Robotics & Computer-Integrated Manufacturing, Vol. 4, No. 1/2, pp. 1-6, 1988 0736-5845/88 $3.00 + 0.00 Printed in Great Britain. Pergamon Press plc

• Paper

T H E P R E C E P T S AND S C I E N C E S O F M A N U F A C T U R I N G

M. E. MERCHANT

Advanced Manufacturing Research, Metcut Research Associates Inc., Cincinnati, Ohio, U.S.A.

There has been much concern over the years about the seeming lack of a sound science base for discrete-product manufacturing. However, the advent of computer technology and its application to manufacturing is now beginning to clarify the real nature of manufacturing and thus of its science base. In this paper, we propose precepts to illustrate the real nature of manufacturing and then explore the character of the sciences most relevant to that nature. The precepts which we propose reveal that manufacturing is a system in which the prime objective is the maximization of output relative to input, with the prime condition for satisfying that objective being the integration of all the elements of that system. The primary tool available to optimize manufacturing by integrating its various elements is the digital computer and its related technologies. Keeping these facts in mind, we explore the character of the sciences most pertinent to them. One significant fact concerning these sciences is that many of them are newer, developing sciences, rather than classical ones.

INTRODUCTION The organized discrete-product manufacturing industry of today can be said to have its origins in the Industrial Revolution of the late 1700s. However, as organized manufacturing slowly developed in vari- ous countries, little if any attention was paid to developing any fundamental understanding of the principles underlying its activities and processes. This was, no doubt, due largely to the fact that these activities and processes appeared to be simple, straightforward, "brute-force" methodologies, amenable to ordinary "common-sense" approaches. This view of manufacturing persisted well through the 1800s (and, unfortunately, even seems to persist in some quarters today). However, as the need to obtain predictable productivity, quality, timeliness and cost effectiveness in discrete-product manu- facturing operations became acute, the necessity of being able to engineer them became clearly evident. Nevertheless, the first approaches to providing a basis for such engineering were primarily empirical. In the field of the machining process, for example, witness F. W. Taylor's pioneering work at the be- ginning of this century on what he called "the art of cutting metals"--a strictly empirical approach. 1

The establishment of an empirical knowledge base for manufacturing operations did, however, lay the groundwork for the development of some funda- mental understanding of the principles underlying discrete-product manufacturing operations. As a

result, the late 1930s and the decade of the 1940s saw the growing evolution of scientific under- standing of discrete-product manufacturing tech- nology, with particular focus on machining technol- ogy. The decade of the 1950s, however, with the advent of the computer-related technology of numeri- cal control, saw the birth of flexible automation of manufacturing. This historic event began to slowly open our eyes to the tremendous potential for im- proving manufacturing capability inherent in compu- ter technology. Furthermore, computer-related technology initiated a major acceleration in the improvement of manufacturing productivity, quality, timeliness and cost effectiveness, which continues today. As a consequence of this initial impact of computer-related technology on manufacturing, the decade of the 1960s saw the development of the systems approach to manufacturing, revealing the possibility of applying the computer to the online automation, optimization and integration of the total system of manufacturing, a process now called sim- ply computer-integrated manufacturing (CIM). The decade of the 1970s served to evaluate and clarify the slowly evolving realization of the tremendous poten- tial of CIM for both economic and social benefit. This process laid the groundwork for the eventual understanding of the true nature of manufacturing. The decade of the 1980s thus proves itself one in which manufacturing, through CIM, is coming of age as a true science-based technology. Thus, the time is

Robotics & Computer-lntegrated Manufacturing • Volume 4, Number 1/2, 1988

now ripe to formulate precepts which state the new understanding of manufacturing and to explore the character of the sciences most pertinent to it.

MANUFACTURING PRECEPTS Let us start with a formulation of precepts. As

stated above, the decade of the 1960s saw the development of the systems approach to manu- facturing, making possible the eventual realization of computer-integrated manufacturing and the potential capability for overall online optimization and flexible automation of manufacturing. Through- out the 1970s, the systems approach, and the possi- bility of realizing CIM, came into ever sharper focus, and led to an increasing understanding of the true nature of manufacturing. Thus, at this stage, we propose the following three precepts as most perti- nent to understanding the true nature of manu- facturing. • Manufacturing is a system, the input to which is

the conceptual modeling of a product and the output of which is a successfully performing pro- duct; it should thus be operated as such a system.

• The prime objective which must be satisfied in the operation of that system is the maximization of output relative to input.

• The prime condition which must be satisfied if that objective is to be accomplished in full is the integration of all the elements of that system.

To illuminate the background from which these statements were derived, let us explore the concept of the systems approach to manufacturing and its relation to CIM.

MANUFACTURING AS A SYSTEM During the 1960s it became increasingly evident

that the digital computer was, basically, a systems

tool. As such, when it was first applied in manu- facturing operations, it brought us to see manu- facturing not just as a collection of various types of activities and processes but also as a sys tem--a system for creating discrete products useful to man. 2

That system, and the capacity of the computer to automate, optimize and integrate it, can be visual- ized and described in various ways. However, in the simplest terms, it can be visualized in the manner shown in Fig. 1. This particular representation of the computer-integrated manufacturing system charac- terizes the system of manufacturing itself as com- posed of five main elements, namely, product design, production planning, production control, production equipment and production processes. These elements, through the capability of the com- puter and computer technology, can eventually be integrated into a total closed-loop feedback system, as illustrated, able to operate as an optimized, flex- ibly automated whole.

There are no hard-and-fast rules concerning the characterization of the manufacturing sys- t e m - o t h e r s have subdivided it differently or used other names for elements similar to those shown. How the system is composed proves relatively immaterial. The important concept to recognize is that all the types of activities, equipment and pro- cesses represented by these terms are (and must be) an integral part of the manufacturing system being automated, optimized and integrated through com- puters. This is particularly true of the product design element of the system.

The reason for the preceding two statements can be recognized most readily by a simplified descrip- tion of the roles and interrelationships of each of the five elements shown in Fig. 1. Furthermore, such a description will clarify the true systems nature of manufacturing and the true nature of CIM.

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Fig. 1. Concept of the computer-integrated manufacturing system.

Precepts and sciences of manufacturing • M. E. MERCHANT

• Produc t design establishes the initial database for production of a proposed product. In a CIM system, this is accomplished through geometric modeling and computer-aided design, while con- sidering the product requirements and the pro- duct concepts of the design engineer. Ideally, however, the design process should be con- strained by the costs incurred in actual production and by the capabilities of existing production equipment and processes. This constraint must be provided through realization of the feedback loop labeled "cost and capabilities" in Fig. 1, providing online simulation of production during design ("virtual production").

• Product ion p lanning takes the database estab- lished by product design and enriches it with production data and information to formulate a plan (program) for the processing and production of the product. In a CIM system, this planning process should, ideally, be constrained by the production costs and by the capabilities of existing production equipment and processes needed to generate an optimized plan. Here again, the "cost and capabilities" loop of Fig. 1 must come into play.

• Product ion control of the actual activity of pro- ducing the product according to plan requires further enrichment of the database with perform- ance data and information on the production equipment and processes. In a CIM system, this involves activities like modeling, simulation and computer-aided scheduling of the production activity. This should include, ideally, online dynamic scheduling as well as control based on the real-time performance of the equipment and processes to assure continuous optimization of the production activity. This must be accomplished through realization of the feedback loop labeled "performance" in Fig. 1.

• Product ion equ ipmen t further enriches the data- base with equipment/process data and informa- tion, resident either in the operators or the equipment, in order to execute production pro- cesses. In a CIM system, this equipment consists of computer-controlled process machinery such as computer numerically controlled (CNC) machine tools, flexible manufacturing systems (FMS), computer-controlled robots, flexibly automated material-handling systems, computer-controlled assembly systems, flexibly automated inspection equipment etc.

• Product ion processes that create the finished pro- duct are carried out by the production equipment. In a CIM system, this is done under the guidance

of the data, information and knowledge resident in the equipment and the total integrated data- base supporting it. These processes consist of material removal, material forming or material consolidation (joining, sintering, assembly etc.), as well as automated quality assurance. From the processes come products which, ideally, are fully assembled, inspected and ready for use. These, then, are the elements which, when effi-

ciently integrated by the computer as a systems tool, reap the very large potential of CIM for economic and social benefit. However, as yet, total computer integration of discrete-product manufacturing, and of the consequent capability for full online optimiza- tion and overall flexible automation, has not been achieved anywhere--although integration of por- tions of the system, as for example flexible manu- facturing systems (FMS), is a full-blown reality in many companies.

There are, no doubt, many reasons why full CIM has not yet been achieved, but two predominate. The first lies in the fact that it is much easier to apply the computer to the optimization and automation of the "bits and pieces"--the elements and sub- elements--of the system of manufacturing than to apply it to the integration of the system as a whole. Thus, manufacturing industry tends to concentrate on the former rather than the latter--often to the extent that it even fails to consider how those optim- ized and automated bits and pieces are to be inte- grated.

Such an approach is indeed unfortunate, since the benefits of integration are prodigious, even when they encompass only a portion of the manufacturing system. Take, for example, the case of flexible manufacturing systems. Such systems, in their most advanced form, integrate the production control, production equipment and production process ele- ments of the manufacturing system of Fig. 1. By so doing, they constitute one of the highest degrees of integration yet achieved in that system. The benefits which even such partial integration achieve are quite impressive. Typical of these are the performance results shown in Table 1. The information presented the.re is a composite of the performance results being obtained with three advanced FMS--one West Ger- man, 3 one Japanese 4 and one American. 5 Table 1 compares the performance improvement obtained with the integrated systems against that of uninte- grated equipment. The advantages and benefits of integration are patently clear.

The second important reason why full CIM has not yet been achieved is that there are many tech- nological problems which must be solved before it

4

Table 1. Typical performance benefits experienced with modern flexible manufacturing systems (composite of results from one

German, one Japanese and one American system)

Robotics & Computer-Integrated Manufacturing • Volume 4, Number 1/2, 1988

QUANTIFIED BENEFITS (comparison between stand-alone Percentage equipment and integrated systems)

Reduction in lead time for product 40 Reduction in lead time for parts 53-75 Reduction in required number of machine tools 53-81 Reduction in required personnel 53-92 Reduction in labor costs per part 90 Reduction in required machining hours 65 Reduction in required floor space 42 Reduction in tooling costs 30 Reduction in total annual costs 24 Reduction in capital investment cost 10 Reduction of inventory of work in progress 90

NON-QUANTIFIED BENEFITS

Improved quality--higher accuracy and reproductibility; lower rework costs, scrap rates and quality-assurance costs

Closer adherence to production schedules--no order chasing

Improved working conditions--decreased accident risk and physical labor; increased challenge

increased flexibility--increased independence of batch size, types of parts and production quantities

can be completely realized. These include such prob- lems as integration of the system's total database, transfer of data and information throughout the system (and through the many transformations which it must thereby suffer) with total integrity, accomplishing the total online presentation to pro- duct designers of the cost-and-capability-require- ments consequences of each design decision which they propose to make and, most importantly, provid- ing system capability to deal with the nondeter- ministic aspects of manufacturing. These technologi- cal aspects lead us directly to the matter of the sciences of manufacturing, since the lack of a solu- tion to such difficulties results from their relation to those sciences.

THE SCIENCES OF MANUFACTURING What are the sciences most relevant to the

engineering of full state-of-the-art manufacturing and the future realization of full computer- integrated manufacturing? At this stage of the metamorphosis which manufacturing is undergoing due to CIM technology, the answer to that question is by no means clear. However, based on consideration of the precepts of manufacturing set forth in this paper and the concept of the manufacturing system embodied

in Fig. 1, Fig. 2 presents a preliminary listing of these sciences. Here the key (underlined) and typical sciences specific to each of the main elements of the CIM system are listed under the boxes cor- responding to those elements, with the key and typical sciences generic to the total system listed beneath.

Study of this listing, preliminary and tentative though it may be, immediately reveals one very significant obse rva t ion - -mos t of the key and system-generic sciences are the newer, developing sciences (some of which don ' t even yet have estab- lished names) rather than the classical ones. While this observation is consistent with the fact that a major metamorphosis in manufacturing technology is now under way, it indicates the fact that only now is manufacturing really beginning to develop a real science base of its own. Furthermore, it largely explains why significant difficulties are encountered in solving the technological problems of full CIM.

The relevance of each of the listed sciences in Fig. 2 to the given element or the overall system is reasonably self-evident and seems to require no further explanation, with one possible exception. That is the listing of artificial intelligence as the key generic science for the overall system of manu- facturing. The reason for such designation of this new and rapidly developing science is the absolutely critical role which it will play in future progress toward full computer- integrated manufacturing. That role has been well delineated by Hatvany. 6 In essence, he makes it clear that the system of manu- facturing (despite the best efforts of the engineer- ing profession to formulate fully deterministic methodologies) can never be a totally deterministic system. One reason for this is that the system neces- sarily interacts with nondeterministic elements in the real world. These include human beings, who are often neither logical nor error-free in their perform- ance, as well as the economic, social and political systems of the world, with all their vagaries. Furthermore, as pointed by Hatvany, the system of manufacturing, even within a given manufacturing company, involves such an overwhelming welter of variables, parameters , interactions, activities, flows of material and information etc., that "ei ther a detailed, explicit algorithm available for each solu- tion procedure, or all the facts, mathematical rela- tions, and models available in perfect arrangement and complete form for a deterministic (and unique) answer" can never be found. What is required then, as he indicates, for realization of the full potential of CIM is intelligent manufacturing systems "capable of solving, within certain limits, unprecedented, unfore-

Precepts and sciences of manufacturing • M. E. MERCHANT

THE SCIENCES OF MANUFACTURING

(KEY AND TYPICAL)

I PRODUCT DESIGN I GEOMETRICAL MODELING

N PRODUCTION PLANNING H PRODUCTION CONTROL ] ]PRODUCTION EQUIPMENT I~ PRODUCTION PROCESSES ]

PROCESS MODELING SIMULATION CONTROL THEORY MATERIALS SCIENCE

MATERIALS SCIENCE MECHANICS OPERATIONS RESEARCH PHYSICS MATERIALS SCIENCE STATISTICAL ANALYSIS CHEMISTRY SIMULATION PROBABILITY THEORY ETC. ETC. ETC.

KINEMATICS AND DYNAMICS METROLOGY FLUID MECHANICS THERMODYNAMICS ELECTRONICS TRIBOLOGY

ETC. ETC.

ARTIFICIAL INTELLIGENCE

CYBERNETICS

INFORMATION THEORY

COMPUTER SCIENCES

BEHAVIORAL SCIENCES

ETC.

Fig. 2.

seen problems on the basis even of incomplete and imprecise information". 6

The science of artificial intelligence must advance considerably to carry out the kinds of inference and intuition needed to overcome the problem of the nondeterministic nature of the overall manufactur- ing system, before its potential can be significantly realized. As A1 technology progresses, however, the manufacturing engineer must be quick to integrate that advancement into the computer-integrated manufacturing system in order to reap the exciting possibilities for further dramatic improvement of manufacturing productivity and quality which that technology promises.

THE FUTURE FACTORY As the precepts, sciences and science base

relevant to manufacturing are further developed and applied towards the realization of full computer-integrated manufacturing, what may we expect the factory of the future ultimately to be like? Although it remains impossible to give a definitive answer to this question, the potential of the technology is clear enough to permit a technological

vignette of the future factory. It might be somewhat as follows.

The process of designing a product will be carried out by iterative communication between the designer and the computer system. The designer will supply the design concepts and requirements and do the creative work. The computer system will supply standardized and other stored information and perform the design calculations. During this design process, as shown by the internal loop labeled "cost and capabilities" in Fig. 1, the computer system will constantly retrieve and evaluate information concerning manufacturing costs and capabilities of the equipment and processes required to produce the alternative features conceived by the designer. The computer system will then use that information to find a design which not only satisfies the product requirements but can also be produced at optimum cost and producibility.

Almost simultaneously, the production planning sector of the system will use this information to set up an optimized production plan by choosing the proper equipment and processes, sequence of operations, operating conditions etc. This numerical

Robotics & Computer-Integrated Manufacturing • Volume 4, Number 1/2, 1988

information will in turn be used to control the array of automatic machines and equipment. These machines and equipment will be capable of setting themselves up, automatically handling parts, selecting their own tooling and carrying out a variety of fabrication processes (removal, forming and consolidation) including product assembly. These machines will be self-optimizing because they will feed back information to the control system through the other internal loop labeled "performance" in Fig. 1. This system, as it constantly receives information on the actual performance of the equipment and processes, will compare these data with the "ideal" performance planned in the earlier phase. When it finds that performance departs from the planned optimum, it will override the original plan, perform dynamic scheduling and adjust operating conditions of the machines and processes as necessary to maintain optimum, minimum-cost performance.

Meanwhile, the machines and equipment will carry on self-diagnosis of their condition. Where an impending malfunction is detected, they will carry out appropriate corrective action, including

automatic replacement of defective modules in the system. Further, the machines also will carry out automatic real-time, in-process inspection of the product throughout each stage of its production so that any deviations from original specifications are automatically corrected and held within prescribed tolerances. Thus, the final assembled product will be completed with full inspection and in full conformity with the original design concepts and requirements.

REFERENCES 1. Taylor, F.W.: On the art of cutting metals. Trans.

ASME 28, 1907. 2. Merchant, M.E.: The future of manufacturing

technology. Frontiers in Manufacturing Technology. University of Michigan, Ann Arbor, 1-9, 1966.

3. Dronsek, M.: Technische und wirtschaftliche Probleme der Fertigung im Flugzeugbau. Proceedings Produktionstechnisches Kolloquium Berlin 1979. Carl Hanser, Munich, pp. 107-115, 1979.

4. Editorial Report Paying a visit to FMS plant. Metalworking Engng. Marketing 4, 1, 72-76, 1982.

5. Editorial Report $10 million FMS at Vought to build fuselage components. Production Eng. 63, 1, 39-40, 1984.

6. Hatvany, J.: The efficient use of deficient information. Ann. CIRP 32, 1,423-425, 1983.