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An optimal path in a bi-criteria AGV-based flexible jobshop manufacturing system having uncertain parameters

Fazlollahtabar, H ; Sharif University of Technology | 2013

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  1. Type of Document: Article
  2. DOI: 10.1504/IJISE.2013.050544
  3. Publisher: 2013
  4. Abstract:
  5. We propose an approach for finding an optimal path in a flexible jobshop manufacturing system considering two criteria of time and cost. With rise in demands, advancement in technology and increase in production capacity, the need for more shops persists. Therefore, a flexible jobshop system has more than one shop with the same duty. The difference among shops with the same duty is in their machines with various specifications. A network is configured in which the nodes are considered to be the shops with arcs representing the paths among the shops. An automated guided vehicle functions as a material handling device through the manufacturing network. To account for uncertainty, we consider time to be a triangular fuzzy number and apply an expert system to infer cost. The objective is to find a path minimising both the time and cost criteria, aggregately. Since time and cost have different scales, a normalisation procedure is proposed to remove the scales. The model being biobjective, the analytical hierarchy process weighing method is applied to construct a single objective. Finally, a dynamic programming approach is presented for computing a shortest path in the network. The efficiency of the proposed approach is illustrated by a numerical example
  6. Keywords:
  7. AGV ; Automated guided vehicle ; Flexible jobshop ; Manufacturing systems ; Analytical Hierarchy Process ; Automated guided vehicles ; Bi objectives ; Bi-criteria ; Cost criteria ; Different scale ; Job-shop ; Manufacturing networks ; Material handling ; Normalisation ; Numerical example ; Optimal paths ; Production capacity ; Shortest path ; Single objective ; Triangular fuzzy numbers ; Uncertain parameters ; Weighing method ; Costs ; Expert systems ; Fuzzy systems ; Mobile robots ; Optimization ; Manufacture
  8. Source: International Journal of Industrial and Systems Engineering ; Volume 13, Issue 1 , 2013 , Pages 27-55 ; 17485037 (ISSN)
  9. URL: http://www.inderscience.com/offer.php?id=50544