The Fuzzy DEA-Based Manufacturing Service Efficiency Evaluation and Ranking Approach for a Parallel Two-Stage Structure of a Complex Product System on the Example of Solid Waste Recycling

Abstract

Accurate production efficiency evaluation can assist enterprises in adjusting production strategies, improving production efficiency, and, thereby, weakening environmental impacts. However, the current studies on production efficiency evaluation do not accurately consider interactions inside the production system in parallel production processes. Based on the concept of the manufacturing service, this paper describes the production process of a complex product system (CoPS) with a manufacturing service chain. An efficiency calculation model based on the triangular intuitionistic fuzzy number–solid waste recycling–super-efficiency data envelopment analysis (TIFN-SWR-SDEA) is proposed under the consideration of the internal parallel structure of the production system on the example of solid waste recycling. Additionally, the technique for order preference by similarity to ideal solution (TOPSIS) method and the entropy weight method were combined to determine the proportion of solid waste recycling, and an improved proposed index rank (PIR) method was employed to rank the efficiency interval results. Finally, the effectiveness and superiority of the method were verified by comparative analysis. The results show that the overall efficiency of the CoPS production system can be improved by using green manufacturing technology, increasing the recycling of renewable resources, using clean energy, and improving the utilization rate of materials in the production process.

Comprehensive intuitionistic fuzzy network data envelopment analysis incorporating undesirable outputs and shared resources

“…In the realm of literature, numerous innovative approaches have emerged to address uncertainty through the two-stage network DEA model. However, these methods face a notable deficiency in effectively integrating shared resources, external inputs/outputs, and undesirable outputs (see [32] , [35] , [36] ).…”