AI SearchBuffer stocks in MRP and related systems
Thevalingam, Kuddythamby
Buffer stocks in MRP and related systems - Bangkok : Asian Institute of Technology, 1988 - 53, [27] p. - Thesis ; no. IE-88-24 . - Asian Institute of Technology. Thesis ; no. IE-88-24 .
A thesis summitted in partial fulfillment of the requirements for the degree of Master of Engineering, School of Engineering and Technology
Thesis (M.Eng.) - Asian Institute of Technology, 1988
This study explores the methods available to protect Material Requirement s Planning (MRP ) or related systems when t here is uncertainty associated with the system. These are multi -stage production systems . The demand for the end item is stochastic and stationary. This leads to buffer stocks in the form of safety stock and safety lead time . A careful survey of recent literature in this area is made to highlight the computati0nally feasible and promising approaches available. One of the important development due to Lambrecht and Muckstadt concern a serial production system under periodic review . Their numerical evidence indicates that optimal inventory control policies, found by Markovian Decision Process (MOP) (with multi- dimensional state space) turns out to yield (S,s) policies for control of echelon inventories. The MDP gets infeasible for large lead times and/or several production stages. For that situation Lambrecht and Muckstadt have proposed a modification to Clark and Scarf approach based on regarding echelon stocks as sing l e stage inventories; wherein they have done away with the penalty function computation in Clark and Scarf method . Moreover t hey have explored the possibility of quantity co-ordination between stages, whose motivation comes from deterministic models. I n this study we examine for condition specified by Lambrecht and Muckstadt for deciding whether or not to employ quantity co- ordination. The numerical evidence in this study indicates that the basic modification of Cl ark and Scarf policy due to Lambrecht and Muckstadt gives close to optimal results, the condition
Production control
Buffer stocks in MRP and related systems - Bangkok : Asian Institute of Technology, 1988 - 53, [27] p. - Thesis ; no. IE-88-24 . - Asian Institute of Technology. Thesis ; no. IE-88-24 .
A thesis summitted in partial fulfillment of the requirements for the degree of Master of Engineering, School of Engineering and Technology
Thesis (M.Eng.) - Asian Institute of Technology, 1988
This study explores the methods available to protect Material Requirement s Planning (MRP ) or related systems when t here is uncertainty associated with the system. These are multi -stage production systems . The demand for the end item is stochastic and stationary. This leads to buffer stocks in the form of safety stock and safety lead time . A careful survey of recent literature in this area is made to highlight the computati0nally feasible and promising approaches available. One of the important development due to Lambrecht and Muckstadt concern a serial production system under periodic review . Their numerical evidence indicates that optimal inventory control policies, found by Markovian Decision Process (MOP) (with multi- dimensional state space) turns out to yield (S,s) policies for control of echelon inventories. The MDP gets infeasible for large lead times and/or several production stages. For that situation Lambrecht and Muckstadt have proposed a modification to Clark and Scarf approach based on regarding echelon stocks as sing l e stage inventories; wherein they have done away with the penalty function computation in Clark and Scarf method . Moreover t hey have explored the possibility of quantity co-ordination between stages, whose motivation comes from deterministic models. I n this study we examine for condition specified by Lambrecht and Muckstadt for deciding whether or not to employ quantity co- ordination. The numerical evidence in this study indicates that the basic modification of Cl ark and Scarf policy due to Lambrecht and Muckstadt gives close to optimal results, the condition
Production control