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Robot appraisement under various dimensions and directions is a crucial issue in real-time manufacturing scenario. Logistic robots are programable-independent movable devices capable of transporting stuffs in a logistic cycle. The purpose of this paper is to opt for the most economical robot under chains of criteria, which is always considered as a sizzling issue in an industrial domain.

The authors proposed a cluster approach, i.e. ratio analysis, reference point analysis and full mutification form, embedded type-2 fuzzy sets with weighted geometric aggregation operator (WGAO) to tackle the elected problem of industrial robot. The motive to use WGAO coupled with type-2 fuzzy sets is to effectively undertake the uncertainty associated with comprehensive information of professionals against defined dimensions. Furthermore, the cluster approach is used to carry out the comparative analysis for evaluating robust scores against candidate robot’s manufacturing firms, considering 59 crucial beneficial and non-beneficial dimensions. A case research study is carried out to demonstrate the validity of the proposed approach.

The most challenging task in real-time manufacturing scenario is robot selection for a particular industrial application. This problem has become more complex in recent years because of advanced features and facilities that are continuously being incorporated into the robots by different manufacturers. In the past decade, robots have been selected in accordance with cost criteria excluding other beneficial criteria, which results in declined product quality, customer’s expectation, ill productivity, higher deliver time, etc. The proposed research incorporates the aforesaid issues and provides the various important attributes needed to be considered for the optimum evaluation and selection of industrial robots.

The need for changes in the technological dimensions (speed, productivity, navigation, upgraded product demands, etc.) of robot was encountered as a hardship work for managers to take wise decision dealing with a wide range of availability of robot types and models with distinct features in the manufacturing firms. The presented work aids the managers in taking their decisions effectively while dealing with the aforesaid circumstances.

The proposed work suggests chains of dimensions (59 crucial beneficial and non-beneficial dimensions) that can be used by managers to measure the economic worth of robot to carry out logistic activities in updated manufacturing environment. The proposed work evolves as an effective cluster approach-embedded type-2 fuzzy sets with WGAO to assess manufacturing firms under availability of low information.

Supplier evaluation is a part of logistic management. In the present era, resilient supply chain performance (RSCP) assessment of the vendor enterprise is respected as a hot topic. The purpose of this paper is to enable the managers to map the performance in percentage system and also enabling managers for identifying the weak indices-metrics, which need to be improved up to ideal or standard level and strong indices-metrics.

The authors found two research gaps via a literature survey. The first research gap revealed that the performance of a resilient supplier is computed solely in terms of a fuzzy mathematical scale. The articles are not yet published, which could measure the RSCP in percentage. The second research gap argued about the mitigation of the multi-level hierarchical resilient vendor/supplier evaluation framework for materializing RSCP and identifying weak and strong performing indices-metrics. To compensate the both research gaps, the authors developed a novel fuzzy gain-loss evolutionary computational approach to assess the performance of a firm in percentage. Next, a revised ranking technique coupled with trapezoidal fuzzy set based fuzzy performance importance index is implemented on the framework to seek weak and strong indices-metrics. The performance loss of each metric using the ideal solution concept considering the attitude of decision makers is also revealed.

The authors found the RSC performance of supplier firm 74 per cent, whereas performance loss 26 per cent, while actual performance is compared with standard fuzzy performance index (SFPI). Performance loss 26 per cent can be compensated by improving the performance of weak indices-metrics.

The novelty of the paper is that the authors used the ideal solution concept to compute the SFPI and compare it with actual FPI for evaluating the gain and loss of resilient supplier firm in percentage and identify weak and strong indices so that managers can improve the performance of weak indices. The work possesses the significant for all organizations, as research work enables the managers to map and improve the RSC performance of any vendor firm in future. The presented work considers the case of an automobile parts supplier industry to validate the developed approach.