Quality risk prediction at a non-sampling station machine in a multi-product, multi-stage, parallel processing manufacturing system subjected to sequence disorder and multiple stream effects

Anna Rotondo, Paul Young and John Geraghty ()

Annals of Operations Research, 2013, vol. 209, issue 1, 255-277

Abstract: Quality risks determined by inspection economies represent a difficult controllable variable in complex manufacturing environments. Planning a quality strategy without being able to predict its effectiveness in all the stations of a system might eventually lead to a loss of time, money and resources. The use of one station to regularly select the samples for a production segment introduces relevant complexities in the analysis of the available quality measurements when they are referred to the other stations in that segment. The multiple streams of product through the parallel machines of the stations and the cycle time randomness, responsible for variation of the item sequence order at each production step, nullify the regularity of the sampling patterns at the machines of the non-sampling stations. This work develops a fundamental model which supports the prediction of the ‘quality risk’, at a given machine in the non-sampling stations, associated with a particular sampling policy for a multi-product, multi-stage, parallel processing manufacturing system subjected to sequence disorder and multiple stream effects. The rationale on which the model is based and successful applications of the model, to scenarios structurally different from those used for its development, give confidence in the general validity of the model here proposed for the quality risk prediction at non-sampling station machines. Copyright Springer Science+Business Media, LLC 2013

Keywords: Quality control; Sampling plan; Quality risk; Sequence-disorder effect; Multiple-stream effect; Multi-product; Multi-stage parallel manufacturing systems; Non-sampling stations (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10479-012-1145-y

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