An optimization‐based approach for designing attribute acceptance sampling plans

Duarte, Belmiro P.M.; Saraiva, Pedro

doi:10.1108/02656710810898630

Cited by 36 publications

(17 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To move towards the advanced level, they should develop a statistically based sampling of incoming carcasses based on historical data of suppliers (e.g. Brown et al, 2000;Tebbutt, 2006;Duarte & Saraiva, 2008). Obviously, in contrast to company B, they had no problems with the food safety parameters in their products and environment (Table 3), which suggests that their current FSMS is sufficient to control these parameters (Jacxsens et al, 2009b).…”

Section: A B Cmentioning

confidence: 96%

A concurrent diagnosis of microbiological food safety output and food safety management system performance: Cases from meat processing industries

et al. 2011

View full text Add to dashboard Cite

Section: A B Cmentioning

confidence: 96%

A concurrent diagnosis of microbiological food safety output and food safety management system performance: Cases from meat processing industries

et al. 2011

View full text Add to dashboard Cite

“…Such plans can directly impact the efficiency and efficacy of the production; if these plans are poorly delineated, then they can compromise product quality and productivity (Duarte & Saraiva, 2008;Hoerl & Snee, 2010;Montgomery, 2013;Lim et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2016

View full text Add to dashboard Cite

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.

show abstract

“…The quality assurance (QA) approach, also known as quality guarantee, started to be disseminated in Brazil from the 1980s onwards. This approach is still widely recommended as an important tool for quality management systems, such as ISO/TS 16949, because it has a direct impact on the relationship between clients and suppliers …”

Section: Introductionmentioning

confidence: 99%

A Framework for Continuous Inspection Plans Using Multivariate Mathematical Methods

Oprime

Ganga

2012

Quality & Reliability Eng

View full text Add to dashboard Cite

The aim of this study was to propose and apply a sampling procedure using mathematical models and multivariate statistics for continuous processes in manufacturing companies. The research presented in this paper can be classified as a descriptive and empirical quantitative study in which the basic interest was in creating a model that describes and analyzes the causal relationships between the quality characteristics (in this case, multivariate) of a process, in order to select the best continuous inspection plan. This framework was applied in a company that supplies the main component producers for the worldwide car industry. The results obtained from applying the multivariate procedures made it possible to select the best continuous inspection plan based on inspection frequency, resultant mean quality, and proportion of the units inspected. This procedure should be tested on new problems and real situations in order to validate the methods used. Copyright © 2012 John Wiley & Sons, Ltd.

show abstract

An optimization‐based approach for designing attribute acceptance sampling plans

Cited by 36 publications

References 18 publications

A concurrent diagnosis of microbiological food safety output and food safety management system performance: Cases from meat processing industries

A concurrent diagnosis of microbiological food safety output and food safety management system performance: Cases from meat processing industries

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

A Framework for Continuous Inspection Plans Using Multivariate Mathematical Methods

Contact Info

Product

Resources

About