Markov modeling and analysis of multi-stage manufacturing systems with remote quality information feedback

Du, Shichang; Xu, Rui; Huang, Delin; Yao, Xufeng

doi:10.1016/j.cie.2015.06.012

Cited by 32 publications

(10 citation statements)

References 47 publications

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“…The methodology of carrying out this project work is divided into the following steps. In each of the steps, lean tools have been used which have been discussed in each section further [14].…”

Section: Methodsmentioning

confidence: 99%

Productivity improvement of leather products industry in Bangladesh using lean tools: a case study

Swarna¹,

Mia²

2018

LFJ

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PRODUCTIVITY IMPROVEMENT OF LEATHER PRODUCTS INDUSTRY IN BANGLADESH USING LEAN TOOLS: A CASE STUDY ABSTRACT. There is great potential for the leather industry in Bangladesh to become one of the country's major foreign exchange earners, experts say. After readymade garments (RMG), productivity improvement can help to enrich profit of a leather products industry by minimizing excess work and developing a new method for particular operation. Nowadays, productivity improvement is a popular topic for any kinds of industry. Therefore, improving productivity is one of the main concerns of leather products industries. Lean manufacturing tools are most important tools that can help to increase productivity in leather products industry. In Bangladesh, few industries use these lean tools which can be proved as a real beneficial one. Hence, this study addresses the implementation of lean principles in a leather goods manufacturing industry in order to evaluate present process cycle efficiency (PCE), lead time and productivity prior to developing an improved strategy to bring the improved PCE, productivity and to reduce the lead time. By applying lean tools in the industry at the production line for bi-fold wallet, productivity has been improved by 85.42%. At the beginning state, the PCE was found 38.19% and after the implementation of lean tools, it would be 77.51% and lead time would also be reduced by 46.68% evaluated by takt time, bottleneck analysis, cause-effect analysis and Pareto analysis. The production flow was optimized by minimizing several non-value-added (NVD) activities such as bottlenecking, machine breakdown, queue time, waiting time, material handling time, etc.

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Section: Methodsmentioning

confidence: 99%

Productivity improvement of leather products industry in Bangladesh using lean tools: a case study

Swarna¹,

Mia²

2018

LFJ

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“…To analyze the quality propagation of MMP with remote quality information feedback (i.e. quality inspection operation is conducted at the end of the production line), Du et al 23 developed a Markov model and investigated the monotonicity properties by deriving the analytical formulas of final product quality, and explored a quality bottleneck identification method based on the proposed Markov model. Among these intense researches, a lot has been done on the effect of process errors on part quality and has made great progress.…”

Section: Literature Reviewmentioning

confidence: 99%

An extended machining error propagation network model for small-batch machining process control of aircraft landing gear parts

Wang

Jiang

2016

Proceedings of the Institution of Mechanical Engineers, Part G:

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The complex structure and small-batch nature of aircraft landing gear parts lead to complex machining error propagation mechanism and manufacturing complexity. An Extended Machining Error Propagation Network model is presented to quantitatively analyze the complex coupling relationship in the Small-batch Multistage Machining Process of aircraft landing gear parts. Firstly, to depict the coupling relationship quantitatively, the Quality Features are defined to describe the machining precision information of Machining Form Features, and the State Elements are defined to describe the running state information of Machining Elements. Then, Machining Form Features, Machining Elements, Quality Features, and State Elements are identified as different network nodes, and the coupling relationships (such as evolving, locating, machining, and attribute) among these nodes are mapped into network edges. Based on the in-process measuring and sensing data of each machining stage, the topological and physical metrics of the network are explored to analyze the error propagation characteristics. Finally, the machining process of an outer cylinder part from aircraft landing gear is studied to verify the proposed methods.

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“…Based on Markov model of quality analysis system, a Markov model in a two-stage manufacturing system with remote quality information feedback was developed [1]. A Markov model to analyze quality propagation in multi-stage manufacturing systems was also developed [2,3]. An analytical method to evaluate the quality performance of flexible manufacturing systems was approved [4].…”

Section: Introductionmentioning

confidence: 99%

A Data-Driven Condition Monitoring of Product Quality Analysis System Based on RS and AHP

et al. 2020

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Mechanical and electrical products have complex structure and intelligent control system, their reliability plays an important role in the normal operation of security facilities. However, most manufacturers usually pay more attention to the product designing and manufacturing quality, with little interest in the intelligent fault diagnosis. The objective of this study is to develop the products quality intelligent analysis and management system based on Rough Set (RS) and Analytic Hierarchy Process (AHP). Firstly, this paper reviews the principle of hardware, software design, monitoring platform and quality analysis system to reduce the number of information transfer with computer technology. Secondly, the fault types and feature extractions of different faults of elevators are presented and simplified by using RS theory. Then, the objective weight of level index model can be obtained by AHP method, and the comprehensive analysis weight of each index is obtained by using the value of subjective and objective weight coefficients with the golden ratio. Finally, a comprehensive decision weight of the major index for quality control analysis system of many vertical elevators is presented. The results show that the data-driven condition monitoring and quality analysis system is a kind of important means to prevent a disaster of complex mechanical and electrical products.

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Markov modeling and analysis of multi-stage manufacturing systems with remote quality information feedback

Cited by 32 publications

References 47 publications

Productivity improvement of leather products industry in Bangladesh using lean tools: a case study

Productivity improvement of leather products industry in Bangladesh using lean tools: a case study

An extended machining error propagation network model for small-batch machining process control of aircraft landing gear parts

A Data-Driven Condition Monitoring of Product Quality Analysis System Based on RS and AHP

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