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I response to international competitive pressures, Western manufacturing organizations have focused a great deal of attention on new techniques and technologies for improving manufacturing activities.1 Two dominant manufacturing strategies have emerged. One is the just-in-time (JIT) manufacturing system, originally developed by Toyota, which includes a range of techniques aimed at simplification and waste reduction within the manufacturing system. The other is the computer-integrated manufacturing (CIM) approach, which uses computer-based information systems to link islands of automation, islands of information, and advanced flexible production technologies throughout the manufacturing organizational system.
Although these two strategies have been developed and adopted more or less independently and their compatibility is not well understood, managers generally assume that both approaches are advantageous for improving the productivity and competitiveness of manufacturing operations. For example, both systems are supposed to increase productivity by improving organizational integration, product quality, and manufacturing flexibility and responsiveness. As such, future factories can be expected to combine some of the characteristics of both the JIT and CIM approaches.
Empirically, however, what is known about the success of the two manufacturing approaches within industry is rather limited. JIT has been shown by Toyota and other Japanese firms to be an effective strategy for improving productivity when implemented appropriately.2 CIM is largely unproven; few well-documented case studies of the system are available. Most of the literature describing CIM considers the system from a purely hypothetical perspective and tends to consist mainly of predictions about its success based on the theoretical potential of CIM technology.3
Despite the limited amount of empirical evidence, there are some indications that the JIT approach is more likely to increase productivity than the CIM system. Two separate international surveys that attempted to examine the determinants of manufacturing productivity drew similar conclusions about the relative contribution the two strategies might make toward firm productivity.4 Both found, for instance, that JIT-type approaches aimed at reducing manufacturing throughput time and simplifying the production system were systematically related to higher productivity levels, whereas investments in advanced technologies showed no such direct relationship. Another study, which examined Italian manufacturing firms, found that JIT implementation was strongly correlated with an overall factory performance indicator as well as a wide range of individual manufacturing performance indicators (fifteen out of the seventeen indicators examined).
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1. An earlier version of this paper was presented at the Eighth International Conference on CAD/CAM Robotics and Factories of the Future. See: “Future Factories and Today’s Organizations,” Proceedings of the Eighth International Conference on CAD/CAM Robotics and Factories of the Future, Metz, France, 17–19 August 1992 (Amsterdam: Elsevier, 1992).
2. Y. Monden, Toyota Production System (Norcross, Georgia: Industrial Engineering and Management Press, Institute of Industrial Engineers, 1983).
3. See, for example, W.G. Doll and M.A. Vonderembse, “Forging a Partnership to Achieve Competitive Advantage: The CIM Challenge,” MIS Quarterly 11 (1987): 205–220; and
J.D. Goldhar and M. Jelinek, “Computer-Integrated Flexible Manufacturing: Organizational, Economic, and Strategic Implications,” Interfaces 15 (1985): 94–105.
4. See J.F. Krafcik, “Triumph of the Lean Production System,” Sloan Management Review, Fall 1988, pp. 41–52;
R.W. Schmenner, “The Merit of Making Things Fast,” Sloan Management Review, Fall 1988, pp. 11–17; and
R.W. Schmenner and B. Rho, “An International Comparison of Factory Productivity,” International Journal of Operations and Production Management 10 (1990): 16–31.
5. M. Perona, G. Spina, and F. Turco, “Success Measure of Just-inTime: Shifting Manufacturing Trade-Offs,” Proceedings of the International Conference on Just-in-Time Manufacturing Systems: Operational Planning and Control Issues, Montreal, 2–4 October 1991 (Amsterdam: Elsevier, 1991), pp. 333–350.
6. See, for example, P.R. Duimering and F. Safayeni, “A Study of the Organizational Impact of the Just-in-Time Production System,” Proceedings of the International Conference on Just-in-Time Manufacturing Systems: Operational Planning and Control Issues, Montreal, 2–4 October 1991 (Amsterdam: Elsevier, 1991), pp. 19–32; and
F. Safayeni, L. Purdy, R. Van Engelen, and S. Pal, “The Difficulties of Just-in-Time Implementation: A Classification Scheme,” International Journal of Operations and Production Management 11 (1991): 27–36.
7. M.J. Ragotte, “The Effect of Human Operator Variability on the Throughput of an AGV System, A Case Study: General Motors Car Assembly Plant Door AGV System” (Waterloo, Ontario: University of Waterloo, Department of Management Sciences, Master’s Thesis, 1990).
8. Goldhar and Jelinek (1985).
9. Krafcik (1988);
Schmenner and Rho (1990); and
J.G. Wacker, “The Complementary Nature of Manufacturing Goals by Their Relationship to Throughput Time: A Theory of Internal Variability of Production Systems,” Journal of Operations Management 7 (1987): 91–106.
10. Wacker (1987).
11. P.R. Duimering, “The Organizational Impact of the Just-in-Time Production System” (Waterloo, Ontario: University of Waterloo, Department of Management Sciences, Master’s Thesis, 1991); and Duimering and Safayeni (1991); and Safayeni et al. (1991).
12. W.R. Ashby, An Introduction to Cybernetics (London: Chapman and Hall, 1957); and
S. Beer, Brain of the Firm: The Managerial Cybernetics of Organization (Chichester, England: John Wiley & Sons, 1981).
13. J.D. Thompson, Organizations in Action (New York: McGraw-Hill, 1967); and
J. Galbraith, Designing Complex Organizations (Reading, Massachusetts: Addison-Wesley, 1973).
14. H. Mintzberg, The Structuring of Organizations (Englewood Cliffs, New Jersey: Prentice-Hall, 1979).
15. Thompson (1967).
16. Galbraith (1973). Other authors have examined organizational implications of increased interdependence under JIT from other perspectives. For example, Klein has looked at the impact on individual worker autonomy. See:
J.A. Klein, “A Reexamination of Autonomy in Light of New Manufacturing Practices,” Human Relations 44 (1991): 21–39. Wilkinson and Oliver have examined the impact on power and control within organizations. See:
B. Wilkinson and N. Oliver, “Power, Control, and the Kanban,” Journal of Management Studies 26 (1989): pp. 47–58.
17. Duimering and Safayeni (1991).
18. Doll and Vonderembse (1987); and Goldhar and Jelinek (1985).
19. K.N. McKay, F.R. Safayeni, and J.A. Buzacott, “Job-Shop Scheduling Theory: What Is Relevant?” Interfaces 18 (1988): 84–90.
20. K.E. Weick, The Social Psychology of Organizing (Reading, Massachusetts: Addison-Wesley, 1969).
21. R.M. Cyert and K.R. MacCrimmon, “Organizations,” in Handbook of Social Psychology, eds. G. Lindzey and E. Aronson (Reading, Massachusetts: Addison-Wesley, 1968).
22. Goldhar and Jelinek (1985); and
P.L. Nemetz and L.W. Fry, “Flexible Manufacturing Organizations: Implications for Strategic Formulation and Organizational Design,” Academy of Management Review 13 (1988): 627–638.
23. Incidentally, one of the authors currently drives a late model North American car with automatic door locks and standard windows, but would still have bought the car if these features were available only as a package.
23. Beer (1981).