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Modeling and analysis of a mixed‐model assembly line with stochastic operation times
Authors:Xiaobo Zhao  Jianyong Liu  Katsuhisa Ohno  Shigenori Kotani
Affiliation:1. Department of Industrial Engineering, Tsinghua University, Beijing 100084, ChinaDepartment of Industrial Engineering, Tsinghua University, Beijing 100084, China;2. Institute of Applied Mathematics, Academy of Mathematics and System Science, Chinese Academy of Sciences, Beijing 100080, China;3. Department of Applied Information Science, Aichi Institute of Technology, Toyota 470‐0392, Japan;4. School of Business Administration, Tokyo Metropolitan University, Tokyo 192‐0397, Japan
Abstract:We consider a mixed‐model assembly line (MMAL) comprised a set of workstations and a conveyor. The workstations are arranged in a serial configuration. The conveyor moves at a constant speed along the workstations. Initial units belonging to different models are successively fed onto the conveyor, and they are moved by the conveyor to pass through the workstations to gradually generate final products. All assembling tasks are manually performed with operation times to be stochastic. An important performance measure of MMALs is overload times that refer to uncompleted operations for operators within their work zones. This paper establishes a method to analyze the expected overload times for MMALs with stochastic operation times. The operation processes of operators form discrete time nonhomogeneous Markov processes with continuous state spaces. For a given daily production schedule, the expected overload times involve in analyzing the Markov processes for finite horizon. Based on some important properties of the performance measure, we propose an efficient approach for calculating the expected overload times. Numerical computations show that the results are very satisfactory. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007
Keywords:mixed‐model assembly line  stochastic operation time  markov process  overload  algorithm
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