Determining the periodicity and planned lead time in serial-production systems with dependent demand and uncertain lead time

Sadeghi, Heibatolah; Makui, Ahmad; Hassan, Heydari

doi:10.5267/j.uscm.2013.06.002

Cited by 7 publications

(3 citation statements)

References 15 publications

(13 reference statements)

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“…The goal was to find the optimal MRP offsetting, so as to minimize the sum of setup cost and average holding costs. Sadeghi et al [13] considered a multiperiod serial production system when lead times for all components are uncertainties. They assumed that lead times for all stages have same distribution and the goal is to minimize the sum of fixed ordering, holding, and backlogging costs.…”

Section: Introductionmentioning

confidence: 99%

Multilevel Production Systems with Dependent Demand with Uncertainty of Lead Times

Sadeghi

Makui

Heydari

2016

Mathematical Problems in Engineering

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This study considers a multilevel assembly system with several components in each sublevel. It is assumed that actual lead time for all components is probabilistic; and periodic order quantity (POQ) policy for ordering is utilized. If at a certain level a job is not received at the expected time, a delay is incurred at the delivery of production at this level and this may result in backorders of the finished product. It is assumed in this case that a fixed percentage of the shortage is backlogged and other sales are lost. In the real situation, some but not all customers will wait for backlogged components during a period of shortage, such as for fashionable commodities or high-tech products with the short product life cycle. The objective of this study is to find the planned lead time and periodicity for the total components in order to minimize the expected fixed ordering, holding, and partial backlogging costs for the finished product. In this study, it is assumed that a percentage of components at each level are scrap. A general mathematical model is suggested and the method developed can be used for optimization planned lead time and periodicity for such an MRP system under lead time uncertainties.

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Section: Introductionmentioning

confidence: 99%

Multilevel Production Systems with Dependent Demand with Uncertainty of Lead Times

Sadeghi

Makui

Heydari

2016

Mathematical Problems in Engineering

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“…Louly and Dolgui (2013) considers multi-period Material Requirement Planning (MRP) under uncertainties lead times with no major restriction on the type of the leadtime distribution. They proposed a model and algorithms, which minimize the sum of the setup and holding costs while satisfying a constraint on the service level and the aim of this model is to find the optimal MRP time phasing corresponding to each periodicity of the POQ policy while Sadeghi et al (2013) considers a multi period serial production system for one product and deals with the problem of planned lead-time calculation in a Material Requirement Planning (MRP) environment under probabilistic lead times. It is assumed that lead times for all stages have the same distribution with different parameters.…”

Section: Introductionmentioning

confidence: 99%

A simulation method for Material requirement planning supply dependent demand and uncertainty lead-time

Sadeghi¹,

Makui²,

Heydari³

2014

Afr. J. Bus. Manage.

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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.

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“…In this paper the redundancy allocation problem (RAP) in systems with serial parallel structures and with choices of redundancy strategy and component type is studied where standby strategy is of cold type. Production system is an example of serial systems [2]. Space exploration and satellite systems achieve high reliability using cold standby redundancy for nonrepairable systems [3].…”

Section: Introductionmentioning

confidence: 99%

A New Nonlinear Multi-objective Redundancy Allocation Model with the Choice of Redundancy Strategy Solved by the Compromise Programming Approach

Sadjadi¹,

Tofigh

Soltani

2014

IJE

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One of the primary concerns in any system design problem is to prepare a highly reliable system with minimum cost. One way to increase the reliability of systems is to use redundancy in different forms such as active or standby. In this paper, a new nonlinear multi-objective integer programming model with the choice of redundancy strategy and component type is developed where standby strategy is of cold type. In the proposed model, system's reliability is maximized along with minimizing system's cost and weight. The proposed model contributes to the literature by determining the redundancy strategies concurrently with determining redundancy levels and component types. The multi-objective model is solved using the mathematical compromise programming technique for different Lp metrics and produces different Pareto solutions.

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Determining the periodicity and planned lead time in serial-production systems with dependent demand and uncertain lead time

Cited by 7 publications

References 15 publications

Multilevel Production Systems with Dependent Demand with Uncertainty of Lead Times

Multilevel Production Systems with Dependent Demand with Uncertainty of Lead Times

A simulation method for Material requirement planning supply dependent demand and uncertainty lead-time

A New Nonlinear Multi-objective Redundancy Allocation Model with the Choice of Redundancy Strategy Solved by the Compromise Programming Approach

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