Optimal Batch Production with Rework Process for Products with Time-Varying Demand Over Finite Planning Horizon

2017 ◽  
pp. 57-68 ◽  
Author(s):  
Lakdere Benkherouf ◽  
Konstantina Skouri ◽  
Ioannis Konstantaras
Keyword(s):  
Planning Horizon ◽  
Time Varying ◽  
Batch Production ◽  
Optimal Batch ◽  
Varying Demand ◽  
Finite Planning Horizon ◽  
Rework Process

scholarly journals A model of a production-repair inventory system with time-varying demand and quality-dependent recovery channels

2021 ◽  
Vol 36 ◽  
pp. 04002
Author(s):  
Ivan Yeo
Keyword(s):  
Raw Materials ◽  
Planning Horizon ◽  
Inventory System ◽  
Raw Material ◽  
Time Varying ◽  
Total Cost ◽  
External Sources ◽  
Varying Demand ◽  
Infinite Planning Horizon ◽  
Better Than

In this paper, we study an inventory system over an infinite planning horizon where a time-varying demand is satisfied by process cycles that consist of a production batch followed by a recovery batch. Our model considers three types of inventory—returned items, serviceable items, and raw material. Furthermore, our model considers two recovery channels—recovery into serviceable items and recovery into raw material. Serviceable items are thus sourced from two inputs—direct recovery and production from raw material. These raw materials can be salvaged from returned items, as well as bought from external sources whenever required. We propose an expression for the unit time total cost as well as a numerical method to find the optimal policy. The properties of the model are studied through numerical experiments, in particular, the feasible situations where hybrid policies are better than pure policies.

Optimal batch ordering over a finite planning horizon

2014 ◽  
Vol 19 (4) ◽  
pp. 385 ◽  
Author(s):  
Abdullah O. Alsuwainea ◽  
Lakdere Benkherouf ◽  
Suresh P. Sethi
Keyword(s):  
Planning Horizon ◽  
Optimal Batch ◽  
Batch Ordering ◽  
Finite Planning Horizon

On Reserve Money for a Fuzzy EOQ Model in an Inflationary Environment Under Supplier Credit

2018 ◽  
pp. 327-348
Author(s):  
Nirmal Kumar Duari ◽  
Tripti Chakrabarti
Keyword(s):  
Planning Horizon ◽  
Economic Feasibility ◽  
Time Varying ◽  
Discounted Cash Flow ◽  
Numerical Examples ◽  
Deterioration Rate ◽  
Eoq Model ◽  
Reserve Capital ◽  
Finite Planning Horizon ◽  
Supplier Credit

We propose to derive a deterministic inventory model for a time varying deterioration rate with an exponential fuzzy demand over a finite planning horizon in this study. We assume that the supplier offers a credit limit to the retailer during which there is no interest charged. However, the retailer has the reserve capital with him to make the payments at the beginning of the transaction, but he decides to take the benefit of the credit limit. Each cycle has shortages, which have been partially backlogged to suit present day competition in the market. Also, the whole study has been done in an inflationary environment using the Discounted Cash Flow (DCF) approach to impart economic feasibility to the model. Numerical examples have been presented with the help of lingo software.

Optimizing preventive maintenance over a finite planning horizon in a semi-Markov framework

2020 ◽  
Author(s):  
Antonio Sánchez Herguedas ◽  
Adolfo Crespo Márquez ◽  
Francisco Rodrigo Muñoz
Keyword(s):  
Preventive Maintenance ◽  
Recurrence Relations ◽  
Direct Calculation ◽  
Planning Horizon ◽  
Practical Implementation ◽  
Practical Application ◽  
Mathematical Solution ◽  
Accumulated Reward ◽  
Finite Planning Horizon

Abstract This paper describes the optimization of preventive maintenance (PM) over a finite planning horizon in a semi-Markov framework. In this framework, the asset may be operating, and providing income for the asset owner, or not operating and undergoing PM, or not operating and undergoing corrective maintenance following failure. PM is triggered when the asset has been operating for τ time units. A number m of transitions specifies the finite horizon. This system is described with a set of recurrence relations, and their z-transform is used to determine the value of τ that maximizes the average accumulated reward over the horizon. We study under what conditions a solution can be found, and for those specific cases the solution τ* is calculated. Despite the complexity of the mathematical solution, the result obtained allows the analyst to provide a quick and easy-to-use tool for practical application in many real-world cases. To demonstrate this, the method has been implemented for a case study, and its accuracy and practical implementation were tested using Monte Carlo simulation and direct calculation.

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