Absorbing Markov Chain Models to Determine Optimum Process Target Levels in Production Systems with Rework and Scrapping
Authors
Abstract:
In this paper, absorbing Markov chain models are developed to determine the optimum process mean levels for both a single-stage and a serial two-stage production system in which items are inspected for conformity with their specification limits. When the value of the quality characteristic of an item falls below a lower limit, the item is scrapped. If it falls above an upper limit, the item is reworked. Otherwise, the item passes the inspection. This flow of material through the production system can be modeled in an absorbing Markov chain characterizing the uncertainty due to scrapping and reworking. Numerical examples are provided to demonstrate the application of the proposed model.
similar resources
absorbing markov chain models to determine optimum process target levels in production systems with rework and scrapping
in this paper, absorbing markov chain models are developed to determine the optimum process mean levels for both a single-stage and a serial two-stage production system in which items are inspected for conformity with their specification limits. when the value of the quality characteristic of an item falls below a lower limit, the item is scrapped. if it falls above an upper limit, the item is ...
full textA Markov Chain Model of Serial Production Systems with Rework
In this paper, we present a Markovian modeling framework that can describe any serial production system with rework. Under this framework, each production stage is represented by a state in the Markov chain. Absorbing states indicate the events of scrapping a product at a production stage or the completion of the finished product. Generalizable formulae for the final absorption probabilities ar...
full textUsing Markov Chain to Analyze Production Lines Systems with Layout Constraints
There are some problems with estimating the time required for the manufacturing process of products, especially when there is a variable serving time, like control stage. These problems will cause overestimation of process time. Layout constraints, reworking constraints and inflexible product schedule in multi product lines need a precise planning to reduce volume in particular situation of lin...
full textA Markov Model to Determine Optimal Equipment Adjustment in Multi-stage Production Systems Considering Variable Cost
Our aim is to maximize expected profit per item of a multi-stage production system by determining best adjustment points of the equipments used based on technical product specifications defined by designer. In this system, the quality characteristics of items produced should be within lower and higher tolerance limits. When a quality characteristic of an item either falls beneath the lower li...
full textA Markovian approach to determining optimum process target levels for a multi-stage serial production system
Consider a production system where products are produced continuously and screened for conformance with their specification limits. When product performance falls below a lower specification limit or above an upper limit, a decision is made to rework or scrap the product. The majority of the process target models in the literature deal with a single-stage production system. In the real-world in...
full textThe economic production quantity with rework process in supply chain management
Cardenas-Barron [L.E. Cardenas-Barron, Economic production quantity with rework process at a single-stage manufacturing system with planned backorders, Computers and Industrial Engineering 57 (2009) 1105–1113] minimizes the annual total relevant cost TC(Q , B) to find the economic production quantitywith rework process at amanufacturing system and assumes that TC(Q , B) is convex. So, the solut...
full textMy Resources
Journal title
volume Volume 3 issue Issue 6
pages 1- 6
publication date 2010-09-28
By following a journal you will be notified via email when a new issue of this journal is published.
Hosted on Doprax cloud platform doprax.com
copyright © 2015-2023