Title
Cross-Trained Worker Assignment And Comparative Analysis On Throughput Of Divisional And Rotating Seru
Abstract
Purpose Seru (cell) manufacturing system has achieved huge success in production. However, related research is limited, especially, the problem of cross-trained worker assignment. The purpose of this paper is to solve this problem for two representative seru types, divisional and rotating seru, and subsequently, compare throughput performance between the two seru types under reasonable worker-task assignment.Design/methodology/approach For the cross-trained worker assignment problem, this research presents new models aiming at maximum throughput of seru and workload balance of workers under considering skill levels (SLs) and several practical constraints. Furthermore, factorial experiments that involve four factors, the number of tasks (NT), gap of task time, SL and gap of SL, are performed to compare throughput performance between divisional and rotating seru.Findings First, the maximum throughput of the divisional seru is better than that of the rotating seru under suitable worker assignment. Second, in the seru which has less difference of task time, throughput performance of the rotating seru is better than the divisional seru when the NT is close to the number of assigned workers. Moreover, the influence tendency of the four factors on throughput gap between the two seru types is significant.Originality/value This research addresses the worker-task assignment for divisional and rotating seru based on their characteristics. Several findings can help decision maker select more applicable seru type according to various production environments from the perspective of optimum throughput.
Year
DOI
Venue
2018
10.1108/IMDS-07-2017-0303
INDUSTRIAL MANAGEMENT & DATA SYSTEMS
Keywords
Field
DocType
Throughput, Divisional seru, Rotating seru, Seru manufacturing system, Worker assignment
Industrial engineering,Manufacturing systems,Workload,Assignment problem,Throughput,Engineering,Management science,Decision maker
Journal
Volume
Issue
ISSN
118
5
0263-5577
Citations 
PageRank 
References 
0
0.34
6
Authors
4
Name
Order
Citations
PageRank
Lang Wu154.86
Felix T. S. Chan21267113.20
Ben Niu323544.62
Li Li4192.42