MINIMIZATION OF WORK IN PROCESS INVENTORY IN HYBRID FLOW SHOP SCHEDULING USING FUZZY LOGIC

Authors

  • Sanjoy Kumar Paul
  • Abdullahil Azeem

DOI:

https://doi.org/10.23055/ijietap.2010.17.2.238

Keywords:

Production systems design, planning and control

Abstract

This paper addresses the Hybrid Flow Shop (HFS) scheduling problems to minimize the total work in process inventory. Job scheduling problems are one of the oldest and real world combinational optimization problems. It is multi objective and complex in nature. There exist some criteria that must be taken into consideration when evaluating the quality of the proposed schedule. Consideration of job and machine reliability is very important during assignment of jobs in each stage to get realistic hybrid flow shop schedule.  In this paper, flow shop problem concerns the sequencing of a given number of jobs through a series of machines in the exact same order on all machines with the aim to satisfy a set of constraint as much as possible and optimize a set of objectives. Fuzzy sets and logic can be used to tackle uncertainties inherent in actual flow shop scheduling problems.  Fuzzy due dates, cost over time and profit rate result the job priority and to determine the machine priority processing time of each machine is considered. MATLAB fuzzy tool box is used to calculate the priorities of jobs and machines at different stages. Finally, jobs are assigned into machines based on a grouping and sequencing algorithm that minimizes the total work in process inventory.

Author Biographies

Sanjoy Kumar Paul

Lecturer, Department of IPE

Bangladesh University of Engineering and Technology (BUET), Dhaka - 1000

Abdullahil Azeem

Associate Professor, Department of IPE

Bangladesh University of Engineering and Technology (BUET), Dhaka - 1000

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Published

2010-06-17

How to Cite

Paul, S. K., & Azeem, A. (2010). MINIMIZATION OF WORK IN PROCESS INVENTORY IN HYBRID FLOW SHOP SCHEDULING USING FUZZY LOGIC. International Journal of Industrial Engineering: Theory, Applications and Practice, 17(2). https://doi.org/10.23055/ijietap.2010.17.2.238

Issue

Section

Production Planning and Control

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