Production scheduling involves operational level decision making at the shop floor that covers not only the manufacturing stage of the product life-cycle, but also the use stage of the processes. Triple bottom line (TBL) including economic, environmental, and social pillars has been introduced to holistically evaluate the performance of a production firm. Despite the substantial research in sustainable manufacturing, a holistic model that considers all three pillars of the TBL for sustainable production scheduling is virtually absent. This paper presents a metric-based model to systematically and holistically evaluate the sustainability of the production schedules. To this aim, we first perform an extensive literature review to identify the fundamental performance metrics in production scheduling. Second, we assess those metrics with respect to the TBL. Third, we show the inconsistencies among the fundamental performance metrics, and consequently among the objectives defined in the TBL. Finally, we propose a generic model for production scheduling for sustainability based on balancing the trade-offs among the inconsistent objectives. The efficiency and effectiveness of the proposed model is demonstrated using a comprehensive numerical study. The proposed model not only provides a sustainable schedule, but also results in better control over the fundamental performance metrics of the production scheduling.
|Number of pages||12|
|Journal||Journal of Manufacturing Systems|
|State||Published - Jan 2020|
Bibliographical noteFunding Information:
We appreciate the supports from the Department of Mechanical Engineering and the Institute for Sustainable Manufacturing (ISM) at the University of Kentucky. The authors would like to appreciate the anonymous reviewers for their constructive comments and suggestions. We also appreciate Ms. Brooke Lawson for her diligent proofreading of this paper.
- Production scheduling
- Trade-off balancing
ASJC Scopus subject areas
- Control and Systems Engineering
- Hardware and Architecture
- Industrial and Manufacturing Engineering