Improving the delivery efficiency of the customer order scheduling problem in a job shop

  • Authors:

  • Sheng-Yuan Hsu;C. -H. Liu

  • Affiliations:

  • Department of Industrial Engineering and Management, Chienkuo Technology University, 1 Chieh-Sou N. Road, Changhua 50094, Taiwan, ROC;Department of Industrial Management, National Pingtung University of Science and Technology, 1, Shuefu Road, Neipu, Pingtung 912, Taiwan, ROC

  • Venue:
  • Computers and Industrial Engineering
  • Year:
  • 2009

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Abstract

The focus of this paper is customer order scheduling (COS) problem, where each order consists of a set of jobs that must be shipped as one batch at the same time. In COS each job is part of a customer order and the make-up of the jobs in the order are pre-specified. Most of the existing research deals with COS in a single machine or in a parallel machine shop for developing an optimal solution. COS is common in a normal job shop, and the more complex the shop, the more complex the scheduling. Most existing research has focused on trying to reduce the completion time of the batch. That is, the focus is only on the point in time the last job is finished, while ignoring the actual duration of the jobs within the same order. The longer it takes to complete all the jobs within an order the more it increases the stock of finished goods and the more it deteriorates the efficiency of the logistics and the supply chain management. A new dispatching rule, referred to as Minimum Flow Time Variation (MFV), has been proposed for COS in a normal job shop, in order to reduce the total time it takes to complete all jobs within the same order. That is, the individual completion times of all jobs for the same customer order will be controlled in order to improve the shipping performance. In the simulation test and statistical analysis, the level of work in process (WIP) under the MFV rule in the finished goods warehouse is reduced by more than 70% compared to any other method. The MFV method will efficiently reduce the stock level of finished goods, and controls the waiting time required before they can be shipped. Depending on the environmental factors, the performance of our proposed method will become increasingly significant the more complex the system.