Defect control analysis for improving quality and productivity: an innovative Six Sigma case study

Shanmugaraja, M.; Nataraj, M.; Gunasekaran, N.

doi:10.1504/ijqi.2011.040428

Cited by 14 publications

(5 citation statements)

References 28 publications

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“…These databases provide online delivery systems with full text access to thousands of high-quality articles and journals that cover a wide range of case studies of casting, chemical, textile, plastic, paper, steel manufacturing, auto, food processing, aerospace, electric and electronics industries. There are 112 research case studies taken for the critical review and analysis of measuring the success of Six Sigma in manufacturing industry (Thomas et al , 2016; Sahoo et al , 2007; Kuthe and Tharakan, 2009; Laureani and Antony, 2012; Singh and Khanduja, 2014; Chiarini, 2015; Andrew, 2009; Andrew and Barton, 2006; Andrew et al , 1994; Rivera and Marovich, 2001; Prashar, 2014a,b; Prashar, 2015; Singh et al , 2012; Bilgen and Sen, 2012; Cheng and Kuan, 2012; Hardeman and Goethals, 2011; Desai, 2012; Desai, 2008; Powell et al , 2017; Pranckevicius et al , 2008; Gijo et al , 2011; Gijo and Scaria, 2010; Gijo et al , 2014; Gijo et al , 2014; Lin and Wong, 2014; Amitrano and Lígia de Oliveira, 2014; Filardi et al , 2015; Wang and Chen, 2012; Radha Krishna and Dangayach, 2007; Nithyanandama and Pezhinkattilb, 2014; Maheshwar, 2012; Besseris, 2011; Barbosa et al , 2014; Sekhar and Mahanti, 2003; Hong, 2012; Nunes, 2015; Wu et al , 2011; Antony et al , 2012; Antony et al , 2016; Chen et al , 2014; Leu and Lee, 2016; Srinivasan et al , 2016; Srinivasan et al , 2014a, b; Chen et al , 2006; Srinivasan et al , 2014a, b; Gupta et al , 2014; Lee and Wei, 2010; Meng et al , 2011; Simanova, 2015; Kumar et al , 2006; Shanmugaraja et al , 2011; Kumar et al , 2007; Dora and Gellynck, 2015; Cabrita et al , 2015; Franchetti and Yanik, 2011; Franchetti and Pukhraj, 2013; Cournoyer et al , 2012; Zhang et al , 2014; Zhang et al , 2014; Shu et al , 2012; Kim et a...…”

Section: Research Methodology Adopted For Studymentioning

confidence: 99%

“…Six Sigma helps to improve productivity, quality of product and achieve customer delight for the auto sector. Kumaravadivel and Natarajan (2013), Singh et al (2016), Kumar et al (2006), Shanmugaraja et al (2011) and Kumar et al (2011) implemented Six Sigma methodology to reduce defects in the process. Srinivasan et al (2014a, b) reduced defects of paint line in shock absorber by using Six Sigma methodology.…”

Section: Classification Frameworkmentioning

confidence: 99%

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Critical review and analysis of measuring the success of Six Sigma implementation in manufacturing sector

Patel

Desai²

2018

IJQRM

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Purpose The purpose of this paper is to capture the status of implementation of Six Sigma in various manufacturing industries and also examine the success of the Six Sigma by using different performance indicators. Design/methodology/approach The methodology of critical review involves the selection and classification of 112 research articles on the implementation of Six Sigma in different manufacturing industries. The selected articles are categorized by the following: articles distribution based on the year of publication, publication database, various journals, contribution of authors, continent, scale of industry, implemented approaches, focused industry, tools and techniques used in phases of Six Sigma methodology, and performance indicators used in Six Sigma implementation. Then after, future scopes of research opportunities are derived based on significant findings. Findings The literature revealed that: Very few work was undertaken on the implementation of Six Sigma in various manufacturing industries like ceramic, paper, gems and jewelry, cement, furniture, stone, fertilizer, forging, paper and surface treatment industries. Most of the researchers have considered very few performance indicators to identify the improvement after Six Sigma implementation. But, there is no clue regarding overall improvement in different perspectives after the implementation of Six Sigma. The financial indicators, personnel indicators, process indicators and customer indicators are useful to measure the overall improvement after the implementation of Six Sigma in the manufacturing sector. Research limitations/implications The study was carried out on the implementation of Six Sigma methodology in various manufacturing industries, and various performance indicators were identified while implementing the Six Sigma methodology. Case studies pertaining to service industries were not covered here. Originality/value Very little research has been carried out to measure the overall success of implementing Six Sigma methodology in manufacturing industries. This paper will provide value to students, researchers and practitioners of Six Sigma by providing insight into the implementation of Six Sigma in manufacturing industries.

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Section: Research Methodology Adopted For Studymentioning

confidence: 99%

Section: Classification Frameworkmentioning

confidence: 99%

Critical review and analysis of measuring the success of Six Sigma implementation in manufacturing sector

Patel

Desai²

2018

IJQRM

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“…According to a study by Shanmugaraja et al [10], it was found that in India, six sigma has been applied in small and medium enterprises (SMEs) by introducing the DMAIC process in the casting process to reduce the rejection rate that occurs. Desai and Prajapati [2] have implemented the six sigma DMAIC process in steel and plastic manufacturing industries, which face a high number of sorting problems.…”

Section: Experimental Designmentioning

confidence: 99%

An Application of Six Sigma for Optimality of Medium Density Fiberboard Production

Jitsamruay¹,

Chinram²,

Poolyarat³

et al. 2023

Int. J. Anal. Appl.

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During the production process of MDF, there is a high level of internal bond (IB) variation. This results in the waste of out-of-standard IB values that account for 0.38 % with damage value over 1 million baht/year. The company required products with fewer volatile compounds from formaldehyde adhesives, focusing on reducing the amount of adhesive but still being strong according to IB-specification which will reduce the cost of production by about 20 − 30 million baht/year. The results of wood sampling and IB testing were divided into 6 areas, namely IB1-IB6. It was found that most of the data were symmetrical except for the IB5 data as the area where the most variation occurs. The distributions of the IB1 and IB6 data showed relatively low variability compared to data from other areas. IB1 - IB6 values were normal distribution, expect for IB5. Process capacity in IB2 was relatively high compared to IB from other areas. From the Correlation Matrix and Correlation Map, it was found that the variables that influenced the IB were Press Factor, % Dosing Glue, Heat Circuit1, Primary Circuit Intel and % Mc After Gluing. To conduct the experiment and find the best variable conditions by 25-2 - Factorial Design (Resolution: III). It was found that Glue = 7.4, Heat1 = 234.4, and Press = 6.5 would give IB = 0.88 which was closest to target (0.7). Glue = 7.1, Heat1 = 233.2, and Press = 6.48 would give IB = 1.15 which was the highest value. Results of production conditions at optimum or maximum that can be generalized from Rayleigh Method Dimensional Analysis was found that at the levels of 7.85, 254.28 and 257.70 of Glue, Heat1 and PrimCirIn, the target response (IB) was 0.7. and at the levels of 8.07, 233.35 and 281.60 of Glue, Heat1 and PrimCirIn resulted in a response value (IB) of 1.27.

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“…In another case study of automobile ancillary SME located in south India, producing automobile aluminum components for various clienteles in India and abroad, Six Sigma was applied to casting process of a two-stroke engine oil pump body to reduce rejection rate mainly due to blow holes. With the application of DMAIC methodology rejection rate was reduced to 4.8 from 17.22 per cent (Shanmugaraja et al , 2011). Ghosh and Maiti (2014) implemented DMAIC approach in a large foundry located in western India to reduce large rejection rate in one of the critical products, grey iron cylinder head casting used in automobiles.…”

Section: Literature Reviewmentioning

confidence: 99%

Competitive advantage through Six Sigma at plastic injection molded parts manufacturing unit

Desai¹,

Prajapati

2017

IJLSS

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Purpose The purpose of this paper is to illustrate the successful application of Six Sigma at a small and medium scale plastic parts manufacturing unit. Overall operational excellence is one of the foundations of global competiveness. Indian industries are also keeping up with achieving and maintaining operational excellence through different improvement tools and methodologies. Plastic parts manufacturing industries in India are also on the move to increase their overall quality, productivity and profitability. However, it appears from the available literature that application of Six Sigma, one of the most effective breakthrough improvement strategies having direct impact on bottom line of the organization, is not being explored to its full potential, especially at plastic parts manufacturing industries in India. This study was thus undertaken at plastic products manufacturing plant to introduce Six Sigma to them by applying the same to their chronic problems and drawing improvements in quality, productivity and profitability. Design/methodology/approach This paper illustrates the real-life case study of improving quality and productivity of injection molding process by phase wiz application of define, measure, analyze, improve and control, the process improvement methodology of Six Sigma. Findings The critical defects, such as short molding, contamination, injection point and flash are reduced from the process leading to annual savings of INR 10.80 lacs. This is a considerable amount for a small concern in question. Research limitations/implications Because this was the pilot project and the firm was of small and medium size, data collection was the major issue, which consequently took considerable time and efforts at define and measure phases. Injection molding is a very salient process for plastic products manufacturing. Almost one-third of plastic products are made by this process. Thus, improving quality of products made out of injection molding process is of paramount importance. The paper is an attempt to exhibit how a small-scale plastic injection molded parts manufacturing unit can put fruitful efforts to achieve competitive advantage through Six Sigma. Originality/value From the review of literature, it appears that application of Six Sigma among plastic parts manufacturing units, especially small and medium, is very rare, not in India but across the globe. This case study has opened up the direction to small- and medium-scale plastic parts manufacturing units to implement Six Sigma and to move a step forward toward achieving competitive advantage.

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Defect control analysis for improving quality and productivity: an innovative Six Sigma case study

Cited by 14 publications

References 28 publications

Critical review and analysis of measuring the success of Six Sigma implementation in manufacturing sector

Critical review and analysis of measuring the success of Six Sigma implementation in manufacturing sector

An Application of Six Sigma for Optimality of Medium Density Fiberboard Production

Competitive advantage through Six Sigma at plastic injection molded parts manufacturing unit

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