An economically designed, integrated quality and maintenance model using an adaptive Shewhart chart

Panagiotidou, Sofia; Nenes, George

doi:10.1016/j.ress.2008.07.003

Cited by 71 publications

(30 citation statements)

References 35 publications

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“…The current paper extends the work of Panagiotidou and Nenes 23 to the Bayesian case. Thus, we share the following common assumptions for the process characteristics:…”

Section: Introductionsupporting

confidence: 54%

“…they assume both operating and non-operating (failure) states, are the works of Tagaras 22 , Panagiotidou and Nenes 23 and Panagiotidou and Tagaras 24 . Tagaras 22 describes, through the use of a Markov chain, the evolution of the process from the in-control state to the failure state through a number of intermediate inferior (out-of-control), yet operating, states.…”

Section: Introductionmentioning

confidence: 99%

“…Panagiotidou and Tagaras 24 provide a model for the economic optimization of both quality control and maintenance procedures in production processes subject to non-exponential quality shifts and failures, combining condition-based Preventive Maintenance with a typical Shewhart chart. Panagiotidou and Nenes 23 use a more sophisticated Vp-Shewhart chart in a Markov chain concept. As shown in that paper, the additional flexibility of the Vp-chart results in significant economic improvement compared to its simpler fixed-parameter counterpart.…”

Section: Introductionmentioning

confidence: 99%

“…A byproduct of the paper is the investigation of the relative effectiveness of the new model compared against the Vp model in the reference 23 . The remainder of the paper is structured in the following manner.…”

Section: Introductionmentioning

confidence: 99%

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A Bayesian model for the joint optimization of quality and maintenance decisions

Nenes

Panagiotidou

2011

Quality & Reliability Eng

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We develop a model for the economic design of a Bayesian control chart for monitoring a process mean. The process may randomly suffer failures that result in a non-operating state, and thus call for an immediate corrective maintenance action, as well as assignable causes that shift the process mean to an undesirable level. Quality shifts, apart from poorer quality outcome and higher operational cost, also result in higher failure rate. Consequently, their removal, besides improving the outcome quality and reducing the quality-related cost, is also a preventive maintenance action since it reduces the probability of a failure. The proposed Bayesian model allows the determination of the design parameters that minimize the total expected quality and maintenance cost per time unit. The effectiveness of the proposed model is evaluated through the comparison of its expected cost against the optimum expected cost of the simpler variable-parameter Shewhart chart.

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“…The current paper extends the work of Panagiotidou and Nenes 23 to the Bayesian case. Thus, we share the following common assumptions for the process characteristics:…”

Section: Introductionsupporting

confidence: 54%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Bayesian model for the joint optimization of quality and maintenance decisions

Nenes

Panagiotidou

2011

Quality & Reliability Eng

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“…MacCarthy and Wasusri, 2002), that is to say dealing with a single "customer" process and a heterogeneous installed base. Further, the reported implementations typically deal with quality in terms of product quality, rather than service quality (Chan and Wu, 2009;Panagiotidou and Nenes, 2009;cf. Yeung et al, 2007).…”

Section: Measuring Service Outcomesmentioning

confidence: 99%

Measuring service outcomes for adaptive preventive maintenance

Öhman

Finne

Holmström

2015

International Journal of Production Economics

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Measuring Service Outcomes for Adaptive Preventive Maintenance AbstractServices account for an increasing share of economic activity in the western world. As part of this, preventive maintenance (PM) service volumes are constantly growing as a result of a growing (and aging) asset population and maintenance outsourcing. While the pursuit of improved service productivity is in the interest of both firms and nations, the challenges of measuring service performance, and more specifically service outcomes, persist. This paper presents an outcome-based measure for fleet PM, which has far-reaching implications considering service productivity and performance measurement.We develop a statistical process control based measure that utilizes data typically available in PM. The measure is grounded in reliability theory, which enables generalization of the measure within PM services but also outlines the limitations of its application. Finally we apply the measure in a PM field service process of a servitized equipment manufacturer.Based on actual maintenance records we show that the service provider could reduce their service output by at least 5-10% without significantly affecting the aggregate service outcome.The developed measure and control process form the basis for adaptive preventive maintenance, which is expected to facilitate the transition towards outcome-based contracts through complementing condition-based maintenance. One of the key benefits of the approach is that it provides a cost-effective way of revealing the scarcely studied phenomenon of service overproduction. Based on our case, we conclude that there are significant 2 productivity gains in making sure that you meet required standards for service output but do not exceed them.

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Reliability and Maintenance Based Design of Machine Tools

Lad

Kulkarni²

2016

Machine Tool Reliability

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In this paper a methodology for selection of optimal machine tool configuration by simultaneously considering reliability and maintenance is developed. Methodology is based on measures like Life Cycle Cost (LCC), Availability (A) and Overall Equipment Effectiveness (OEE). These measures explicitly consider the user's cost structure and shop floor level policy parameters. A simulation based Genetic Algorithm (GA) is used to solve the simultaneous optimization problem. Case example using operations and maintenance data of a CNC grinding machine is presented.

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An economically designed, integrated quality and maintenance model using an adaptive Shewhart chart

Cited by 71 publications

References 35 publications

A Bayesian model for the joint optimization of quality and maintenance decisions

A Bayesian model for the joint optimization of quality and maintenance decisions

Measuring service outcomes for adaptive preventive maintenance

Reliability and Maintenance Based Design of Machine Tools

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