A quantitative simulation-based conceptual design evaluation approach integrating bond graph and rough VIKOR under uncertainty. (20th December 2022)

• Record Type: Journal Article
• Authors: Jing, Liting; Wang, Jiaxin; Xie, Jing; Feng, Di; Wang, Jianxiang; Peng, Xiang; Jiang, Shaofei
• Is Part Of: Journal of cleaner production. Volume 380:Part 2(2022)
• Publication Date: 2022-12-20
• Subjects: Conceptual scheme simulation -- Bond graph -- Rough VIKOR -- AMESim -- Conceptual design decision; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2022.134928
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: Conceptual design evaluation is a vital stage of new product development, which determines the sustainability, safety, quality of the final design, as well as its impact on the production cycle cost and manufacturability. Notwithstanding, pertinent evaluation methods advocate quantifying the subjective assessments of conceptual schemes (CSs) by decision makers (DMs) based on qualitative evaluation objectives, but the lack of physical performance verification of CSs with respect to quantitative objectives, leading to inconsistency between the optimal CS and the actual design requirements. To fill the issue, a quantitative simulation-based CS evaluation approach integrating bond graph and rough VIKOR is proposed. First, the bond elements that satisfy the physical effects corresponding to the realization of the function is obtained by function-effect mapping, and the functional structure is transformed into a bond graph model. Second, the AMESim components that satisfy the mathematical model of the above bond graph model are sought, the simulation model without detailed structural parameters is constructed to realize the simulation analysis of the scheme performance. Third, the rough VIKOR model is used to integrate the simulation data and the subjective assessments for the optimal ranking of CSs under uncertainty. Besides, rough number is introduced to aggregate the evaluation information of multi-DMs to improve the objectivity of decision process. Eventually, a cutting variable-speed device case study is further employed to verify the proposed simulation approach, and comparison results show that the proposed model can provide design decision support for value product development and reduce the waste of design resources through early design verification. Highlights: Function-effects mapping is used to transform functional model into a bond graph. Construct a simulation model of the scheme bond graph based on AMESim components. Rough set technology is used to aggregate simulation data and subjective evaluation. Case verification of cutting speed change device scheme of the shearer.