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A simulation method for Material requirement planning supply dependent demand and uncertainty lead-time
Author(s) -
Haibatolah Sadeghi,
Makui Ahmad,
Mehdi Heydari
Publication year - 2014
Publication title -
african journal of business management
Language(s) - English
Resource type - Journals
ISSN - 1993-8233
DOI - 10.5897/ajbm2013.7211
Subject(s) - monte carlo method , probabilistic logic , lead time , scheduling (production processes) , lead (geology) , computer science , order (exchange) , production (economics) , holding cost , product (mathematics) , production planning , mathematical optimization , material requirements planning , operations research , reliability engineering , engineering , operations management , mathematics , economics , statistics , geometry , finance , geomorphology , artificial intelligence , macroeconomics , geology
Materials requirements planning (MRP) is a widely used method for production planning and scheduling. Planned lead-time (PLT) and lot size are two of the input parameters for MRP systems, which determine planned order release dates. In this paper deals with material requirement planning for a three levels production and assembly system with several types of components and one type of final product, in multi periods. In this paper, we assume that components lead-times are probabilistic. A MRP approach with periodic order quantity (POQ) policy is used for the planning of components. The objective is minimizing the sum of the all components holding cost, final product backlogging cost, final product holding cost and setup costs. The main policies in this model determine the periodic order quantity, and planned lead-times. Monte-Carlo simulation is used to generate numerous scenarios based on the components lead time, and by using Monte-Carlo simulation we can find the suitable solution for this problem.   Keywords: planned lead-time; periodic order quantity; uncertainty, Monte-Carlo simulation; Probabilistic lead-time

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