Big data-based research on active remanufacturing comprehensive benefits evaluation of mechanical product

Abstract

ABSTRACT The rapid upgrading of mechanical products has caused serious waste of resources and environmental pollution. For improving the level of resources utilization and reduce the environmental pollution, this paper proposes a model to comprehensively evaluate the benefits of active remanufacturing (AR) of mechanical products based on big data analysis. The proposed model makes a comparison of the benefits of AR products and original products from the three aspects of economy, environment and user experience, and highlights the AR advantages of in-service mechanical products. Firstly, after collecting and analyzing various feedback information from the original manufacturers (OM), retailers (Rs), maintenance personnel (Ms) and end users, quality function deployment (QFD) is used to forecast the AR cost and evaluate of the economic benefits employing the smoothing index method. Secondly, the environmental benefits of different products are evaluated when analyzing the actual operating environment, operating specifications and remanufactured energy consumption of in-service products. Then, the user satisfaction survey of in-service mechanical products is conducted through market research, and the user experience evaluation is performed separately using fuzzy quantification and smoothing index methods. Finally, the feasibility and accuracy of model is verified by an in-service machine tool CA6180.