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Information Technology and Manufacturing: A Preliminary Report on Research Needs 5 Nonresearch Leverage Points The effective use of information technology in manufacturing depends on more than research per se. As discussed in this chapter, it depends on success in (1) motivating effective collaboration and technology transfer between industry and academia, (2) motivating individuals within manufacturing enterprises to implement information technology, and (3) ensuring, through education, training, and retraining, that the skill base in manufacturing shifts in concert with the new types of tools, techniques, and organizational structures made possible by information technology. In some instances, these essentially practical recommendations contain their own requirements for research, including social science research. TECHNOLOGY TRANSFER AND ACADEMIC-INDUSTRIAL INTERACTION No matter how good the ideas and advances developed by academic research groups, they are useless in a manufacturing context unless transferred to industry.1 For effective transfer, the relationship between academia and industry must be strengthened. This is not a new problem, but it is particularly acute in the area of manufacturing technology—and resolving it is more important now than ever before. Manufacturing is entering an exciting and explosive era. Although most of the important recent developments in design and manufacturing come from industry, manufacturing firms and their information technology system vendors need the knowledge base of the academic researchers, and those researchers need new and fundable challenges from the manufacturing environment. Therefore any steps that the National Science Foundation (NSF) might take to foster increased communication between academia and the manufacturing industry could have major long-term impact. The seeds of the technology transfer problem for manufacturing lie in the culture of universities. Research priorities and career imperatives for academic researchers must change to permit design and other manufacturing-related disciplines and activities to command respect and attract researchers.2 Another challenge for academia is the inherently interdisciplinary and multidisciplinary nature of manufacturing problems. Tenure often depends on evidence of the faculty member’s ability to be successful independently, whereas the range of technologies needed in manufacturing is beyond one person’s capabilities. Industry recognizes this by forming design teams and finding ways to reward all the participants. In academia, many forces are already motivating collaborative research, which is presenting new challenges (and opportunities) to administrators.3 Industry can help to
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Information Technology and Manufacturing: A Preliminary Report on Research Needs BOX 5.1 TEACHING FACTORIES A teaching factory is a collection of processing and control equipment (including tools, fixtures, machines, computers, and interfaces) organized so that a product or family of products can be produced. The factory would demonstrate a variety of activities and principles, including the specifics of processing, control, system and product design, associated management, and their interactions. The interactions of all of these activities are what differentiates the teaching factory from a conventional manufacturing laboratory. The study of manufacturing, like other engineering education activities, is a process that requires a strong laboratory experience, in which difficult concepts and poorly understood interactions can be demonstrated and learning can be reinforced. Research to develop innovative and economic means of creating teaching factories is necessary to prepare the manufacturing specialists for the factory of the future as well as to develop deep research understanding of specific processes. One variation on the concept of a teaching factory—the extension of the manufacturing enterprise into academic institutions—would be made possible by a broader, enhanced national information infrastructure such as that envisioned as enabling greater inter-enterprise integration and the virtual enterprise concept (see “Enterprise and Inter-enterprise Integration” in Chapter 4). Efforts to develop remote access should specifically address problems related to electronic connectivity, the transfer of technically complex principles, and shared access to expensive manufacturing equipment and critical information or knowledge. articulate to academia the basic intellectual issues of manufacturing, not only to help guide research but also to make those issues recognizable to people in traditional disciplines. Industry can also impress upon manufacturing faculty (many of whom have limited expertise in information technology) the need for industry involvement and the increasing importance of information technology to manufacturing. A variety of mechanisms could foster better academic-industrial interaction relating to manufacturing. A fellowship or sabbatical program, for example, could place academics in factories and factory people in academia for periods of about a year. (Shorter periods have proven less satisfactory; periods of about a year allow the researcher to better understand the special qualities and inherent problems of the manufacturing environment, to explore its different operations and dimensions (e.g., by rotating through different units), and to contribute substantially to addressing a problem.4) Historically, this concept has been thwarted by tenure pressures that militate against long absences from the university by researchers during the period in which they are forming their research programs. To succeed now, mechanisms are needed to ensure that researchers are not penalized for this kind of investment of time and effort. Testbeds are needed to help researchers see if their ideas are valid. It is not possible to set aside portions of real factories for such experiments. Yet testbeds must be realistic enough to enable researchers not only to find out if their ideas work but also to learn the constraints of real manufacturing environments and discover opportunities and research problems (Box 5.1). The Metal Oxide Semiconductor Implementation Service (MOSIS) provides such a testbed for designers of chips; the concept of a “mechanical MOSIS” service has been proposed in the past, and it continues to be attractive as a vehicle for rapid prototyping. (A key to such a service would be to make sure that manufacturing aspects are sufficiently visible to designers and other academic users.) Any program that provides major funding for academic research in manufacturing will likely increase academia’s interest in manufacturing; of course, that is an objective of the
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Information Technology and Manufacturing: A Preliminary Report on Research Needs FCCSET Advanced Manufacturing Technology Initiative. Another mechanism for boosting the prestige of manufacturing would be an NSF postdoctoral program for manufacturing fellows. Matching grants would leverage limited federal funds with industrial resources, using industrial support to signal areas of particular interest to industry. Similarly, funding could be directed to appropriate university-industry partnerships that are launched with explicit mechanisms for technology transfer. IMPLEMENTATION ISSUES Manufacturing managers, including members of this committee, express concern that they already have more technology than they can use well. They note that many human obstacles must be overcome before today’s, let alone tomorrow’s, information technology can be used to maximum effect in manufacturing. Attention to the managerial and cultural preconditions for effective use of information technology is an important precursor and correlate to the development and application of advanced manufacturing systems.5 Manufacturing managers know that realizing the promise of information technologies to help improve factory performance is not easy. In particular, there are many opportunities for a mismatch. Expectations may differ between technology supplier and user—indeed, users may have had too little input into the design of new systems. It may take so long to achieve a solution that it may come only after the problem has largely disappeared or been fixed by other means. A new system may not make use of embedded systems that are too expensive to discard. The skills required may differ significantly from those of the existing work force (see “Education, Training, and Retraining” below). Risk aversion is a fundamental problem, arising from the fact that many of the new information technologies are untested in actual manufacturing lines. New systems are not used because they are untested, and they cannot be tested because no one wants to be the guinea pig. Another contributor to risk aversion is time pressure. Bringing in new systems consumes valuable production time, which may not easily be recovered. It is easier (and therefore common) for a production engineer to work with the old, perhaps less efficient, system than to lose production time to install and test a new system. The scope of change inherent in manufacturing systems can confound financial analyses. The financial impact may appear too large to justify for a single factory, even if the new technology appears worthwhile for the enterprise overall. In addition, the benefits of investing in a new system may be hard to quantify, especially if they relate to quality. Research is needed to support more appropriate financial and business justifications and to better define the cost of quality, the cost of insufficient quality, and the trade-offs among quality, time, and money (Box 5.2). One mechanism that could contribute to better planning for the time and real cost involved in implementing new systems (although not necessarily changing those quantities) would be an extension of the “beta test” concept into manufacturing environments.6 Beta tests can assess the fidelity of a product to its design specification, augmenting a real production environment with special instrumentation to assess errors or relay feedback to developers. Although pilot plants have been used for years as laboratories to assess production concepts, research is needed to explore how actual production facilities, operating at normal volumes, can be used directly for achieving continuous improvements or innovation. Legitimizing beta test periods would disclose the need for and real costs of the practice to manufacturing management at the proposal stage. The beta test concept could also provide a basis for links to research facilities, with the benefit of enhancing the understanding of what does and does not work in a given type of system or application. Research could help to
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Information Technology and Manufacturing: A Preliminary Report on Research Needs BOX 5.2 INFORMATION TECHNOLOGY DEPLOYMENT AND JUSTIFICATION Information technology was originally used in fairly narrow ways: accounting and clerical functions were automated, personnel records were placed in rudimentary databases, and controllers were developed for individual machines. For these applications the financial justification could be made on fairly traditional grounds, such as cost reduction (usually by machines and systems replacing people) or the improved quality associated with better machine control. As information technology has matured, as the cost mix (hardware, software, and labor) associated with it has changed, and as its applications have broadened, it has become more difficult to comprehend the impact that an information system will have and, consequently, to judge whether or not an investment in the technology will pay off.* The benefits of better understanding would extend to organizations of all sizes. It has proven particularly difficult to justify the costs of providing the infrastructure required to maintain and enhance information technology. There is no straightforward relationship between information services and the yield or quality of the finished product. Consequently, justifications for the infrastructure have to be made on more speculative, qualitative rather than quantitative, arguments. Better metrics for measuring the value of support systems are needed. These could also contribute to better cost management. Recent efforts to develop activity-based costing may be helpful to manufacturers in this context; additional research into applications of this approach in the manufacturing context may be useful As companies attempt to become more agile, reduce the time required to respond to market needs, and begin to explore the merits of “virtual enterprises,” they will need tools to help determine what should be measured. How, for example, should one translate the metrics of agility into realistic financial terms? How can one measure the costs at organizational boundaries and judge whether information technology will improve an operation enough to justify the costs of the system? The speed with which enterprise-wide systems will be deployed will, to a large degree, depend on how well companies are able to understand these issues. That understanding would benefit from research into “exchange rates” between agility and financial metrics as well as case studies of enterprises that have implemented complex information systems. * See forthcoming report: Computer Science and Telecommunications Board, National Research Council. 1993. Information Technology in the Service Society: A 21st Century Lever. National Academy Press, Washington, D.C. (in press). Also see Kaplan, Robert S. 1989. “Management Accounting for Advanced Technological Environments,” Science 245(4920):819–823. See also Kaplan, Robert S. 1986. “Must CIM Be Justified by Faith Alone?” Harvard Business Review 64(2):87–95. define the tools, techniques, and practices appropriate to beta testing in manufacturing contexts. EDUCATION, TRAINING, AND RETRAINING The obstacles described above in “Implementation Issues” are among the factors motivating the current concern of management theorists and analysts with the “management of change.” According to this perspective, successful enterprises of the future must change rapidly and frequently. Information, types of media, tools, processes, organizational structures, and so on will change, rendering knowledge and skills obsolete several times in
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Information Technology and Manufacturing: A Preliminary Report on Research Needs an individual’s career. Continuing education will have to be genuine and managed by individuals and institutions; education and training will have to inculcate adaptability and the expectation of change. These outcomes will be difficult to achieve because change provokes anxiety and stress. Research into techniques and tools to help enterprises and individuals understand and manage the process of change could facilitate the kinds of evolution of organizations and skills that many analysts anticipate. Expectations for frequent change and greater employee autonomy imply that the manufacturing enterprise of the future will depend more on the knowledge and skill sets of each employee. Several needs follow from this assumption: Education of senior managers, to help them make informed decisions about using new, expensive, and perhaps risky information technology; Education and training of middle managers, to help them reduce barriers to trying new technology that may seem only to consume time and resources or imperil their own jobs; Education of designers, engineers, manufacturing engineers, and toolmakers to give them an increased technical base so that they can better understand and use computer technology and design relevant software; Training of factory workers, who are expected to use this new technology to improve their performance and that of their facility; and Retraining of factory workers whose skills are not compatible with the information technology paradigm and who may have to seek alternative jobs. These needs can be summarized as three major requirements: Education of managers and supervisors to improve their general knowledge, to help them make better decisions; Education of designers, engineers, and manufacturing engineers to improve the design and development of information technology for manufacturing; and Training and retraining to improve factory workers’ ability to perform well in the production environment. Education issues are ubiquitous and topical; in addition, renewal and currency of employee process- and product-specific knowledge have long been a major problem for all manufacturing enterprises. Needed are better means of delivery and better understanding of human issues such as motivation (or fear based on inadequate technical education and the resulting wish to fall back on intuition and experience). Possible approaches to addressing the need for ongoing education include conferences and seminars for senior and middle managers; publication of educational materials; close collaboration among academicians, designers, engineers, and factory workers; and television and audio tape courses. Computer aids—computer-aided instruction—also may be brought to bear on the education and training requirements of an enterprise, providing efficient and customized education that allows a person to learn quickly and selectively. Programs of the future will have to move away from the lecture format and the fixed-sequence documentaries of today. They will have to be interactive and user-friendly to meet the MTV generation’s different expectations and attention spans for educational programming. Multimedia and virtual reality technology may hold promise for providing a flexible, socially acceptable, and nonthreatening interface for educational and skill-building programs; a national information infrastructure and future home and factory systems offer the means to distribute and use such programs. The
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Information Technology and Manufacturing: A Preliminary Report on Research Needs delivery systems will have to provide overview data as well as fundamental knowledge. NSF support of these technologies, perhaps through Education and Human Resources Directorate programs, could increase the skill base of the manufacturing sector, as well as of other sectors of society in general. The challenge of providing new educational technology can easily be underestimated. But it is a complex, multifaceted task. The target population spans a wide range of educational backgrounds, capabilities, and needs. Some individuals will want a high-level overview of the material, and others will want in-depth courses with detailed practice sessions. The work force today spans multiple languages in the domestic United States, and specific topics will also be made available to people in other countries and from different cultures. Thus the content of educational programs and information is critical, the quality of presentation must meet modern expectations, and usability must be tunable to purpose. NOTES 1. For example, new design methods developed in academia are especially hard to transfer to industry because industry normally gets such methods from computer-aided design (CAD) vendors. So the transfer takes two steps (from academia to CAD vendors, and from CAD vendors to their customers). However, CAD companies are typically small and very limited in their resources, so they cannot afford to take risks on new research ideas. Instead, they take their clues from their major customers. Consequently, a technology transfer strategy for design methods must enlist the support of potential users as well as equip the CAD vendors. 2. Industry should be more open and accepting of new ideas, and it should be more willing to expose both data and problems to academic researchers. Academics should recognize the importance intellectually as well as nationally of, and pay more attention to, the problems being encountered by industry, especially those regarding scale and complexity. Unfortunately, manufacturing is dismissed in many academic circles as a shrinking portion of the GNP symbolized by unexciting smokestack factories. For perspective on the larger problem of nurturing academic work related to system development, see forthcoming report: Computer Science and Telecommunications Board, National Research Council. 1993. Academic Careers for Experimental Computer Scientists and Engineers. National Academy Press, Washington, D.C. (in press). 3. See Computer Science and Telecommunications Board, National Research Council. 1993. National Collaborators: Applying Information Technology for Scientific Research. National Academy Press, Washington, D.C. 4. Industry could reciprocate by funding further education for its workers. One example of a useful exchange is the MIT Leaders for Manufacturing program, which links engineering and business school faculty with industrial representatives and involves master theses developed by students “on location” in manufacturing environments. 5. See forthcoming report: Computer Science and Telecommunications Board, National Research Council. 1993. Information Technology in the Service Society: A 21st Century Lever. National Academy Press, Washington, D.C. 6. Software developers draw on objective third-party users in beta tests of new products or versions to verify functional capabilities and ensure lack of defects. Explicitly applying the concept and practice of a beta testing period into production launch activities would provide for significant first trials of the custom software typical of manufacturing information systems.
Representative terms from entire chapter: