Energy-efficient multi-level collaborative optimization for robotic manufacturing systems

Wenjun Xu; Hang Du; Jiayi Liu; Bitao Yao; Zude Zhou; Duc Truong Pham

doi:10.1016/j.procir.2018.03.230

Energy-efficient multi-level collaborative optimization for robotic manufacturing systems

Wenjun Xu, Hang Du, Jiayi Liu, Bitao Yao, Zude Zhou, Duc Truong Pham

Mechanical Engineering

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

192 Downloads (Pure)

Abstract

Aiming at the multi-level hierarchy framework of robotic manufacturing systems, how to realize a comprehensive energy-efficient optimization of the whole system is crucial to realize the sustainability of manufacturing. In this paper, the production-process oriented physical energy consumption model and digital model of industrial robots together with their interaction mechanisms are studied. Then, the concurrent assessment and evolution prediction approaches of robotic manufacturing systems are presented, as well as the collaborative optimization method based on knowledge evolution. Finally, a case study is implemented to verify the effectiveness of the proposed method.

Original language	English
Pages (from-to)	316-321
Journal	Procedia CIRP
Volume	72
DOIs	https://doi.org/10.1016/j.procir.2018.03.230
Publication status	Published - 27 Jun 2018

Keywords

robotic manufacturing systems
multi-level hierarchy
energy-efficient
collaborative optimization

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.procir.2018.03.230Licence: Creative Commons: Attribution-NonCommercial-NoDerivs (CC BY-NC-ND)

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https://www.sciencedirect.com/science/article/pii/S2212827118303901Licence: Creative Commons: Attribution-NonCommercial-NoDerivs (CC BY-NC-ND)

Cite this

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title = "Energy-efficient multi-level collaborative optimization for robotic manufacturing systems",

abstract = "Aiming at the multi-level hierarchy framework of robotic manufacturing systems, how to realize a comprehensive energy-efficient optimization of the whole system is crucial to realize the sustainability of manufacturing. In this paper, the production-process oriented physical energy consumption model and digital model of industrial robots together with their interaction mechanisms are studied. Then, the concurrent assessment and evolution prediction approaches of robotic manufacturing systems are presented, as well as the collaborative optimization method based on knowledge evolution. Finally, a case study is implemented to verify the effectiveness of the proposed method.",

keywords = "robotic manufacturing systems, multi-level hierarchy, energy-efficient, collaborative optimization",

author = "Wenjun Xu and Hang Du and Jiayi Liu and Bitao Yao and Zude Zhou and {Truong Pham}, Duc",

year = "2018",

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doi = "10.1016/j.procir.2018.03.230",

language = "English",

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T1 - Energy-efficient multi-level collaborative optimization for robotic manufacturing systems

AU - Xu, Wenjun

AU - Du, Hang

AU - Liu, Jiayi

AU - Yao, Bitao

AU - Zhou, Zude

AU - Truong Pham, Duc

PY - 2018/6/27

Y1 - 2018/6/27

N2 - Aiming at the multi-level hierarchy framework of robotic manufacturing systems, how to realize a comprehensive energy-efficient optimization of the whole system is crucial to realize the sustainability of manufacturing. In this paper, the production-process oriented physical energy consumption model and digital model of industrial robots together with their interaction mechanisms are studied. Then, the concurrent assessment and evolution prediction approaches of robotic manufacturing systems are presented, as well as the collaborative optimization method based on knowledge evolution. Finally, a case study is implemented to verify the effectiveness of the proposed method.

AB - Aiming at the multi-level hierarchy framework of robotic manufacturing systems, how to realize a comprehensive energy-efficient optimization of the whole system is crucial to realize the sustainability of manufacturing. In this paper, the production-process oriented physical energy consumption model and digital model of industrial robots together with their interaction mechanisms are studied. Then, the concurrent assessment and evolution prediction approaches of robotic manufacturing systems are presented, as well as the collaborative optimization method based on knowledge evolution. Finally, a case study is implemented to verify the effectiveness of the proposed method.

KW - robotic manufacturing systems

KW - multi-level hierarchy

KW - energy-efficient

KW - collaborative optimization

U2 - 10.1016/j.procir.2018.03.230

DO - 10.1016/j.procir.2018.03.230

M3 - Article

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VL - 72

SP - 316

EP - 321

JO - Procedia CIRP

JF - Procedia CIRP

ER -

Energy-efficient multi-level collaborative optimization for robotic manufacturing systems

Abstract

Keywords

UN SDGs

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