A real-time production operations decision support system for solving stochastic production material demand problems

  • Authors:

  • T. C. Poon;K. L. Choy;F. T. S. Chan;H. C. W. Lau

  • Affiliations:

  • Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong;Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong;Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong;School of Management, University of Western Sydney, Sydney, Australia

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2011

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Abstract

Nowadays, shop floor managers are facing numerous unpredictable risks in the actual manufacturing environment. These unpredictable risks not only involve stringent requirements regarding the replenishment of materials but also increase the difficulty in preparing material stock. In this paper, a real-time production operations decision support system (RPODS) is proposed for solving stochastic production material demand problems. Based on Poon et al. (2009), three additional tests are proposed to evaluate RFID reading performance. Besides, by using RPODS, the real-time status of production and warehouse operations are monitored by Radio Frequency Identification (RFID) technology, and a genetic algorithm (GA) technique is applied to formulate feasible solutions for tackling these stochastic production demand problems. The capability of the RPODS is demonstrated in a mould manufacturing company. Through the case study, the objectives of reducing the effect of stochastic production demand problems and enhancing productivity both on the shop floor and in the warehouse are achieved.