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Production Economics with the Use of Theory of Constraints

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Języki publikacji
EN
Abstrakty
EN
The article is a literature review in the scope of theory of constraints in manufacturing companies developed by E. Goldratt. Particular emphasis is placed on the economic sphere of such companies as opposed to the literature dedicated to solving production control problem by using DBR technique advocated by developers and active users of theory of constraints. The article aims to show the approach to the presentation of measurements developed by theory of constraints in the context of corporate net profit and return on invested money in productive activities in the real industrial plants. This is called throughput accounting that indicates the effectiveness of money processing in the production system. In addition, literature analysis aims to show the degree of utilization of theory of constraints in scientific environments in the context of efficiency measures in achieving the goal objective of making money or achieving degree of operational expenses savings in production systems.
Słowa kluczowe
Rocznik
Strony
79--88
Opis fizyczny
Bibliogr. 41 poz., fig.
Twórcy
  • Institute of Production Engineering and Automation, Cracow University of Technology, Krakow, 31-864, Poland
Bibliografia
  • 1. Badri S.A., Ghazanfari M. & Shahanaghi K. (2014), A multi-criteria decision-making approach to solve the product mix problem with interval parameters based on the theory of constraints, International Journal of Advanced Manufacturing Technology, Vol. 70, pp. 1073-1080.
  • 2. Balakrishnan J. & Cheng C.H. (2000), Theory of constraints and linear programming: a re-examination, International Journal of Production Research, Vol. 38, No. 6, pp. 1459-1463.
  • 3. Bhattacharya A. & Vasant P. (2007), Soft-sensing of level of satisfaction in TOC product-mix decision heuristic using robust fuzzy-LP, European Journal of Operational Research, Vol. 177, pp. 55-70.
  • 4. Bylinski G. (1983), An efficiency guru with a brown box, Fortune, Vol. 108, pp. 120-132.
  • 5. Chaharsoogi S.K., Jafari N. (2007), A simulated annealing approach for product mix decisions, Scienta Iranica, Vol. 14, No. 3, pp. 230-235.
  • 6. Corbett T. (1998), Throughput accounting, North River Press, Great Barrington, MA.
  • 7. Croci F., Pozzetti A. (2000), OPT scheduling performances: a case study, Production Planning & Control, Vol. 11, No. 1, pp. 82-89.
  • 8. Cyplik P., Hadaś Ł. & Domański R. (2009), Implementation of the theory of constraints in the area of stock management within the supply chain - a case study, LogForum, Vol. 5, No. 3, pp. 1-12.
  • 9. Darlington J., Francis M., Found P. & Thomas A. (2015), Design and implementation of a Drum-Buffer-Rope pull-system, Production Planning & Control, Vol. 26, No. 6, pp. 489-504.
  • 10. Engelgardt E. (2005), Theory of constraints and throughput accounting in the light of paradigms of accounting science (questionnaire results), Theoretical Journal of Accounting, Vol. 30, pp. 22-10.
  • 11. Geri N. & Ronen B. (2005), Relevance lost: the rise and fall of activity-based costing, Human Systems Management, Vol. 24, No. 2, pp. 133-144.
  • 12. Goldratt E.M. (1990), The haystack syndrome, North River Press, Great Barrington, MA.
  • 13. Goldratt E.M. (1994), It’s not luck, North River Press, Great Barrington, MA.
  • 14. Goldratt E.M. (1997), Critical Chain, North River Press, Great Barrington, MA.
  • 15. Goldratt E.M. & Cox J. (1984), The goal: a process of ongoing improvement, North River Press, Croton-on-Hudson, NY.
  • 16. Goldratt E.M. & Fox R.E. (1986), The race, North River Press, Croton-on-Hudson, NY.
  • 17. Golmohammadi D. (2015), A study of scheduling under the theory of constraints, Naval Research Logistics, Vol. 62, pp. 357-369.
  • 18. Golmohammadi D., Mansouri S.A. (2015), Complexity and workload considerations in product mix decisions under the theory of constraints, International Journal of Production Economics, Vol. 165, pp. 38-50.
  • 19. Gonzales P.L., Framinan J.M. & Ruiz-Usano R. (2010), International Journal of Computer Integrated Manufacturing, Vol. 23, No. 2, pp. 155-167.
  • 20. Gupta M. & Snyder D. (2009), Comparing TOC with MRP and JIT: a literature review, International Journal of Production Research, Vol. 47, No. 13, pp. 3705-3739.
  • 21. Hadaś Ł. & Karaskiewicz F. (2014), Algorithm of the implementation and continuous flow in unbalanced production unit condition - a case study, Research in Logistics & Production, Vol. 4, No. 1, pp. 91-100.
  • 22. Ifandoudas P. & Gurd B. (2010), Costing for decision-making in a theory of constraints environment, Journal of Applied Management Accounting Research, Vol. 8, No. 1, pp. 43-58.
  • 23. Kaplan R.S. & Cooper R. (1998), Cost and effect: Using integrated cost systems to drive profitability and performance, Harvard Business School Press, Boston.
  • 24. Koliński A. & Tomkowiak A. (2010), Using the analysis of bottlenecks in production management, Gospodarka Materiałowa & Logistyka, Vol. 9, pp. 16-21.
  • 25. Kosieradzka A. & Skorupa P. (2006), An improvement of a paints production process using the theory of constraints, Zarządzanie Przedsiębiorstwem, Vol. 1, pp. 28-37.
  • 26. Linhares A. (2009), Theory of constraints and the combinatorial complexity of the product-mix decision, International Journal of Production Economics, Vol. 121, pp. 121-129.
  • 27. Lockamy A. & Spencer M.S. (1998), Performance measurement in a theory of constraints environment, International Journal of Production Research, Vol. 36, No. 8, pp. 2045-2060.
  • 28. Miltenburg J. (1997), Comparing JIT, MRP and TOC, and embedding TOC into MRP, International Journal of Production Research, Vol. 35, No. 4, pp. 1147-1169.
  • 29. Naor M., Bernardes E.S. & Coman A. (2013), Theory of constraints: is it a theory and a good one?, International Journal of Production Research, Vol. 51, No. 2, pp. 542-554.
  • 30. Rajesh M. (2014), A mixed integer linear goal programming model for optimizing multiple constrained resources product-mix problem under the theory of constraints, IUP Journal of Operations Management, Vol. 13, No. 1, pp. 7-19.
  • 31. Sobreiro V.A. & Nagano M.S. (2012), A review and evaluation on constructive heuristics to optimize product mix based on the theory of constraints, International Journal of Production Research, Vol. 50, No. 20, pp. 5936-5948.
  • 32. Souren R., Ahn H. & Schmitz C. (2005), Optimal product mix decisions based on the Theory of Constraints? Exposing rarely emphasized premises of Throughput Accounting, International Journal of Production Research, Vol. 43, pp. 361-374.
  • 33. Souza F.B., Sobreiro V.A., Nagano M.S. & Manfrinato J.W.S. (2013), When less is better: Insights from the product mix dilemma from the theory of constraints perspective, International Journal of Production Research, Vol. 51, No. 19, pp. 5839-5852.
  • 34. Spencer M.S., Cox J.F. (1995), Optimum Production Technology (OPT) and the Theory of Constraints (TOC): analysis and genealogy, International Journal of Production Research, Vol. 33, No. 6, pp. 1495-1504.
  • 35. Steele D.C., Philipoom P.R., Malhotra M.K. & Fry T.D. (2005), Comparisons between drum-buffer-rope and material requirements planning: a case study, International Journal of Production Research, Vol. 43, No. 15, pp. 3181-3208.
  • 36. Śliwczyński B. & Koliński A. (2012), Efficiency analysis system of material management, LogForum, Vol. 8, No. 4, pp. 297-310.
  • 37. Ye T., Han W. (2008), Determination of buffer sizes from drum-buffer-rope (DBR)-controlled production systems, International Journal of Production Research, Vol. 46, No. 10, pp. 2827-2844.
  • 38. Wacker J.G. (2004), A theory of formal conceptual definitions: developing theory-building measurement instruments, Journal of Operations Management, Vol. 22, pp. 629- 650.
  • 39. Wang J.Q., Sun S.D., Si S.B. & Yang H.A. (2009), Theory of constraints product mix optimization based on immune algorithm, International Journal of Production Research, Vol. 47, No. 16, pp. 4521-4543.
  • 40. Watson K.J., Blackstone J.H. & Gardiner S.C. (2007), The evolution of a management philosophy: The theory of constraints, Journal of Operations Management, Vol. 25, pp. 387-402.
  • 41. Watson K.J. & Patti A. (2008), A comparison of JIT and TOC buffering philosophies on system performance with unplanned machine downtime, International Journal of Production Research, Vol. 46, No. 7, pp. 1869-1885.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-63dfdd97-6f82-47bf-8de6-46c6af12392b
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