Spare Part Management Using Economic Order Quantity Model With Fuzzy-Analytical Hierarchy Process (Fuzzy-AHP) Optimization
Maintenance is one of the pillar in developing world class manufacturing. One of the accountability of maintenance team is the control of spare parts inventory. For a high transaction spare part, controlling the correct quantity is a real challenge. Several methods have been proposed by researchers...
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English English |
| Published: |
2019
|
| Subjects: | |
| Online Access: | http://eprints.utem.edu.my/id/eprint/24958/1/Spare%20Part%20Management%20Using%20Economic%20Order%20Quantity%20Model%20With%20Fuzzy-Analytical%20Hierarchy%20Process%20%28Fuzzy-Ahp%29%20Optimization.pdf http://eprints.utem.edu.my/id/eprint/24958/2/Spare%20Part%20Management%20Using%20Economic%20Order%20Quantity%20Model%20With%20Fuzzy-Analytical%20Hierarchy%20Process%20%28Fuzzy-Ahp%29%20Optimization.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Maintenance is one of the pillar in developing world class manufacturing. One of the accountability of maintenance team is the control of spare parts inventory. For a high transaction spare part, controlling the correct quantity is a real challenge. Several methods have been proposed by researchers to cater the issue. Owing to this reason, this project investigates economic order quantity (EOQ) application in a spare part management and inventory, and optimization of EOQ with Fuzzy Logic Analytic Hierarchy Process AHP (Fuzzy AHP). The objective is to determine the best combination of material and fabricator of a specified spare part using AHP and triangular and trapezoidal Fuzzy AHP. EOQ model was used to quantify the ideal quantity of the spare part to be purchased. For the three AHP models, five main criteria were used to decide; cost, quality, productivity, delivery time and quantity, and to support, another sets of sub-criteria to the five criteria as mentioned. Eight solutions or alternatives were to be chosen from. One of the alternative from the AHP hierarchy, has consistently been produced as the result calculated from AHP and Fuzzy AHP. Based on the final result, it is recorded that the first rank is alternative 8 (OPTION 8), thus for AHP is at 16.466%, triangular AHP at 13.115% and trapezoidal AHP at 13.332%. This consolidate that Fuzzy AHP are able to support AHP result with the correct data analyzed. From this alternative, an EOQ model is calculated, and then simulated in a visual form for a time period. Numerical examples are provided to illustrate the model from a case study. 87 pieces of the spare part is suggested as the EOQ for the specified part. Other quantity such as maximum quantity, minimum quantity and ordering point were also defined. Other decision making tool such as Analytic Network Process (ANP), AHP with Technique for Order of Preference by Similarity to Ideal Solution (AHP-TOPSIS) and Preference Ranking Organization Method for Enrichment of Evaluations (Promethee) are extensions for this research. Finally, industrial application is in the best interest to fully understand the impact of this research. |
|---|