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Article: An optimization model for energy-efficient machining for sustainable production

TitleAn optimization model for energy-efficient machining for sustainable production
Authors
KeywordsSTEP-NC
Ant colony optimization algorithm
Energy-efficient machining
Issue Date2019
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/jclepro
Citation
Journal of Cleaner Production, 2019, v. 232, p. 1121-1133 How to Cite?
AbstractSustainable production plays an important role in product lifecycle management by considering the social sustainability. Energy-efficient machining is an efficient approach for sustainable production in current manufacturing sectors. Although many related efforts have been achieved, a comprehensive energy optimization approach oriented to manufacturing parts is still a challenge. Therefore, this paper selects Standard for the Exchange of Product model data-Numerical Control (STEP-NC) as the enabling technology to achieve energy-efficient machining. An optimization model is proposed based on the energy calculation method using the workingstep in STEP-NC. An improved ant colony optimization (ACO) solution, consisting of encoding and decoding, initialization, machining scheme generation, idea of local multiple iteration, evaluation, pheromone evaporation and update, is presented. A part with typical manufacturing features is applied to verify the effectiveness of the proposed approach. The generated solution can provide a comprehensive machining scheme for low energy demandI by improving the efficiency with 25% for solving the optimization problem.
Persistent Identifierhttp://hdl.handle.net/10722/272205
ISSN
2017 Impact Factor: 5.651
2015 SCImago Journal Rankings: 1.721

 

DC FieldValueLanguage
dc.contributor.authorWang, H-
dc.contributor.authorZhong, RY-
dc.contributor.authorLiu, G-
dc.contributor.authorMu, W-
dc.contributor.authorTian, X-
dc.contributor.authorLeng, D-
dc.date.accessioned2019-07-20T10:37:43Z-
dc.date.available2019-07-20T10:37:43Z-
dc.date.issued2019-
dc.identifier.citationJournal of Cleaner Production, 2019, v. 232, p. 1121-1133-
dc.identifier.issn0959-6526-
dc.identifier.urihttp://hdl.handle.net/10722/272205-
dc.description.abstractSustainable production plays an important role in product lifecycle management by considering the social sustainability. Energy-efficient machining is an efficient approach for sustainable production in current manufacturing sectors. Although many related efforts have been achieved, a comprehensive energy optimization approach oriented to manufacturing parts is still a challenge. Therefore, this paper selects Standard for the Exchange of Product model data-Numerical Control (STEP-NC) as the enabling technology to achieve energy-efficient machining. An optimization model is proposed based on the energy calculation method using the workingstep in STEP-NC. An improved ant colony optimization (ACO) solution, consisting of encoding and decoding, initialization, machining scheme generation, idea of local multiple iteration, evaluation, pheromone evaporation and update, is presented. A part with typical manufacturing features is applied to verify the effectiveness of the proposed approach. The generated solution can provide a comprehensive machining scheme for low energy demandI by improving the efficiency with 25% for solving the optimization problem.-
dc.languageeng-
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/jclepro-
dc.relation.ispartofJournal of Cleaner Production-
dc.subjectSTEP-NC-
dc.subjectAnt colony optimization algorithm-
dc.subjectEnergy-efficient machining-
dc.titleAn optimization model for energy-efficient machining for sustainable production-
dc.typeArticle-
dc.identifier.emailZhong, RY: zhongzry@hku.hk-
dc.identifier.authorityZhong, RY=rp02116-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.jclepro.2019.05.271-
dc.identifier.scopuseid_2-s2.0-85067008220-
dc.identifier.hkuros298460-
dc.identifier.volume232-
dc.identifier.spage1121-
dc.identifier.epage1133-
dc.publisher.placeNetherlands-

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