Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/104111
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dc.contributorDepartment of Industrial and Systems Engineeringen_US
dc.creatorChoy, KLen_US
dc.creatorHo, GTSen_US
dc.creatorLee, CKHen_US
dc.creatorLam, HYen_US
dc.creatorCheng, SWYen_US
dc.creatorSiu, PKYen_US
dc.creatorPang, GKHen_US
dc.creatorTang, Ven_US
dc.creatorLee, JCHen_US
dc.creatorTsang, YPen_US
dc.date.accessioned2024-02-05T08:46:23Z-
dc.date.available2024-02-05T08:46:23Z-
dc.identifier.issn0925-5273en_US
dc.identifier.urihttp://hdl.handle.net/10397/104111-
dc.language.isoenen_US
dc.publisherElsevier BVen_US
dc.rights© 2016 Elsevier B.V. All rights reserved.en_US
dc.rights© 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.rightsThe following publication Choy, K. L., Ho, G. T. S., Lee, C. K. H., Lam, H. Y., Cheng, S. W. Y., Siu, P. K. Y., Pang, G. K. H., Tang, V., Lee, J. C. H., & Tsang, Y. P. (2016). A recursive operations strategy model for managing sustainable chemical product development and production. International Journal of Production Economics, 181(B), 262–272 is available at https://doi.org/10.1016/j.ijpe.2016.07.011.en_US
dc.subjectCase-based reasoningen_US
dc.subjectFuzzy logicen_US
dc.subjectOperations strategyen_US
dc.subjectProduct developmenten_US
dc.subjectSustainable consumptionen_US
dc.subjectSustainable productionen_US
dc.titleA recursive operations strategy model for managing sustainable chemical product development and productionen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage262en_US
dc.identifier.epage272en_US
dc.identifier.volume181en_US
dc.identifier.issueBen_US
dc.identifier.doi10.1016/j.ijpe.2016.07.011en_US
dcterms.abstractSustainable consumption and production is a critical issue in the chemical industry due to increasing public concerns on environmental and safety issues. Organizations are urged to improve the quality of chemical products while minimizing the environmental impacts during production. In current practice, chemists and formulators have to determine both the ingredients to be used and the machine parameter settings during product development and production. Without appropriate operations strategies for managing sustainable consumption and production, a significant portion of the ingredients, toxic materials and pollutants are wasted or emitted during the trial-and-error processes when developing chemical products. In addition, inappropriate machine parameter settings, such as blending speed and blending temperature, result in inefficient energy use. Motivated by these issues, this paper describes a recursive operations strategy (ROS) model for achieving sustainable consumption and production in the chemical industry. The ROS model first identifies the business strategy, and then defines operations strategies by assessing the competitive priorities and policies with the use of artificial intelligence, including case-based reasoning and fuzzy logic, so as to manage the operations functions. The effectiveness of the model is verified by means of a case study. The results indicate that the model can provide direct guidelines for the users to develop products based on previously developed products. By so doing, the number of trials for testing various ingredient formulae can be reduced, minimizing the ingredient waste. The proposed model is also capable of achieving continuous improvement and determining the optimal production process conditions for avoiding unnecessary energy consumption.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationInternational journal of production economics, Nov. 2016, v. 181, pt. B, p. 262-272en_US
dcterms.isPartOfInternational journal of production economicsen_US
dcterms.issued2016-11-
dc.identifier.scopus2-s2.0-84992424413-
dc.description.validate202402 bcchen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberISE-0903-
dc.description.fundingSourceRGCen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS6689159-
dc.description.oaCategoryGreen (AAM)en_US
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