Affiliation:
1. Kuwait University, Kuwait
Abstract
Material flow in production systems can be controlled by a purely push-pull (just-in-time), or by a hybrid push-pull control mechanism. One type of push-pull production control can be implemented by controlling only the last stage during part withdrawals to trigger the production at the first stage. While the final stage is operated according to a pull mechanism, intermediate stages are operated according to a push system of control in order to keep the work-in-process (WIP) at a constant level. Since the WIP levels are limited in hybrid systems, production output rate is very susceptible to equipment failures. In order to establish suitable WIP capacities between the stages of production, it is essential to analyze the production line using appropriate models and tools. This paper develops a discrete iterative model to study and analyze behavior of a push-pull system with unreliable equipment at any stage. The model is utilized to optimize WIP capacities at intermediate stages and number of kanbans at the last stage. Furthermore, an experimental design is set up to analyze effects of various maintenance policies, line design parameters, and operational factors on line performance measures by using simulation results from the model.
Subject
Information Systems,Management Information Systems
Cited by
5 articles.
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1. Hybrid Push-Pull Systems: Classification, Optimal Methods and Uncertainty;2021 International Conference on Computational Science and Computational Intelligence (CSCI);2021-12
2. An Efficient Approach for the Reentrant Parallel Machines Scheduling Problem under Consumable Resources Constraints;International Journal of Information Systems and Supply Chain Management;2016-07
3. Implementing a Hybrid Push-Pull System Using Genetic Algorithms;IEEE Latin America Transactions;2015-10
4. Modeling of Maintenance Operations;Encyclopedia of Business Analytics and Optimization;2014
5. Analysis of Maintenance Operations: A Case Application;Encyclopedia of Business Analytics and Optimization;2014