A simulation-based finite capacity MRP procedure not depending on lead time estimation

2011 ◽  
Vol 11 (3) ◽  
pp. 237 ◽  
Author(s):  
Tommaso Rossi ◽  
Margherita Pero
Keyword(s):  
Lead Time ◽  
Time Estimation ◽  
Finite Capacity ◽  
Simulation Based

Decoupled Lead Time in finite capacity flowshop: a feedback loop approach

2019 ◽  
Author(s):  
Guillaume Dessevre ◽  
Guillaume Martin ◽  
Pierre Baptiste ◽  
Jacques Lamothe ◽  
Robert Pellerin ◽  
...  
Keyword(s):  
Lead Time ◽  
Feedback Loop ◽  
Finite Capacity

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.

Lead time control in multi-class multi-stage assembly systems with finite capacity

2013 ◽  
Vol 66 (4) ◽  
pp. 808-817 ◽  
Author(s):  
Saeed Yaghoubi ◽  
Siamak Noori ◽  
Amir Azaron
Keyword(s):  
Lead Time ◽  
Assembly Systems ◽  
Finite Capacity ◽  
Time Control ◽  
Multi Stage

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.

scholarly journals A simulation-based finite capacity scheduling system

1997 ◽  
Author(s):  
Alexander J. Weintraub ◽  
Andrew Zozom ◽  
Thorn J. Hodgson ◽  
Denis Cormier
Keyword(s):  
Finite Capacity ◽  
Scheduling System ◽  
Simulation Based

scholarly journals A Simulation-Based Model for Determining Safety Inventory at a Fixed-time Period System

2019 ◽  
Vol 8 (12) ◽  
pp. 2775-2780
Keyword(s):  
Lead Time ◽  
Fixed Time ◽  
Service Level ◽  
Microsoft Excel ◽  
Time Period ◽  
Simulation Based ◽  
Period System ◽  
Daily Forecast ◽  
Visual Basic Application ◽  
Normally Distributed

This paper develops a simulation model for determining safety inventory associated with a certain value of cycle service level in a fixed-time period system. The model takes into account actual amount of materials received from suppliers, and deviation from probability distribution of daily forecast demand. Constraints on order size are also embodied into the model. This model was constructed by using Visual Basic Application added in Microsoft Excel. After developing the model, hypotheses testing is employed to verify the model. This model allows identifying safety inventory under uncertain conditions which prohibits from the use of ordinary mathematical formula. The model was locally verified. Stochastic variables including customer demand and supplier’s lead time are assumed to be normally distributed. Independent demand items are considered and backorders are not allowed. Under specific conditions, such as distributions of demand and lead time are normally distributed, and fixed-time period system is being used. This model allows materials planner promptly identifies safety inventory associated with a certain level of cycle service level. Furthermore, planner can perceive the affects of changing input parameters on the amount of safety inventory required. There were very few researches focus on variations of demand and lead time at the same time. In reality, this case usually happens, thus the firms have been facing highly variations form both supplier and customers. Therefore, this paper intends to close this gap by simulating these factors and taken into account for determining safety inventory.

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