Title

Joint Energy, Maintenance, and Throughput Modeling for Sustainable Manufacturing Systems

Abstract

With increasing concerns on climate change and energy shortage, manufacturing industries must adopt more sustainable production and facility control strategies. Such strategies require operational practices that emphasize sustainability by considering economic, energy, and environmental aspects simultaneously. In this paper, a new combined production scheduling model that jointly considers energy control and maintenance implementation to address the concerns of energy consumption, intelligent maintenance, and throughput improvement simultaneously is proposed. Multiple measures are combined and evaluated using a single objective, i.e., cost minimization. Particle swarm optimization, with a local optimal avoidable mechanism and a time varying inertial weight, is used to solve the cost minimization problem to find a near optimal solution of production and maintenance schedules. A numerical case study is implemented and the results show that the cost per unit production can be reduced up to 27% compared to the existing benchmark strategies. The implications to practitioners with respect to the tradeoff between cost and throughput/energy consumption, and the model applicability considering energy tariff structure, are also discussed to provide more insights for using the proposed joint model in the real world. The proposed model advances the state-of-the-art on maintenance and energy scheduling, which is typically performed exclusively. It is expected to guide operational activities on shop floors toward sustainability.

Department(s)

Engineering Management and Systems Engineering

Comments

Article in Press

Keywords and Phrases

Energy Consumption; Energy Consumption; Intelligent Maintenance; Job Shop Scheduling; Maintenance Engineering; Manufacturing Systems; Production Scheduling; Sustainable Manufacturing; Throughput

International Standard Serial Number (ISSN)

2168-2216; 2168-2232

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2018 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

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