scholarly journals Simulation-Based Optimization of a Two-Echelon Continuous Review Inventory Model with Lot Size-Dependent Lead Time

Processes ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1014
Author(s):  
Ibrahim Alharkan ◽  
Mustafa Saleh ◽  
Mageed Ghaleb ◽  
Abdulsalam Farhan ◽  
Ahmed Badwelan
Keyword(s):  
Supply Chain ◽  
Lead Time ◽  
Shop Floor ◽  
Lot Size ◽  
Continuous Review ◽  
Inventory Costs ◽  
Size Dependent ◽  
Simulation Based ◽  
Simulation Based Optimization ◽  
Total Inventory

This study analyzes a stochastic continuous review inventory system (Q,r) using a simulation-based optimization model. The lead time depends on lot size, unit production time, setup time, and a shop floor factor that represents moving, waiting, and lot size inspection times. A simulation-based model is proposed for optimizing order quantity (Q) and reorder point (r) that minimize the total inventory costs (holding, backlogging, and ordering costs) in a two-echelon supply chain, which consists of two identical retailers, a distributor, and a supplier. The simulation model is created with Arena software and validated using an analytical model. The model is interfaced with the OptQuest optimization tool, which is embedded in the Arena software, to search for the least cost lot sizes and reorder points. The proposed model is designed for general demand distributions that are too complex to be solved analytically. Hence, for the first time, the present study considers the stochastic inventory continuous review policy (Q,r) in a two-echelon supply chain system with lot size-dependent lead time L(Q). An experimental study is conducted, and results are provided to assess the developed model. Results show that the optimized Q and r for different distributions of daily demand are not the same even if the associated total inventory costs are close to each other.

scholarly journals MATERIAL REQUIREMENT PLANNING UNTUK MEMENUHI PRODUKSI PADA CV. BANGUN CIPTA ARTHA DI BADUNG

2020 ◽  
Vol 9 (2) ◽  
pp. 426
Author(s):  
I Made Sugita Yasa ◽  
Kastawan Mandala
Keyword(s):  
Inventory Management ◽  
Lot Sizing ◽  
Raw Materials ◽  
Raw Material ◽  
Exact Order ◽  
Lot Size ◽  
Inventory Costs ◽  
Material Requirement Planning ◽  
Material Requirement ◽  
Total Inventory

Inventory management without Material Requirement systems in CV. Bangun Cipta Artha resulted in the lot size for each order of raw materials not optimal. One concept that can be used to plan and control raw materials is the Material Requirement Planning. This study is to determine the number of sizes of raw material orders, the exact order time, the method that produces the lowest cost for each raw material, and the effect of using MRP on inventory costs. This research conducted on 160x200cm spring bed products. Data was analyzed by making production master schedules, determining net requirements, determining lot size, and making MRP tables. Based on the results, the determination the best lot sizing is the order quantiy period which results in a total inventory cost of Rp. 26,475,220 where the total cost is lower, compared to lot for lot method which Rp. 43,464,000. part period balancing Rp. 33,106,576, and conventional method Rp.49,472,912. Keywords: Material Requirement Planning (MRP), Sizing Lot, Lot For Lot, Balancing Part Period, Period Order Quantiy

A Simulation-Based Methodology for Lot-Size Optimization

2008 ◽  
Vol 392-394 ◽  
pp. 866-872 ◽  
Author(s):  
Y. Kou ◽  
Jian Jun Yang
Keyword(s):  
Lead Time ◽  
Object Oriented ◽  
Size Optimization ◽  
Control Points ◽  
Production Environment ◽  
Lot Size ◽  
Work In Process ◽  
Simulation Based ◽  
Product Manufacturing ◽  
Set Up

In the process of lot size optimization, various factors such as machine capability and parts assembly lead time need to be considered. Within small batch and multi-items production environment, kitting parts entering to assembly systems in time may valid shorten product manufacturing period, and reduce the quantity of work-in-process (WIP). This paper built up a mathematical model with the objective function of reducing set up costs, shortening cycle of part production and reducing WIP and with constraints of machine capabilities, part process planning and kitting requirement. An object-oriented simulation model is established to control the behavior of logistics objects to meet the target functions through rules aggregation and constraints at the control points, resulting in an optimal production result.

Review on Inventory Controlling of Building Materials Supply Chain from Uncertainty Demands in Civil Engineering

2012 ◽  
Vol 174-177 ◽  
pp. 3441-3443
Author(s):  
Bin Yang
Keyword(s):  
Supply Chain ◽  
Building Materials ◽  
Simulated Annealing Algorithm ◽  
Supply And Demand ◽  
Cost Models ◽  
Inventory Cost ◽  
Inventory Costs ◽  
Total Inventory ◽  
Annealing Algorithm ◽  
The Difference

Inventory control is a necessary strategy that enterprises use to offset the effect of uncertainties in manufacturing, supply and demand. Normally, probability distribution is used to analyze the uncertainty problems, however, this analysis can’t be completed with inadequate data, resulting in an increase in inventory costs. The paper establishes inventory cost models of single supply chain member under uncertainty demands and applies Simulated Annealing Algorithm to imitate the models in 52 weeks to seek for the optimal speaking for amount and anew speaking for point so that compares the difference of supply chain total inventory cost and the sufficing rate of order for goods between independently and collaborated controlling strategy in supply chain, and in order to provide the necessary theoretical supports for the enterprises to establish supply chain partnerships and possibly improve the supply chain capability of providing external integration.

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