Hong Zhaoxi, Cui Kaiyue, Feng Yixiong, Song Jinyuan, Hu Bingtao, Tan Jianrong
Ningbo Innovation Center, Zhejiang University, Ningbo, 315100, People's Republic of China.
State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou, 310027, People's Republic of China.
Sci Rep. 2024 Aug 23;14(1):19649. doi: 10.1038/s41598-024-70159-2.
With the increasingly severe energy supply and environmental pressures, high-end equipment is gradually adopted to reduce the carbon emissions of manufacturing industry which makes its low-carbon structural design a critical research hotspot. The best structural scheme can be got by multi-attribute decision-making (MADM) with design requirements. However, the decision-making attributes in the structural design of high-end equipment are too many at first and low-carbon attributes are seldom fully considered. Moreover, there are a large amount of related data with linguistic vagueness, interval uncertainty, and information incompleteness, which fail to be handled simultaneously. There, this paper proposes an integrated MADM method of low-carbon structural design for high-end equipment based on attribute reduction considering incomplete interval uncertainties. First, distribution reduction of low-carbon structural design is carried out to obtain the minimum attribute set and encompass low-carbon attributes comprehensively. Second, a collaborative filtering algorithm is utilized to complete the missing data in the subsequent design process. Third, interval rough numbers (IRNs) are integrated into DEMATEL-ANP (DANP) and multi-attribute border approximation area comparison (MABAC) to quickly rank the alternative schemes for high-end equipment and determine which is the best. The rationality and robustness of the proposed method are verified through the case study and comparative analysis of a hydraulic forming machine.
随着能源供应和环境压力日益严峻，高端设备逐渐被采用以降低制造业的碳排放，这使得其低碳结构设计成为关键的研究热点。通过基于设计要求的多属性决策（MADM）可以得到最佳结构方案。然而，高端设备结构设计中的决策属性起初过多，且很少充分考虑低碳属性。此外，存在大量具有语言模糊性、区间不确定性和信息不完整性的相关数据，无法同时处理。因此，本文提出一种基于考虑不完全区间不确定性的属性约简的高端设备低碳结构设计集成MADM方法。首先，对低碳结构设计进行分布约简以获得最小属性集并全面涵盖低碳属性。其次，利用协同过滤算法在后续设计过程中完成缺失数据。第三，将区间粗糙数（IRN）集成到DEMATEL-ANP（DANP）和多属性边界近似区域比较（MABAC）中，以快速对高端设备的备选方案进行排序并确定最佳方案。通过对液压成型机的案例研究和对比分析，验证了所提方法的合理性和鲁棒性。
