IEEE Access (Jan 2020)

Design Sustainability of Reconfigurable Machines

  • Olayinka Mohammed Olabanji,
  • Khumbulani Mpofu

DOI
https://doi.org/10.1109/ACCESS.2020.3037998
Journal volume & issue
Vol. 8
pp. 215956 – 215976

Abstract

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This paper presents the sustainability assessment for reconfigurable machines based on cosine similarity measures and Euclidean distances. The methodology entails the application of four peculiar sustainability indicators (Reconfigurability, Manufacturing, Functionality, and Life Cycle Analysis) that are suitable for reconfigurable machines alongside the traditional sustainability indicators (Environmental, Social, and Economic). An index relating chart approach is proposed for determining the indices of the peculiar and traditional sustainability indicators and their sub-indicators. The chart involves the identification of viable links of the sub-indicators of an indicator and the sub-indicators of other indicators. The viable links are fuzzified using the fuzzy trapezoidal set because of the multi-dimensions and units of the sustainability indicators. The cosine similarity measures of the sustainability indicators were aggregated to estimate the sustainable similarity measures of the reconfigurable machines while the Euclidean distance estimates the distances of the indicators to best and worst sustainable performance in order to identify the sustainability indicators for improvement. Experts' opinions are applied to appraise the availability of sub-indicators in the four reconfigurable machine prototypes (vibrating screen, assembly fixture, bending press machine, and flexible fixture) used as case studies. A sensitivity analysis was carried out to validate the computational process of the methodology. The sensitivity analysis shows that the application of cosine similarity measures is suitable for assessment of sustainability considering the closeness of the similarity measures for the defuzzified values of the trapezoidal fuzzy numbers and the cosine similarity values of the aggregating matrix of the indicators. Also, the findings that can be deduced from the results of the appraisal of the case studies presented in this article shows that high sustainable index and similarity measures can be achieved by creating a balance in the performance of all the sustainable indicators. The results from the assessment also support the fact that improving one sustainability indicator because of its closeness to the worst sustainable performance may cause other indicators not to perform satisfactorily.

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