A Job-Shop Scheduling Decision-Making Model for Sustainable Production Planning With Power Constraint

调度(生产过程) 可再生能源 作业车间调度 计算机科学 数学优化 工业工程 运筹学 工程类 运营管理 地铁列车时刻表 数学 操作系统 电气工程
作者
Daniela Carlucci,Paolo Renna,Sergio Materi
出处
期刊:IEEE Transactions on Engineering Management [Institute of Electrical and Electronics Engineers]
卷期号:70 (5): 1923-1932 被引量:20
标识
DOI:10.1109/tem.2021.3103108
摘要

Improving environmental sustainability and reducing energy cost are becoming central topics of decision-making in manufacturing. Increasingly manufactures are looking for new solutions that allow them to become more energy efficient and sustainable. Regarding energy cost issue, it is well known that the electricity costs in manufacturing systems strongly depend on the reached peak power. On the other hand, the power required by a manufacturing system affects the adoption of renewable energy sources. The use of renewables, indeed, encompasses fluctuations in energy supply and requires adapting production processes to a power constraint. The article proposes a decision model for the scheduling in a job-shop manufacturing system that simultaneously deals with the power constraint and the variable speed of machine tools. Defining the maximum value of the usable power, decisions can be taken on production scheduling, by adapting the processing speed of several machines that work simultaneously, to the power availability. The model allows decision makers to plan production, taking into account the impossibility of exceeding a certain power and assuming the minimization of the makespan as an objective function. Managers can utilize the scheduling model in all the different contexts, where there is a power limit. The test cases show how the proposed model allows to obtain an efficient scheduling under a constant and variable power constraint. The findings highlight that the model can be employed to reduce the peak power and encourage the use of renewables in manufacturing systems, thus obtaining an efficient scheduling and a more sustainable production.
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