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

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...

Mô tả chi tiết

Lưu vào:
Hiển thị chi tiết
Tác giả chính: Chia-Nan Wang, Zhao-Hong Cheng, Nguyen Ky Phuc Phan, Van Thanh Nguyen
Định dạng: journal-article
Ngôn ngữ:en_US
Thông tin xuất bản: 2022
Chủ đề:
Truy cập trực tuyến:http://repository.vlu.edu.vn:443/handle/123456789/545
Từ khóa: Thêm từ khóa bạn đọc
Không có từ khóa, Hãy là người đầu tiên gắn từ khóa cho biểu ghi này!
Mô tả
Tóm tắt: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.