Search results

1 – 10 of 41
To view the access options for this content please click here
Article
Publication date: 2 January 2018

Anoop Kumar Sahu, Nitin Kumar Sahu, Atul Kumar Sahu, Harendra Kumar Narang and Mridul Singh Rajput

In the presented research, the authors have conducted the literature review and organised real interviews of fruit retailers (FRs) to construct the advanced hierarchical…

Abstract

Purpose

In the presented research, the authors have conducted the literature review and organised real interviews of fruit retailers (FRs) to construct the advanced hierarchical structural (AHS) chain of macro-micro parameters for measuring the performances of defined fruit supply bazaars (FSBs). Apart from this, the purpose of this paper is to develop the grey set-based scorecard model for solving the proposed AHS chain of macro-micro parameters.

Design/methodology/approach

The performance of FSBs is linked with the supply of fruits towards clients under a feasible rate, which circuitously depends upon the evaluation of the economic locality of FSBs. The authors developed an advanced hierarchical structure of macro-micro parameters via a literature survey and considered these parameters based on the sampling score of FRs corresponding to select feasible FSBs/alternatives. Furthermore, the authors developed a grey set-based scorecard model for undertaking the incomplete information of FRs against the hierarchical structure.

Findings

It is found that the work is well suited for FRs as they can measure the performances of defined FSBs in accordance with their own opinions under the proposed AHS of macro-micro parameters. Apart from this, the work is useful for benchmarking the vegetable supply bazaars (VSBs) on the replacement of AHS. The proposed hierarchical structure with a grey-based scorecard model is flexible in its nature and can undertake more than 1,000 macro-micro parameters and FRs to access potential decision.

Originality/value

The conducted research work has a precise value for evaluating the economic FSB locality. The overall performance scores of considered FSB localities are computed as (∂1)=1.991, (∂2)=2.567 and (∂3)=2.855, where (∂3) is found to be more significant than available FSBs. This work can be used for opting the economic locality of VSB too.

To view the access options for this content please click here
Article
Publication date: 17 January 2020

Rohit Agrawal and Vinodh S.

Sustainable manufacturing facilitates the development of products with lower environmental impact. Additive manufacturing (AM) processes are incorporated with sustainable…

Abstract

Purpose

Sustainable manufacturing facilitates the development of products with lower environmental impact. Additive manufacturing (AM) processes are incorporated with sustainable characteristics such as minimum material consumption, energy efficiency and minimum transportation. The purpose of this paper is to report a study on sustainability evaluation of AM process using a grey-based approach.

Design/methodology/approach

Sustainable AM process is gaining importance. From this viewpoint, this paper presents the evaluation of sustainability of AM process. The evaluation model includes 3 enablers, 18 criteria and 54 attributes. Grey-based approach is used for sustainability evaluation. Expert inputs are used for computing the grey index. Expert inputs are obtained and they are aggregated at three levels to calculate the overall grey performance index, which indicates sustainability level of AM processes. Furthermore, weaker areas are identified through determination of grey performance importance index (GPII) values.

Findings

The calculated grey index is (3.510, 16.177), which implies that AM process is sustainable. Weaker attributes are determined on the basis of the computation of GPII values.

Practical implications

The study has been executed on the basis of the opinion from experts with practical experience. Hence, the inferences are found to be practically feasible. The identified weaker attributes from the study would enable the manufacturers and practitioners to focus more on weaker areas for enhancing the sustainability of AM processes. The study has made an evaluation from sustainability perspective of AM processes, which would enable practitioners to assess AM processes from TBL sustainability orientation.

Originality/value

The development of sustainability evaluation model and application of a grey-based approach for assessment of AM process are the original contributions of this study.

Details

Grey Systems: Theory and Application, vol. 10 no. 4
Type: Research Article
ISSN: 2043-9377

Keywords

To view the access options for this content please click here
Article
Publication date: 22 June 2021

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…

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.

Details

Grey Systems: Theory and Application, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2043-9377

Keywords

To view the access options for this content please click here
Article
Publication date: 5 July 2013

S. Mishra, S. Datta and S.S. Mahapatra

The purpose of this paper is to develop an agility evaluation approach to determine the most suitable agile system for implementing mass customization (MC) strategies…

Abstract

Purpose

The purpose of this paper is to develop an agility evaluation approach to determine the most suitable agile system for implementing mass customization (MC) strategies. Evaluating the alternatives and comparing across them, the best practices of the efficient organization can be identified and transferred to different organizations.

Design/methodology/approach

Grey relation approach is a simple mathematical technique useful in situations where the information is not known precisely. Grey relation approach has been applied to measure the agility of various organizations based on agile entities and accordingly the organizations are ranked. The ranking so obtained is compared with the ranking obtained by a popular multi‐attribute decision making (MADM) process known as Fuzzy TOPSIS (technique for order preference by similarity to ideal solution) to test the robustness of the proposed method. It is to be noted that grey theory considers the condition of the fuzziness and can deal flexibly with the fuzziness situation.

Findings

It is demonstrated that the grey approach is an appropriate method for solving MADM problems in an uncertain situation with less computational efforts. The alternatives can easily be benchmarked and the best agile system can be selected. As the ranking obtained through grey relation approach closely agree with the ranking found from Fuzzy TOPSIS method, the robustness of the proposed approach is validated. Both the methods lead to choosing a suitable agile system related to mass customization.

Research limitations/implications

In this paper, the proposed approach has been compared with Fuzzy TOPSIS method to test the robustness of the method. Other MADM approaches may be used for comparison purpose to gain insight into the methodology of the proposed approach.

Originality/value

An alternative approach for MADM is proposed to obtain good decisions in an uncertain environment and used for agility evaluation in selected organizations. As agile manufacturing is relatively a new concept, certain and complete information on systems are not available. In such situations, the proposed method can deal with the issue conveniently and results in workable solutions.

Details

Benchmarking: An International Journal, vol. 20 no. 4
Type: Research Article
ISSN: 1463-5771

Keywords

To view the access options for this content please click here
Article
Publication date: 17 May 2018

Atul Kumar Sahu, Deepti Naval, Harendra Kumar Narang and Mridul Singh Rajput

Agile practices are important for executing business dealings proficiently in today’s scenario, as they thrust on implicating strategies for meeting quick market…

Abstract

Purpose

Agile practices are important for executing business dealings proficiently in today’s scenario, as they thrust on implicating strategies for meeting quick market requirements. These practices are noteworthy from the point of competitiveness and for fulfilling customer’s demands speedily and promptly. The purpose of this paper is to appraise agile supplier selection dilemma based on analytical hierarchy process (AHP), which accompanied grey information. The authors drafted a group of momentous agile supplier selection measures, which can be utilized by the group of industrial and manufacturing industries to measure the status of agile parameters in their partner firms. G-TOPSIS approach to handling the case of agile supplier selection problem is presented by the authors in this work.

Design/methodology/approach

The conception of AHP, grey theory and TOPSIS techniques is fused in this study, under the application arena of agile supply chain management (ASCM). The AHP principals are implicated in the first phase to define the priority importance weights of agile measures and, additionally, grey theory and TOPSIS principals are fused in the second phase to fabricate a significant agile supplier selection model.

Findings

A merged approach accompanying multiple measures is developed for aiding decision making and for modeling qualitative characteristics of agile arena under grey domain. The present work can be utilized to access the agile performance characteristics of the organization and can define the status of their partner suppliers. The technical guidelines of AHP and G-TOPSIS approach are explained in this study to be implicated in distinguish decision fields. An educational podium for dispensing the theoretical knowledge on supply chain management, ASCM and agility is presented in this study.

Originality/value

A second-level hierarchical structure is built by the authors to facilitate the managers in taking effective decision pertaining to agile measure in their organizations. The lists of qualitative characteristics are catalogued from the literature review in this study. The built model can undertake risk associated in defining the nature of agile criterions as grey concept can undertake risk associated with the system. Thus, the authors implicated G-TOPSIS approach to handling the case of agile supplier selection problem in this study. The presented hierarchical structure will capably assist the industrial and manufacturing firms to react toward random and unpredictable market requirements, along with attaining organizations goals and profits.

Details

Grey Systems: Theory and Application, vol. 8 no. 3
Type: Research Article
ISSN: 2043-9377

Keywords

To view the access options for this content please click here
Article
Publication date: 20 January 2012

Chunguang Bai, Joseph Sarkis, Xiaopeng Wei and Lenny Koh

The purpose of this paper is to introduce a methodology to help evaluate, select, and monitor sustainable supply chain performance measurement that can be integrated into…

Abstract

Purpose

The purpose of this paper is to introduce a methodology to help evaluate, select, and monitor sustainable supply chain performance measurement that can be integrated into a performance management system (PMS).

Design/methodology/approach

Grey‐based neighborhood rough set theory is used to help arrive at a core set of important business and environmental performance measures for sustainable supply chains. The supply chain operations reference (SCOR) model is used to develop both business and environmental measures for supply chain sourcing.

Findings

A case illustration shows the applicability of the methodology. A sensitivity analysis shows that variations in outcome considerations may greatly influence the set of key performance measures for a sustainable supply chain PMS.

Research limitations/implications

The methodology and presentation is conceptual, yet the tool can provide very useful interpretations for both researchers and practitioners.

Practical implications

The tool can be valuable for companies that are trying to identify key environmental and business performance measures for their supply chains. It helps save resources by not requiring the management of a burdensome and complex set of performance measures.

Originality/value

This is one of the few approaches that helps to clearly identify and narrow the set of performance measures for sustainable supply chains. It attempts to do so with minimal information loss. It is also the first time that grey techniques have been integrated with neighborhood rough set methodology.

Details

Supply Chain Management: An International Journal, vol. 17 no. 1
Type: Research Article
ISSN: 1359-8546

Keywords

To view the access options for this content please click here
Article
Publication date: 1 April 2021

Tooraj Karimi and Arvin Hojati

The purpose of this paper is to design an inference engine to measure the level of readiness of each bank before starting the corporate sustainability auditing process…

Abstract

Purpose

The purpose of this paper is to design an inference engine to measure the level of readiness of each bank before starting the corporate sustainability auditing process. Based on the output of the designed inference engine, the audition team can decide about the audition resources and the auditing process.

Design/methodology/approach

In this paper, the hybrid rough and grey set theory are used to design and create a rule model system to measure the sustainability level of banks. First, 16 rule models are extracted using rough set theory (RST), and the cross-validation of each model is done. Then, the grey clustering is used to combine the same condition attributes and improve the validity of the final model. A total of 16 new rule models are extracted based on the decreased condition attributes, and the best model is selected based on the cross-validation results.

Findings

By comparing the accuracy of rough-gray’s rule models and as a result of decreasing the condition attributes, a proper increase in the accuracy of all models is obtained. Finally, the Naive/Genetic/object-related reducts model with 95.6% accuracy is selected as an inference engine to measure new banks’ readiness level.

Originality/value

Sustainability measurement of banks based on RST is a new approach in the field of corporate sustainability. Furthermore, using the grey clustering for combining the condition attributes is a novel solution for improving the accuracy of the rule models.

Details

Journal of Modelling in Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-5664

Keywords

To view the access options for this content please click here
Article
Publication date: 18 June 2020

Tooraj Karimi and Arvin Hojati

In this study, a hybrid rough and grey set-based rule model is designed for diagnosis of one type of blood cancer called multiple myeloma (MM). The grey clustering method…

Abstract

Purpose

In this study, a hybrid rough and grey set-based rule model is designed for diagnosis of one type of blood cancer called multiple myeloma (MM). The grey clustering method is used to combine the same condition attributes and to improve the validity of the final model.

Design/methodology/approach

Some tools of the rough set theory (RST) and grey incidence analysis (GIA) are used in this research to analyze the serum protein electrophoresis (SPE) test results. An RST-based rule model is extracted based on the laboratory SPE test results of patients. Also, one decision attribute and 15 condition attributes are used to extract the rules. About four rule models are constructed due to the different algorithms of data complement, discretization, reduction and rule generation. In the following phases, the condition attributes are clustered into seven clusters by using a grey clustering method, the value set of the decision attribute is decreased by using manual discretizing and the number of observations is increased in order to improve the accuracy of the model. Cross-validation is used for evaluation of the model results and finally, the best model is chosen with 5,216 rules and 98% accuracy.

Findings

In this paper, a new rule model with high accuracy is extracted based on the combination of the grey clustering method and RST modeling for diagnosis of the MM disease. Also, four primary rule models and four improved rule models have been extracted from different decision tables in order to define the result of SPE test of patients. The maximum average accuracy of improved models is equal to 95% and related to the gamma globulins percentage attribute/object-related reducts (GA/ORR) model.

Research limitations/implications

The total number of observations for rule extraction is 115 and the results can be improved by further samples. To make the designed expert system handy in the laboratory, new computer software is under construction to import data automatically from the electrophoresis machine into the resultant rule model system.

Originality/value

The main originality of this paper is to use the RST and GST together to design and create a hybrid rule model to diagnose MM. Although many studies have been carried out on designing expert systems in medicine and cancer diagnosis, no studies have been found in designing systems to diagnose MM. On the other hand, using the grey clustering method for combining the condition attributes is a novel solution for improving the accuracy of the rule model.

Details

Grey Systems: Theory and Application, vol. 10 no. 4
Type: Research Article
ISSN: 2043-9377

Keywords

To view the access options for this content please click here
Article
Publication date: 15 October 2020

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…

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.

To view the access options for this content please click here
Article
Publication date: 2 February 2015

Santosh Kumar Sahu, Saurav Datta and Siba Sankar Mahapatra

Supply chain performance (SCP) extent can be attributed as a function of multiple criteria/attributes. Most of the criterions/attributes being intangible in nature; SCP…

Abstract

Purpose

Supply chain performance (SCP) extent can be attributed as a function of multiple criteria/attributes. Most of the criterions/attributes being intangible in nature; SCP appraisement relies on the subjective judgment of the decision makers. Moreover, quantitative appraisement of SCP appears to be very difficult due to involvement of ill-defined (vague) performance measures as well as metrics. The purpose of this paper is to develop an efficient decision support system (DSS) to facilitate SCP appraisement, benchmarking and related decision making.

Design/methodology/approach

This study explores the concept of fuzzy logic in order to tackle incomplete and inconsistent subjective judgment of the decision makers’ whilst evaluating supply chain’s overall performance. Grey relational analysis has been adopted in the later stage to derive appropriate ranking of alternative companies/enterprises (in the same industry) in view of ongoing SCP extent.

Findings

In this work, a performance appraisement index system has been postulated to gather evaluation information (weights and ratings) in relation to SCP measures and metrics. Combining the concepts of fuzzy set theory, entropy, ideal and grey relation analysis, a fuzzy grey relation method for SCP benchmarking problem has been presented. First, triangular fuzzy numbers and linguistic evaluation information characterized by triangular fuzzy numbers have been used to evaluate the importance weights of all criteria and the superiority of all alternatives vs various criteria above the alternative level. Then, the concept of entropy has been utilized to solve the adjusted integration weight of all objective criteria above the alternative level. Moreover, using the concept of the grey ration grades, various alternatives have been ranked accordingly.

Originality/value

Finally, an empirical example of selecting most appropriate company has been used to demonstrate the ease of applicability of the aforesaid approach. The study results showed that this method appears to be an effective means for tackling multi-criteria decision-making problems in uncertain environments. Empirical data have been analysed and results obtained thereof, have been reported to exhibit application potential of the said fuzzy grey relation based DSS in appropriate situation.

Details

Grey Systems: Theory and Application, vol. 5 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

1 – 10 of 41