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Production control in moving bottlenecks in conditions of unit and small-batch production

Wybrane pełne teksty z tego czasopisma
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Języki publikacji
EN
Abstrakty
EN
Since the production is aimed at fulfilling specific needs of demanding customers and not at filling warehouses, the production volume should reflect the volume of orders. In times of fight for the client every order has to be performed on time. What is more, in limes of fight for shortening the delivery cycle, meeting safe deadlines, that is distant in time, is not enough. Companies are forced to meet short deadlines with keeping the product price competitiveness condition. It is hardly possible without a proper, APS (Advanced Planning System) class, advanced planning support system. Currently, advanced planning systems arc coming into use, however (heir cost exceeds the possibilities of small and medium enterprises and algorithms used often require great customization to industries' needs and conditions of unit and small-hatch production. The paper has been drawn on the basis of research on overloads of moving bottlenecks in conditions of unit and small batch production in real conditions having a big number of resources and tasks. The methods used so far are not capable of finding the global optimum of such big data ranges. At present few working enterprises in conditions of unit and small batch production, especially in small and medium-sized enterprises (SME), are exploiting techniques of the production process optimization. For this reason computer tools for applying to the industrial scale arc needed. The above method basis on the data so far collected in computer systems. Results of preliminary research were introduced from applying the possibility of TOC (Theory of Constraints) to the industrial scale for reducing bottlenecks in unit and small batch production. The authors built a heuristic algorithm which could find solution good enough and based on TOC assumptions and verification of assumptions using tests in real production systems. The above method found application to the industrial scale, as extension of the ERP class system.
Rocznik
Strony
229--239
Opis fizyczny
Bibliogr. 10 poz., rys., tab.
Twórcy
autor
autor
  • Department of Industrial Engineering, University of Bielsko-Biała, 2 Willowa St., 43-309 Bielsko-Biała, Poland, jmatuszek@ath.bielsko.pl
Bibliografia
  • [1] G. Schmidt, "Modeling production scheduling systems", Int. J. Production Economics 46-47, 109-118 (1996).
  • [2] J. Mleczko, "Optimization of tasks in an operational production plan in conditions of unit and small batch production", Applied Computer Science. Modeling of Manufacturing Process 4(1), 61-79 (2008).
  • [3] C. Smutnicki, Algorithms of Arranging Tasks, Akademicka Oficyna Wydawnicza EXIT, Warszawa, 2002, (in Polish).
  • [4] N. Robertson and T. Perera, "Automated data collection for simulation", Simulation Practice and Theory 9, 349-364 (2002).
  • [5] M. Gupta and A. Kohli, "Enterprise resource planning systems and its implications for operations function", Technovation 26, 687-696 (2006).
  • [6] Rao and S. Singiresu, Engineering Optimization - Theory and Practice, John Wiley & Sons, London, 1996.
  • [7] E. Goldratt and J. Cox, The Goal - A Process of Ongoing Improvement, North River Press Publishing Corporation, Great Barrington, 1992.
  • [8] T.C. Jones and D. Dugdale, "Theory of constraints: transforming ideas?", British Accounting Review 30, 73-91 (1998).
  • [9] T. Corbett, Throughput Accounting, North River Press Publishing Corporation, Great Barrington, 1999.
  • [10] G. Zulch and S. Stowasscr, "The digital factory: An instrument of the present and the future", Computers in industry 56, 323-324 (2005).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPG5-0040-0023
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