Component oriented remanufacturing decision-making for complex product using DEA and interval 2-tuple linguistic TOPSIS^*

Abstract

Remanufacturing has been attracting attentions of global manufacturers as an important sustainable development strategy. Component oriented remanufacturing decision-making for complex product involving two phases is proposed in this paper. The first phase is to decide which components to be remanufactured using DEA. To overcome the drawback of traditional DEA without weight constraints, an augmented DEA is applied to evaluate the efficiencies of the pre-selected components considering manufacturing characteristic, comparative cost advantage and general returned status. The second phase is to select an appropriate remanufacturing concept for each efficient component. Interval 2-tuple linguistic model is used in obtaining and collecting experts' evaluations. Besides subjective experts' weights, the objective weights of them are considered in the group decision-making process, which are determined by the precision degree of information experts have given. TOPSIS integrated with interval 2-tuple fuzzy linguistic representation model is proposed to rank alternative remanufacturing concepts. A new distance measuring method between two interval 2-tuple vectors is given out considering both the subjective and objective criteria weights. The objective criterion weight is determined by the discrete degree of the performances of all alternatives on this criterion. A case study is carried out to demonstrate the effectiveness of the developed remanufacturing decision-making approach for complex product.

RECLAIM: Toward a New Era of Refurbishment and Remanufacturing of Industrial Equipment

“…In a more contemporary work, Darghouth et al (2017) focused on the requirements of OEM perspectives for an effective remanufacturing process. Finally, the usefulness of the remanufacturing process was identified in many research works that were devoted either to machine tools ( Ullah et al (2016) ) or to a special kind of production machines ( Geng et al (2016) ).…”

A Pythagorean Fuzzy TOPSIS Method Based on Novel Correlation Measures and Its Application to Multiple Criteria Decision Analysis of Inpatient Stroke Rehabilitation

“…More precisely, the rationale of classical TOPSIS methods is that the best compromise alternative should have the shortest distance from the positive-ideal solution and the longest distance from the negative-ideal solution [1,6,7]. TOPSIS has hitherto been widely studied by researchers and practitioners and have been successfully applied to several fields of real decision-makings [1,[7][8][9][10][11]. ID:p0095 Regarding the uncertainty in real situations, many fuzzy extensions related studies have been explored to enrich the theory of TOPSIS MCDA problems involve risks and uncertainties in nature [2,13].…”

“…In this regard, the fuzzy set theory is very suitable and effective to handle the MCDA problems under vague, uncertain, and incomplete information environment. From this perspective, different versions of TOPSIS based on fuzzy sets have been developed for considering uncertainties and vagueness in MCDA problems, such as the fuzzy TOPSIS [14,15], the generalized fuzzy TOPSIS [1], the analytic network process weighted fuzzy TOPSIS [16], the intuitionistic fuzzy TOPSIS [7,9,17], the interval-valued intuitionistic fuzzy linguistic TOPSIS [18], the interval type-2 fuzzy TOPSIS [10,12], and so on. Although numerous papers with fuzzy sets have been proposed for developing extensions of TOPSIS and applied to different application areas, relatively little attention has been paid to the extended TOPSIS dealing with MCDA problems under complex uncertainty based on Pythagorean fuzzy (PF) sets.…”

A New Fuzzy Multiple Attribute Decision Making Method Based on the Utility Transformation Functions

“…Additionally, the methods for MADM with the extended 2TLIM have been extensively studied. Just as the TOPSIS methods [14,15], the grey relational analysis methods [16,17], the VIKOR methods [18,19]. The key step of the methods is the aggregation of evaluation value.…”