CN

周丹

Associate professor

Supervisor of Master's Candidates

Date of Employment:2004-04-01

School/Department:机械制造工程系

Administrative Position:制造工程系党支部书记

Education Level:Postgraduate (Doctoral)

Business Address:机械楼609东

Gender:Female

Degree:Doctoral degree

Status:Employed

Alma Mater:合肥工业大学

Discipline:Mechanical Design and Theory
Mechatronic Engineering
Other specialties in Mechanical Engineering
Mechanical Manufacture and Automation

Paper Publications

Toward sustainable joint optimisation for product family and supply chain configuration with smart contracting consideration

Release time:2024-03-07 Hits:

DOI number:10.1080/09544828.2023.2271775

Journal:Journal of Engineering Design

Key Words:Product family configuration;supply chain configuration;leader-follower optimisation;non-dominated sorting genetic algorithm-II; DC charging piles

Abstract:This article underscores the necessity for sustainable and environmentally friendly manufacturing practices in product family configuration (PFC) projects, which are paramount to the global economy. Nevertheless, conventional approaches often fixate solely on design aspects, overlooking downstream supply chain configuration (SCC) considerations and the corresponding environmental benefits. Consequently, there is an escalating demand for an integrated optimisation approach that encompasses both PFC and SCC to realise economic and environmental advantages. This study delves into a methodology that integrates blockchain smart contracts as binary 0–1 variables with waste recycling and utilisation, yielding a comprehensive multi-objective model. The proposed methodology seamlessly incorporates considerations for both PFC and SCC. Furthermore, a nested leader-follower optimisation algorithm, based on the non-dominated sorting genetic algorithm-II (NSGA-II), has been devised with the objective of achieving triple benefits: augmented profits, maintenance revenue, and diminished environmental emissions. In conclusion, this research contributes to the advancement of sustainable collaborative optimisation through the innovative utilisation of blockchain smart contracts and multi-level modelling. To demonstrate the effectiveness of the proposed methodology, it is applied to a 60 KW DC electric vehicle (EV) charging piles, accompanied by a sensitivity analysis to assess its management implications.

Indexed by:Journal paper

Discipline:Engineering

Document Type:J

Translation or Not:no

Date of Publication:2023-10-19

Included Journals:SCI

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