Cost Considerations

  • Chrissoleon T. Papadopoulos
  • Michael J. Vidalis
  • Michael E. J. O’Kelly
  • Diomidis Spinellis
Part of the Springer Optimization and Its Applications book series (SOIA, volume 31)


A major consideration in the management of production is to understand the cost impact of various designs. Much of the work relating to overall production management including the design of facilities would seem to indicate that the decision processes are serial rather than concurrent or iterative feedback. The classical idea would appear to be that the engineering designers decide on the layout of the line with primary interest in the engineering performance measures of the stations and subsequently this design is costed and justified on some concept closely related to discounted cash flow. There are a number of papers discussing the inadequacy of the approach just outlined, particularly in relation to systems with inherent flexibility and the justification of which may be more strategic rather than tactical.

An appropriate philosophy for world-class companies is for the company to re-invent itself from time to time. This is in contrast to the view that a company can retain its competitive advantage by simply being effective in existing markets. Although it is important to retain or improve one’s position in existing markets, it is often in the development of new markets, new customers and new products or services that the health of the company is ensured. Re-invention therefore is a questioning philosophy of how the company can do better today and what it should be doing tomorrow. Clearly, it is a mixture of continuous improvement in all aspects of its activities and new product development. Thus, manufacturing strategy should support marketing strategy and give competitive advantage to the organization. In the light of this strategic trust, investments in production facilities should be carefully assessed from the point of view, of quality, flexibility, time-to-market, dependability, market positioning as well as cost. It is of course difficult to put all these diverse tangible and intangible benefits into one overall metric with the view to choosing particular marketing and manufacturing strategies including production systems designs. From the decision theory point of view what is involved is a multiple-criteria decision problem. However, the authors are unaware of any published work which applies techniques of multiple-criteria decision making such as ranking/scaling methods, analytical hierarchical processes to the selection, at a strategic level of a particular production system. There is an obvious need to reconcile the point of view of the economists, who would be concerned with opportunity costs, and the approach of accountants who are generally more interested in using actual historical or projected tangible costs, with the imperatives of manufacturing engineering and the operating philosophies and desires of production management, perhaps through a process of brainstorming and Delphi methods. Arising out of the strategic analysis, outline and broadly based decisions on the required manufacturing facilities and capabilities of the company would be developed. For example, decisions might be made to invest in automation to develop flexible manufacturing systems (FMS) or to use production lines. At a level below the strategic level, tactical level decisions must be undertaken to specify, for example, location, size and general layout of manufacturing facility, production machine processes, efficiency/effectiveness, required throughput, capital cost targets, quality targets, degree of flexibility envisaged and operating cost targets for each of the manufacturing systems specified in outline form at the strategic level. Finally, it is at the detailed design level that the production line, if one is required, is completely specified with regard to the number of stations, the equipment at each station, the number of operatives at each station, the inter-station buffer capacities and the work-load allocation to achieve the required throughput. Issues related to maintenance and reliability of equipment need to be considered. The overall objective is to meet the target cost per unit produced. The focus of this book is at this detailed design level.


Objective Function Production Line Cash Flow Balance Line Strategic Level 


  1. 1.
    Altiok, T. (1997), Performance Analysis of Manufacturing Systems, Springer-Verlag.Google Scholar
  2. 2.
    Altiok, T. and Stidham, S. Jr. (1983), The allocation of interstage buffer capacities in production lines, AIIE Transactions, Vol. 15, No. 4, pp. 292–299.Google Scholar
  3. 3.
    Beged Dov, A.G., Carmichael, C.D., Ferguson, S.T., Mitchel, I.E., and Strube, W.H. (1968), Production programming by revenue curve analysis, Proceedings of the Second Winter Simulation Conference on Applications of Simulations, pp. 53–57.Google Scholar
  4. 4.
    Blank, L. and Carrasco, H. (1985), The economics of new technology: System design and development methodology, Annual International Industrial Engineering Conference Proceedings, pp. 161–168.Google Scholar
  5. 5.
    Boer, C.R. and Metzler, V. (1986), Economic evaluation of advanced manufacturing by means of simulation, Material Flow, Vol. 3, pp. 215–224.Google Scholar
  6. 6.
    Boothroyd, G. (1982), Economics of Assembly Systems, Journal of Manufacturing Systems, Vol. 1, No. 1, pp. 111–126.Google Scholar
  7. 7.
    Canada, J.R. and Sullivan, W.G. (1990), Persistent pifalls and applicable approaches for justification of advanced manufacturing systems, Engineering Costs and Production Economics, Vol. 18, pp. 247–253.CrossRefGoogle Scholar
  8. 8.
    Carrasco, H. and Blank, L. (1987), Prototype development of an investment tracking system for life cycle costing, World Productivity Forum & 1987 International Industrial Engineering Conference Proceedings, pp. 211–216.Google Scholar
  9. 9.
    Christy, P.D. and Kleindorfer, B.G. (1990), Simultaneous cost and production analysis of manufacturing systems, Proceedings of the Winter Simulation Conference, pp. 582–589.Google Scholar
  10. 10.
    Gustavson, R.E. (1983), Choosing manufacturing systems based on unit cost, Proceedings of the 13th International Symposium on Industrial Robots and Robots, Vol. 1, pp. 4-85–4-104.Google Scholar
  11. 11.
    Haider, S.W. and Blank, L.T. (1983), A role for computer simulation in the economic analysis of manufacturing systems, Proceedings of the Winter Simulation Conference, pp. 199–206.Google Scholar
  12. 12.
    Hedge, G.G., Ramamurthy, K., Tadikamalla, P.R., and Kekre, S. (1988), Capacity choice, work-in-process inventory and throughput: A simulation study, Proceedings of the Winter Simulation Conference, pp. 662–666.Google Scholar
  13. 13.
    Helber, S. (1999), Performance Analysis of Flow Lines with Non-Linear Flow of Material, Springer-Verlag.Google Scholar
  14. 14.
    Hutchinson, G.K. and Holland, J.R. (1982), The economic value of flexible automation, Journal of Manufacturing Systems, Vol. 1, No. 2, pp. 215–227.Google Scholar
  15. 15.
    Jensen, P.A., Pakath, R., and Wilson, J.R. (1988), Optimal buffer inventories for multistage production systems with failures, SMM 88-1, School of Industrial Engineering, Purdue University.Google Scholar
  16. 16.
    Jeong, K.C. and Kim, Y.-D. (2000), Heuristics for selecting machines and determining buffer capacities in assembly systems, Computers & Industrial Engineering, Vol. 38, pp. 341–360.CrossRefGoogle Scholar
  17. 17.
    Karmarkar, U. (1987), Manufacturing configuration, capacity and mix decisions considering operational costs, Journal of Manufacturing Systems, Vol. 6, Part 4, pp. 315–324.Google Scholar
  18. 18.
    Meredith, J.R. and Suresh, N.C. (1986), Justification techniques for advanced manufacturing technologies, International Journal of Production Research, Vol. 24, No. 5, pp. 1043–1057.Google Scholar
  19. 19.
    Moerman, P.A. (1988), Economic evaluation of investments in new production technologies, Engineering Costs and Production Economics, Vol. 13, pp. 241–262.CrossRefGoogle Scholar
  20. 20.
    Monga, A. and Zuo, M.J. (2001), Optimal design of series-parallel systems considering maintenance and salvage value, Computers & Industrial Engineering, Vol. 40, No. 4, pp. 323–337.Google Scholar
  21. 21.
    Noble, J.S. and Tanchoco, J.M.A. (1993), Design justification of manufacturing systems – A review, The International Journal of Flexible Manufacturing Systems, Vol. 5, pp. 5–25.CrossRefGoogle Scholar
  22. 22.
    Smith, J.M. and Chikhale, N. (1994), Buffer allocation for a class of non-linear stochastic knapsack problems, Department of Industrial Engineering and Operations Research, University of Massachusetts, Amherst.Google Scholar
  23. 23.
    Smith, J.M. and Daskalaki, S. (1988), Buffer space allocation in automated assembly lines, Operations Research, Vol. 36, pp. 343–358.CrossRefGoogle Scholar
  24. 24.
    Son, Y.K. (1991), A cost estimation model for advanced manufacturing systems, International Journal of Production Research, Vol. 29, No. 3, pp. 441–452.MathSciNetGoogle Scholar
  25. 25.
    Spinellis, D., Papadopoulos, C., and MacGregor Smith, J. (2000), Large production line optimization using simulated annealing, International Journal of Production Research, Vol. 38, No. 3, pp. 509–541.MATHGoogle Scholar
  26. 26.
    Tempelmeier, H. (2003), Simultaneous buffer and work-load optimization for asynchronous flow production systems, In Proceedings of the Fourth Aegean International Conference on the Analysis of Manufacturing Systems, July, 1–4, 2003, Samos Island, Greece, pp. 31–39.Google Scholar
  27. 27.
    Yeralan, S., Dieck, A.J., and Darwin, R.F. (1986), Economically optimum maintenance, repair and buffering operations in manufacturing systems, The Engineering Economist, Vol. 31, No. 4, pp. 279–292.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Chrissoleon T. Papadopoulos
    • 1
  • Michael J. Vidalis
    • 2
  • Michael E. J. O’Kelly
    • 3
  • Diomidis Spinellis
    • 4
  1. 1.Department of EconomicsAristotle University of ThessalonikiThessalonikiGreece
  2. 2.Department of Business AdministrationUniversity of the AegeanChiosGreece
  3. 3.Department of Industrial EngineeringNational University of Ireland University College GalwayGalwayIreland
  4. 4.Department of Management ScienceUniversity of Economics & BusinessAthensGreece

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