Quality Analysis in Acyclic Production Networks
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Abraham Gutierrez
Abstract
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.
Funding source: Austrian Science Fund
Award Identifier / Grant number: P29355-N35
Funding statement: Abraham Gutierrez acknowledges financial support from the Austrian Science Fund project FWF P29355-N35.
Acknowledgements
The authors wish to thank Alessandro Chiancone, Herwig Friedl, Jérôme Depauw, and Marc Peigné for stimulating discussing during this project. Grateful acknowledgement is made for hospitality from TU-Graz where the research was carried out during visits of Sebastian Müller.
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© 2019 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Quality Analysis in Acyclic Production Networks
- Bivariate Dynamic Weighted Survival Entropy of Order 𝛼
- Optimal Design of Reliability Acceptance Sampling Plan Based on Sequential Order Statistics
- A New Method of Estimating the Process Capability Index with Exponential Distribution Using Interval Estimate of the Parameter
- Developing a Flexible Methodology for Modeling and Solving Multiple Response Optimization Problems
- On the Reliability for Some Bivariate Dependent Beta and Kumaraswamy Distributions: A Brief Survey
Articles in the same Issue
- Frontmatter
- Quality Analysis in Acyclic Production Networks
- Bivariate Dynamic Weighted Survival Entropy of Order 𝛼
- Optimal Design of Reliability Acceptance Sampling Plan Based on Sequential Order Statistics
- A New Method of Estimating the Process Capability Index with Exponential Distribution Using Interval Estimate of the Parameter
- Developing a Flexible Methodology for Modeling and Solving Multiple Response Optimization Problems
- On the Reliability for Some Bivariate Dependent Beta and Kumaraswamy Distributions: A Brief Survey
