Designing a multivariate–multistage quality control system using artificial neural networks

Niaki, Seyed Taghi Akhavan; Davoodi, Mehdi

doi:10.1080/00207540701504348

Cited by 52 publications

(26 citation statements)

References 26 publications

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“…From the perspective of control, Niaki and Davoodi (2009) designed a multivariate multistage scheme to monitor and diagnose the possible causes of out-of-control signals. Their approach considers several autocorrelated stages and several correlated quality characteristics within a particular stage.…”

Section: Related Studiesmentioning

confidence: 99%

A multistage and multiple response optimization approach for serial manufacturing system

Bera

Mukherjee

2016

European Journal of Operational Research

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Section: Related Studiesmentioning

confidence: 99%

A multistage and multiple response optimization approach for serial manufacturing system

Bera

Mukherjee

2016

European Journal of Operational Research

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“…Heredia-Langner, Montgomery, and Carlyle (2002) considered partial inspection strategy for all stages. Niaki and Davoodi (2008) developed a method to establish a quality control plan system for all stages. Others considered the problem of MMP inspection with other factors, such as time-varying quality (Veatch 2000) and inspection error (Shiau 2002).…”

Section: Literature Reviewmentioning

confidence: 99%

Engineering model-based Bayesian monitoring of ramp-up phase of multistage manufacturing process

Yao

Huang

2015

International Journal of Production Research

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Process monitoring of full mass production phase of multistage manufacturing processes (MMPs) has been successfully implemented in many applications; however, monitoring of ramp-up phase of MMPs is often more difficult to conduct due to the limited information to establish valid process control parameters (such as mean and variance). This paper focuses on the estimation of the process control parameters used for monitoring scheme design of ramp-up phase of MMPs. An engineering model of variation propagation of an MMP is developed and reconstructed to a linear model, establishing a relationship between the error sources and the variation of product characteristics. Based on the developed linear model, a two-step Bayesian method is proposed to estimate the process control parameters. The performance of the proposed Bayesian method is validated with simulation data and real-world data, and the results demonstrate that the proposed method can effectively estimate process parameters during ramp-up phase of MMP.

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“…The quality control of inter-enterprise manufacturing is that quality control task is decided, assigned, acted and evaluated by the mode that core enterprise be used as centre and partner enterprises be used as partners, the demand of market and customers is direction, internal enterprises quality control information is integrated based on Web and database technology [1][2][3][4][5].…”

Section: The Similarity Characteristic Of Quality Control Function Fomentioning

confidence: 99%

“…In order to control effectively extended enterprise quality, a new model must be established to adapt to the requirement of quality control for extended enterprise. [1][2][3][4][5]. Holon is a system construct unit, and it has cooperation characteristics relative to upper organization and selfdiscipline characteristics relative to lower organization.…”

Section: Introductionmentioning

confidence: 99%

A Method Product Quality Control between Enterprises and its Implementation

Tian

2010

2010 Second International Workshop on Education Technology and Computer Science

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Along with the intensification of global competition and the complexity of manufacturing products, the cooperation among enterprises becomes more closely, and the range of quality control extends from internal to the external enterprises. To the demand of product quality control among enterprises, based on holon theory, the product quality control holonic structure for extended enterprises is constructed by the similarity characteristic of quality control function in extended enterprises. In the structure, the autonomy and cooperative quality control holon are established by the analysis of cooperation operation among holons, and the structure can complete vertical and lateral complex cooperation in internal and external cooperation among quality control holons to improve the ability and efficiency of product quality control. The implementation framework of the product quality control holonic structure is constructed by multi-agent system. Based on the negotiation mechanism of multi-agent, the implementation framework can be developed to realize the quality control for extended enterprises. Finally, the implementation framework can be demonstrated and validated the proposed idea by Flexsim software. It shows that the product quality control holonic structure for extended enterprises can satisfy the agility, distribution, and robustness requirements the quality control among enterprises.

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Designing a multivariate–multistage quality control system using artificial neural networks

Cited by 52 publications

References 26 publications

A multistage and multiple response optimization approach for serial manufacturing system

A multistage and multiple response optimization approach for serial manufacturing system

Engineering model-based Bayesian monitoring of ramp-up phase of multistage manufacturing process

A Method Product Quality Control between Enterprises and its Implementation

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