An Integrated Imperfect Production-Inventory Model with Lot-Size-Dependent Lead-Time and Quality Control

In recent times, in the literature of inventory management there exists a notorious interest in production-inventory models focused on imperfect production processes with a deterministic time horizon. Nevertheless, it is well-known that there is a high influence and impact caused by the learning effect on the production-inventory models in the random planning horizon. This research work formulates a mathematical model for a re-workable multi-item production-inventory system, in which the demand of the items depends on the accessible stock and selling revenue. The production-inventory model allows shortages and these are partial backlogged over a random planning horizon. Also, the learning effect on the rework policy, inflation, and the time value of money are considered. The main aim is to determine the optimum production rates that minimize the expected total cost of the multi-item production-inventory system. A numerical example is solved and a detailed sensitivity analysis is conducted in order to study the production-inventory model.

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Three-layer supply chain in an imperfect production inventory model with two storage facilities under fuzzy rough environment

Journal of Uncertainty Analysis and Applications ◽

10.1186/s40467-014-0017-1 ◽

2014 ◽

Vol 2 (1) ◽

Cited By ~ 16

Author(s):

Amalesh Kumar Manna ◽

Jayanta Kumar Dey ◽

Shyamal Kumar Mondal

Keyword(s):

Supply Chain ◽

Inventory Model ◽

Imperfect Production ◽

Production Inventory ◽

Storage Facilities

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

Processes ◽

10.3390/pr8091014 ◽

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.

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