Diagnostic errors and repetitive sequential classifications in on-line process control by attributes

Quinino, Roberto da Costa; Colin, Emerson Carlos; Ho, Linda Lee

doi:10.1016/j.ejor.2009.02.017

Cited by 14 publications

(7 citation statements)

References 14 publications

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“…Further details see Quinino and Suyama (2002), Quinino and Ho (2004) and Trindade et al (2007a, b). A hybrid model based on the sequential results of repetitive classifications was proposed by Quinino and Ho (2004) and Quinino et al (2010).…”

Section: Introductionmentioning

confidence: 99%

On-Line Process Control of the Number of Non-Conformities in the Inspected Item

Vasconcelos¹,

Medeiros²,

Ho³

2012

BJOPM

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Generally, production systems as automatic welding process, production of ceramic products, making clothes use automatic control and to evaluate the quality of their production processes, they employ on-line process control. The control system consists of a periodic inspection of one item after every m produced items. The number of non-conformities is monitored in the inspected item and if it exceeds the control limit, then it is decided that the process is out-of-control and the process is stopped for adjustment, otherwise the production continues. The process starts in-control with a fixed non-conformities rate and, after an assignable cause, this rate increases leading the system to operate out of control. The process remains in these conditions until the change is detected and the process adjusted. After adjustment, the process returns to operate in-control. The aim of this paper is to present an economic approach to monitor the rate of non-conformities in a production by on-line process control. To design such type of process, an average cost per item produced is achieved through the properties of an ergodic Markov chain and the two required parameters: the inspection interval and the upper control limit are obtained by minimizing the average cost per produced item. A numerical example illustrates the proposal. It was identified the most important factors which result a considerable impact on the average cost per item: the probability of a shift in the parameter of Poisson distribution; cost to send non-conforming items to the customers; the in-control non-conformity rate; the specification limit and the cost of adjustment.

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Section: Introductionmentioning

confidence: 99%

On-Line Process Control of the Number of Non-Conformities in the Inspected Item

Vasconcelos¹,

Medeiros²,

Ho³

2012

BJOPM

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“…Concerning on-line process control approaches, most articles (Taguchi et al, 1989;Nayebpour and Woodall, 1993;Wu, 1991, 1995;Trindade et al, 2007;Ho et al, 2007;Quinino et al, 2010) present economical designs for long-run production. In contrast, Ho and Trindade (2009) proposed an online economical X (variable) control chart model for short-run production.…”

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confidence: 98%

“…Wang and Sheu (2003) determined the optimal production-maintenance policy with inspection errors. Quinino et al (2010) suggested the repetitive classifications to minimize the impact of the inspection errors. Ferrell and Chhoker (2002) studied the design of economically optimal acceptance sampling plans with inspection error.…”

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confidence: 99%

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On-Line Process Control using Attributes with Misclassification Errors: An Economical Design for Short-Run Production

Bessegato

Quinino²,

Duczmal³

et al. 2012

Communications in Statistics - Theory and Methods

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On-line process control consists of inspecting a single item for every m (integer and m ≥ 2) produced items. Based on the results of the inspection, it is decided whether the process is in-control (the fraction of conforming items is p 1 ; State I) or outof-control (the fraction of conforming items is p 2 < p 1 ; State II). If the inspected item is non conforming, it is determined that the process is out-of-control, and the production process is stopped for an adjustment; otherwise, production continues. As most designs of on-line process control assume a long-run production, this study can be viewed as an extension because it is concerned with short-run production and the decision regarding the process is subject to misclassification errors. The probabilistic model of the control system employs properties of an ergodic Markov chain to obtain the expression of the average cost of the system per unit produced, which can be minimised as a function of the sampling interval, m. The procedure is illustrated by a numerical example.

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“…Ding et al (1998) examine the question whether it is better to repetitively test rejected components or to repetitively test accepted components. Choosing between these two policies depends on the tradeoff between scrapping costs and outgoing quality; see also Ding and Gong (2008) and Quinino et al (2010) for variations of this problem. Sequencing issues and imperfect testing have both been considered in the inspection of multi-characteristic components; we refer to Raouf et al (1983), Schmidt and Bennett (1972) and Tang and Tang (1994) for examples.…”

Section: Literature Reviewmentioning

confidence: 99%

Sequential Testing of <i>k</i>-out-of-<i>n</i> Systems with Imperfect Tests

et al. 2015

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Abstract. A k-out-of-n system configuration requires that, for the overall system to be functional, at least k out of the total of n components be working. We consider the problem of sequentially testing the components of a k-out-of-n system in order to learn the state of the system, when the tests are costly and when the individual component tests are imperfect, which means that a test can identify a component as working when in reality it is down, and vice versa. Each component is tested at most once. Since tests are imperfect, even when all components are tested the state of the system is not necessarily known with certainty, and so reaching a lower bound on the probability of correctness of the system state is used as a stopping criterion for the inspection.We define different classes of inspection policies and we examine global optimality of each of the classes. We find that a globally optimal policy for diagnosing k-out-of-n systems with imperfect tests can be found in polynomial time when the predictive error probabilities are the same for all the components. Of the three policy classes studied, the dominant policies always contain a global optimum, while elementary policies are compact in representation. The newly introduced class of so-called 'interrupted block-walking' policies combines these merits of global optimality and of compactness.

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Diagnostic errors and repetitive sequential classifications in on-line process control by attributes

Cited by 14 publications

References 14 publications

On-Line Process Control of the Number of Non-Conformities in the Inspected Item

On-Line Process Control of the Number of Non-Conformities in the Inspected Item

On-Line Process Control using Attributes with Misclassification Errors: An Economical Design for Short-Run Production

Sequential Testing of <i>k</i>-out-of-<i>n</i> Systems with Imperfect Tests

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