Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/66516
Title: A recursive operations strategy model for managing sustainable chemical product development and production
Authors: Choy, KL 
Ho, GTS
Lee, CKH
Lam, HY
Cheng, SWY
Siu, PKY
Pang, GKH
Tang, V
Lee, JCH
Tsang, YP
Keywords: Sustainable consumption
Sustainable production
Product development
Operations strategy
Case-based reasoning
Fuzzy logic
Issue Date: 2016
Publisher: Elsevier
Source: International journal of production economics, Nov. 2016, v. 181, part B, p. 262-272 How to cite?
Journal: International journal of production economics 
Abstract: Sustainable 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.
URI: http://hdl.handle.net/10397/66516
ISSN: 0925-5273
DOI: 10.1016/jAjpe.2016.07.011
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