Synergy of fuzzy AHP and Six Sigma for capacity waste management in Indian automotive industry

Rathi, Rajeev; Khanduja, Dinesh; Sharma, Satpal

doi:10.5267/j.dsl.2015.1.005

Cited by 31 publications

(14 citation statements)

References 42 publications

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“…Vickery et al (2016) utilized hierarchical regression model to test hypotheses concerning the main effects of product and process modularity and the effects of their interactions with complexity on new product introduction performance, and the results are statistically verified. Rathia et al (2015) represented an approach for selection of capacity waste factors at an automotive industry using fuzzy logic based on the AHP method. The key customary parameters in the model are mined from the brainstorming session with DMs and reports from the literature.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy assessment analysis and key improvements to a production system

Shiau

Chang

2019

TQM

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Purpose The framework of Six Sigma Define-Measure-Analyze-Improve-Control was applied in this study, and various tools and techniques were used at different stages to implement lean measures to ensure quality. The purpose of this paper is to develop a decision-making framework that assesses key quality performance to ensure that practitioners improve quality and control by modeling and optimizing production processes. Design/methodology/approach A model of a quality performance index system was established. The weights of factors and sub-factors, which were estimated using an FAHP, were used as a reference for the decision maker under fuzzy uncertainly to make a decision, and thus, results present the bottlenecks in processes. Furthermore, any other factors that may affect the key process bottlenecks must be considered. The critical to quality characteristics were determined, and factor levels were set. The interaction between the factors was analyzed, their significance was studied using the Design of experiments and the parameters were predicted. Finally, quality improvement decisions were made through failure mode and effects analysis. Findings The implementation results of this research prove that the proposed model could successfully determine the key processes and focus on the improvement of critical quality factors under limited resources. Originality/value This study establishes a set of performance appraisal methods for production systems, which can be used for improving productivity and quality.

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Section: Introductionmentioning

confidence: 99%

Fuzzy assessment analysis and key improvements to a production system

Shiau

Chang

2019

TQM

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“…It is an organized approach to improve processes and services, since it is based on scientific and statistical tools to create significant reduction in variations (Johannsen et al, 2011). It has been accepted as a governing strategy that employs an incessant improvement methodology to reduce process variability and forced out capacity waste inside the processes using quality and statistical techniques (Rathi et al, 2015). Six Sigma improves organisational performance in order to boost customer's satisfaction on products and services.…”

Section: Introductionmentioning

confidence: 99%

“…MADM approach has been effectively used in a lot of decision making tasks in industrial and research field (Gwo-Hshiung, 2010). It includes a variety of decision making techniques like; Analytic Hierarchy Process (AHP) (Rathi et al, 2015), VlseKriterijumska Optimisacija I Kompromisno Resenje (VIKOR) (Tong, Chen, & Wang, 2007), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) (Yong, 2006), Additive Weighting (AW) (Modarres & Sadi-Nezhad, 2005), Weighted Product Method (WPM) (M. Wang, Liu, Wang, & Lai, 2010) and many more, and among these, VIKOR and TOPSIS are the outstanding approaches for decision making in complex situations (Opricovic & Tzeng, 2004). There are various applications for the VIKOR and TOPSIS approaches as reported in literature in various sectors like; material selection (Anojkumar et al, 2015), supply chain, supplier selection (Wu & Liu, 2011), health care sector (Zeng et al, 2013), renewable energy project selection (San Cristóbal, 2011), machine tool selection (Önüt et al, 2008) and many more (Devi, 2011;.…”

Section: Introductionmentioning

confidence: 99%

A fuzzy MADM approach for project selection: a six sigma case study

Rathi¹,

Khanduja²,

Sharma³

2016

10.5267/j.dsl

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Six Sigma is a strategic approach of significant value in achieving overall excellence. It helps to accomplish the organizations strategic aim through the effectual use of project controlled methodology. As Six Sigma is a project controlled approach, it is necessary to prioritize projects which give utmost economic benefits to the firm. In real practice, Six Sigma projects selection is very tough assignment because poor project selection also happens even in the well-managed organizations and this can weaken the success and trustworthiness of the Six Sigma practice. The present study aims to develop a project selection approach based on a combination of fuzzy and MADM technique to help organizations determine proper Six Sigma projects and identify the priority of these projects mainly in automotive companies. VIKOR and TOPSIS methods have been used to select the proper Six Sigma project composed with fuzzy logic. In this context, seven critical parameters have been considered for selection of finest alternative. The weights of evaluation criteria are obtained using the MDL (modified digital logic) method and final ranking is calculated through primacy index obtained by using fuzzy based VIKOR and TOPSIS methodology. A factual case study from automotive industry is used to investigate the efficacy of the planned approach.

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“…For this, the methodology of the fuzzy analytic hierarchy process (AHP) implemented by Buckley (1985) was employed. Fuzzy AHPs have been applied across a range of fields, including construction (Hsieh et al 2004;Jaskowski et al 2010), education (Goksu 2008;Celik, Kandakoglu, & Er 2009), human resources (Chou et al 2012), location selection (Bilisik et al 2014), marine engineering (Miri Lavasani et al 2011;Wang & Chin 2011;Celik & Kandakoglu 2012;Yanar & Tozan 2012), the automotive industry (Nepal et al 2010;Badizadeh & Khanmohammadi 2011;Bilgen & Sen 2012;Ghadimi et al 2012;Rathi et al 2015), supplier selection (Chan et al 2008;Kilincci & Onal 2011;Yucenur et al 2011;Shaw et al 2012;Rezaei et al 2014) and technology management (Erensal et al 2006). A comprehensive description of the methodology is expounded in the next section.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of shipyard selection criteria for shipowners using a fuzzy technique

Kafalı

Özkök

2015

Journal of Marine Engineering & Technology

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There are various stages to the process of acquiring a vessel. First, a decision must be made on what vessel is needed. Next, an appropriate shipyard is selected; this decision is very significant, as it will determine the workmanship quality and delivery date of the vessel to be manufactured. From the point of view of a shipowner, receiving the vessel on time and manufactured to specification is crucial. From the point of view of the shipyard, it is vital to take as many orders as possible; therefore, one of the highest priorities of shipyards is to be the first choice for as many shipowners as possible in order to increase their requirement for steel fabrication and consequently their profits. In this study, the shipyard selection criteria for shipowners are presented and the degree of importance of each criterion is determined using a fuzzy analytic hierarchy process (AHP) technique. The aim of the study is to provide shipyards with information about the perspective of shipowners with regard to the shipyard selection process, thus allowing shipyards to strengthen their weaknesses and increase the number of shipowners which choose them to manufacture their ships.

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Synergy of fuzzy AHP and Six Sigma for capacity waste management in Indian automotive industry

Cited by 31 publications

References 42 publications

Fuzzy assessment analysis and key improvements to a production system

Fuzzy assessment analysis and key improvements to a production system

A fuzzy MADM approach for project selection: a six sigma case study

Evaluation of shipyard selection criteria for shipowners using a fuzzy technique

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