Optimal periodical time for preventive replacement based on a cumulative repair-cost limit and random lead time

2009 ◽  
Vol 223 (4) ◽  
pp. 333-345 ◽  
Author(s):  
Y-H Chien ◽  
C-C Chang ◽  
S-H Sheu
Keyword(s):  
Lead Time ◽  
Repair Cost ◽  
Preventive Replacement ◽  
Random Lead Time ◽  
Cost Limit

Optimal repair/replacement policy for a general repair model

2001 ◽  
Vol 33 (1) ◽  
pp. 206-222 ◽  
Author(s):  
Xiaoyue Jiang ◽  
Viliam Makis ◽  
Andrew K. S. Jardine
Keyword(s):  
Average Cost ◽  
Failure Time ◽  
Operating Time ◽  
Replacement Policy ◽  
Repair Cost ◽  
Virtual Age ◽  
Preventive Replacement ◽  
Long Run ◽  
Special Cases ◽  
Cost Limit

In this paper, we study a maintenance model with general repair and two types of replacement: failure and preventive replacement. When the system fails a decision is made whether to replace or repair it. The repair degree that affects the virtual age of the system is assumed to be a random function of the repair-cost and the virtual age at failure time. The system can be preventively replaced at any time before failure. The objective is to find the repair/replacement policy minimizing the long-run expected average cost per unit time. It is shown that a generalized repair-cost-limit policy is optimal and the preventive replacement time depends on the virtual age of the system and on the length of the operating time since the last repair. Computational procedures for finding the optimal repair-cost limit and the optimal average cost are developed. This model includes many well-known models as special cases and the approach provides a unified treatment of a wide class of maintenance models.

scholarly journals An Inventory Model for Deteriorating Drugs with Stochastic Lead Time

2018 ◽  
Vol 15 (12) ◽  
pp. 2772 ◽  
Author(s):  
Jian Li ◽  
Lu Liu ◽  
Hao Hu ◽  
Qiuhong Zhao ◽  
Libin Guo
Keyword(s):  
Shelf Life ◽  
Inventory Management ◽  
Lead Time ◽  
Service Level ◽  
Inventory Model ◽  
Effective Management ◽  
Product Availability ◽  
Stochastic Lead Time ◽  
Random Lead Time ◽  
The Right

Inventory management of deteriorating drugs has attracted considerable attention recently in hospitals. Drugs are a kind of special product. Two characteristics of some drugs are the shorter shelf life and high service level. This causes hospitals a great deal of difficulty in inventory management of perishable drugs. On one hand, hospitals should increase the drug inventory to achieve a higher service level. On the other hand, hospitals should decrease the drug inventory because of the short shelf life of drugs. An effective management of pharmaceuticals is required to ensure 100% product availability at the right time, at the right cost, in good conditions to the right customers. This requires a trade-off between shelf-life and service level. In addition, many uncontrollable factors can lead to random lead time of drugs. This paper focuses on deteriorating drugs with stochastic lead time. We have established a stochastic lead time inventory model for deteriorating drugs with fixed demand. The lead time obeyed a certain distribution function and shortages were allowed. This model also considered constraints on service level, stock space and drug shelf life. Through the analysis of the model, the shelf life of drugs and service level were weighted in different lead time distributions. Empirical analysis and sensitivity analysis were given to get reach important conclusions and enlightenment.

Optimal number of minimal repairs before replacement based on a cumulative repair-cost limit policy

2010 ◽  
Vol 59 (4) ◽  
pp. 603-610 ◽  
Author(s):  
Chin-Chih Chang ◽  
Shey-Huei Sheu ◽  
Yen-Luan Chen
Keyword(s):  
Optimal Number ◽  
Repair Cost ◽  
Cost Limit
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