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Article
Publication date: 20 November 2024

Chien-Chun Ku, Kang-Ting Ma, Thi Nhu Quyen Le and Chen-Fu Chien

This study aimed to optimize the dyeing scheduling process with uncertain job completion time to reduce resource consumption and wastewater generation, and while reconciling the…

Abstract

Purpose

This study aimed to optimize the dyeing scheduling process with uncertain job completion time to reduce resource consumption and wastewater generation, and while reconciling the conflicting objectives of minimizing the makespan and the need to limit the production on specific machines to minimize rework.

Design/methodology/approach

We employed a UNISON framework that integrates fuzzy decision tree (FDT) to optimize dyeing machine scheduling by minimizing the makespan and water consumption, in which the critical attributes such as machine capacity and processing time can be incorporated into the scheduling model for smart production.

Findings

An empirical study of a high-tech textile company has shown the validity and effectiveness of the proposed approach in reducing the makespan and water consumption by over 8% while high product quality and efficiency being maintained.

Originality/value

High-tech textile industry is facing the challenges in reducing the environmental impact of the dyeing process while maintaining product quality and efficiency for smart production. Conventional scheduling approaches have not addressed the relationship between machine groups and reworking, resulting in difficulty in controlling the makespan and water consumption and increasing costs and environmental issues. The proposed approach has addressed uncertain job completion via integrating FDT into the scheduling process to effectively reduce makespan and wastewater. The results have shown practical viability of the developed solution in real settings.

Details

Industrial Management & Data Systems, vol. 124 no. 11
Type: Research Article
ISSN: 0263-5577

Keywords

Article
Publication date: 20 February 2023

Cristina Fernandes, João Ferreira and Pedro Mota Veiga

The purpose of this study is use a bibliometric analysis to explore the relational nature of knowledge creation in WFM in operations. Companies live under constant pressure to…

Abstract

Purpose

The purpose of this study is use a bibliometric analysis to explore the relational nature of knowledge creation in WFM in operations. Companies live under constant pressure to find the best ways to plan their workforce, and the workforce emangement (WFM) is one of the biggest challenges faced by managers. Relevant research on WFM in operations has been published in a several range of journals that vary in their scope and readership, and thus the academic contribution to the topic remains largely fragmented.

Design/methodology/approach

To address this gap, this review aims to map research on WFM in operations to understand where it comes from and where it is going and, therefore, provides opportunities for future work. This study combined two bibliometric approaches with manual document coding to examine the literature corpus of WFM in operations to draw a holistic picture of its different aspects.

Findings

Content and thematic analysis of the seminal studies resulted in the extraction of three key research themes: workforce cross-training, planning workforce mixed methods and individual workforce characteristics. The findings of this study further highlight the gaps in the WFM in operations literature and raise some research questions that warrant further academic investigation in the future.

Originality/value

Likewise, this study has important implications for practitioners who are likely to benefit from a holistic understanding of the different aspects of WFM in operations.

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