PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
2014 | 5 | nr 3 | 23--32
Tytuł artykułu

A Predictive Model of Multi-Stage Production Planning for Fixed Time Orders

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The traditional production planning model based upon a deterministic approach is well described in the literature. Due to the uncertain nature of manufacturing processes, such model can however incorrectly represent actual situations on the shop floor. This study develops a mathematical modeling framework for generating production plans in a multistage manufacturing process. The devised model takes into account the stochastic model for predicting the occurrence of faulty products. The aim of the control model is to determine the number of products which should be manufactured in each planning period to minimize both manufacturing costs and potential financial penalties for failing to fulfill the order completely. (original abstract)
Rocznik
Tom
5
Numer
Strony
23--32
Opis fizyczny
Twórcy
  • Lublin University of Technology, Poland
  • National Research Council in Italy
  • Lublin University of Technology, Poland
  • Technical University of Košice, Slovakia
  • Lublin University of Technology, Poland
Bibliografia
  • [1] Relich M., Fuzzy project scheduling using constraint programming, Applied Computer Science, 9, 1, 3-16, 2013.
  • [2] Gola A., Genetic-Based Approach to Production Planning with Minimization Cost of Manufacturing, Actual Problems of Economics, 153, 3, 496-503, 2014.
  • [3] Gola A., Świć A., Design of storage subsystem of flexible manufacturing system using the computer simulation method, Actual Problems of Economics, 142, 4, 312-318, 2013.
  • [4] Wang S., Sarker B.R., Optimal models for a multistage supply chain system controlled by kanban under just in- time philosophy, European Journal of Operational Research, 172, 179-200, 2006.
  • [5] Pochet Y., Mathematical Programming Models and Mormulations for Deterministic Production Planning Problems in: Jünger M., Naddet D., Computat. Comb. Optimization, Springer-Verlag, Berlin Heidelberg 2001.
  • [6] Pochet Y., Wolsey L.A., Production Planning by Mixed Integer Programming, Springer Science, 2006.
  • [7] Gąska D., Świć A, Practical implementation of computerized production management information system in a production company, Applied Computer Science, 6, 1, 75- 90, 2010.
  • [8] Fransoo J.C., A Typology of Production Control Situations in Process Industries, International Journal of Operations & Production Management, 14, 12, 47-57, 1994.
  • [9] Chen H., Yang P., Yao D., Chao, Optimal control of a simple assembly system, Operations Research Letters, 14, 4, 199-205, 1993.
  • [10] Benjaafar S., ElHafsi M., Production and inventory control of a single product assemble-to-order system with multiple customer classes, Management Science, 52, 12, 1896-1912, 2006.
  • [11] Benjaafar S., ElHafsi M., Yee C.Y., Zhou W., Optimal control of assembly systems with multiple stages and multiple demand classes, Operations Research, 59, 2, 522-529, 2011.
  • [12] Simpson N.C., Multiple level production planning in rolling horizon assembly environments, European Journal of Operation Research, 114, 15-28, 1999.
  • [13] Millhiser W.P., Apostolos N.B., Optimal admission control in series production systems with blocking, IIE Transactions, 45, 10, 1035-1047, 2013.
  • [14] Gershwin S.B., Design and operation of manufacturing systems: The control-point policy, IEE Transactions, 32, 891-906, 2000.
  • [15] Kushner H.J., Control and optimal control of assemble to order manufacturing systems under heavy traffic, Stochastics and Stochastic Reports, 6, 3&4, 233-272, 1999.
  • [16] Plabeck E.L., Ward A.R., Optimal control of a high-volume assemble-to-order system with maximum leadtime quotations and expediting, Queuing Systems, 60, 1-2, 1-69, 2008.
  • [17] Ceryan O., Duenyas I., Koren Y., Optimal Control of an Assembly System with Demand for the End-Product and Intermediate Components, IEE Transactions, 44, 5, 386-403, 2012.
  • [18] Liao G.L., Optimal economic production quantity policy for randomly failing process with minimal repair, backorder and preventive maintenance, International Journal of System Science, 44, 9, 1602-1612, 2013.
  • [19] Sarkar M., Sarkar B., An economic manufacturing quantity model with probabilistic deterioration in a production system, Economic Modeling, 31, 245- 252, 2013.
  • [20] Diponegoro A., Sarker B.R., Finite horizon planning for a production system with permitted shortage and fixed-interval deliveries, Computers & Operations Research, 33, 2387-2404, 2006.
  • [21] Terkaj W., Tolio T., A Stochastic approach to the FMS Loading Problem, CIRP Journal of Manufacturing Systems, 35, 5, 481-490, 2006.
  • [22] Ghelase D., Daschievici L., Marinescu V., Epureanu A., Method for control of the make-to-order manufacturing system on the base of earning power assessment, The International Journal of Advanced Manufacturing Technology, 65, 9-12, 1439-1458, 2013.
  • [23] Felea I., Dzitac S., Vesselenyi T., Dzitac I., Decision Support Model for Production Distrubance Estimation, International Journal of Information Technology & Decision Making, 13, 3, DOI: 10.1142/S0219622014500576.
  • [24] Kozłowski E., Gola A., Świć A., Model of Production Control in Just-in-Time Delivery System Conditions, Advances in Manufacturing Science and Technology, 38, 1, 77-88, 2014.
  • [25] Guide V.D.R. Jr., Production planning and control for remanufacturing: industry practice and research needs, Journal of Operations Management, 18, 4, 467-483, 2000.
  • [26] Kozłowski E., The linear quadratic stochastic optimal control problem with random horizon at finite number of events independent of state system, System Science, 36, 3, 5-11, 2010.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171331459

Zgłoszenie zostało wysłane

Zgłoszenie zostało wysłane

Musisz być zalogowany aby pisać komentarze.
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.