Open Access

ARTICLE

Scheduling Optimization Modelling: A Case Study of a Woven Label Manufacturing Company

by Chia-Nan Wang¹, Zhao-Hong Cheng^2,*, Nguyen Ky Phuc Phan³, Van Thanh Nguyen⁴

1 Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan
2 Department of International Business, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan
3 Faculty of Industrial Engineering and Management, International University, Ho Chi Minh City, 70000, Vietnam
4 Faculty of Commerce, Van Lang University, Ho Chi Minh City, 70000, Vietnam

* Corresponding Author: Zhao-Hong Cheng. Email:

(This article belongs to the Special Issue: Impact of Industry 4.0 on Supply Chain Management and Optimization)

Computer Systems Science and Engineering 2021, 38(2), 239-249. https://doi.org/10.32604/csse.2021.016578

Received 05 January 2021; Accepted 17 February 2021; Issue published 23 April 2021

Abstract

Production scheduling involves all activities of building production schedules, including coordinating and assigning activities to each person, group of people, or machine and arranging work orders in each workplace. Production scheduling must solve all problems such as minimizing customer wait time, storage costs, and production time; and effectively using the enterprise’s human resources. This paper studies the application of flexible job shop modelling on scheduling a woven labelling process. The labelling process includes several steps which are handled in different work-stations. Each workstation is also comprised of several identical parallel machines. In this study, job splitting is allowed so that the power of work stations can be utilized better. The final objective is to minimize the total completion time of all jobs. The results show a significant improvement since the new planning may save more than 60% of lead time compared to the current schedule. The contribution of this research is to propose a flexible job shop model for scheduling a woven labelling process. The proposed approach can also be applied to support complex production scheduling processes under fuzzy environments in different industries. A practical case study demonstrates the effectiveness of the proposed model.

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