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Printing Spare Parts in Remote
Locations
By Bram Westerweel, Rob Basten, Jelmar den Boer, Geert-Jan
van Houtum
RNLA mission involvement
26-9-2018SINTAS AM workshop 2
MINUSMA (Mali)
26-9-2018SINTAS AM workshop 3
NLD – MALI: 4000 KM
Supply options (1)
26-9-2018SINTAS AM workshop 4
Supply options (2)
26-9-2018SINTAS AM workshop 5
Operating bases in remote locations
26-9-2018SINTAS AM workshop 6
Forward operations in remote locations
26-9-2018SINTAS AM workshop 7
On-site printing results (1)
26-9-2018SINTAS AM workshop 8
On-site printing results (2)
26-9-2018SINTAS AM workshop 9
On-site printing results (3)
26-9-2018SINTAS AM workshop 10
Model building
Supply of spare parts
• Scheduled replenishment to the base every 𝑳 periods
• On-site printing as an option for backorders that occur in
between replenishments
26-9-2018SINTAS AM workshop 11
Model building
Spare parts characteristics and demand
• Replenishment and printing has a zero-period lead time
• Printed parts have a higher probability of failure 𝒑 𝒑 > 𝒑 𝒓
• Unit ordering costs 𝒄 𝒓 and 𝒄 𝒑
• Number of systems = 𝑵
We assume that printed parts are removed and disposed of
at the end of each order cycle
26-9-2018SINTAS AM workshop 12
Simple optimal policy structure
26-9-2018SINTAS AM workshop 13
Model application
The RNLA provides us with data on ~3000 spare parts for
three of its systems
26-9-2018SINTAS AM workshop 14
Where to start?
Not all parts can be printed and technical assessments are
labor intensive
• Multiple criteria determine printing potential. We use a
scoring framework adapted from Knofius et al. (2016)
• 100 spare parts are assessed by the RNLA’s AM expert
• 14 parts can be printed with the current printer
26-9-2018SINTAS AM workshop 15
Parameterization based on Mali
Printing costs are determined based on volume 𝒗, printing
speed 𝒔, raw material cost 𝒄 𝒎, and depreciation cost per hour 𝒄 𝒅
Printed parts are estimated to fail approximately 10 times faster
than regular parts 𝒑 𝒑 = 𝟏𝟎𝒑 𝒓
Installed base size = [𝟔, 𝟖, 𝟒𝟐]
Holding costs 𝒉 = 𝒄 𝒓/𝟑𝟔𝟓
Weekly replenishment to the main operating base 𝑳 = 𝟕 𝒅𝒂𝒚𝒔
26-9-2018SINTAS AM workshop 16
Application results for Mali
26-9-2018SINTAS AM workshop 17
Application results for Mali
26-9-2018SINTAS AM workshop 18
Application results for Mali
• Base stock levels decrease by 74% and downtime by 92%
26-9-2018SINTAS AM workshop 19
Application results for Mali
• Base stock levels decrease by 74% and downtime by 92%
• We find a -0.52 correlation coefficient between the spare parts
rank and annual savings
26-9-2018SINTAS AM workshop 20
The impact of printing in Mali
To what extent are these parts representative of the entire set?
• Technical feasibility is not a criterion of the part ranking method
• This implies that 10-20% of parts can be printed
• And this number will grow as technology develops
We only considered 3 systems, but there are many more!
26-9-2018SINTAS AM workshop 21
Extension: Operations closer to home
Sometimes parts can be expedited overnight at a premium cost in
case of a shortage
• Denote unit expediting costs by 𝒄 𝒆 > 𝒄 𝒓 and 𝒄 𝒆 > 𝒄 𝒑
Illustrating a new optimal policy structure
26-9-2018SINTAS AM workshop 22
Extension: Operations closer to home
Suppose that 𝒄 𝒆 = 𝟒𝒄 𝒓 (Recall that printing saves 58% by itself)
• Expediting saves 9.8% as a stand-alone option
• Combining expediting and printing saves 58.7%
On-site printing will also impact operations closer to the
Netherlands and its allies
26-9-2018SINTAS AM workshop 23
Conclusions
On-site AM will significantly affect the RNLA’s operations in
remote locations by:
• Decreasing required storage space via reduced base-stock levels
• Increased asset availability by a cheap temporary solution to
inventory shortages
Benefits are attained even if printed parts have much worse
characteristics than regular parts!
On-site AM can be applied to a substantial subset of parts
26-9-2018SINTAS AM workshop 24
Broader implications
26-9-2018SINTAS AM workshop 25

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180926 TUE-RNLA - Printing Spare Parts in Remote Locations

  • 1. Printing Spare Parts in Remote Locations By Bram Westerweel, Rob Basten, Jelmar den Boer, Geert-Jan van Houtum
  • 3. MINUSMA (Mali) 26-9-2018SINTAS AM workshop 3 NLD – MALI: 4000 KM
  • 6. Operating bases in remote locations 26-9-2018SINTAS AM workshop 6
  • 7. Forward operations in remote locations 26-9-2018SINTAS AM workshop 7
  • 8. On-site printing results (1) 26-9-2018SINTAS AM workshop 8
  • 9. On-site printing results (2) 26-9-2018SINTAS AM workshop 9
  • 10. On-site printing results (3) 26-9-2018SINTAS AM workshop 10
  • 11. Model building Supply of spare parts • Scheduled replenishment to the base every 𝑳 periods • On-site printing as an option for backorders that occur in between replenishments 26-9-2018SINTAS AM workshop 11
  • 12. Model building Spare parts characteristics and demand • Replenishment and printing has a zero-period lead time • Printed parts have a higher probability of failure 𝒑 𝒑 > 𝒑 𝒓 • Unit ordering costs 𝒄 𝒓 and 𝒄 𝒑 • Number of systems = 𝑵 We assume that printed parts are removed and disposed of at the end of each order cycle 26-9-2018SINTAS AM workshop 12
  • 13. Simple optimal policy structure 26-9-2018SINTAS AM workshop 13
  • 14. Model application The RNLA provides us with data on ~3000 spare parts for three of its systems 26-9-2018SINTAS AM workshop 14
  • 15. Where to start? Not all parts can be printed and technical assessments are labor intensive • Multiple criteria determine printing potential. We use a scoring framework adapted from Knofius et al. (2016) • 100 spare parts are assessed by the RNLA’s AM expert • 14 parts can be printed with the current printer 26-9-2018SINTAS AM workshop 15
  • 16. Parameterization based on Mali Printing costs are determined based on volume 𝒗, printing speed 𝒔, raw material cost 𝒄 𝒎, and depreciation cost per hour 𝒄 𝒅 Printed parts are estimated to fail approximately 10 times faster than regular parts 𝒑 𝒑 = 𝟏𝟎𝒑 𝒓 Installed base size = [𝟔, 𝟖, 𝟒𝟐] Holding costs 𝒉 = 𝒄 𝒓/𝟑𝟔𝟓 Weekly replenishment to the main operating base 𝑳 = 𝟕 𝒅𝒂𝒚𝒔 26-9-2018SINTAS AM workshop 16
  • 17. Application results for Mali 26-9-2018SINTAS AM workshop 17
  • 18. Application results for Mali 26-9-2018SINTAS AM workshop 18
  • 19. Application results for Mali • Base stock levels decrease by 74% and downtime by 92% 26-9-2018SINTAS AM workshop 19
  • 20. Application results for Mali • Base stock levels decrease by 74% and downtime by 92% • We find a -0.52 correlation coefficient between the spare parts rank and annual savings 26-9-2018SINTAS AM workshop 20
  • 21. The impact of printing in Mali To what extent are these parts representative of the entire set? • Technical feasibility is not a criterion of the part ranking method • This implies that 10-20% of parts can be printed • And this number will grow as technology develops We only considered 3 systems, but there are many more! 26-9-2018SINTAS AM workshop 21
  • 22. Extension: Operations closer to home Sometimes parts can be expedited overnight at a premium cost in case of a shortage • Denote unit expediting costs by 𝒄 𝒆 > 𝒄 𝒓 and 𝒄 𝒆 > 𝒄 𝒑 Illustrating a new optimal policy structure 26-9-2018SINTAS AM workshop 22
  • 23. Extension: Operations closer to home Suppose that 𝒄 𝒆 = 𝟒𝒄 𝒓 (Recall that printing saves 58% by itself) • Expediting saves 9.8% as a stand-alone option • Combining expediting and printing saves 58.7% On-site printing will also impact operations closer to the Netherlands and its allies 26-9-2018SINTAS AM workshop 23
  • 24. Conclusions On-site AM will significantly affect the RNLA’s operations in remote locations by: • Decreasing required storage space via reduced base-stock levels • Increased asset availability by a cheap temporary solution to inventory shortages Benefits are attained even if printed parts have much worse characteristics than regular parts! On-site AM can be applied to a substantial subset of parts 26-9-2018SINTAS AM workshop 24