Quality Analysis in Acyclic Production Networks
| Autor: | Abraham Gutierrez, Sebastian Müller |
|---|---|
| Přispěvatelé: | Institut de Mathématiques de Marseille (I2M), Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
FOS: Computer and information sciences
Statistics and Probability 0209 industrial biotechnology Computer science media_common.quotation_subject Mathematics - Statistics Theory Statistics Theory (math.ST) 02 engineering and technology 010501 environmental sciences Statistics - Applications 01 natural sciences 020901 industrial engineering & automation FOS: Mathematics Discrete Mathematics and Combinatorics Production (economics) Applications (stat.AP) Quality (business) Safety Risk Reliability and Quality Computer Science::Distributed Parallel and Cluster Computing ComputingMilieux_MISCELLANEOUS 0105 earth and related environmental sciences media_common Applied Mathematics Reliability engineering [MATH.MATH-PR]Mathematics [math]/Probability [math.PR] 90B30 90B15 62M02 62M05 Anomaly detection Statistics Probability and Uncertainty |
| Zdroj: | Stochastics and Quality Control Stochastics and Quality Control, 2019, 34 (2), pp.59-66. ⟨10.1515/eqc-2019-0014⟩ |
| ISSN: | 2367-2390 |
| DOI: | 10.1515/eqc-2019-0014⟩ |
| Popis: | The production network under examination consists of a number of workstations. Each workstation is a parallel configuration of machines performing the same kind of tasks on a given part. Parts move from one workstation to another and at each workstation a part is assigned randomly to a machine. We assume that the production network is acyclic, that is, a part does not return to a workstation where it previously received service. Furthermore, we assume that the quality of the end product is additive, that is, the sum of the quality contributions of the machines along the production path. The contribution of each machine is modeled by a separate random variable. Our main result is the construction of estimators that allow pairwise and multiple comparison of the means and variances of machines in the same workstation. These comparisons then may lead to the identification of unreliable machines. We also discuss the asymptotic distributions of the estimators that allow the use of standard statistical tests and decision making. |
| Databáze: | OpenAIRE |
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