A time-based order fill rate model for spare parts

The service central warehouse at Vanderlande holds numerous spare parts on stock to fill up client orders for spare parts. In this study the supply chain of spare parts at Vanderlande is reviewed and eventually an inventory model for the service central warehouse is created which maximizes the percentage of client orders that’s entirely filled inside a given timeframe, with regards to the total holding costs. Actual life data has been entered to the model and led to substantial enhancements in both holding costs and order fill rate in comparison with the present stock levels…


1. Introduction
1.1. Company description
1.1.1. Organization
1.1.2. Service department
1.1.3. Service central warehouse
1.2. Research assignment
1.2.1. Research goals
1.2.2. Problem statement
1.2.3. Research questions
1.3. Outline of the thesis
2. Supply chain
2.1. Customers
2.2. Demand streams
2.2.1. Emergency orders
2.2.2. Preventive maintenance orders
2.2.3. Replenishment orders
2.2.4. Spare part packages
2.2.5. Revisions, modifications and retrofits (RMR)
2.3. Demarcation
2.3.1. Demand streams
2.3.2. Performance
2.3.3. Two types of spare parts
2.4. Current performance
2.5. Conclusion
3.1. Supply chain characteristics
3.2. Literature
3.3. Approach
4. Order line fill rate model
4.1. Definitions and notations
4.2. Modeling assumptions
4.2.1. General assumptions
4.2.2. Basic model assumptions
4.3. Calculations
4.3.1. Calculating the order line fill rate
4.3.2. Determining reorder point and replenishment order quantity
4.4. Model verification
4.4.1. Test instances
4.4.2. Simulation study
4.4.3. Results
4.5. Conclusion
5. Order fill rate model
5.1. Including variable replenishment lead time
5.1.1. Modeling options
5.1.2. Verification
5.1.3. Results
5.2. Including delivery timeframe in performance measure
5.2.1. Modeling approach
5.2.2. Verification
5.2.3. Results
5.3. Adding fixed supplier delivery days
5.3.1. Periodic review model
5.3.2. Verification
5.3.3. Results
5.4. Calculation of order fill rate
5.4.1. Calculating order fill rate from order line fill rates
5.4.2. Verification
5.4.3. Results
5.4.4. Validation
5.4.5. Determine reorder points
5.4.6. Greedy heuristic
5.5. Conclusion
6. Results and analysis
6.1. Data
6.1.1. Available data
6.1.2. Desired data
6.2. Results
6.2.1. Basic scenario
6.2.2. Model adjustments
6.2.3. Comparison to current stock levels
6.3. Analysis of parameters
6.3.1. Minimum demand rate to remain original order quantity
6.3.2. Minimum demand rate for inclusion
6.3.3. Timeframe
6.3.4. Demand rate weights
6.4. Scenarios
6.5. Separation of service orders
6.6. Conclusion
7. Implementation
7.1. Software
7.1.1. Applying the model
7.1.2. Categorization of spare parts
7.1.3. Results
7.2. Training
8. Conclusions and recommendations
8.1. Conclusions
8.2. Recommendations
8.2.1. Recommendations for performance improvement
8.2.2. Recommendations for model extensions
8.2.3. Recommendations for implementation of the model
A. Definitions
B. Derivations
B.1. Order line fill rate calculation for the basic model
B.1.1. Using compound Poisson demand
B.1.2. Two moments method
B.2. Determining the reorder point R if the order quantity Q is given….

Source: University of Twente

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