through the use of computers.

Automation in record handling or data processing deserves special mention because it falls outside the conventional scope of automation. Since the 1950s electronic computers have replaced and supplemented the use of mechanical devices in manipulating Hollerith cards. This change in technology has resulted in a dramatic decline in computing cost per operation and has given business increasing flexibility in the manipulation of and access to various records. Computer operations are under the control of a program that utilizes the “feedback” principle: the sequence of operations is determined by the outcome of a previous operation.

The scope of automation. Without agreement on a definition of automation, it is difficult to delineate its scope. Nevertheless, it may be worthwhile to cite some statistics that indicate the extent of the acceptance of automatic techniques.

New ideas about the organization of production processes appear to have permeated most business organizations. A survey conducted by the McGraw-Hill Company in the middle 1960s (Universe… 1964) indicated that some automatic control and measurement devices and data-handling systems were used by 21,000 out of 32,000 manufacturing establishments employing over 100 persons. Nearly nine out of ten petroleum, instrument, computer, or control equipment plants reported using these devices. Two-thirds of equipment, machinery, and metal-working plants also were using control systems. Undoubtedly, the sophistication of the control systems must have varied from plant to plant, but their prevalence is surprisingly high.

Another survey conducted by McGraw-Hill queries businessmen annually about investment decisions. In 1963 this survey indicated that nearly $7 billion, or 18 per cent of the gross investment in manufacturing (and roughly one-third of investment in machinery), was being spent on equipment that respondents considered either automatic or advanced. Expenditures on automatic or advanced equipment accounted for 11 per cent of the gross investment of manufacturing in 1955 and, according to the survey, are still increasing; businessmen were planning to spend $8 billion on this type of equipment in 1964 and in succeeding years. The share of investment devoted to automationvaried considerably from industry to industry. In the forefront were communications, transportation, electrical machinery, steel, and automobile manufacturers (McGraw-Hill, Department of Economics 1963).

These two surveys give only an inkling of the scope of automation. The definition of control systems in the first survey is not rigorous, and the response to a question about what constitutes advanced types of machinery cannot help but be subjective. Probably some control systems used in the plants are no more complicated than circuit breakers. Similarly, an industry that became mechanized or automated in the early 1950s may be reporting automated plants as conventional, while a backward industry may be reporting more intensively mechanized plants as advanced. Two conclusions can be drawn from the results of these surveys: that automation, to some degree, is common to most manufacturing establishments in the United States and that its tempo is increasing rapidly.

The impression persists that automatic techniques have spread widely, but not very deeply, in the production process. There are a number of roadblocks to the adoption of automatic techniques. First, because of technological difficulties, it often requires vast resources and is risky. Thus, automation is generally—though not always—adopted by enterprises that are bigger than average. The management of smaller enterprises may not have the foresight or be willing to risk the resources to adapt modern technologies to their needs. Even more important, a small enterprise may not have long enough runs of a similar product to justify economically an automated process. Most automated processes are inflexible and are expensive to re-engineer and change, especially those which deal with noncontinuous processes. In certain areas, such as data processing, technology favors the larger firm. The cost per throughput of larger machines is much lower than that of smaller machines, and only large companies can afford large machines. Set-up costs—in this case, programming —are proportional to the complexity of the job, not its volume. The cost per data-processing unit of work is much less for large companies that have many repetitive jobs.

Second, automation—especially Detroit automation—requires that raw materials of a uniform quality be fed into the production line. Minor adjustments of a machine tool because of excessive hardness of steel cannot be made as easily by machines as they can be by humans. In most manufacturing industries, automation is feasible only when precise techniques of measurement are developed and the nomenclature and quality of parts are standardized.

To summarize, some features of automatic production are common to many U.S. manufacturing enterprises. The spread of these features is retarded by certain characteristics of automatic processes, namely, the risk associated with violent change, the inflexibility of the production methods, and the need for raw materials of uniform quality.

Automation and productivity

Side by side with efforts at automation, there occur improvements in mechanization, changes in organization, product improvements, and other changes that can materially affect the productivity of workers. Since automatic processes affect only a small part of the production effort of a given enterprise, one way to assess the effect of automation on productivity is to compare a period when the technology was not available with the present time. Another way of estimating the effect of automation is to examine the productivity trends of industries in which automatic methods of production have been widely adopted and to contrast them with other industries in which they have not.

Neither of these approaches will measure the effect of automation upon productivity with certainty. For instance, changes in output per production man-hour for manufacturing in the United States have fluctuated between a small improvement of 0.7 per cent per annum in the first decade of this century to a high of 4.6 per cent in the 1919–1929 period. During the great depression the rate of improvement in production per man-hour fell to 1.9 per cent. From 1948 to 1961 the average rate of increase in productivity per man-hour was 3.9 per cent (for these and other relevant figures, see U.S. Bureau of the Census 1965c, p. 236, Table No. 318). Preliminary estimates for the early 1960s, which are subject to considerable revision, place the increase in productivity at somewhere near 4.0 per cent. These figures tend to indicate that the impact of the new technologies developed since the end of the war is not unprecedented and that it may be likened to what the assembly line, the endless-chain drives, and individual drives (substituted for overhead drives for machinery) did for the manufacturing industry in the 1920s.

Also, without minimizing the impact of automation (defined in its narrower terms), it is important to realize that other mechanization techniques have not yet fully permeated the economy and that considerable improvements in productivity can occur, as they have in past decades, merely through further mechanization. A recent study by the U.S. Bureau of Labor Statistics (1964b) examined technological trends in 36 major American industries. It characterized the prospects of the U.S. economy as follows: 10 industries were likely to have their productivity affected by devices that principally partook of the mechanization process; 10 more, by automation processes; and the remaining 16, by a combination of the two. This survey indicates that there is still considerable room for improvement in productivity by mechanizing the handling of raw materials and finished products, the installation of more up-to-date and faster conventional equipment, and rationalization of existing production processes. It also points to the improvements in productivity that can come about from better scheduling of labor with the help of computers, the impact of electronic data processing on the front office, and the integration of the production process through a marriage of control and instrument devices with existing production techniques.

Another way of trying to estimate the impact of automation on productivity is to examine technological developments in industries where output per employee increased faster than the average in the recent past. For instance, productivity per employee in the 1950–1960 period grew faster than 4 per cent in the following industries: agriculture, coal mining, motor vehicle manufacturing, aircraft and aerospace industries, textiles, chemicals, petroleum manufacturing, radio and television (in mass communication), telephone, air transportation, and electric and gas and steam plants (Jaffe 1963). For many of these industries, better mechanization, improved organization, or the introduction of new products, rather than feedback or Detroit automation, must be credited with the productivity increase; in this category fall agriculture, coal mining, textiles, radio and television, and air transportation. Other industries, such as motor vehicle manufacturing, aircraft and aerospace, chemicals, and petroleum, probably owe their increases in productivity to the techniques that fall under the heading of automation. The telephone industry and utilities, which have high rates of productivity increase, probably take their place in between the other two categories; part of the improvement in productivity in these industries is due to an improvement in organization or the introduction of new products, such as bigger generators in electric utilities or message-switching equipment in telephones; and part is due to automation of the billing procedure, the use of computers for the dispatch of power, and the routing of telephone calls.

Employment and changes in productivity

The impact of changes in production techniques upon employment has varied considerably from industry to industry. In some industries, such as chemicals and aerospace, remarkable increases in productivity have been paralleled by employment increases. In others, such as automobile manufacturing or meat packing, the productivity increases—remarkable or just average—reduced the number of available jobs. In general, industries for which the demand increased faster than average had larger than average productivity increases, and the impact of productivity upon employment, with the exception of such industries as coal mining, did not result in as much dislocation as might have been the case (for more detailed analysis of these trends, see Jaffe 1963, p. 1601).

One can find numerous references to the impact of automation or productivity on the number of jobs available in the United States (see, for instance, Clague 1961; Killingsworth 1963). Most of these statements are made in a static context; it is assumed that a given level of production would be achieved with or without an increase in productivity. The difference between the labor force required in the current year to produce the current output and that which would have been required to produce the same output in any previous year with a lower productivity has often been described as the impact of automation on the job market. This shortsighted point of view assumes that investment, wages, and consumption are in no way affected by the productivity of the labor force. In actual fact, if productivity were to remain static, it is quite likely that the volume of investment goods purchased would decline, wages would stay constant or fall, and consumption would be at a different level.

Automation and rapid technological change should be looked upon in the broader context of how they affect income distribution, the demand for new investment, and so on, and hence how they affect the level at which the economy will stabilize. The consistently high unemployment rates experienced by the United States in the late 1950s and early 1960s raise doubts about the ability of our society to adapt easily to rapid technological change. These doubts are not new and were voiced often during the 1930s, although no systematic effort was made to analyze them in order to explain underemployment.

Under what circumstances can technological change cause underemployment? The most obvious circumstance would be technological unemployment, that is, when workers used in oldfashioned production processes are thrown out of jobs and cannot readjust to the requirements of the new production processes. There is little evidence that this is the case to any greater degree in the 1960s than previously. Most firms manage to retrain some of their employees for new production processes, getting along with fewer employees as they increase production. Workers who lose jobs are no less mobile than workers thrown out of jobs in previous periods of U.S. history (Gallaway 1963). Unemployment rates during the early 1960s, either by industry or by occupations, do not appear to have been affected by technological change (Gordon 1964). Although there is no consensus on the reasons for unemployment, a considerable number of social scientists have blamed inadequate demand [seeEmployment and unemployment].

Inadequate demand can be brought about by technological change if either investment or consumption is affected unfavorably. For instance, if a highly automated plant costs no more (and sometimes costs less) than a conventional plant, there can be overwhelming reasons for substituting a little capital for a lot of labor and thus depressing the level of investment. In those instances where a shift can be made from mechanical technologies to pneumatic processes in moving materials, or when mechanical or manual methods of metal cutting or inspection can be replaced by electronic technology, the cost advantages are overwhelmingly on the side of sophisticated technical processes. Hence the demand for investment per production unit may decline. Unless the industry scraps old producers’ goods at an accelerated rate and replaces them with new equipment more rapidly than heretofore (and there are a number of institutional reasons why this is not done, in addition to the very economic reason that variable costs of the old process should be larger than the variable and fixed costs of the new process), the total demand for investment in the economy may not rise fast enough to equal savings. Hence unemployment ensues.

The balance between savings and investment may not be restored because: prices may not be reduced to reflect the savings in the production process; and technological changes may affect the job content drastically, making job-evaluation standards increasingly subjective and resulting in wage setting based on historical standards rather than on competitive considerations. Even if—and especially if—bargaining for wages in technologically advanced industries results in a proportional or greater than proportional sharing of benefits with labor, we may move to a bipolar society that consists of a shrinking number of steadily employed workers with high incomes and a large mass of workers with less steady jobs and low incomes.

This is not the place to go into a detailed and rigorous discussion of the conditions that may result in rising employment. Suffice it to say here that technological change has, even before this most recent period, restricted the number of production jobs or, for that matter, the total number of jobs in manufacturing. For instance, the same number of workers was employed in manufacturing in the United States in 1919 as in 1939— about 10.5 million persons. Between 1948 and 1960 employment in that sector increased by only one million, that is, from 15.5 to 16.5 million (U.S. Bureau of the Census 1965b, p. 220, Table No. 305). During some periods in U.S. history, increases in productivity have been sufficient to satisfy the increased demand for manufactured goods. Whenever this occurs, jobs for a growing labor force must be found in other sectors of the economy.

Besides the over-all increases or decreases in employment that result from technological change, automation or new technological breakthroughs may affect the distribution of workers within an enterprise. In the past decades we have observed a decrease in the share of production workers in total employment and an increase in overhead staffs in most industries. This shift has given increasing concern to the unions, who do not control the loyalty of the front office, and it has also given considerable grounds to wits who have ascribed this tendency to “Parkinson’s law” (for which, see Parkinson 1957).

Two opposing tendencies have contributed to the growth of overhead staffs. First, the increased mechanization and automation in the factory have reduced the number of persons on the factory floor. Under these circumstances, the proportion of persons in the front office, per unit produced, would increase even if their number remained constant. Second, the mechanization of conventional front office jobs, which has tended to decrease the number of office people, has been offset by a more important secondary effect: it has encouraged the centralization of record-keeping functions. Clerical functions on the production floor have been pulled into the front office. Currently, the jobs of assistant foreman, record keeper, and parts clerk are becoming less common on the factory floor. Even the foreman’s job is being threatened, as scheduling, an important foreman’s prerogative, is done increasingly by computer (for these and related trends see, for instance, U.S. Bureau of Labor Statistics 1962 and the other case studies in the same series).

Skills and education

There is considerable divergence of opinion on the subject of skills required for jobs in industries that are being automated. A number of ex-cathedra statements have been made to the effect that skill requirements in industries with advanced technologies are much higher than those in technologically conventional industries. Succor for these views can be found in two areas. First, the average skill level of workers in the United States has increased in every decade since the beginning of the century. In other words, clerical occupations have grown faster than skilled ones, the skilled faster than the semiskilled, and semiskilled faster than unskilled occupations. In the 1950s the absolute number of unskilled workers in the U.S. labor force declined (U.S. Bureau of the Census 1965a, p. 228, Table No. 313). Second, there is some evidence that the growth of skilled occupations is more prevalent in industries with high increases in productivity per employee than in those with low productivity (unpublished research by the present writer).

Detailed studies of employment in plants with automatic processes have indicated that the new skills are not comparable with the old ones (see, for instance, Bright 1958, pp. 176–191). Generally these new skills can be acquired, and the jobs staffed, by workers with backgrounds equivalent to those of semiskilled operators. In the increasingly important maintenance area, where growing numbers of automated-factory workers are being employed, the weight of empirical evidence favors those scholars who believe that job requirements are at the semiskilled level.

The whole controversy about skills has a hollow ring. The majority of companies that have radically altered their production processes have had considerable success in retraining workers for the new jobs. This retraining was generally done under their own auspices and in a relatively short time. The crucial point is that the new jobs had very few of the characteristics of the old ones. In automated processes the production worker’s role consists of monitoring, information handling, and adjusting and maintaining of machinery. The principal challenge of the job is to coordinate the rhythm of the production process under his control with that of other members of the team responsible for other areas of the process. In most instances, the work is likely to require manual dexterity and judgment but is not very tiring physically. Workers have often complained of the strains brought about by these conditions.

These strains are different in degree, but not in kind, from those imposed by the continuous assembly line, inasmuch as each operation depends upon the successful completion of a previous operation. The decreased size of work teams and the increasing physical isolation of workers have often been mentioned as sources of dissatisfaction by workers transferred to automatic processes (Walker 1957; Mann & Hoffman 1960). New working conditions requiring less physical labor and more mental exertion are often not highly regarded by workers who prefer physical labor. On the other hand, the prestige of working in a new plant goes a long way to offset this resentment. Studies of the change-over to automatic processes have uncovered a great deal of apprehension before and during the change-over but have come to the conclusion that workers were equally or more satisfied with new working conditions after the end of the shakedown period (see Faunce et al. 1962 for a review of some relevant case studies).

Automatic processes have been resented by older workers, supervisors, and workers with a high status in the old process. Older workers have had psychological difficulties in adjusting themselves to new working conditions and have often been reluctant to give up old skills acquired over the years. Supervisors, in those cases where the number of subordinates has been reduced, have often strongly resented the introduction of the new equipment. They have been apprehensive about their own status. Furthermore, especially with front office automation, supervisors have lost some leeway in scheduling of work, deciding the format of the work, and so on. For instance, bills have to be rendered in a certain form in a mechanized office. Partial payments must also be arranged according to instructions of a central methods staff. Among white-collar workers another area of stress has been the introduction of shift work. Clerical workers are being increasingly used on second and third shifts to keep computers busy.

The effect of front office automation upon management has been studied least of all. A number of observers have claimed that some middlemanagement jobs have been eliminated by computers (Melitz 1961; Uris 1963). These jobs were generally of a routine supervisory nature but were often the road used for promotion to management. It is very likely that front office automation will affect the promotion route to management drastically, forcing large corporations to rely more on the promotion of professionals to management jobs. So far its effect has been very slight (Whisler 1965). Except for shifting some of the power fulcrums to areas that produce the increased volume of “facts,” management has not changed its practices substantially. One of the reasons for this slow adaptation has been the difficulty of retrieving facts for management decisions on an exception basis. The introduction by most computer manufacturers of products that make such retrieval possible will affect management practices drastically if some way is found to quantify essentially intuitive processes, which are the basis for most management decisions.

Upgrading the average level of skills among production workers is not central to automation or automatic processes and sometimes is not relevant to it. Time and again unskilled jobs are eliminated because of decisions that have nothing to do with automation, thus resulting in a rise in the average skill level. For instance, many unskilled jobs are being eliminated in the area of material handling, sometimes through the introduction of mechanical devices such as the forklift. In other cases, since automated processes are self-contained and reduce the waste and dirt attendant on the manufacturing operation, a number of inplant service jobs are being eliminated.

The above discussion indicates that the skills and rhythms of work necessary to automatic processes may be acquired, without any drastic upheaval, by workers currently employed in industry. This has serious implications for the educational requirements of the workers of tomorrow. In the less than full employment situation of the late 1950s and early 1960s, workers who had not completed high school had considerable difficulty in finding new job openings. This fact led to the unwarranted conclusion that the new jobs opening up in the economy required at least a high school education. Actually, an examination of labor mobility between jobs shows that a large number of workers move from the unskilled to the semiskilled category, and from the semiskilled to the skilled category, without the benefit of a high school diploma (see the tabulations on educational attainment of the U.S. population for 1960, in U.S. Bureau of the Census 1963). It is much more likely that under conditions of less than full employment employers choose to hire the best-educated applicants, without regard for the educational requirements for the job. An examination of the educational achievement of new entrants in the labor force in the decade of the 1950s bears out this conclusion (unpublished research by A. J. Jaffe and the present writer). Perhaps it would be better to justify the increased emphasis on education in a highly productive society on the basis of what that society can afford, rather than what it needs.

Reactions to rapid technological change

Rapid technological change, whether it be automation or not, does produce certain dislocations in the economy. We have seen that in the United States in the late 1950s and early 1960s it caused employment to grow more slowly than the number of people who were seeking jobs. Under these circumstances it is only natural for labor unions to be greatly concerned about the rate of introduction of innovations and the effect of these innovations on job opportunities for their members.

The ability of unions to negotiate the rate at which innovations may be introduced by management depends on the past scope of their contracts (for a review, see U.S. Bureau of Labor Statistics 1964a). With few exceptions, unions have been ineffective in retarding the adoption of labor-saving practices. In a number of industries, such as railroads, steel, and that of the longshoremen, where in an earlier period management lost the right to make work assignments, changes in working conditions were less easy to impose than in such industries as automobile manufacturing, meat packing, and textiles, where these rights were reserved by management. In the first category mechanization or automation was delayed; and when it was finally adopted, management had to pay a healthy price for union agreement. For instance, the West Coast longshoremen required management to deposit $29 million in trust, during the five and a half years following October 1960, to “buy out” rights to abrogate the most restrictive work rules. The money was to be used for annual wage guarantees, early retirement, and death benefits.

Some unions have negotiated separation payments for workers who may be laid off because of technological change. Others have tried to protect job security by negotiating job rights that would extend to the company as a whole, rather than to a given plant. Still others, faced with the prospect of shrinking numbers of jobs, have attempted to minimize layoffs by including provisions in union contracts to encourage retirement of workers at age 60 instead of age 65. Less effective union-negotiated contracts provide for a 90-day notification before a plant shutdown, and, in at least one instance, the union negotiated for the establishment of a fund to study the problems of laid-off workers (Kennedy 1962).

The increasing concern for facilitating the mobility of the labor force has prompted a government committee to recommend the vesting of pension funds to workers, thus allowing an employee to transfer his pension fund from one employer to another as he changes jobs. Other government efforts to promote mobility, such as job retraining, have had equally little impact on the labor force. Unless specific job openings exist, it is difficult to know what skills to impart to workers. The most promising way of attacking unemployment—the resettlement of workers from depressed areas— has not become a major tool of U.S. manpower policy, although it has been favorably received in such economically advanced countries as Sweden.

All economic changes are painful for the less skilled, older, and minority-group workers—especially Negroes; this is the conclusion of a survey of the impact of industrial dislocation upon workers from 1929 to 1962 (Haber et al. 1963). The ability of workers to adjust to the change depends upon the health of the economy at the time the disruption hits them. The implication of these findings is obvious: adjustments to rapid technological change can best be aided by action that stabilizes the economy at a high level of employment.

This conclusion runs counter to the belief of a number of social scientists who claim that minimum wages and union-set wage levels play a large part in causing unemployment. Members of this school of thought believe that the substitution of capital for labor has been accelerated by wage levels artificially pegged too high. Empirical studies of the reasons for mechanization indicate that other factors play an extremely important part in this process (see, for instance, Bright 1958, chapter 5; Erbe 1962; Clayton 1962; and contrast U.S. Office of Manpower 1965). In some instances plants have been automated because it was not feasible to integrate production on a larger scale in any other way. In other instances new technologies, which were not capital intensive (i.e., did not require more capital investment per worker), reduced the labor content of the process so much that a small decline in real wages would have had no influence in arresting the change-over. The influence of small changes in wage levels on employment needs better empirical justification before it is given much weight.

In any discussion of technological change or automation, it is essential to keep in mind that the techniques of production are only one of many factors that influence the size and composition of the labor force. Dictates of taste, as well as government policy, probably have far more important effects upon the labor force composition. For instance, the preference of U.S. consumers for slimmer television chassis encouraged manufacturers to substitute printed circuits for wiring and incidentally eliminated many skilled jobs. Also, between 1950 and 1960 professional, technical, and kindred workers in the labor force increased by 2.4 million. In 1960, the 7.2 million professionals accounted for 11.3 per cent of the labor force, as compared to 4.9 million in 1950, or 8.3 per cent of the labor force (U.S. Bureau of the Census 1965a, p. 228, Table No. 313). These figures could imply that modern production processes demand much more professional participation. Actually, some 60 per cent of this increase occurred in industries that are not considered to be marketoriented, such as education and welfare, and in defense-oriented industries, such as aerospace, the electronic industries, and communications.

Automation, which is a subset of technological change, has probably accelerated the increase in productivity of the working force. It has probably been less instrumental in changing the skill composition of workers than has popularly been believed. Many of the problems that have been associated with it are due to the inability of the economy to adjust to rapid technological change.

The future impact of automation

The spread of automation has coincided with a general acceleration of mechanization; together, the two processes have raised the productivity of the labor force. It is not easy to delimit the future impact of automation on the productivity of the economy. In areas where it can be applied, increases in the productivity of the labor force have often been spectacular. On the other hand, such increases in productivity are not unprecedented: similar increases occurred with the introduction of the assembly line, for example, in motorcar manufacturing. The future impact of automation is hence dependent on the number of areas to which it will spread.

The prospects of a utopia, or a Calvinist hell, where work will become redundant, are not likely to face Western society in the near future. Historically, periods of increases in productivity have been followed by periods of stagnation in the rate of increase in productivity. Especially in the United States, where more and more demand is concentrated in the service area, which has been untouched by automation, the prospects are not good for general idleness as a way of life.

Automation is also unlikely to revolutionize the structure of society. Less has been heard about the ascendance of the technocrats during the current upsurge in productivity than during the 1930s. The innovators and the participants in new production processes appear not to have gained much status or power. New occupations, which generally enjoy a high status, have lost standing faster than ever before. In 1958, when computers were first introduced on a large scale, programmers were required to have a graduate degree in mathematics. Six years later, many programmers had nothing more than a high school education, and their status in the business hierarchy is continuously declining.

The big challenge to the U.S. and other Western economies is to bring out cheaply, through automation or otherwise, new products that will tempt the consumer’s jaded taste. These new products, in turn, will stimulate investment. In European countries, where increases in productivity have been equally spectacular, no underemployment problem has occurred; the population’s unsated demand for consumer durables has kept economic activity at an extremely high level. In the United States this demand was satisfied in preceding decades, and policies to stimulate aggregate demand were not adopted early enough. Further rapid increases in productivity as a result of wider application of automation techniques can benefit our society if economic policies are all shaped so as to permit demand to increase in step with productivity.

Joseph N. Froomkin

[See alsoEmployment and unemployment; Industrial relations, article onthe sociology of work; Labor force; Leisure; Productivity; Technology; Workers.]

BIBLIOGRAPHY

Automation is often discussed under the more general headings “technological change” and “productivity.” Most of the relevant literature in English has originated in the United States, where several government bodies have published hearings, compilations of readings, and statistical surveys in the area, as well as a number of special studies and reports. The most comprehensive of these so far are U.S. Congress, Senate 1964 and U.S. Bureau of Labor Statistics 1962–1964. The U.S. President’s Commission on Automation 1966 was not available to the present writer.

Of the large body of academic research and writing, the most valuable works are those based on case studies of individual companies. Outstanding examples are Walker 1957; Bright 1958; Mann & Hoffman 1960. Michigan State University … 1958–1961 is a valuable bibliography. Symposia that accurately reflect academic thinking on automation are Automation 1962 and American Assembly 1962.

Most journalistic or business analyses limit themselves to case studies of a single process or industry. Many articles of this kind, of varied interest to social scientists, have been published in Automation; Computers and Automation; Control Engineering; Datamation; Fortune; and Productivity Measurement Review. Somewhat more comprehensive studies of particular industries have been undertaken by the U.S. Department of Labor, Bureau of Labor Statistics, whose current lists of publications should be regularly consulted. Many of these and other comparable studies are listed in U.S. Bureau of Labor Statistics 1963, which is also useful for its systematic listing of the most commonly discussed topics relating to automation.

Outside the United States, automation is most often treated in the broader context of technological change. In Europe, references to automation can be found in current lists of publications of the Organization for Economic Cooperation and Development. In the U.S.S.R., case studies of automated processes frequently appear in Ekonomicheskaia gazeta. Two recent Soviet books deserve some attention: Veinberg 1964, which deals with the labor force implications of automation; and Kats 1964, which is a more general study of productivity. Conference on Labor Productivity … 1964 is an illuminating exchange of views between Eastern and Western economists on concepts of productivity.

American Assembly 1962 Automation and Technical Change. Edited by John T. Dunlop. Englewood Cliffs, N.J.: Prentice-Hall.

Automation. Edited by Charles C. Killingsworth. 1962 American Academy of Political and Social Science, Annals Special Issue No. 340.

Automation: The Magazine of Automatic Production Operations. → Published since 1954.

Beaumont, Richard A.; and Helfgott, Roy B. 1964 Management, Automation and People. New York: Industrial Relations Counselors.

Bright, James R. 1958 Automation and Management. Boston: Harvard Univ., Graduate School of Business Administration, Division of Research.

Clague, Ewan 1961 Social and Economic Aspects of Automation. Monthly Labor Review 84, no. 9:957–960.

Clayton, Curtis T. 1962 Automatic Ships—Only Hope for the U.S. Merchant Marine? Control Engineering 9:73–76.

Computers and Automation. → Published since 1951.

Conference on Labor Productivity, Cadenabbia, Italy, 1961 1964 Labor Productivity. Edited by John T. Dunlop and Vasilii P. Diatchenko. New York: McGraw-Hill.

Control Engineering: Instrumentation and Automatic Control Systems. → Published since 1954.

Datamation: The Automatic Handling of Information. → Published since 1957.

Ekonomicheskaia gazeta. → Published since 1956.

Erbe, J. Raymond 1962 Electrical Equipment for Automation of the Blast Furnace. Blast Furnace and Steel Plant [1962] July:641–652.

Faunce, William A.; Hardin, Einar; and Jacobson, Eugene H. 1962 Automation and the Employee. American Academy of Political and Social Science, Annals 68:60–68.

Fortune. → Published since 1930.

Gallaway, L. E. 1963 Labor Mobility, Resource Allocation and Structural Unemployment. American Economic Review 53:694–716.

Gordon, R. A. 1964 Has Structural Unemployment Worsened? Industrial Relations 3:53–77.

Haber, William et al. 1963 The Impact of Technological Change: The American Experience. Kalamazoo, Mich.: Upjohn Institute for Employment Research.

Jaffe, A. J. 1963 [Prepared Statement.] Part 5, page 1601 in U.S. Congress, Senate, Committee on Labor and Public Welfare, Nation’s Manpower Revolution. Hearings before the Subcommittee on Employment and Manpower, 88th Congress, 1st Session. Washington: Government Printing Office.

Kats, A. I. 1964 Proizvoditel’nost’ truda v S.S.S.R. i glavnykh kapitalisticheskikh stranakh (Work Productivity in the Soviet Union and in the Main Capitalistic Countries). Moscow: Ekonomika.

Kennedy, Thomas 1962 Automation Funds and Displaced Workers. Boston: Harvard Univ., Graduate School of Business Administration, Division of Research.

Killingsworth, Charles C. 1963 [Testimony.] Part 5, pages 1475–1479 in U.S. Congress, Senate, Committee on Labor and Public Welfare, Nation’s Manpower Revolution. Hearings before the Subcommittee on Employment and Manpower, 88th Congress, 1st Session. Washington: Government Printing Office.

McGraw-Hill, Department of Economics, Annual Survey of Investment Decisions. → Published annually in mimeographed form for a limited distribution.

Macmillan, Robert H. 1956 Automation: Friend or Foe? Cambridge Univ. Press.

Mann, Floyd C.; and Hoffman, L. Richard 1960 Automation and the Worker: A Study of Social Change in Power Plants. New York: Holt.

Melitz, P. W. 1961 Impact of Electronic Data Processing on Managers. Advanced Management 26:4–6.

Michael, Donald N. 1965 The Next Generation: The Prospects Ahead for the Youth of Today and Tomorrow. New York: Random House.

Michigan State University of Agriculture and Applied Science, Labor and Industrial Relations Center 1958–1961 Economic and Social Implications of Automation. Vols. 1–2. East Lansing, Mich.: The Center. → Volume 1: A Bibliographic Review, by G. Cheek, 1958. Volume 2: An Annotated Bibliography: Literature, 1957–1960, by E. Hardin, W. B. Eddy, and S. E. Deutsch, 1961.

Parkinson, Cyril Northcote 1957 Parkinson’s Law, and Other Studies in Administration. Boston: Houghton Mifflin. → A satire on bureaucracy in which it is maintained, inter alia, that paperwork increases, rather than decreases, in proportion to the size of the administrative and clerical staff.

Productivity Measurement Review. → Published since 1955 in English and French.

Salter, W. E. G. 1960 Productivity and Technical Change. Cambridge Univ. Press.

Solow, Robert M. 1964 The Nature and Sources of Unemployment in the United States. Stockholm: Almqvist & Wiksell.

U.S. Bureau of Labor Statistics 1962 Impact of Technological Change and Automation in the Pulp and Paper Industry. Bulletin No. 1347. Washington: Government Printing Office.

U.S. Bureau of Labor Statistics 1962–1964 Implications of Automation and Other Technological Developments: A Selected Annotated Bibliography. Washington: Government Printing Office.

U.S. Bureau of Labor Statistics 1963 Implications of Automation and Other Technological Developments: A Selected Annotated Bibliography. Bulletin No. 1319–1. Washington: Government Printing Office.

U.S. Bureau of Labor Statistics 1964a Recent Collective Bargaining and Technological Change. Report No. 266. Washington: Government Printing Office.

U.S. Bureau of Labor Statistics 1964b Technological Trends in 36 Major American Industries. A study prepared for the President’s Committee on Labor-Management Policy. Washington: Government Printing Office.

U.S. Bureau of The Census 1963 U.S. Census of Population: 1960; Subject Reports: Occupation by Industry. Final Report PC(2)–7C. Washington: Government Printing Office.

U.S. Bureau of the Census 1965a Employed Persons, by Sex and Major Occupation Group: 1950 to 1965. Table No. 313. Page 228 in U.S. Bureau of the Census, Statistical Abstracts of the United States: 1965. Washington: The Bureau.

U.S. Bureau of the Census1965b Employees in Nonagricultural Establishments—Annual Averages, by Industry: 1940 to 1965. Table No. 305. Page 220 in U.S. Bureau of the Census, Statistical Abstracts of the United States: 1965. Washington: The Bureau.

U.S. Bureau of the Census 1965c Indexes of Real Product per Man-hour for the Private Economy 1947 to 1964. Table No. 318. Page 236 in U.S. Bureau of the Census, Statistical Abstracts of the United States: 1965. Washington: The Bureau.

U.S. Congress, Joint Committee on the Economic Report 1955 Automation and Technological Change. Report of the Sub-committee on Economic Stabilization. Washington: Government Printing Office.

U.S. Congress, Senate, Committee on Labor and Public Welfare 1963–1964 Nation’s Manpower Revolution. Hearings before the Sub-committee on Employment and Manpower, 10 vols. Washington: Government Printing Office.

U.S. Congress, Senate, Committee on Labor and Public welfare 1964 Selected Readings in Employment and Manpower. 6 vols. Compiled for the Subcommittee on Employment and Manpower. Washington: Government Printing Office.

U.S. National Resources Committee 1937 Technological Trends and National Policy, Including the Social Implications of New Inventions. Washington: Government Printing Office.

U.S. National Science Foundation, Office of Special studies 1959— Current Projects on Economic and Social Implications of Science and Technology. Washington: Government Printing office.

U.S. Office of Manpower, Automation and Training 1965 Management Decision to Automate. Washington: The Office. → Contains eight case studies adapted from a report with the same title by Richard S. Roberts, Jr.

Universe of Control System Design and Use in U.S. Manufacturing Plants. 1964 New York: McGraw-Hill. → A research report from Control Engineering.

Uris, Auren 1963 Middle Management and Technological Change: Abstract. Management Review 52, October: 55–58.

Veinberg, Adolf M. 1964 Vliianie tekhnicheskogo progressa na kharakter truda (The Influence of Technical Progress on the Character of Work). Moscow: Ekonomika.

Walker, Charles R. 1957 Toward the Automatic Factory: A Case Study of Men and Machines. New Haven: Yale Univ. Press.

Whisler, Thomas L. 1965 The Management and the Computer. Journal of Accountancy 60:27–32.

Automation

Automation is the art of making processes or machines self-acting or self-moving. Automation also means the technique of making a device, machine, process, or procedure more fully automatic. Automated machinery may range from simple sensing devices to autonomous robots and other sophisticated equipment. Automation of operations may encompass the automation of a single operation or the automation of an entire facility.

There are many different reasons to automate. Increased productivity is normally the major reason for many companies desiring a competitive advantage. Automation also offers low operational variability. Variability is directly related to quality and productivity. Other reasons to automate include the presence of a hazardous working environment and the high cost of human labor. Some businesses automate processes in order to reduce production time, increase manufacturing flexibility, reduce costs, eliminate human error, or make up for a labor shortage. Decisions associated with automation are usually concerned with some or all of these economic and social considerations.

For small business owners, weighing the pros and cons of automation can be a daunting task. The speed with which technology is advancing combined with a natural resistance to change makes it easy for a business owner to put off changes in the hope that by waiting he or she will be able to acquire more powerful automation equipment for less in the near future. But consultants contend that it is important not to put off implementation of new and more efficient technologies.

TYPES OF AUTOMATION

Although automation can play a major role in increasing productivity and reducing costs in service industries—as in the example of a retail store that installs bar code scanners in its checkout lanes—automation is most prevalent in manufacturing industries. In recent years, the manufacturing field has witnessed the development of major automation alternatives. Some of these types of automation include:

• Information technology (IT)
• Computer-aided manufacturing (CAM)
• Numerically controlled (NC) equipment
• Robots
• Flexible manufacturing systems (FMS)
• Computer integrated manufacturing (CIM)

Information technology (IT) encompasses a broad spectrum of computer technologies used to create, store, retrieve, and disseminate information. It is in the area of information technology where most of the more flexible and non-industry-specific advances are now being made.

Computer-aided manufacturing (CAM) refers to the use of computers in the different functions of production planning and control. CAM includes the use of numerically controlled machines, robots, and other automated systems in the manufacturing process. Computer-aided manufacturing also includes computer-aided process planning (CAPP), group technology (GT), production scheduling, and manufacturing flow analysis. Computer-aided process planning (CAPP) means the use of computers to generate process plans for the manufacture of different products. Group technology (GT) is a manufacturing philosophy that aims at grouping different products and creating different manufacturing cells for the manufacture of each group.

Numerically controlled (NC) machines are programmed versions of machine tools that execute operations in sequence on parts or products. Individual machines may have their own computers for that purpose; such tools are commonly referred to as computerized numerically controlled (CNC) machines. In other cases, many machines may share the same computer; these are called direct numerically controlled machines.

Robots are a type of automated equipment that may execute different tasks that are normally handled by a human operator. In manufacturing, robots are used to handle a wide range of tasks, including assembly, welding, painting, loading and unloading of heavy or hazardous materials, inspection and testing, and finishing operations.

Flexible manufacturing systems (FMS) are comprehensive systems that may include numerically controlled machine tools, robots, and automated material handling systems in the manufacture of similar products or components using different routings among the machines.

A computer-integrated manufacturing (CIM) system is one in which many manufacturing functions are linked through an integrated computer network. These manufacturing or manufacturing-related functions include production planning and control, shop floor control, quality control, computer-aided manufacturing, computer-aided design, purchasing, marketing, and other functions. The objective of a computer-integrated manufacturing system is to allow changes in product design, to reduce costs, and to optimize production requirements.

AUTOMATION AND THE SMALL BUSINESS OWNER

Understanding and making use of automation-oriented strategic alternatives is essential for manufacturing firms of all shapes and sizes. It is particularly important for smaller companies, which, due to their inherent advantage of being more flexible, are able to implement changes somewhat more quickly and thus gain competitive advantage more quickly. But experts note that whatever your company's size, automation of production processes is no longer sufficient in many industries.

The computer has made it possible to control manufacturing more precisely and to assemble more quickly. Today, with the aid of the computer, companies must move to the next logical step in automation—the automatic analysis of data into information that is useful to employees in implementing on-the-fly changes to production processes. Opportunities now lie primarily in the automation of information and not in automation of labor. The work that is being done now in advanced manufacturing is work to manage and control the process.

Small business owners face challenges in several distinct areas as they prepare their enterprises for the technology-oriented environment in which the vast majority of them will operate. Three primary issues are employee training, management philosophy, and financial issues.

Employee Training

Many business owners and managers operate under the assumption that acquisition of fancy automated production equipment or data processing systems will instantaneously bring about measurable improvements in company performance. But as countless consultants and industry experts have noted, even if these systems eliminate work previously done by employees, they ultimately function in accordance with the instructions and guidance of other employees. Therefore, if those latter workers receive inadequate training in system operation, the business will not realize the full benefits of new system put into place.

An essential key to automation success for small business owners is the establishment of a thorough education program for employees. It is also useful to set up a framework through which workers can provide input on the positive and negative aspects of new automation technology. The application of automation technology is growing but it is the human factor that remains essential in assuring the effective installation and use of these new technologies.

Management Philosophy

Many productive business automation systems, whether in the realm of manufacturing or data processing, call for a high degree of decision-making responsibility on the part of those who operate the systems. As both processes and equipment become more automatically controlled, the need for human management of these automated systems does not diminish. These new technologies—enabler tools, if you will—are changing the employee's job from one of physically laboring to one of monitoring and supervising an entire process.

But many organizations are reluctant to empower employees to this degree, either because of legitimate concerns about worker capabilities or a simple inability to relinquish power. In the former instance, training and/or workforce additions may be necessary; in the latter, management needs to recognize that such practices ultimately hinder the effectiveness of the company. Part of implementing automating systems includes the reworking of the entire process, including the roles and tasks held by all members of an organization.

Financial Issues

It is essential for small businesses to anticipate and plan for the various ways in which new automation systems can impact on bottom-line financial figures. Factors that need to be weighed include tax laws, long-term budgeting, and current financial health.

Depreciation tax laws for software and hardware are complex, which leads many consultants to recommend that business owners use appropriate accounting assistance in investigating their impact. Budgeting for automation costs can be complex as well, but as with tax matters, business owners are encouraged to educate themselves for this ongoing process. With the relatively short life of most new technology it is critical that annual reinvestments on technology become a part of all business plans. Deciding upon an affordable spending level requires a strategic look at the business to determine the role that new technologies play in the success of the business.

Once new automation systems are in operation, business owners and managers should closely monitor financial performance for clues about their impact on operations. As with any potentially cost saving or time saving process, the savings are only achieved if the process is correctly implemented. Proper monitoring of the new systems helps to identify problems with their implementation and make corrections so that the anticipated savings can be obtained.

The accelerating pace of automation in various areas of business can be dizzying. It will be a challenge for small businesses to keep pace—or stay ahead—of such changes. But the forward-thinking business owner will plan ahead, both strategically and financially, to ensure that the ever-more automated world of business does not leave him or her behind. The key is careful implementation of the proper tools, not rapid acceptance of all new technologies.

see also Robotics

BIBLIOGRAPHY

Bartholomew, Doug. "Automation Advance." Industry Week. 15 May 2000.

Burgess, Stephen. Managing Information Technology in Small Business. Idea Group Inc., 2002.

"Hot Trends in Automation." Instrumentation and Automation News. June 2005.

"Improving Productivity through Automation." Automation. May 2004.

Marks, Gene. Outfoxing the Small Business Owner. Adams Media, 2005.

Merker, Renate, and Wolfgang Schwartz. System Design Automation. Springer, 2001.

                                 Hillstrom, Northern Lights

                                  updated by Magee, ECDI

Automation

History

Types of automation

The role of computers in automation

Applications

In the home

The human impact of automation

Resources

Automation is the use of scientific and technological principles and control systems (such as computers) to control the manufacture of machines and processes that take over work normally performed by humans. The term is derived from the longer term automatization (to make something involuntary or automated) or from the phrase automatic operation. Delmar S. Harder, a plant manager for the General Motors Corporation, is credited with first having used the term in 1935. Automation is also considered to be more technically advanced that mechanization (which is the use of machinery to assist humans).

History

Ideas for ways of automating tasks have been in existence since the time of the ancient Greeks. Greek engineer and mathematician Hero (Heron) of Alexandria (c. 10–70), for example, is credited with having developed an automated system that would open a temple door when a priest lit a fire on the temple altar. The real impetus for the development of automation came, however, during the Industrial Revolution of the early eighteenth century. Many of the steam-powered devices built by James Watt, Richard Trevithick, Richard Arkwright, Thomas Savery, Thomas Newcomen, and their contemporaries were simple examples of machines capable of taking over the work of humans. One of the most elaborate examples of automated machinery developed during this period was the drawloom designed by French inventor and textile worker Basile Bouchon in 1725. The instructions for the operation of the Bouchon loom were recorded on sheets of paper in the form of holes. The needles that carried thread through the loom to make cloth were guided by the presence or absence of those holes. The manual process of weaving a pattern into a piece of cloth through the work of an individual was transformed by the Bouchon process into an operation that could be performed mindlessly by merely stepping on a pedal.

Types of automation

Automated machines can be subdivided into two large categories—open-loop and closed-loop machines, which can then be subdivided into even smaller categories. Open-loop machines are devices that, once started, go through a cycle and then stop. A common example is the automatic dishwashing machine. Once dishes are loaded into the machine and a button pushed, the machine goes through a predetermined cycle of operations: pre-rinse, wash, rinse, and dry, for example. A human operator may have choices as to which sequence the machine should follow—heavy wash, light wash, warm and cold, and so on—but each of these operations is alike in that the machine simply does the task and then stops. Many of the most familiar appliances in homes today operate on this basis. A microwave oven, a coffee maker, and a CD (compact disc) player are examples.

Larger, more complex industrial operations also use open-cycle operations. For example, in the production of a car, a single machine may be programmed to place a side panel in place on the car and then weld it in a dozen or more locations. Each of the steps involved in this process—from placing the door properly to each of the different welds—takes place according to instructions programmed into the machine.

Closed-loop machines

Closed-loop machines are devices capable of responding to new instructions at some point in their operation. The instructions may come from the operation being performed or from a human operator. The ability of a machine to change its operation based on new information is known as feedback. One example of a closed-loop operation is the machine used in the manufacture of paper. Paper is formed when a suspension of pulpy fibers in water is emptied onto a conveyer belt whose surface is a sieve. Water drains out of the suspension, leaving the pulp on the belt. As the pulp dries, paper is formed. The rate at which the pulpy suspension is added to the conveyer belt can be automatically controlled by a machine. A sensing device at the end of the conveyor belt is capable of measuring the thickness of the paper and reporting back to the pouring machine on the condition of the product. If the paper becomes too thick, the sensor can tell the pouring machine to slow the rate at which pulpy suspension is added to the belt. If the paper becomes too thin, the sensor can tell the machine to increase the rate at which the raw material is added to the conveyor belt.

Many types of closed-loop machines exist. Some contain sensors, but are unable to make necessary adjustments on their own. Instead, sensor readings are sent to human operators who monitor the machine’s operation and input any changes it may need to make in its functioning. Other closed-loop machines contain feedback mechanisms, like the papermaking machine described above. The results of the operation determine what changes, if any, the machine has to make.

Still other closed-loop machines have feedforward mechanisms. That is, the first step they perform is to examine the raw materials that come to them and then decide what operations to perform. Letter-sorting machines are of this type. The first step such a machine takes in sorting letters is to read the zip code on the address and then send the letter to the appropriate sub-system.

The role of computers in automation

Since the 1960s, the nature of automation has undergone dramatic changes as a result of the availability of computers. For many years, automated machines were limited by the amount of feedback data they could collect and interpret. Thus, their operation was limited to a relatively small number of alternatives. When an automated machine is placed under the control of a computer, however, that disadvantage disappears. The computer can analyze a vast number of sensory inputs from a system and decide which of many responses it should make.

Artificial intelligence

The availability of computers has also made possible a revolution in the most advanced of all forms of automation, operations that are designed to replicate human thought processes. An automated machine is said to be thinking if the term is used for only the simplest of mental processes: “Should I do A or B,” for example. The enormous capability of a computer, however, makes it possible for a machine to analyze many more options, compare options with each other, consider possible outcomes for various options, and perform basic reasoning and problem-solving steps not contained within the machine’s programmed memory. At this point, the automated machine is approaching the types of mental functions normally associated with human beings; it is therefore said to have artificial intelligence.

If not quite human-level intelligence, at least animal-level. For example, researchers at Genobyte, a company in Boulder, Colorado, developed Robokoneko, a robot kitten (ko=child, neko=cat, in Japanese). The cat’s brain, the Cellular Automata Machine (CAM) designed by Hugo de Garis of Advanced Telecommunications Research (Kyoto, Japan), contains nearly 40 million artificial neurons. The CAM-Brain’s neurons are real electronic devices, rather than the software simulations used in most artificial intelligence research. The neural net circuit modules, with a maximum of 1, 000 neurons each, are evolved at speeds of less than a second using a special computer chip, called a field programmable gate array (FPGA). Researchers hope the CAM-Brain will, for the first time, allow a robot to interact with stimuli in its environment to develop the sort of intelligence seen in animals, allowing the kitten to walk, turn, jump, arch its back, and sit up. In 2005, Japanese scientists from Osaka University created a human looking robot (an android) by the name of Repliee Q1Expo. With the look of an Asian woman, the robot contains sensors, actuators, and motors that allow human-like movements such as the fluttering of eyelids, the shaking of hands, and the breathing of lungs.

Applications

Manufacturing companies in virtually every industry are achieving rapid increases in productivity by taking advantage of automation technologies. When one thinks of automation in manufacturing, robots usually come to mind. The automotive industry was the early adopter of robotics, using these automated machines for material handling, processing operations, and assembly and inspection. Donald A. Vincent, executive vice president of Robotic Industries Association, predicts a greater use of robots for assembly, paint systems, final trim, and parts transfer will be seen in the near future.

Vincent expects other industries, such as the electronics industry, to heavily invest in robotics as well. Such industries have propelled the mass customization of electronic goods; the miniaturization of electronics goods and their internal components; and the re-standardization of the semiconductor industry, which, Vincent says, completely retooled itself in 2004.

Robotics will continue to expand into the food and beverage industry, where robots will perform such tasks as packaging, palletizing, and filling. The aerospace, appliance, and non-manufacturing markets are also potential markets for robotics.

One can break down automation in production into basically three categories: fixed automation, programmable automation, and flexible automation. The automotive industry primarily uses fixed automation. Also known as hard automation, this refers to an automated production facility in which the sequence of processing operations is fixed by the equipment layout. A good example of this would be an automated production line where a series of workstations are connected by a transfer system to move parts between the stations. What starts as a piece of sheet metal in the beginning of the process becomes a car at the end.

Programmable automation is a form of automation for producing products in batches. The products are made in batch quantities ranging from several dozen to several thousand units at a time. For each new batch, the production equipment must be reprogrammed and changed to accommodate the new product style.

Flexible automation is an extension of programmable automation. Here, the variety of products is sufficiently limited so that the changeover of the equipment can be done very quickly and automatically. The reprogramming of the equipment in flexible automation is done off-line; that is, the programming is accomplished at a computer terminal without using the production equipment itself.

Computer numerical control (CNC) is a form of programmable automation in which a machine is controlled by numbers (and other symbols) that have been coded into a computer. The program is actuated from the computer’s memory. The machine tool industry was the first to use numerical control to control the position of a cutting tool relative to the work part being machined. The CNC part program represents the set of machining instructions for the particular part, while the coded numbers in the sequenced program specify x-y-z coordinates in a Cartesian axis system, defining the various positions of the cutting tool in relation to the work part.

In the home

There has been much talk about the automated home where everything in the house is networked and controlled through digital technology via the computer. Experts predict that eventually a homeowner will be able to set the thermostat, start the oven, and program a DVD (digital video disc) player from the office or the home thanks to computers.

KEY TERMS

Closed-loop machine— A machine in which operation is controlled (by the machine or by a human operator) by the input or output of the machine.

Feedback mechanism— A process by which the behavior of a machine is affected by the functions performed by that machine.

Feedforward mechanism— A process by which the behavior of a machine is affected by the nature of the materials or data being fed into the machine.

Open-loop machine— A machine that performs some type of operation determined by a predetermined program and that cannot adjust its own operation as a result of changes in the output of that operation.

The human impact of automation

The impact of automation on individuals and societies has been profound. On one level, machines are now performing many otherwise unpleasant and/or time-consuming tasks: dishwashing being one of the obvious examples. The transformation of the communications industry is another example of how automation has enhanced the lives of people worldwide. Today, millions of telephone calls that once would have passed through human operators are now handled by automatic switching machines.

Other applications of automation in communications systems include local area networks (LAN) and communications satellites. A LAN operates like an automated telephone company, however, in that it can transmit not only voice, but also digital data between terminals in the system. Satellites, necessary for transmitting telephone or video signals throughout the world, depend on automated guidance systems to place and retain the satellites in predetermined orbits.

For banking, automatic tellers are ubiquitous. The medical industry employs robots to aid the doctor in analyzing and treating patients. Automatic reservation, navigation, and instrument landing systems, not to mention automatic pilots, have revolutionized the travel industry.

However, automation has also resulted in drastic dislocations in employment patterns. When one machine can do the work of ten workers, most or all of those people must be relocated or retrained to learn newer, higher, or completely different skills. Whether or not this is a wholly negative impact has been strongly debated. As population and consumer demand for the products of automation increases, new jobs have been created.

Positive impacts on employment patterns include computerized programs that help designers in many fields develop and test new concepts quickly, without ever building a physical prototype. Automated systems also make it much easier for people to carry out the work they do in non-traditional places. They may be able to stay home, for example, and do their jobs by communicating with other individuals and machines by means of highly automated communications systems.

Resources

BOOKS

Braungart, Michael, and William McDonough. Cradle to Cradle: Remaking the Way We Make Things. North Point Press, 2002.

Brooks, Rodney Allen. Flesh and Machines: How Robots Will Change Us. New York: Pantheon Books, 2002.

Craig, John J. Introduction to Robotics: Mechanics and Control. Upper Saddle River, NJ: Pearson Education, 2005.

Dunlop, John. Automation and Technological Change. Englewood Cliffs, NJ: Prentice-Hall, 1962.

Liu, John X., editor. Computer Vision and Robotics. New York: Nova Science, 2006.

McComb, Gordon. The Robot Builder’s Bonanza. New York: McGraw-Hill, 2006.

O’Brien, Robert, and the Editors of Life magazine. Machines. New York: Time Incorporated, 1964.

Selig, J. M. Geometric Fundamentals of Robotics. New York: Springer, 2005.

Trefil, James. Encyclopedia of Science and Technology. New York: Routledge, 2001.

PERIODICALS

“Time-Triggered Control Network For Industrial Automation.” Assembly Automation Heffernan Volume: 22, no. 1 (2002): 60-68.

David E. Newton

Automation

Automation is the use of scientific and technological principles in the manufacture of machines that take over work normally done by humans. This definition has been disputed by professional scientists and engineers, but in any case, the term is derived from the longer term automatization or from the phrase automatic operation. Delmar S. Harder, a plant manager for General Motors, is credited with first having used the term in 1935.

History

Ideas for ways of automating tasks have been in existence since the time of the ancient Greeks. The Greek inventor Hero (fl. about a.d. 50), for example, is credited with having developed an automated system that would open a temple door when a priest lit a fire on the temple altar. The real impetus for the development of automation came, however, during the Industrial Revolution of the early eighteenth century. Many of the steam-powered devices built by James Watt, Richard Trevithick, Richard Arkwright, Thomas Savery, Thomas Newcomen, and their contemporaries were simple examples of machines capable of taking over the work of humans. One of the most elaborate examples of automated machinery developed during this period was the drawloom designed by the French inventor Basile Bouchon in 1725. The instructions for the operation of the Bouchon loom were recorded on sheets of paper in the form of holes. The needles that carried thread through the loom to make cloth were guided by the presence or absence of those holes. The manual process of weaving a pattern into a piece of cloth through the work of an individual was transformed by the Bouchon process into an operation that could be performed mindlessly by merely stepping on a pedal.

Types of automation

Automated machines can be subdivided into two large categories—open-loop and closed-loop machines, which can then be subdivided into even smaller categories. Open-loop machines are devices that, once started, go through a cycle and then stop. A common example is the automatic dishwashing machine. Once dishes are loaded into the machine and a button pushed, the machine goes through a predetermined cycle of operations: pre-rinse, wash, rinse, and dry, for example. A human operator may have choices as to which sequence the machine should follow—heavy wash, light wash, warm and cold, and so on—but each of these operations is alike in that the machine simply does the task and then stops. Many of the most familiar appliances in homes today operate on this basis. A microwave oven, a coffee maker, and a CD player are examples.

Larger, more complex industrial operations also use open-cycle operations. For example, in the production of a car, a single machine may be programmed to place a side panel in place on the car and then weld it in a dozen or more locations. Each of the steps involved in this process—from placing the door properly to each of the different welds—takes place according to instructions programmed into the machine.

Closed-loop machines

Closed-loop machines are devices capable of responding to new instructions at some point in their operation. The instructions may come from the operation being performed itself or from a human operator. The ability of a machine to change its operation based on new information is known as feedback. One example of a closed-loop operation is the machine used in the manufacture of paper. Paper is formed when a suspension of pulpy fibers in water is emptied onto a conveyer belt whose surface is a sieve. Water drains out of the suspension, leaving the pulp on the belt. As the pulp dries, paper is formed. The rate at which the pulpy suspension is added to the conveyer belt can be automatically controlled by a machine. A sensing device at the end of the conveyor belt is capable of measuring the thickness of the paper and reporting back to the pouring machine on the condition of the product. If the paper becomes too thick, the sensor can tell the pouring machine to slow the rate at which pulpy suspension is added to the belt. If the paper becomes too thin, the sensor can tell the machine to increase the rate at which the raw material is added to the conveyor belt.

Many types of closed-loop machines exist, such as the papermaking machine. Some contain sensors, but are unable to make necessary adjustments on their own. Instead, sensor readings are sent to human operators who monitor the machine's operation and input any changes it may need to make in its functioning. Other closed-loop machines contain feedback mechanisms, like the papermaking machine described above. The results of the operation determine what changes, if any, the machine has to make

Still other closed-loop machines have feedforward mechanisms. That is, the first step they perform is to examine the raw materials that come to them and then decide what operations to perform. Letter-sorting machines are of this type. The first step such a machine takes in sorting letters is to read the zip code on the address and then send the letter to the appropriate sub-system.

The role of computers in automation

Since the 1960s, the nature of automation has undergone dramatic changes as a result of the availability of computers. For many years, automated machines were limited by the amount of feedback data they could collect and interpret. Thus, their operation was limited to a relatively small number of alternatives. When an automated machine is placed under the control of a computer, however, that disadvantage disappears. The computer can analyze a vast number of sensory inputs from a system and decide which of many responses it should make.

Artificial intelligence

The availability of computers has also made possible a revolution in the most advanced of all forms of automation, operations that are designed to replicate human thought processes. An automated machine is said to be "thinking" if the term is used for only the simplest of mental processes: "Should I do A or B," for example. The enormous capability of a computer, however, makes it possible for a machine to analyze many more options, compare options with each other, consider possible outcomes for various options, and perform basic reasoning and problem-solving steps not contained within the ma chine's programmed memory. At this point, the automated machine is approaching the types of mental functions normally associated with human beings, and is therefore said to have artificial intelligence .

If not quite human-level intelligence, at least animal-level. For example, researchers at Genobyte, a company in Boulder, CO, developed Robokoneko, a robot kitten (ko=child, neko=cat, in Japanese). The cat's brain , the Cellular Automata Machine (CAM) designed by Hugo de Garis of Advanced Telecommunications research (Kyoto, Japan), contains nearly 40 million artificial neurons. The CAM-Brain's neurons are real electronic devices, rather than the software simulations used in most artificial intelligence research. The neural net circuit modules, with a maximum of 1,000 neurons each, are evolved at speeds of less than a second using a special computer chip, called a field programmable gate array (FPGA). Researchers hope the CAM-Brain will, for the first time, allow a robot to interact with stimuli in its environment to develop the sort of intelligence seen in animals, and that it will allow the kitten to walk, turn, jump, arch its back, and sit up.

Applications

Manufacturing companies in virtually every industry are achieving rapid increases in productivity by taking advantage of automation technologies. When one thinks of automation in manufacturing, robots usually come to mind. The automotive industry was the early adopter of robotics , using these automated machines for material handling, processing operations, and assembly and inspection. Donald A. Vincent, executive vice president, Robotic Industries Association, predicts a greater use of robots for assembly, paint systems, final trim, and parts transfer will be seen in the near future.

Vincent expects other industries to heavily invest in robotics as well. Industries such as the electronics industry, with its need for mass customization of electronic goods, the miniaturization of electronics goods and their internal components, and the re-standardization of the semiconductor industry, which, he says, will completely retool itself by 2004. Robotics will continue to expand into the food and beverage industry where they will perform such tasks as packaging, palletizing, and filling; as well as the aerospace, appliance, and non-manufacturing markets.

One can break down automation in production into basically three categories: fixed automation, programmable automation, and flexible automation. The automotive industry primarily uses fixed automation. Also known as "hard automation," this refers to an automated production facility in which the sequence of processing operations is fixed by the equipment layout. A good example of this would be an automated production line where a series of workstations are connected by a transfer system to move parts between the stations. What starts as a piece of sheet metal in the beginning of the process, becomes a car at the end.

Programmable automation is a form of automation for producing products in batches. The products are made in batch quantities ranging from several dozen to several thousand units at a time. For each new batch, the production equipment must be reprogrammed and changed over to accommodate the new product style.

Flexible automation is an extension of programmable automation. Here, the variety of products is sufficiently limited so that the changeover of the equipment can be done very quickly and automatically. The reprogramming of the equipment in flexible automation is done off-line; that is, the programming is accomplished at a computer terminal without using the production equipment itself.

Computer numerical control (CNC) is a form of programmable automation in which a machine is controlled by numbers (and other symbols) that have been coded into a computer. The program is actuated from the computer's memory. The machine tool industry was the first to use numerical control to control the position of a cutting tool relative to the work part being machined. The CNC part program represents the set of machining instructions for the particular part, while the coded numbers in the sequenced program specifies x-y-z coordinates in a Cartesian axis system, defining the various positions of the cutting tool in relation to the work part.

In the home

There has been a lot of talk about the "automated home" where everything in the house is networked and controlled via the computer through digital technology. Experts predict that eventually a homeowner will be able to set the thermostat , start the oven, and program a DVD player from the office or the home study thanks to computers.

The human impact of automation

The impact of automation on individuals and societies has been profound. On one level, many otherwise unpleasant and/or time-consuming tasks are now being performed by machines: dishwashing being one of the obvious examples. The transformation of the communications industry is another example of how automation has enhanced the lives of people worldwide. Today, millions of telephone calls that once would have passed through human operators are now handled by automatic switching machines.

Other applications of automation in communications systems include local area networks (LAN) and communications satellites. A LAN operates like an automated telephone company, however, they can transmit not only voice, but also digital data between terminals in the system. Satellites, necessary for transmitting telephone or video signals throughout the world, depend on automated guidance systems to place and retain the satellites in predetermined orbits.

For banking, automatic tellers are ubiquitous. The medical industry employs robots to aid the doctor in analyzing and treating patients. Automatic reservation, navigation, and instrument landing systems, not to mention automatic pilots have revolutionized the travel industry.

However, automation has also resulted in drastic dislocations in employment patterns. When one machine can do the work of ten workers, most or all of those people must be relocated or retrained to learn newer and higher skills. Whether or not this is a wholly negative impact has been strongly debated. As population and consumer demand for the products of automation increases, new jobs have been created.

Positive impacts on employment patterns include computerized programs that help designers in many fields develop and test new concepts quickly, without ever building a physical prototype. Automated systems also make it much easier for people to carry out the work they do in non-traditional places. They may be able to stay home, for example, and do their jobs by communicating with other individuals and machines by means of highly automated communications systems.

Resources

books

"Automatic Control in Industry." In The Illustrated Science andInvention Encyclopedia. Vol. 2, pp. 192-96. Westport, CT:
H. S. Stuttman, Inc., Publishers, 1982.

Braungart, Michael and William McDonough. Cradle to Cradle: Remaking the Way We Make Things. North Point Press, 2002.

Decelle, Linda S. "Automation." In McGraw-Hill Encyclopedia of Science & Technology. 7th ed. Vol. 1, pp. 300-04. New York: McGraw-Hill Book Company, 1992.

Dunlop, John. Automation and Technological Change. Englewood Cliffs, NJ: Prentice-Hall, 1962.

O'Brien, Robert, and the Editors of Life magazine. Machines. New York: Time Incorporated, 1964.

Stringer, Howard. Opening Keynote Consumer ElectronicsShow in Las Vegas. 1999.

Trefil, James. Encyclopedia of Science and Technology. The Reference Works, Inc., 2001.

periodicals

"Technology Bulletin." Design News (February 15, 1999).

"Time-Triggered Control Network For Industrial Automation." Assembly Automation Author/s: Heffernan Volume: 22, no. 1 (2002): 60-68.

Vincent, Donald. "The North American Robotics Industry: Leading the Charge to a Productive 21st Century." RAS Robotics and Automation Society (Sept. 1999).

David E. Newton

KEY TERMS

Closed-loop machine

—A machine whose operation is controlled (by the machine or by a human operator) by the input or output of the machine.

Feedback mechanism

—A process by which the behavior of some machine is affected by the functions performed by that machine.

Feedforward mechanism

—A process by which the behavior of a machine is affected by the nature of the materials or data being fed into the machine.

Open-loop machine

—A machine that performs some type of operation determined by a predetermined program and that cannot adjust its own operation as a result of changes in the output of that operation.

AUTOMATION

Roots of Automation

"Automation" refers more to an ideal for industrial production than any one set of technologies or practices. The word was coined in 1946 by the Ford Motor Company's vice president, Dale S. Harder, who used it to describe the automatic or semiautomatic mechanical equipment then coming into use for the assembly of automobiles, the machining of automobile parts, and the stamping of sheet metal items such as fenders. While the popular press sometimes described these machines as "robots," implying a humanlike flexibility of application, the technologies Harder described were designed to perform a single task. Later, the term automation was often used to describe computer-controlled (usually programmable) machines that did include the potential to work on various different tasks. What Harder described was the culmination of the evolution of machine production underway for at least a century and was an extension of what had previously called "mechanization." This mechanization was largely a nineteenth-century phenomenon, involving the deskilling of work or the outright replacement of craft workers with machines. This movement was reaching its limits at Ford and elsewhere by 1950, just at the time when university and military researchers were investigating a new technology that combined traditional production machinery, especially machine tools, and the newly developed electronic computer. By the early 1950s, there would be a distinction in engineering circles between "Detroit auto-mation," relying on purely mechanical means, and computer automation.

The impetus for this development was the military's desire to produce aircraft parts at a high rate of speed and with high quality control. Also, aircraft and missiles were then being developed which used parts that were extremely difficult to make, and it was believed that a machine could do a better job than even the most skilled machinist. The U.S. Air Force, working closely with engineers at MIT and elsewhere, introduced the first "numerically controlled" (NC) machine tools in the late 1940s. These machine tools used technologies derived from the computer to control the motions of the machine in accordance with a predetermined program. An NC-equipped machine tool could be conveniently reprogrammed whenever necessary, avoiding the inflexibility that was seen as the major pitfall of Detroit automation. Although the early machines did not completely eliminate human labor, they approached the ideal. Later, engineers distinguished these NC tools from so-called computer numerical control (CNC), which received instructions from a general-purpose computer, often linked to the tool by wires. CNC is the standard technology used today, although its commercial success was slow in coming. While the aircraft industry, largely because of military support, widely adopted NC and CNC machine tools by the 1960s, few other industries followed suit. Few consumer products were as profitable as aircraft parts, making NC/CNC tools too expensive to justify.

Reaction in 1950s

There was sustained resistance to the adoption of NC and CNC tools for other reasons as well. Labor unions saw these technologies as a threat and forecasted massive technological unemployment. The public's reaction to the threat of automated factories was generally unfavorable, despite attempts by industrialists to provide reassurances. One of the most influential books of the era was John Diebold's Automation (1952), which explained the alleged advantages of the technology to the nonexpert. Countering Diebold, Kurt Vonnegut's 1952 novel Player Piano was a dystopic vision of what might happen if automation succeeded. So powerful was the idea of automation that the image of the "push button factory" of the near future became a cliché in movies and the popular press in the 1950s. In the auto industry and elsewhere, unions were able to reach a compromise with managers, allowing automated equipment to be installed in factories while preserving the wages and hours of most workers. The new factories qualitatively degraded the work experience for many highly skilled machinists and greatly reduced the need for them over the long term. Other types of automated equipment did eliminate some of the simplest assembly and materials-handling tasks, leading to some loss of jobs. However, automated production machinery eventually reduced costs and improved the quality of many items.

Other Forms of Automation

Outside the automobile and aircraft industries, automation of another sort also began to emerge in the early twentieth century. Engineers in the chemical industries, where it was common to employ complex, continuously operating processes, developed a form of automation beginning in the 1930s. There large-scale reactions such as the "cracking" of petroleum were monitored and controlled from centralized control rooms. Sensors and actuators, often in the form of pneumatically operated devices, connected the control room to the plant itself. Despite great differences between the chemical and metalworking industries, engineers by the 1940s also described this as part of the same general automation movement. Similarly, the growing size and complexity of electric power plants in the post-1945 period stimulated experiments with centralized control of the boilers, steam turbines, generators, and switch gear associated with the stations. Relying on pneumatic or electrical controls, the power industry thus also developed a distinctive variety of automation. With the advent of nuclear power in the 1950s, the design of this type of centralized automation reached a high state. The control room of a nuclear plant, filled with switches and dials, became an easily recognized symbol of the industry by the 1970s, when many such plants were in operation. There were also nonindustrial applications of automation. A prime example is the sorting of mail, which was done almost entirely by hand until the 1950s. The Post Office sponsored a far-reaching program to automate sorting processes, installing its first semiautomatic mail sorter in Baltimore in 1956. By 1965, the Post Office had installed its first optical character recognition device, which allowed a machine to sort some letters according to their city, state, and ZIP code.

Robotics

An example of the eventual convergence of Detroit-style automation and electronic computing is the development of the industrial robot. Long a feature of science fiction, the first robots were merely armlike mechanical devices, specially designed to handle one particular task. Their utility was limited to applications where high temperature or other factors made it impossible or dangerous for people to perform the same tasks. However, programmable robots appeared as early as 1954, when Universal Automation offered its first product, the Unimation robot. Although General Motors installed such a robot on a production line in 1962, sales of robots were quite limited until the 1970s. During the 1960s, many universities participated in the development of robots, and although many concepts carried over into the industrial robotics field, these did not immediately result in commercial adoption.

It was Japanese companies that moved rapidly into robot utilization in the 1970s. Kawasaki Corporation purchased the Unimation robot technology, and by 1990 forty companies in Japan were manufacturing industrial robots. The shock accompanying the rapid penetration of the domestic auto market by Japanese auto companies led American corporate leaders to adopt Japanese methods, speeding up the diffusion of industrial robotics in the United States.

The Microchip's Role in the Success of Automation

A key technical and economic factor in the widespread success of various forms of automation technologies in the 1980s and 1990s was the development of the microprocessor.

This tiny electronic device was invented in the United States in the late 1970s, intended for use in calculators and computers. However, its utility as an industrial process controller was almost immediately exploited. Less well known to the public than the microprocessor, a similar device called the microcontroller outsells the microprocessor today. The original applications for the microcontroller were as an electronic replacement for electromechanical devices called process controllers, such as the ones used in chemical plants. Process controllers incorporated logic circuits that were usually not programmable. They were used to regulate multistep industrial processes using a timed cycle. A familiar example of such a device is the electromechanical switch/timer used on home washing machines for many years. Process controllers using microprocessors or microcontrollers allowed convenient reprogramming, and eventually these were linked together to provide overall monitoring and control of plant activities from a remote central computer or control room.

The Electronics Industry as Automation's Prophet

At the beginning of the twenty-first century, American industries were still in the process of implementing automated production systems. The highest overall level of automation was in the manufacturing of microelectronic devices such as microprocessors and memory chips. The microelectronics industry builds devices on such a small scale and requires such high levels of cleanliness that some kind of mechanical handling is necessary if only to keep levels of contamination and breakage to a minimum. Microelectronics companies have pushed forward the development of specialized, computer-controlled equipment for manufacturing, inspecting, and handling chips.

The Institute of Radio Engineers held its first conference on the use of automated equipment in the manufacture of electronic parts in 1954. By 1960, the Western Electric Corporation had constructed a highly automated plant for assembling electrical components called resistors in North Carolina, which became a showpiece for automated production. Yet after the invention of the integrated circuit in 1958, the scale of chip production did not justify robotic handling of the chips, which were simply carried from machine to machine by hand or placed on conveyor belts. Chip manufacturers actually preferred hand labor to automated equipment until the diminishing size of the chips and the extreme level of attention paid to particulate contamination compelled them to isolate the manufacturing process inside closed "microenvironments" in the 1980s. By this time, the cost of robotic arms and similar products had dropped, and the reliability of the systems had risen from a few thousand average hours between failures to over 80,000 hours. While in the 1980s there was considerable talk about "lights out" chip fabrication facilities completely devoid of humans, that goal has proven less attractive over time, as corporations have continued to rely on some operators even in this highly automated industry.

BIBLIOGRAPHY

Adler, Paul S., and Bryan Borys. "Automation and Skill: Three Generations of Research on the NC Case." Politics and Society 17 (September 1989): 377–402.

Beniger, James R. The Control Revolution: Technological and Pronomic Origins of the Information Society. Cambridge, Mass.: Harvard University Press, 1986.

Bennett, Stuart. A History of Control Engineering, 1930–1955. Stevenage, U.K.: Institute of Electrical Engineers, 1993.

Noble, David F. Forces of Production: A Social History of Industrial Automation. New York: Knopf, 1984.

DavidMorton

See alsoAircraft Industry ; Assembly Line ; Automobile Industry ; Mass Production ; Robotics .