A Novel Analytical Modeling Approach for Quality Propagation of Transient Analysis of Serial Production Systems

Production system modeling (PSM) for quality propagation involves mapping the principles between components and systems. While most existing studies focus on the steady-state analysis, the transient quality analysis remains largely unexplored. It is of significance to fully understand quality propag...

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Main Authors: Shihong Liu, Shichang Du, Lifeng Xi, Yiping Shao, Delin Huang
Format: Article
Language:English
Published: MDPI AG 2022-03-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/22/6/2409
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author Shihong Liu
Shichang Du
Lifeng Xi
Yiping Shao
Delin Huang
author_facet Shihong Liu
Shichang Du
Lifeng Xi
Yiping Shao
Delin Huang
author_sort Shihong Liu
collection DOAJ
description Production system modeling (PSM) for quality propagation involves mapping the principles between components and systems. While most existing studies focus on the steady-state analysis, the transient quality analysis remains largely unexplored. It is of significance to fully understand quality propagation, especially during transients, to shorten product changeover time, decrease quality loss, and improve quality. In this paper, a novel analytical PSM approach is established based on the Markov model, to explore product quality propagation for transient analysis of serial multi-stage production systems. The cascade property for quality propagation among correlated sequential stages was investigated, taking into account both the status of the current stage and the quality of the outputs from upstream stages. Closed-form formulae to evaluate transient quality performances of multi-stage systems were formulated, including the dynamics of system quality, settling time, and quality loss. An iterative procedure utilizing the aggregation technique is presented to approximate transient quality performance with computational efficiency and high accuracy. Moreover, system theoretic properties of quality measures were analyzed and the quality bottleneck identification method was investigated. In the case study, the modeling error was 0.36% and the calculation could clearly track system dynamics; quality bottleneck was identified to decrease the quality loss and facilitate continuous improvement. The experimental results illustrate the applicability of the proposed PSM approach.
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spelling doaj.art-ddccb511f9584e9b8f3b2cf4951b864e2023-11-30T22:20:57ZengMDPI AGSensors1424-82202022-03-01226240910.3390/s22062409A Novel Analytical Modeling Approach for Quality Propagation of Transient Analysis of Serial Production SystemsShihong Liu0Shichang Du1Lifeng Xi2Yiping Shao3Delin Huang4Department of Industrial Engineering and Management, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, ChinaDepartment of Industrial Engineering and Management, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, ChinaDepartment of Industrial Engineering and Management, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, ChinaCollege of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, ChinaCollege of Mechanical Engineering, Donghua University, Shanghai 201620, ChinaProduction system modeling (PSM) for quality propagation involves mapping the principles between components and systems. While most existing studies focus on the steady-state analysis, the transient quality analysis remains largely unexplored. It is of significance to fully understand quality propagation, especially during transients, to shorten product changeover time, decrease quality loss, and improve quality. In this paper, a novel analytical PSM approach is established based on the Markov model, to explore product quality propagation for transient analysis of serial multi-stage production systems. The cascade property for quality propagation among correlated sequential stages was investigated, taking into account both the status of the current stage and the quality of the outputs from upstream stages. Closed-form formulae to evaluate transient quality performances of multi-stage systems were formulated, including the dynamics of system quality, settling time, and quality loss. An iterative procedure utilizing the aggregation technique is presented to approximate transient quality performance with computational efficiency and high accuracy. Moreover, system theoretic properties of quality measures were analyzed and the quality bottleneck identification method was investigated. In the case study, the modeling error was 0.36% and the calculation could clearly track system dynamics; quality bottleneck was identified to decrease the quality loss and facilitate continuous improvement. The experimental results illustrate the applicability of the proposed PSM approach.https://www.mdpi.com/1424-8220/22/6/2409production systemstransient analysisqualitybottleneckMarkov models
spellingShingle Shihong Liu
Shichang Du
Lifeng Xi
Yiping Shao
Delin Huang
A Novel Analytical Modeling Approach for Quality Propagation of Transient Analysis of Serial Production Systems
Sensors
production systems
transient analysis
quality
bottleneck
Markov models
title A Novel Analytical Modeling Approach for Quality Propagation of Transient Analysis of Serial Production Systems
title_full A Novel Analytical Modeling Approach for Quality Propagation of Transient Analysis of Serial Production Systems
title_fullStr A Novel Analytical Modeling Approach for Quality Propagation of Transient Analysis of Serial Production Systems
title_full_unstemmed A Novel Analytical Modeling Approach for Quality Propagation of Transient Analysis of Serial Production Systems
title_short A Novel Analytical Modeling Approach for Quality Propagation of Transient Analysis of Serial Production Systems
title_sort novel analytical modeling approach for quality propagation of transient analysis of serial production systems
topic production systems
transient analysis
quality
bottleneck
Markov models
url https://www.mdpi.com/1424-8220/22/6/2409
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