Date: 01-03-2016 Location: Eindhoven University of Technology

1. BIM based process mining
Enabling knowledge reassurance and fact-based problem
discovery within the AECFM industry
Graduation thesis for Construction Management and Engineering Msc by :
Stijn van Schaijk

3. Always the same problems?

4. Complexity in the construction
sector?
• Winch (1987): construction projects are amongst
the most complex of all activities.
• Gidado (1996): rapid increase in the complexity of
construction processes.
• Lots of specialists/experts/companies

5. A construction project team

6. A new construction project team

7. Large fragmentation results in…

8. … short learning curve

9. … short learning curve

10. As a result of knowledge loss
• Same problems over and over…

11. As a result of knowledge loss
• Wastes/spoilings

12. As a result of knowledge loss
• A lot of improvements possible in terms of quality,
speed, efficiency and money!

13. Target of the research:

14. How?
• Knowledge reassurance with Building Information
Modelling and Process Mining.
• Learn from previous projects.
• Finding bottlenecks and planning deviation.
• Develop a method with tools to reuse data from
previous projects.

16. What is BIM?

17. What is Process Mining?
https://www.youtube.com/watch?v=7oat7MatU_U

19. Case studies: Construction
process mining

20. Case study: Construction design
process mining

21. Case study: Construction design
process mining
• Analysis of the design process of a road project

22. Case study: Construction design
process mining
• Event log export from Relatics
• ± 140.000 events

23. Planned process of verification a specification
1. Create/Import Specification
2. Connect Specification to Upper/Lower Specification
3. Assign Specification description
4. Assign control responsibility
5. Assign Specification to Project phase
6. Assign Specification to Person
7. Connect Specification to Work package activity 1
8. Connect Specification to Work package activity 2
9. Connect Specification to Work package activity 3
10. Create work package (WPA) verification
11. Assign work package (WPA) verification to Person
12. Add document of prove
13. Add note to WPA verification

24. As-planned:

25. As-planned:

26. As-happend:
Most extreme result:
1 specification had 1904 process steps

27. Most extreme result:
1 specification had 1904 process steps

28. Most extreme result:
1 specification had 1904 process steps

29. Conclusion case study
“Process mining analytics did us realize that we use our
IT systems to store information, but those systems don’t
automatically facilitate an efficient process.”
-Process engineer, contractor
More info? Read
http://www.slideshare.net/StijnvanSchaijk/case-study-
construction-design-process-mining

30. Case studies: Construction
process mining

31. Continuous improvement cycle
during construction projects
• How: Plan, (Autonomous-) Capture, Analyse and
Reuse process data from construction sites
• Finding and storing bottlenecks and planning deviation

32. Case study: Schependomlaan
Nijmegen
• Partners:
• Hendriks Bouw en Ontwikkeling
• Dreamfocus Droned
• RAAMAC
IFC model

33. Need for tools

34. Plan
1. Connect planning to IFC
2. Generate As-planned models

35. Capture
1. Scan construction site with drone
2. Create As-built point cloud model (Structure from
motion)
3. Compare As-built with As-planned
4. Merge results with event log

36. 1. Scan construction site with drones
(Dreamfocus Droned
https://www.youtube.com/watch?v=QbBf31bY0xw )

37. 2. Create As-built point cloud
model
• Structure from motion techniques, how does it
work?

38. Take a lot of images of an object
• Around 300 pictures generated from drone movie

39. Identify points in the images that can
possibly be detected in other images

40. Search for corrseponding points in
other images

41. Compute camera positions and 3D
point positions such that
corresponding viewing rays intersect
• (Matlab script)

42. Result: As-built point cloud

43. 4. Compare As-planned and As-
built

44. Elements missing according to
dronescan
• Week 26 : 9 missing elements - windows and
insulation parts.
• Week 27 : 50 missing elements - windows
• Week 28 : 89 missing elements - windows,
insulation, brick facades, and prefab elements.
• Week 29 : 18 missing elements - windows,
insulation and brick facades.
• Week 30 : 4 missing elements - windows.

45. Final event log
• 3661 events tagged ‘On time’, or ‘Too late’

46. Plan
CaptureAnalyse
Reuse
3. Analyse

47. Event log analytics
1. As-planned vs As-built
2. Durations
3. Process variants
4. Bottlenecks
5. Social analytics

48. Analytics concrete floor
• Query: Give me all the processes related to the
material “Breedplaatvloer”

49. Concrete floors

50. Concrete floors

51. Social analytics
• Query: who is most influential on the project?

52. Social analytics
• Query: Which tasks has ‘Timmerman 1’ done at this
project?

53. 4. Reuse
• Tool: Planning consult with BIMserver
Plan
CaptureAnalyse
Reuse

54. 4. Reuse

55. Planning consult

56. Risk visualization

57. Planning advice and risk identification

58. Case study recap
Plan
CaptureAnalyse
Reuse

59. Results & discussion
• Found reuse applications for as-planned BIMs
• Advice: As-planned models contain valuable data, reuse
them

60. Results & discussion
• Used state of the art for process capturing.
• Advice: Allign planning and capturing tools.

61. Results & discussion
• Bridged gap process mining and BIM

62. Results & discussion
• Discovered potentials process mining in
construction industry.
• Read case study design process mining
• http://www.slideshare.net/StijnvanSchaijk/case-study-construction-design-process-
mining
• Read case study facility management process
mining:
• http://www.slideshare.net/StijnvanSchaijk/case-study-process-mining-with-facility-
management-data

63. Further work
Project level

64. Further work
Company level
(Process oriented data warehouse)

65. Further work
Industry level

66. Further work
• Reuse facility management data for new projects
• Identify risks in very early stages

67. Further work
• More alignment between physical and digital
world, so more data.
• Real time data reuse so failures can be predicted

68. You can reuse:
Dataset:
http://bit.do/DataSetSchependomlaan
Tools
• Eventlog generator: https://www.youtube.com/watch?v=LOJsHvGq-KE
• Planning consult: https://www.youtube.com/watch?v=nJTh_0Xmra0
Thesis
http://www.slideshare.net/StijnvanSchaijk/building-information-
model-bim-based-process-mining

69. Thanks to all who have helped
Questions?Dreamfocus
Droned