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Reverse MRP under uncertain and imprecise demand

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Abstract

This paper presents an algorithm for scheduling the disassembly of discrete parts characterized by a well-defined product structure in an uncertain environment. Gupta and Taleb (Int J Prod Res 32(8):1857–1866, 1994) defined an algorithm, the reverse MRP, that can be applied to a product structure in which there is a certain demand for components and a need to know the number of products to disassemble in order to fulfill the demand for said components. Although they considered deterministic data, real information about the demand of used components is often ambiguous, vague or imprecise. To address this fact, we have re-formulated the reverse MRP algorithm using a fuzzy logic approach, incorporating imprecision and subjectivity into the model formulation and solution process. An extensive experimental framework is presented to illustrate the performance of the algorithm.

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References

  1. Taleb KN, Gupta SM (1997) Disassembly of multiple product structures. Comput Ind Eng 32:949–961

    Article  Google Scholar 

  2. Kim H-J, Lee D-H, Xirouchakis P, Züst, R (2003) Disassembly scheduling with multiple product types. Annals of CIRP 52:403–406

    Article  Google Scholar 

  3. Neuendorf KP, Lee D-H, Kiritsis D, Xirouchakis P (2001) Disassembly scheduling with parts commonality using Petri nets with timestamp. Fund Inform 47:295–306

    MathSciNet  MATH  Google Scholar 

  4. Gupta SM, Taleb KN (1994) Scheduling disassembly. Int J Prod Res 32(8):1857–1866

    Article  MATH  Google Scholar 

  5. Lambert AJD (1995) Optimal disassembly of complex products. Int J Prod Res 35(9):2509–2523

    Article  MATH  Google Scholar 

  6. Pnueli Y, Zussman E (1997) Evaluating the end-of-life value of a product and improving it by redesign. Int J Prod Res 35(4):921–942

    Article  MATH  Google Scholar 

  7. Moore KE, Gungor A, Gupta SM (1998) A Petri net approach to disassembly process planning. Comput Ind Eng 35:165–168

    Article  Google Scholar 

  8. Lambert AJD, Gupta SM (2005) Context of end-of-life disassembly. In: Disassembly Modeling for Assembly, Maintenance, Reuse, and Recycling, edited by CRC Press, 23

  9. Taleb KN, Gupta SM, Brennan L (1997) Disassembly of complex product structures with parts and materials commonality. Prod Plan Control 8(3):225–269

    Article  Google Scholar 

  10. Murthy DNP, Ma L (1991) MRP with uncertainty: A review and some extensions. Int J Prod Econ 25:51–64

    Article  Google Scholar 

  11. Lee D-H, Kang J-G, Xirouchakis P (2001) Disassembly planning and scheduling: review and further research. J Eng Manuf 215 (5):695–710

    Article  Google Scholar 

  12. Lee, D-H, Xirouchakis P, Züst R (2002) Disassembly scheduling with capacity constrains. Annals of the CIRP 51:387–390

    Article  Google Scholar 

  13. Lee D-H, Kim H-J, Xirouchakis P (2004) Disassembly scheduling: An integer programming approach. J Eng Manuf 218(10):1357–1372

    Article  Google Scholar 

  14. Lee D-H, Xirouchakis P (2004) A two-stage heuristic for disassembly scheduling with assembly product structure. J Oper Res Soc 55:287–297

    Article  MATH  Google Scholar 

  15. Guiffrida AL, Nagi R (1998) Fuzzy set theory applications in production management research: A literature survey. J Intell Manuf 9(1):39–56

    Article  Google Scholar 

  16. Karwowski W, Evans GW (1986) Fuzzy concepts in production management research: a review. Int J Prod Res 24(1):129–147

    Article  Google Scholar 

  17. Davis T (1993) Effective supply chain management. Sloan Manage Rev 34(4):35–46

    Google Scholar 

  18. Mula J, Poler R, García-Sabater JP, Lario FC (2006) Models for production planning under uncertainty: A review. Int J Prod Econ 103:271–285

    Article  Google Scholar 

  19. Petrovic D, Roy R, Petrovic R (1999) Supply chain modelling using fuzzy sets. Int J Prod Econ 59:443–453

    Article  Google Scholar 

  20. De Bodt MA, van Wassenhove LN (1983) Cost increases due to demand uncertainty in MRP lot sizing. Decis Sci 14:345–362

    Article  Google Scholar 

  21. Wacker JG (1985) A theory of material requeriment planning (MRP): An empirical methodology to reduce uncertainty in MRP systems. Int J Prod Res 23:807–824

    Article  Google Scholar 

  22. Kerr RM, Walker RN (1989) A job shop scheduling system based on fuzzy arithmetic. Third International Conference on Expert Systems and the Leading Edge, South Carolina, USA, 433–450

  23. Lee YY, Kramer BA, Hwang CL (1991) A comparative study of three lot-sizing methods for the case of fuzzy demand. Int J Oper Prod Manage 11:72–80

    Article  Google Scholar 

  24. Grabot B, Geneste L, Reynoso-Castillo G, Vérot S (2005) Integration of uncertain and imprecise orders in the MRP method. J Intell Manuf 16:215–234

    Article  Google Scholar 

  25. Watanabe T (1990) Job-shop scheduling using fuzzy logic in a computer integrated manufacturing environment. Fifth International Conference on Systems Research, Informatics and Cybernetics, August 6–12, Germany: Baden–Baden

  26. Inuiguchi M, Sakawa M, Kume Y (1994) The usefulness of possibilistic programming in production planning problems. Int J Prod Econ 33:45–52

    Article  Google Scholar 

  27. Fargier H, Thierry C (2000) The use of possibilistic decision theory in manufacturing planning and control. In: R. Slowinski and M. Hapke (eds.) Fuzzy Master Production Scheduling in Scheduling under Fuzziness. Springer-Verlag, Berlin, pp 45–59

  28. Mula J, Poler R, García-Sabater JP (2007) Material requirement planning with fuzzy constraints and fuzzy coefficients. Fuzzy Sets Syst 158:783–793

    Article  MathSciNet  MATH  Google Scholar 

  29. Ho C-Y (1989) Evaluating the impact of operating environments on MRP system nervousness. Int J Prod Res 27(7):1115–1135

    Article  Google Scholar 

  30. Grabot B, Geneste L (1998) Management of imprecision and uncertainty for production activity control. J Intell Manuf 9:431–446

    Article  Google Scholar 

  31. Geneste L, Grabot B, Letouzey A (2003) Scheduling uncertain orders in the customer-subcontractor context. Eur J Oper Res 147(2):297–311

    Article  MATH  Google Scholar 

  32. Dubois D, Prade H (1989) Processing fuzzy temporal knowledge. IEEE Trans Syst Man Cybern 19(4):729–744

    Article  MathSciNet  Google Scholar 

  33. Gupta A, Maranas CD (2003) Managing demand uncertainty in supply chain planning. Comput Chem Eng 27:1219–1227

    Article  Google Scholar 

  34. Barba-Gutiérrez Y, Adenso-Diaz B, Gupta SM (2008) Lot-sizing in reverse MRP for scheduling disassembly. Int J Prod Econ 112(2):741–751

    Article  Google Scholar 

  35. Mula J, Poler R, Garcia JP (2006) MRP with flexible constraints: A fuzzy mathematical programming approach. Fuzzy Set System 157:74–97

    Article  MathSciNet  MATH  Google Scholar 

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  1. Escuela Politécnica Superior de Ingeniería, Campus de Gijón, 33204, Gijón, Spain

    Y. Barba-Gutiérrez & B. Adenso-Díaz

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  1. Y. Barba-Gutiérrez
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  2. B. Adenso-Díaz
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Correspondence to B. Adenso-Díaz.

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Barba-Gutiérrez, Y., Adenso-Díaz, B. Reverse MRP under uncertain and imprecise demand. Int J Adv Manuf Technol 40, 413–424 (2009). https://doi.org/10.1007/s00170-007-1351-y

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  • DOI: https://doi.org/10.1007/s00170-007-1351-y

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