Anoop Kumar Sahu, Atul Kumar Sahu and Nitin Kumar Sahu
In present research, the authors conducted the massive literature review and collected the information, in regards to material handling system (MHS) to build a multi criteria MHS…
Abstract
Purpose
In present research, the authors conducted the massive literature review and collected the information, in regards to material handling system (MHS) to build a multi criteria MHS hierarchical module consists of ecological cum fiscal criteria. Moreover, similar literature review assisted the authors to resolve and eventually construct the effectual and robust approach. The purpose of this paper is to facilitate the managers for benchmarking the MHS alternatives operating under similar module via robust decision support system (DSS).
Design/methodology/approach
In present research, the proposed module dealt with ecological (subjective) and fiscal (objective) criteria, where subjective criteria associated with incompleteness, vagueness, imprecision, as well as inconsistency, solicited the discrete information in terms of Grey set via linguistic scale from experts panel. The objective information (capital) has been assigned by expert’s panel in terms of Grey set. To robustly evaluate and select the admirable MHS, three approaches named: degree of possibility, technique for order preference similar to ideal solution as well as Grey relational analysis fruitfully applied to connect and unite discrete information.
Findings
The performance evaluation of MHSs has been carried out under concert of individual fiscal criteria excluding ecological criteria in past researches. Moreover the previous developed DSS tackled sole approach under individual fiscal criteria. The authors found the broad applications of fuzzy sets except Grey set theory in the same context for measuring the performance of MHS alternatives. Aforesaid research gaps have been transformed into research objectives by incorporating the module for both fiscal cum ecological criteria. This research embraces a robust DSS, which has been explored to select the admirable MHS alternative.
Originality/value
An empirical case study has been carried out in order to demonstrate the legitimacy of holistic Grey-MCDM method, implemented over multi criteria MHS hierarchical module. Proposed DSS seems to be the best for organisations, which believe to appraise and select the MHS including fiscal as well as ecological criteria excluding individual fiscal criteria. Moreover, subjective cum objective or individual subjective or objective criteria can be extended with respect to varieties of MHSs.
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Atul Kumar Sahu, Prabhu M. and K.T. Vigneswara Rao
The occurrence of COVID-19 has impacted the wide-reaching dimensions of manufacturing, materials, procurement, management, etc., and has loaded disruptions in the wide range of…
Abstract
Purpose
The occurrence of COVID-19 has impacted the wide-reaching dimensions of manufacturing, materials, procurement, management, etc., and has loaded disruptions in the wide range of supply chain (SC) activities. The impact of COVID-19 has twisted supplier performance and influenced stakeholders’ thinking towards selecting supplier sources and making strategic sourcing decision for convinced arrangement of construction management (CM) resources. Nowadays, suppliers are intently evaluated by stakeholders in post-COVID-19 phase to induce agile availability of CM resources. Accordingly, this paper aims to demonstrate competent CM dimensions under post COVID-19 scenario for ease managing construction projects by the stakeholders.
Design/methodology/approach
The authors have implicated Grey Sets Theory along with decision-making trial and evaluation laboratory (DEMATEL) technique for understanding significant outcomes. Varieties of diverse decision aspects responsible for strategically influencing supplier sourcing decision is projected under post COVID-19 scenario for handling construction projects by the stakeholders.
Findings
This study investigated sustainable construction management dimensions (SCMD) at the stage of resource deliveries and client aspirations under post COVID-19 situation. The study demonstrated “Lead time” as the most crucial, “Product Range” as the second and “Customers dealings and relationship” as the third crucial aspect considering by the stakeholders for selecting supplier sources based on the attainment of performance score of 0.1338, 0.1273 and 0.1268, respectively. It is found that high lead time stimulates the stakeholders to divert their orders to other competent supplier sources holding a low degree of lead time as compared.
Research limitations/implications
The present study rollovers its existence by serving critical thinking, conceptual modelling, criteria identification and evaluation under CM domain for drafting effectual strategies by the suppliers. The study investigated the impact of COVID-19 on stakeholders’ decision-making and enlisted SCMD that strategically stimulated them in choosing supplier sourcing decision.
Originality/value
The present study realizes the insights of stakeholders in the post COVID-19 scenario related to the supplier sources based on performance score. The study quantified sustainable supplier attribute for construction work and practices. The study analysed the expectations of the stakeholders purchasing different varieties of construction materials from supplier sources for civil works in the post COVID-19 scenario.
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Atul Kumar Sahu, Harendra Kumar Narang, Mridul Singh Rajput, Nitin Kumar Sahu and Anoop Kumar Sahu
Based on the existing literature in the field of green supply chain management (GSCM), the purpose of this paper is to find essential to conceptualize and develop an efficient…
Abstract
Purpose
Based on the existing literature in the field of green supply chain management (GSCM), the purpose of this paper is to find essential to conceptualize and develop an efficient appraisement platform for the purpose of benchmarking green alternative in supply chain network.
Design/methodology/approach
The authors explored multiple approaches, i.e. Višekriterijumsko kompromisno rangiranje (VIKOR), simple additive weighting (SAW) and grey relational analysis (GRA) by amalgamating fuzzy sets theory to select the most appropriate alternative for GSCM. The work is supported by triangular fuzzy number sets to choose the green alternative industry among available industries, while dealing with the uncertainty and vagueness in GSCM. A case study is exposed to identify strong and weak indices and to exhibit the feasibility of the proposed work.
Findings
It is requisite by the managers of many firms to identify the strong and weak indices relating their firms. Thus, the authors presented an approach for measuring and appraising the performance of the selected green alternative by determining the strong and weak indices. The presented work illustrates the performance measurement model that identifies comprehensive GSCM practices of the firms. The presented work incorporates green supply chain activities to support environmental sustainability throughout the supply chain.
Research limitations/implications
GSCM is necessary to the firms, as it considers impact onto the environment due to their supply chain activities. The authors build decision support system to facilitate the managers of various firms for modeling green practices in their decision making. The authors attempt to devise a conceptual framework linked with knowledge-based theory.
Originality/value
The authors conceptualized VIKOR, SAW and GRA methodology to rank and benchmark the green performance of distinguish alternative industries among available industries. Additionally, the performance measurement model for the selected significant green alternative is presented for determining the strong and weak indices.
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Xiaohui Guo, Atul kumar Sahu, Nitin Kumar Sahu and Anoop Kumar Sahu
In the presented research work, the authors fabricated the multiple MS plate (Grade: IS 2062) specimens and applied a novel integrated computational TRIFMRG approach with grey…
Abstract
Purpose
In the presented research work, the authors fabricated the multiple MS plate (Grade: IS 2062) specimens and applied a novel integrated computational TRIFMRG approach with grey relational analysis (GRA) toward solving weld bead optimization problem in MIG welding procedure. The objective of research is to determine the optimum setting between MIG welding input process parameters, e.g. welding current, open circuit voltage and thickness of plate in attaining high tensile strength with weld bead geometry quality characteristics, e.g. bead width, reinforcement, penetration and dilution in investigating define MS specimens.
Design/methodology/approach
The Taguchi's L9 orthogonal array (OA) design is respected to conduct the experiments on MS plate specimens to attain output objectives. Later, the evaluated multiple output objectives are transformed into single response by applying a novel integrated computational TRIFMRG approach with GRA. Thereafter, the outset of signal-to-noise ratio (S/N ratio) accompanied by ANOVA (Analysis of variance) is explored to optimize objective function.
Findings
The computed results are confirmed by conducting the experiments on same identical specimens. The outcome of the confirmation tests yielded an improvement of 0.24454, 0.372486, 0.686635 and 0.4106846 in grey relational grade (GRG), overall ratio index, reference grade and full multiplicative index, respectively, after validating the results.
Originality/value
In the presented work, the authors constructed a novel integrated computational TRIFMRG approach via clustering GRA, overall ratio index (ORI), full multiplicative index (FMI) with GRA-reference grade (RG) and tested as well as applied with Taguchi concept to attain objective of the research work.
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Nan Li, M. Prabhu and Atul Kumar Sahu
The main purpose of present study is to model the replacement policy under uncertainty for managerial application based on grey-reliability approach by considering the subjective…
Abstract
Purpose
The main purpose of present study is to model the replacement policy under uncertainty for managerial application based on grey-reliability approach by considering the subjective views of quality control circle (QCC). The study objectively links the optimality between individual replacement and group replacement policies for determining the minimum operational costs. The integrated framework between QCC, replacement theory, grey set theory and supply chain management is presented to plan replacement actions under uncertainty.
Design/methodology/approach
The study proposes the concept of grey-reliability index and built a decision support model, which can deal with the imprecise information for determining the minimum operational costs to plan subsequent maintenance efforts.
Findings
The findings of the study establish the synergy between individual replacement and group replacement policies. The computations related to the numbers of failures, operational costs, reliability index and failure probabilities are presented under developed framework. An integrated framework to facilitate the managers in deciding the replacement policy based on operational time towards concerning replacement of assets that do not deteriorate, but fails suddenly over time is presented. The conceptual model is explained with a numerical procedure to illustrate the significance of the proposed approach.
Originality/value
A conceptual model under the framework of such items, whose failures cannot be corrected by repair actions, but can only be set by replacement is presented. The study provides an important knowledge based decision support framework for crafting a replacement model using grey set theory. The study captured subjective information to build decision model in the ambit of replacement.
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Da Kang, M. Prabhu, Ramyar Rzgar Ahmed, Zhuo Zhang and Atul Kumar Sahu
In the present era, executives are shifting keenly toward industrial Internet of things (IIoTs) spheres. It is observed that IIoTs spheres become a key for each industry to grow…
Abstract
Purpose
In the present era, executives are shifting keenly toward industrial Internet of things (IIoTs) spheres. It is observed that IIoTs spheres become a key for each industry to grow up and bear the largest entrepreneurship opportunities globally and is linked to improve the shifting sphere of publics (SSPs). The core objective of research work is SSPs, which is nexus on secondary objectives. The authors proposed the two DSSs ( decision support systems) to full fill secondary objectives as discussing: In case of first objective, the authors proposed a fuzzy-DSS, which assists the executives to identify the weak and poor performing IIoTs spheres so that performance of IIoTs spheres can be accelerated. In case of second objective, grey-DSS aids the same executives to evaluate and benchmark alternative partner under considered IIoTs spheres so that the best partner can be chosen by company 4.0.
Design/methodology/approach
The authors conducted the significant systematic literature review and realistic empirical survey in the context of industry IIoTs spheres and extract the appropriate IIoTs spheres. Next, the authors built a framework by compiling the global standardized IIoTs spheres. The framework is utilized to build the two DSSs such as fuzzy- and grey-DSS (to full fill secondary objectives). The both DSSs are simulated by acting on a case study. The authors implemented the fuzzy set coupled with degree of similarity approach on proposing framework as a part of first case-objective and hybrid technique accompanied with grey set on same framework as a part of second case-objective, respectively.
Findings
A South African automobile parts manufacturing company is investigated as a case study company 4.0 for the prototype testing and simulation of DSSs. The performance gaps are computed and measured by subtracting each sphere's weight of functional units (FUs) from evaluated ideal weight. The weak performing spheres and FUs are suggested to be improved in future as a part of first objective. Next, A3 parts supplier/partner is advised as the best alternative by simulating the grey-DSS under IIoTs framework as a part of second case-objective. Both secondary objectives (two DSSs) are framed to attain the core objective (SSPs).
Originality/value
As discussed, the core objective of research work is to attain the SSPs, linked to secondary objectives. The research work integrates the knowledge and thinking of SSPs as well as IIoTs researchers to create the novel mathematical and statistical IIoTs in focusing on advance SSPs networks. The research work is momentous for entire Industry 4.0 companies, which troubles to bear more entrepreneurship opportunities (improving the SSPs) at global standard.
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Nitin Kumar Sahu, Atul Kumar Sahu and Anoop Kumar Sahu
Robot appraisement under various dimensions and directions is a crucial issue in real-time manufacturing scenario. Logistic robots are programable-independent movable devices…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Research limitations/implications
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.
Originality/value
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.
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Anil Kumar, Amit Pal, Ashwani Vohra, Sachin Gupta, Suryakant Manchanda and Manoj Kumar Dash
Supplier selection for capital procurement is a major strategic decision for any automobile company. The decision determines the success of the company and must be taken…
Abstract
Purpose
Supplier selection for capital procurement is a major strategic decision for any automobile company. The decision determines the success of the company and must be taken systematically with the utmost transparency. The purpose of this paper is to construct capital procurement decision-making model to optimize supplier selection in the Indian automobile industry.
Design/methodology/approach
To achieve the stated objective, a combined approach of fuzzy theory and AHP-DEMATEL is applied. Evaluation parameters are identified through an extensive literature review and criteria validation has been introduced through a Fuzzy Delphi method by using fuzzy linguistic scales to handle the vagueness of information. AHP is employed to find the priority weight of criteria, although an inter-relationship map among criteria is not possible through AHP alone since it considers all criteria as independent. To overcome this, DEMATEL is used to establish cause-effect relationships among criteria.
Findings
The results show that the total cost of ownership (TOC) is the first weighted criterion in supplier selection for capital procurement, followed by manufacturing flexibility and maintainability, then conformity with requirement. The cause-effect model shows that supplier profile, TOC, service support and conformity with requirement are in the cause group and are considered to be the most critical factors in selecting the supplier.
Originality/value
The study’s outcome can help the automobile industry to optimize their selection process in selecting their suppliers for capital procurement; the proposed model can provide guidelines and direction in this regard.
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Zitong He, Xiaolin Ma, Jie Luo, Anoop Kumar Sahu, Atul kumar Sahu and Nitin Kumar Sahu
Advanced manufacturing machines (AMMs) are searched as a momentous asset across the manufacturing societies for quenching and addressing the production units under economical…
Abstract
Purpose
Advanced manufacturing machines (AMMs) are searched as a momentous asset across the manufacturing societies for quenching and addressing the production units under economical circumstances, i.e. production of high-quality of goods under feasible cost. AMMs are significant in holding the managers against their rivals and competitors with high profit margins. The authors developed the decision support mechanism/portfolio (DSM-P) consist of knowledge-based cluster approach with a dynamic model. The purpose of research work is to measure overall economic worth of AMMs under objective and grey-imperfect (mixed) data by exploring the proposed DSM-P.
Design/methodology/approach
The authors developed the DSM-P that consist of knowledge-based cluster, three multi-criteria decision-making (MCDM) techniques-1-2-3 with complementary grey relational analysis-4(GRA), approach with a dynamic model (complied by technical plus cost and agility measures of AMMs). The proposed DSM-P enables the manager to map the overall economic worth of candidate AMMs under objective and grey-mixed data.
Findings
The presented DSM-P assist the managers for handling the selection problem of AMMs, i.e. CNCs, robots, automatic-guided vehicle, etc under mixed (objective cum grey) data. To enable the readers for intensely understand the work, the utility of proposed approach is displayed by illustrating a polar robot evaluation and selection problem. It is ascertained that the robot candidate-11 alternative is fulfilling the entire technical cum cost and agility measures.
Originality/value
The DSM-P provides more precise and reliable outcomes due to a usage of the dominance theory. Under the dominance theory, the ranks are obtained by MCDM techniques-1-2-3 are compared with ranks gathered by the GRA-4 under objective cum grey data, formed the novelties in presented research work. From a future perspective, the grey-based models in DSM-P can be built/extended/constructed more extensive and can be simulated by the same approach.
Details
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Atul Kumar Sahu, Anup Kumar, Anoop Kumar Sahu and Nitin Kumar Sahu
Today, industrial revolutions demands advanced technologies, means, mediums, tactics and so forth for optimizing their operating behavior and opportunities. It is probed that the…
Abstract
Purpose
Today, industrial revolutions demands advanced technologies, means, mediums, tactics and so forth for optimizing their operating behavior and opportunities. It is probed that the effectual results can be seized into system by not only developing advance means and technologies, but also capably adapting these developed technologies, their user interface and their utilization at optimum levels. Today, industrial resources need perfect synchronization and optimization for getting elevated results. Accordingly, present study is furnished with the purpose to expose quality-driven insights to march toward excellence by optimizing existing resources by the industrial organizations. The present study evaluates quality attributes of mechanical machineries for seizing performance opportunities and maintaining competitiveness via synchronizing and reconfiguring firm's resources under quality management system.
Design/methodology/approach
In the present study, Kano’s integrated approach is implemented for supporting decision rational concerning industrial assets. The integrative Kano–analytic hierarchy process (AHP) approach is used to reflect the relative importance of quality attributes. Kano and AHP tactics are integrated to define global relative weight and their computational medium is adapted along with ratio analysis, reference point theory and TOPSIS technique for understanding robust decision. The study described an interesting idea for underpinning quality attributes for benchmarking system substitutes. A machine tool selection case is discussed to disclose the significant aspect of decision-making and its virtual qualities.
Findings
The decision executives can realize massive benefits by streaming quality data, advanced information, technological advancements, optimum analysis and by identifying quality measures and disruptions for gaining performance deeds. The study determined quality measures for benchmarking machine tool substitute for industrial applications. Momentous machine alternatives are evaluated by means of technical structure, dominance theory and comparative analysis for supporting decision-making of industrial assets based on optimization and synchronization.
Research limitations/implications
The study linked financial, managerial and production resources under sole platform to present a technical structure that may assist in improving the performance of the manufacturing firms. The study provides a decision support mechanism to assist in reviewing the momentous resources to imitate a higher level of productive strength toward the manufacturing firms. The study endeavors its importance toward optimizing resources, which is an evident requirement in industries as the same not only saves money, escalates production, improves profit margins and so forth, but also gratifies the consumption of scarce natural resources.
Originality/value
The study stressed that advance information can be sought from system characteristics in the form of quality measures and attributes, which can be molded for gaining elevated outcomes from existing system characteristics. The same demands decision supports tools and frameworks to utilize data-driven information for benchmarking operations and supply chain activities. The study portrayed an approach for ease of utilizing data-driven information by the decision-makers for demonstrating superior outcomes. The study originally conceptualized multi-attributes appraisement framework associated with subjective cum objective quality measures to evaluate the most significant machine tool choice amongst preferred alternatives.