Attaining competitive positioning through SPC – an experimental investigation from SME

Sharma, Rajiv Kumar; Kharub, Manjeet

doi:10.1108/mbe-10-2013-0050

Cited by 24 publications

(32 citation statements)

References 41 publications

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“…However, it demands time to employees to dedicate to SPC and to make the appropriate decisions to apply the control charts; to observe the technical aspects, such as the statistical assumptions used at the time to generate the chart; to identify the critical characteristics during the application of the statistical control charts; and to analyze and remove the special causes. Such time demand requires top management support to be fulfilled (Lim & Antony, 2013;Mahanti & Evans, 2012;Sharma & Kharub, 2014). Therefore, the present study aims at confirming the following research hypothesis:…”

Section: Formulating the Research Hypothesesmentioning

confidence: 61%

“…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%

“…In case the process is out of control, the mechanisms that enable the operator to make adjustments whenever necessary should be adopted in order to bring the process back to stability Ahmed et al (2012), Bhote (1987), Lim & Antony (2013), Mahanti & Evans (2012), Sharma & Kharub (2014).…”

Section: Identifying the Research Variablesmentioning

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: Formulating the Research Hypothesesmentioning

confidence: 61%

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 application of statistical tools such as control charts, histogram, caused and effect diagram along with process capability analysis is presented in the study to eliminate quality problems arising out of various assignable causes during machining of crankcase. It is observed from the study that when the special or assignable causes of variation are present in manufacturing, the process is deemed to be outof-control then use of SPC [5]. Depend on this view in this research SPC will use for knowing the condition of quality control.…”

Section: Introductionmentioning

confidence: 96%

Quality Control of Product: Statistical Process Control

Putri¹,

Septyandi²,

Rohandani³

2016

Proceedings of the 2016 Global Conference on Business, Management and Entrepreneurship

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the problems faced by PT. Wahana Java Semesta Intermedia are still the emergence of defect products in every production and it escaped from quality control checked thus it reaches the consumer. This study aimed to analyze the application of products quality control system applied in PT. Wahana Java Semesta Intermedia, Radar Banten Newspaper products whether it is well within the control or not and looking for the factors that causing to the defect products. Data collection and information obtained from interviews and documentation for the number of products and production defects for three months in PT. Wahana Java Semesta Intermedia. The methods used to analyze products quality control by using statistical process control and fishbone diagram to determine the cause of defects products. Results showed that products quality control in PT. Wahana Java Semesta Intermedia is still controlled by the largest type of defects that is blurred ink with defects percentage 59.79% and with 1.26% percentage of defects from amount of checked production. Factors causing defects products are human, machine, work methods, environment and materials, in this case human is the primary cause of defects products.

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“…This may be a result of: i) cultural paradigms; ii) the types of groups used to promote and improve the field of statistical quality control, such as task force and semi-autonomous groups; iii) governance within groups (centralized or decentralized, use of specific methods or routines and monitoring of activities); and iv) understanding and applying new technics and tools in the problem identification stage and solution (Juran & Gryna, 1991;Atkinson, 1994;Chapman & Hyland, 1997;Bond, 1999;Harrison, 2000;Bechet et al, 2000;Jabnoun, 2001;Hyland et al, 2003;Jager et al, 2004;Fryer et al, 2007;Marin-Garcia et al, 2008;Mahanti & Evans, 2012;Rantamäki et al, 2013;Sharma & Kharub;Lim et al, 2014).…”

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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Attaining competitive positioning through SPC – an experimental investigation from SME

Cited by 24 publications

References 41 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

Quality Control of Product: Statistical Process Control

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

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