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Research Papers

Energy-Oriented Maintenance Decision-Making for Sustainable Manufacturing Based on Energy Saving Window

[+] Author and Article Information
Tangbin Xia

Mem. ASME
State Key Laboratory of Mechanical
System and Vibration,
Department of Industrial Engineering,
School of Mechanical Engineering,
Shanghai Jiao Tong University,
Shanghai 200240, China
e-mail: xtbxtb@sjtu.edu.cn

Lifeng Xi, Shichang Du, Lei Xiao

State Key Laboratory of Mechanical
System and Vibration,
Department of Industrial Engineering,
School of Mechanical Engineering,
Shanghai Jiao Tong University,
Shanghai 200240, China

Ershun Pan

State Key Laboratory of Mechanical
System and Vibration,
Department of Industrial Engineering,
School of Mechanical Engineering,
Shanghai Jiao Tong University,
Shanghai 200240, China
e-mail: pes@sjtu.edu.cn

1Corresponding author.

Manuscript received June 1, 2017; final manuscript received December 28, 2017; published online February 15, 2018. Assoc. Editor: Karl R. Haapala.

J. Manuf. Sci. Eng 140(5), 051001 (Feb 15, 2018) (12 pages) Paper No: MANU-17-1349; doi: 10.1115/1.4038996 History: Received June 01, 2017; Revised December 28, 2017

In recent years, the industry's responsibility to join in sustainable manufacturing becomes huge, while innovating sustainability has been a new trend. Industrial enterprises are pursuing energy reduction to meet future needs for sustainable globalization and government legislations for green manufacturing. To run a manufacturing line in an energy-efficient manner, an energy-oriented maintenance methodology is developed. At the machine layer, the multi-attribute model (MAM) method is extended by modeling the energy attribute. Preventive maintenance (PM) intervals of each machine are dynamically scheduled according to the machine deterioration, maintenance effects, and environmental conditions. At the system layer, a novel energy saving window (ESW) policy is proposed to reduce energy for the whole line. Energy consumption interactivities, batch production characteristics, and system-layer maintenance opportunities are comprehensively considered. Real-time choice of PM adjustments is scheduled by comparing the energy savings of advanced PM and delayed PM. The results prove the energy reduction achieved by this MAM-ESW methodology. It effectively utilizes standby power, reduces energy consumption, avoids manufacturing breakdown, and decreases scheduling complexity. Furthermore, this energy-oriented maintenance framework can be applied not only in the automotive industry but also for a broader range of manufacturing domains such as the aerospace, semiconductor, and chemical industries.

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Figures

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Fig. 1

Design of MAM-ESW methodology

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Fig. 2

Illustration of ESW programming

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Fig. 3

Flowchart of energy-oriented maintenance decision-making

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Fig. 4

Maintenance energy comparison with periodic machine-layer models

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Fig. 5

System-layer cumulative energy savings in batch cycles

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Fig. 6

TES comparison with classical policies

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