Statistical techniques for quality

Xie, Min; Goh, T.N.

doi:10.1108/09544789910272913

Cited by 41 publications

(27 citation statements)

References 6 publications

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“…There are two important aspects associated with SPC implementation: the managerial aspect, also called organizational; and the technical or operational aspects (Does et al, 1997;Mason & Antony, 2000;Elg et al, 2008;Putri & Yusof, 2008;Rohani et al, 2009;Rohani et al, 2010;Xie & Goh, 1999). These two aspects of SPC implementation were taken into consideration in the analysis conducted in the current study.…”

Section: Identifying Csf For Spc Implementationmentioning

confidence: 99%

“…The most cited CSFs in the literature (80% of the 173 citations about CSF) are shown in Table 1. (1) Gordon et al (1994), (2) Does et al (1997), (3) Rungtusanatham et al (1999), (4) Xie & Goh (1999), (5) Mason & Antony (2000), (6) Antony et al (2000), (7) Rungasamy et al (2002), (8) Antony & Taner (2003), (9) Grigg & Walls (2007a), (10) Grigg & Walls (2007b), (11) Chen et al (2008), (12) Elg et al (2008), (13) Putri & Yusof (2008), (14) Phyanthamilkumaran & Fernando (2008), (15) Rohani et al (2009), (16) Rohani et al (2010), (17) Mahanti & Evans (2012), (18) Rantamaki et al (2013), (19) Sharma & Kharub (2014), (20) Lim et al (2014).…”

Section: Identifying Csf For Spc Implementationmentioning

confidence: 99%

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Impact analysis of critical success factors on the benefits from statistical process control implementation

Soriano

Oprime

Lizarelli

2017

Prod.

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The Statistical Process Control -SPC is a set of statistical techniques focused on process control, monitoring and analyzing variation causes in the quality characteristics and/or in the parameters used to control and process improvements. Implementing SPC in organizations is a complex task. The reasons for its failure are related to organizational or social factors such as lack of top management commitment and little understanding about its potential benefits. Other aspects concern technical factors such as lack of training on and understanding about the statistical techniques. The main aim of the present article is to understand the interrelations between conditioning factors associated with top management commitment (Support), SPC Training and Application, as well as to understand the relationships between these factors and the benefits associated with the implementation of the program. The Partial Least Squares Structural Equation Modeling (PLS-SEM) was used in the analysis since the main goal is to establish the causal relations. A cross-section survey was used as research method to collect information of samples from Brazilian auto-parts companies, which were selected according to guides from the auto-parts industry associations. A total of 170 companies were contacted by e-mail and by phone in order to be invited to participate in the survey. However, just 93 industries agreed on participating, and only 43 answered the questionnaire. The results showed that the senior management support considerably affects the way companies develop their training programs. In turn, these trainings affect the way companies apply the techniques. Thus, it will reflect on the benefits gotten from implementing the program. It was observed that the managerial and technical aspects are closely connected to each other and that they are represented by the ratio between top management and training support. The technical aspects observed through SPC application directly affect the benefits from the program.

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Section: Identifying Csf For Spc Implementationmentioning

confidence: 99%

Section: Identifying Csf For Spc Implementationmentioning

confidence: 99%

Impact analysis of critical success factors on the benefits from statistical process control implementation

Soriano

Oprime

Lizarelli

2017

Prod.

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“…These two aspects have an impact on business competitiveness, especially in improving the industry productivity and quality of products (Xie & Goh, 1999;Bamford & Greatbanks, 2005;Sadikoglu & Zehir, 2010;Hoerl & Snee, 2010).…”

Section: Introductionmentioning

confidence: 99%

“…There are several books and papers on the use of statistical tools and technics for improving quality and productivity (Box et al, 1978;Chen, 1997;Xie & Goh, 1999;Jones et al, 2001;Montgomery & Runger, 2003;Bamford & Greatbanks, 2005;Ehie & Sheu, 2005;He & Grigoryan, 2005;Chakraborti, 2006;Triefenbach, 2008;Chakraborti et al, 2008;Hoerl & Snee, 2010;Boone & Chakraborti, 2011;Zhang et al, 2011;Oprime & Ganga, 2013;Montgomery, 2013;Bataineh & Al-Dwairi, 2012). Employees have started to join improvement groups, mainly through Kaizen programs, and they have been trained in statistical technics of quality monitoring and control.…”

Section: Introductionmentioning

confidence: 99%

A bibliometric analysis of 50 years of worldwide research on statistical process control

et al. 2016

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Resumo: Um crescente número de trabalhos sobre controle estatístico do processo (CEP) emergiu nos últimos cinquentaAbstract: An increasing number of papers on statistical process control (SPC) has emerged in the last fifty years, especially in the last fifteen years. This may be attributed to the increased global competitiveness generated by innovation and the continuous improvement of products and processes. In this sense, SPC has a fundamentally important role in quality and production systems. The research in this paper considers the context of technological improvement and innovation of products and processes to increase corporate competitiveness. There are several other statistical technics and tools for assisting continuous improvement and innovation of products and processes but, despite the limitations in their use in the improvement projects, there is growing concern about the use of SPC. A gap between the SPC technics taught in engineering courses and their practical applications to industrial problems is observed in empirical research; thus, it is important to understand what has been done and identify the trends in SPC research. The bibliometric study in this paper is proposed in this direction and uses the Web of Science (WoS) database. Data analysis indicates that there was a growth rate of more than 90% in the number of publications on SPC after 1990. Our results reveal the countries where these publications have come from, the authors with the highest number of papers and their networks. Main sources of publications are also identified; it is observed that the publications of SPC papers are concentrated in some of the international research journals, not necessarily those with the major high-impact factors. Furthermore, the papers are focused on industrial engineering, operations research and management science fields. The most common term found in the papers was cumulative sum control charts, but new topics have emerged and have been researched in the past ten years, such as multivariate methods for process monitoring and nonparametric methods.

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“…Statistical Process Control (SPC) is a statistical approach for assisting operators, supervisors and managers to manage quality and to eliminate special causes of variability in a process [19]. The initial role of SPC is to prevent rather than identify product or process deterioration, but Xie and Goh (1999) suggest for its new role to actively identifying opportunities for process improvement [20]. The main tools in SPC are control charts.…”

Section: Statistical Process Controlmentioning

confidence: 99%

Assessing the Awareness and Usage of Quality Control Tools with Emphasis to Statistical Process Control (SPC) in Ethiopian Manufacturing Industries

Berhe¹,

Gidey²

2016

IIM

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Introduction: The present work was devoted to assess the awareness and usage of quality control tools with the emphasis on statistical process control in Ethiopian manufacturing industries. Semi structured questionnaire has been employed to executive and technical managers of manufacturing industries of various size and specialism across the country. Stratified random sample method by region was used to select sample industries for the study. The samples used for this study are industries mainly from Oromiya, Addis Ababa, Tigray, Amara, SNNP and Dire-dawa regions proportional to their size of the available industries. Methods: Exploratory method and descriptive statistics was used for data analysis. Available documents and reports related to quality control policy of the selected companies were investigated. Results and Discussions: The number of manufacturing industries involved in this study was 44. Of the sampled manufacturing industries about 60% are from Oromiya and Addis Ababa regions. It has been reported that 100% of the respondents said that the importance of quality control tools is very important to their organizations' productivity and quality improvement (Figure 3). Quality control professionals were also asked the extent to which quality control system is working in their industry and majority of the respondents (45%) have indicated that quality control system is working to some extent in their respective industries (Figure 18). Conclusions and Recommendations: Most of the quality department of the industries did not fully recognize the importance of statistical process control as quality control tools. This is mainly due to lack of awareness and motivation of the top managements, shortage of man power in the area, and others together would make it difficult to apply quality control tools in their organization. In general, the industries in Ethiopia are deficient in vigor and found to be stagnant hence less exposed to a highly competitive market and don't adopt the latest quality control techniques in order to gain knowledge about systems to improve quality and operational performance. We conclude that quality management system has to be established as an independent entity with a real power and hence the quality control department which is responsible for quality can make an irreversible decision with respect to quality of any given product. Moreover, the concerned bodies (government and ministry of industries) should give attention and work together with universities to ensure how these statistical process control techniques could be incorporated in a curriculum of the universities at higher levels in degree and masters programs. Furthermore, different trainings which could improve quality and efficiency of their respective management system should be given as short and long term to the employees including top and middle managers found in various industries relevant to their process.

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Statistical techniques for quality

Cited by 41 publications

References 6 publications

Impact analysis of critical success factors on the benefits from statistical process control implementation

Impact analysis of critical success factors on the benefits from statistical process control implementation

A bibliometric analysis of 50 years of worldwide research on statistical process control

Assessing the Awareness and Usage of Quality Control Tools with Emphasis to Statistical Process Control (SPC) in Ethiopian Manufacturing Industries

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