An integrated framework for the design of material flow systems

  • Bernhard F. Rembold
  • J. M. A. Tanchoco

Abstract

Material flow is a significant factor in the design of manufacturing systems. The designer of a material flow system is faced not only with the specification of individual system components but also with the overall objective of the manufacturing system. The association between components and the interaction of the material flow system with the manufacturing system are the basis by which its performance is judged. A material flow system design may be optimal in itself, but if the design cannot be integrated into the overall manufacturing system, it may have a negative impact on the manufacturing system performance. Therefore, the designer is expected to analyse the role of each component as a part of the total system and consider its influence on the overall system performance.

Keywords

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References

  1. Anderson, R.B. (1989) The Student Edition of MathCAD, Addison Wesley, Reading, MA.Google Scholar
  2. Andersson, M. (1985) AGV system simulation — A planning tool for AGV route layout. Proceedings of the 3rd International Conference on AGV Systems, Stockholm, Sweden, pp. 291–6.Google Scholar
  3. Apple, J.M. (1972) Material Handling System Design, The Ronald Press Co. New York, NY.Google Scholar
  4. Autodesk Inc. (1985) AutoCAD User’s Manual.Google Scholar
  5. Baumgarten, H. (1989) Trends in Logistics. Proceedings of the 7th International Conference on AGV Systems, 13–14 June, Berlin, Germany, 3–10.Google Scholar
  6. Borland International (1989) Quattro Pro User’s Guide.Google Scholar
  7. Brentano, L. (1984) Distributed CAD/CAM: Myth and Reality. IEEE Computer Graphics and Applications, 4(8), 18–22.CrossRefGoogle Scholar
  8. Brunsen, H. and Maiwald, R. (1992) INPAS — Integriertes Packereiplanungssystem. Short Report, Fraunhofer-Institut für Materialfluß und Logistik, Joseph-von-Fraunhofer-Str., 2–4, 4600 Dortmund 50, Germany.Google Scholar
  9. Cardinal, D.J. (1985) File Server Offers Transparent Design Tools. Computer Design, June, 147–54.Google Scholar
  10. Carver, B. (1989) Frameworks: the Design Environment of the 1990’s. Electronic Products, September, 19–28.Google Scholar
  11. CMS Research (1990) MAST Simulation Environment — User’s Manual Version 3.0. Google Scholar
  12. Daniell, J. and Director, S.W. (1989) An Object Oriented Approach to CAD Tool Control Within a Design Framework. Proceedings of the 26th ACM/IEEE Design Automation Conference, Las Vegas, NV, Paper 14.1, pp. 197–202.Google Scholar
  13. DeMori R. and Prager, R (1987) An expert system for verification and tuning of simulation models, in Artificial Intelligence in Engineering: Tools and Technigues, (eds D. Sriram and R.A. Adey), Computational Mechanics, Southampton Boston, pp. 160–75.Google Scholar
  14. Dixon, J.R., Simmons, M.K. and Cohen, P.R. (1984) An Architecture for Applications of Artificial Intelligence to Design. Proceedings of the 21st IEEE Design Automation Conference, Albuquerque, NM, pp. 634–40.Google Scholar
  15. Egbelu, P.J. and Tanchoco, J.M.A. (1982a) AGVSim User’s Manual. Technical Report No. 8204, Department of Industrial Engineering and Operations Research, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.Google Scholar
  16. Egbelu, P.J. (1987) The use of non-simulation approaches in estimating vehicle requirements in automated guided vehicle based transport systems. Material Flow, 4, 17–32.Google Scholar
  17. Eppinger, S.D., Whitney, D.E. and Gebala, D.A. (1982) Organizing the Tasks in Complex Design Projects: Development of Tool to Represent Design Procedures. Proceedings NSF Design and Manufacturing Systems Conference, Atlanta, GA, January 8–10.Google Scholar
  18. Fink, P.K., Lusth, J.C. and Duran, J.W. (1985) A general expert system design for diagnostic problem solving. IEEE Transactions on Pattern Analysis and Machine Intelligence, 7(5), 353–560.CrossRefGoogle Scholar
  19. Fishburn, P.C. (1967) Methods of estimating additive utilities. Management Science, 13(7), 435–53.CrossRefGoogle Scholar
  20. Floss, P. and Talavage, J. (1990) A knowledge-based design assistant for intelligent manufacturing systems. Journal of Manufacturing Systems, 9(2), 87–102.CrossRefGoogle Scholar
  21. Frydman, C., Giambasi, N., Gatumel, M. et al. (1989) DeBuMa: Description, Building and Management of Applications. Proceedings of the 26th ACM/IEEE Design Automation Conference, Las Vegas, NV, pp. 203–208.Google Scholar
  22. Gaskins, R.J. and Tanchoco, J.M.A. (1987) Flow path design for AGV systems. International Journal of Production Research, 25(6), 667–76.CrossRefGoogle Scholar
  23. Gaskins, R.J. and Tanchoco, J.M.A. (1989) AGUSIM2 — a development tool for AGVS controller design. International Journal of Production Research, 27(6), 915–26.CrossRefGoogle Scholar
  24. Gottheil, K., Kachel, G., Kathoefer, T. et al. (1988) The CADLab Workstation CWS — An open system for tool integration, in Tool Integration and Design Environments, (ed F.J. Rammig), North Holland, Netherlands.Google Scholar
  25. Haabma, J. (1988) The NMP-CAD-Based System — An open and integrating framework for CAD tools, in Tool Integration and Design Environments, (ed F.J. Rammig), North Holland, Netherlands.Google Scholar
  26. Heim, J.A. (1990) Integration of distributed heterogenous models for design of manufacturing systems. PhD Thesis, School of Industrial Engineering, West Lafayette, IN, USA.Google Scholar
  27. Hofmann, H., Caviedes, J., Bourne, J. et al. (1986) Building expert systems for repair domains. Expert Systems, 3(1), 4–11.CrossRefGoogle Scholar
  28. Hollingum, J. (1988) Renishaw probes new manufacturing methods. FMS Magazine, 6(2), 75–7.Google Scholar
  29. Howe, A., Cohen, P., Dixon, J. et al. (1986) Dominic: A domain-independent program for mechanical engineering design, in Applications of Artificial Intelligence in Engineering Problems, (eds D. Sriram and R.A. Adey), Springer-Verlag: Berlin, Germany, pp. 289–99.Google Scholar
  30. Kaspi, M. and Tanchoco, J.M.A. (1990) Optimal flow path design of unidirectional AGV systems. International Journal of Production Research, 28(6), 1023–30.CrossRefGoogle Scholar
  31. Krishnamurthy, E.V. (1989) Parallel Processing — Principles and Practice, Addison Wesley, Reading, MA.MATHGoogle Scholar
  32. Kuprat, T. (1990) Fördertechnik im Fertigungsbetrieb. VDl-Z, 133(6), 98–106.Google Scholar
  33. Law, A.M. and Haider, S.W. (1989) Selecting simulation software for manufacturing applications: Practical guidelines and software survey. Industrial Engineering, May, 33–46.Google Scholar
  34. Law, A.M. and Kelton, W.D. (1991) Simulation Modeling and Analysis, McGraw Hill, New York.Google Scholar
  35. Leung, L.C., Khator, S.K. and Kimbler, D.L. (1987) Assignment of AGVs with different vehicle types. Material Flow, 4(1&2), 65–72.Google Scholar
  36. Lesch, U. (1990) FFS-Planer. VDI-Z, 132(1), 26–31.Google Scholar
  37. Lotus Development Corporation (1990) 1–2–3 For Sun: User’s Reference.Google Scholar
  38. MacCrimmon, K.R. (1973) An overview of multiple objective decision making, in Multiple Criteria Decision Making, (eds J. Cochrane and M. Zeleny), University of South Carolina Press, Columbia, SC, pp. 18–44.Google Scholar
  39. MacCrimmon, K.R. and Siu, J.K. (1974) Making trade-offs. Decision Sciences, 5, 680–703.CrossRefGoogle Scholar
  40. Mackulak, G.T. (1984) High level planning and control: An IDEFo analysis for airframe manufacture. Journal of Manufacturing Systems, 3(2), 121–33.CrossRefGoogle Scholar
  41. MathWorks (1990) Pro-MatLab User’s Guide.Google Scholar
  42. Maxwell, W.L. and Muckstadt, J.A. (1982) Design of automated guided vehicle systems. IIE Transactions, 14(2), 114–24.Google Scholar
  43. McGinnis, L.F. (1989) Computer-aided facility design revisited: A prototype design workstation for AGV systems, in Progress in Material Handling and Logistics, (eds J.A. White and I.W. Pence), Springer-Verlag, Berlin, pp. 67–93.Google Scholar
  44. Middendorf, W.H. (1989) Design of Devices and Systems, 2nd edn, Marcel Dekker, New York.Google Scholar
  45. Milberg, J., Burger, C. and Zetlmayer, H. (1992) Flexible Regelung der Produktion mit Entscheidungsunterstützenden Systemen. VDI-Z, 134(5), 140–5.Google Scholar
  46. Miller, R.K. (1987) Automated Guided Vehicle Systems, SME Publications, Dearborn, MI.Google Scholar
  47. Mitta, D.A. (1991) A methodology for quantifying expert system usability. Human Factors, 33(2), 233–45.Google Scholar
  48. Moser, E., Rust, H. and Golze, U. (1988) Knowledge-based tool box management system, in Tool Integration and Design Environments, (ed F.J. Rammig), North Holland, Netherlands, pp. 211–21.Google Scholar
  49. Mostow, J. (1985) Towards better models of the design process. AI Magazine, Spring, 44–57.Google Scholar
  50. Müller, T. (1983) Automated Guided Vehicles, IFS Publications, Bedford.Google Scholar
  51. Naylor, A.W. and Volz, R.A. (1988) Integration and flexibility of software for integrated manufacturing systems, in Design and Analysis of Integrated Manufacturing Systems, (ed W.D. Compton), National Academy Press, Washington, DC.Google Scholar
  52. Pritsker, A.A.B. (1986) Introduction to Simulation and SLAMII, 3rd ed, Holsted Press (Wiley), New York.Google Scholar
  53. Rembold, B.F. and Tanchoco, J.M.A. (1992) The Next Step in AGVS Design Workstations. Proceedings of the First IIE Industrial Engineering Research Conference, Chicago, IL, pp. 113–6.Google Scholar
  54. Rembold, B.F. and Tanchoco, J.M.A. (1994a) A modular framework for the design of material flow systems. International Journal of Production Research, 32(1), pp. 1–21.CrossRefMATHGoogle Scholar
  55. Rembold, B.F. and Tanchoco, J.M.A. (1994b) Selecting and sequencing design tools in developing material flow systems models. International Journal of Production Research, 32(2), pp. 243–62.CrossRefMATHGoogle Scholar
  56. Rembold, B.F. and Tanchoco, J.M.A. (1994c) Material flow system model evaluation and improvement. International Journal of Production Research, forthcoming.Google Scholar
  57. Schönheit, M. and Wiegershaus U. (1990) Flexible Fertigungssysteme für Mittelständische Unternehmen. VDI-Z, 132(9), 58–65.Google Scholar
  58. Schroer, B.J. (1989) A simulation assitant for modelling manufacturing systems. Simulation, November, 201–6.Google Scholar
  59. Sedgewick, R. (1992) Algorithms in C++, Addison Wesley, Reading, MA.Google Scholar
  60. Segal, M. and Whitt, W. (1989) A queueing network analyzer for manufacturing, in Teletraffic Science for New Cost-Effective Systems, Networks and Services, (ed M. Bonati), North Holland, Netherlands, pp. 1146–52.Google Scholar
  61. Sharp, G.P. and Liu, F.-H.F. (1990) An analytical method for configuring fixed-path, closed loop material handling systems. International Journal of Production Research, 28(4), 757–83.CrossRefGoogle Scholar
  62. Shodhan, R.H. (1989) COMAND: A computer consultant for design, operation and control of flexible manufacturing systems. PhD thesis, Purdue University, School Industrial Engineering, West Lafayette, IN, USA.Google Scholar
  63. Solberg, J.I. (1981) Capacity planning with a stochastic workflow model. AIIE Transactions, 13(2), 116–22.CrossRefGoogle Scholar
  64. Solberg, J.J. and Heim, J.A. (1989) Managing information complexity in material flow systems, in Advanced Information Technologies for Industrial Material Flow, Systems, (eds S.Y. Nof and C.L. Moodie) NATO ASI Series, Vol. F53, Springer-Verlag, Berlin.Google Scholar
  65. Spur, G., Hirn, W. and Seliger, G. (1983) The Role of Simulation in Design of Manufacturing Systems. Proceedings of the 5th International IFIP/IFAC Conference on Programming Research and Operations Logistics in Advanced Manufacturing Technology, Leningrad, USSR, pp. 349–73.Google Scholar
  66. Suri, R. and Hildebrandt, R.R. (1984) Modelling FMS’s using mean value analysis. Journal of Manufacturing Systems, 3(1), 27–38.CrossRefGoogle Scholar
  67. Talavage, J. and Hannam, R.G. (1988) Flexible Manufacturing Systems in Practice, Marcel Dekker, New York.Google Scholar
  68. Tanchoco, J.M.A., Egbelu, P.J. and Taghaboni, F. (1987) Determination of the total number of vehicles in an AGV-based material transport system. Material Flow, 4, 33-51.Google Scholar
  69. Tompkins, J.A. and White, J.A. (1984) Facilities Planning, John Wiley, New York.Google Scholar
  70. Tzafestas, S.G. (1987) A look at the knowledge-based approach to system fault diagnosis and supervisory control, in System Fault Diagnosis, Reliability, and Related Knowledge-Based Approaches, 2, (ed S.G. Tzafestas), D. Reidel, Boston, MA, pp. 3–15.CrossRefGoogle Scholar
  71. Warnecke, H.J., Steinhilper, R. and Zeh, K.-P. (1986) Simulation as an integral part of FMS planning, in Simulation Applications in Manufacturing, (ed R.D. Hurrion), IFS Publications, Berlin, Germany, pp. 131–47.Google Scholar
  72. Wolfram, S. (1988) Mathematica — A System for Doing Mathematics by Computer, Addison-Wesley, Reading, MA.MATHGoogle Scholar
  73. Wysk, R.A., Egbelu, P.J., Zhou, C. et al. (1987) Use of spread sheet analysis for evaluating AGV systems. Material Flow, 4, 53–64.Google Scholar

Further Reading

  1. Ashayeri, J., Gelders, L.F. and Van Looy, P.M. (1985) Micro Computer Simulation in Design of Automated Guided Vehicle Systems. Material Flow, 2, 37–48.Google Scholar
  2. Bakkalbasi, O. and McGinnis, L.F. (1988) ABC’s of Preliminary In-House Planning of AGVS Applications. Proceedings of the AGVS 88 Forum and Exhibit, Cincinnati, OH, Session 8, 13–48.Google Scholar
  3. Bastide, R. and Sibertin-Blanc, C. (1991) Modeling a Flexible Manufacturing System by Means of Cooperative Objects, in Computer Applications in Production and Engineering: Integration Aspects, (eds G. Doumeingts, J. Browne and J. Tomljanovich), North Holland: Elsevier, Netherlands, pp. 593–601.Google Scholar
  4. Booch, G. (1991) Object Oriented Design With Applications, Benjamin/Cummings, Redwood City, CA.Google Scholar
  5. Bozer, Y.A. and Srinivasan, M.M. (1991) Tandem AGV Systems: A Partitioning Algorithm and Performance Comparison With Conventional AGV Systems. Unpublished Paper, Department of Industrial and Operations Engineering, The University of Michigan, Ann Arbor, MI, USA.Google Scholar
  6. Coad, P. and Yourdon, E. (1991) Object Oriented Analysis, 2nd edn, Yourdon Press, Englewood Cliffs, NJ.Google Scholar
  7. Duffau, B. and Bardin, C. (1985) Evaluating AGVS Circuits by Simulation. Proceedings of the 3rd International Conference on AGV Systems, Stockholm, Sweden, pp. 229–45.Google Scholar
  8. Edwards, W. (1977) The use of multiattribute utility measurement for social decision making, in Conflicting Objectives in Decision, (eds D.E. Bell, R.L. Keeney and H. Raiffa), John Wiley, Chichester, pp. 274–76.Google Scholar
  9. Egbelu, P.J. and Tanchoco, J.M.A. (1982b), Operational Consideration for the Design of AGV-Based Material Handling Systems. Technical Report No. 8201, Department of Industrial Engineering and Operations Research, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.Google Scholar
  10. Egbelu, P.J. and Tanchoco, J.M.A. (1984) Characterization of AGV dispatching rules. International Journal of Production Research, 22(3), 359–74.CrossRefGoogle Scholar
  11. Fishburn, P.C. (1965) Independence in utility theory with whole product sets. Operations Research, 13(1), 28–45.MathSciNetCrossRefGoogle Scholar
  12. Fisher, E.L. (1986) An AI-based methodology for factory design. AI Magazine, Fall, 72–85.Google Scholar
  13. Glassey, C.R. and Adiga, S. (1990) Berkeley library of objects for control of manufacturing (BLOCS/M), in Applications of Object Oriented Programming, (eds L.J. Pinson and R.S. Wiener), Addison-Wesley, Reading, MA, pp. 1–27.Google Scholar
  14. van Haarpen, N.T. (1987) Integrated Systems for Computer Aided Design. Proceedings of International Conference on Engineering Design, Boston, MA, pp. 426–33.Google Scholar
  15. Jones, A.H. and Burge, S.E. (1989) An expert system design using cause-effect representations and simulation for fault diagnosis, in Knowledge-Based Systems Diagnosis and Control, (ed S.G. Tzafestas), Plenum Press, New York, pp. 71–80.Google Scholar
  16. Keeney, R.L. and Raiffa, H. (1976) Decisions With Multiple Objectives: Preferences and Value Tradeoffs, John Wiley, New York.Google Scholar
  17. Kiesewetter, S.A., Dörken, T.P., Melchert, M. et al. (1991) Flexible Fertigung im Jahresübersicht. VDI-Z, 133(8), 58–75.Google Scholar
  18. King, C.U. and Fisher, E.L. (1986) Object Oriented Shop Floor Design, Simulation and Evaluation. Proceedings of the Fall Industrial Engineering Conference, Dallas, TX, pp. 131–7.Google Scholar
  19. Koff, G.A. and Boldrin, B. (1985) Automated guided vehicles, in Materials Handling Handbook, (ed R. Kulweic), John Wiley, New York.Google Scholar
  20. Mahadevan, B. and Narendran, T.T. (1990) Design of an automated guided vehicle based material handling system for a flexible manufacturing system. International Journal of Production Research, 28(9), 1611–22.CrossRefGoogle Scholar
  21. Martinez, J., Alla, H. and Silva, M. (1986) Petri nets for the specifications of FMSs, in Modelling and Design of Flexible Manufacturing Systems, (ed A. Kusiak), North Holland, Netherlands.Google Scholar
  22. Matson, J.O., Swaminathan, S.R. and Mellichamp, J.M. (1990) Knowledge-Based Material Handling Eguipment Selection. Proceedings of the International Industrial Engineering Conference, San Francisco, CA, pp. 212–7.Google Scholar
  23. Rembold, B.F. and Tanchoco, J.M.A. (1991) A Graphical Editor for the Design of Material Flow Systems, Technical Report, School of Industrial Engineering, Purdue University, West Lafayette, IN, USA.Google Scholar
  24. Ritz, G.J. (1990) Total Engineering Project Management, McGraw Hill, New York.Google Scholar
  25. Schönheit, M., Wiegershaus, U. and Kiesewetter, S. (1990) Fachgebiete im Jarhresübersicht: Flexible Fertigung. VDI-Z, 132(10), 92–109.Google Scholar
  26. Shewchuk, J.P. and Chang, T.C (1991) An Approach to Object-Oriented Discrete-Event Simulation of Manufacturing Systems. Proceedings of the 1991 Winter Simulation Conference, Phoenix, AZ, pp. 302–11.Google Scholar
  27. Shubin, H. and Ulrich, J.W. (1982) IDT: An Intelligent Diagnostic Tool. Proceedings of the National Conference on Artificial Intelligence, Pittsburgh, PA, pp. 290–5.Google Scholar
  28. Taghaboni, F. and Tanchoco, J.M.A. (1988) A LISP-based controller for free-ranging automated guided vehicle systems. International Journal of Production Research, 26(2), 173–88.CrossRefGoogle Scholar
  29. Tanchoco, J.M.A. and Agee, M.H. (1981) Plan unit loads to interact with all components of warehouse systems. Industrial Engineering, June, 36–48.Google Scholar
  30. Tanchoco, J.M.A. and Sinriech, D. (1992) OSL — Optimal Single Loop guide paths for AGVS. International Journal of Production Research, 30(3), 655–81.Google Scholar
  31. Wright, J.A. (1989) Systems Thinking: A Guide to Managing in a Changing Environment, Society of Manufacturing Engineers, Dearborn, MI.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 1994

Authors and Affiliations

  • Bernhard F. Rembold
  • J. M. A. Tanchoco

There are no affiliations available

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