SlideShare a Scribd company logo
1 of 24
ESTIMATING THE IMPACT
OF INCIDENTS ON
PROCESS DELAY
Felix Mannhardt, Petter Arnesen,
Andreas D. Landmark
2
3
Image sources: banenor.no
4
Case Activity
Railway Traffic Control Logs
5
Railway Traffic Logs – Example Process Model
What is process delay?
6
Definition A
Expected/Scheduled
vs.
Actual Performance
Definition B
Normal performance
vs.
Actual performance
What is known about incidents?
7
Image sources: banenor.no
What is known about incidents?
8
Incident Log
Issue registered
Mover/motor
turnout km 453
Work order created
Repair
Process
Work Order
DB
Manual
registration
Manual
registration
Registered?
Work started?
Contractor notified?
When was it fixed?
The Problem – Linking Incidents to Delay
9
• Internal performance factors
• Alignments to project performance information
• Identification of slow variants / combination of attributes
• Identification of slow resources
• Prediction of performance
• Remaining time to completion
• Some work considering inter-case parameters
• Visualisation of performance
• Dotted chart
• Others: Process Profiler, Performance Spectrum etc.
10
Existing work
None is addressing
the linking/estimation
challenge!
Proposed Approach – Assumptions #1
11
Proposed Approach – Assumptions #2
12
Resource required for trains
to pass station Støren!
Image sources: banenor.no
Proposed Approach – Impact Estimation #1
13 Step 1: Collect performance information from event log
Case 5262 took about 460s
for activity LMO-STØ (single track)
Approx. time for incident
on turnout XYZ
𝑇𝑖𝑛𝑐𝑖𝑑𝑒𝑛𝑡
Proposed Approach – Impact Estimation #2
14 Step 2: Determine normal process performance
Proposed Approach – Impact Estimation #3
15 Step 3: Classify activity instances into three classes
Proposed Approach – Impact Estimation #4
16 Step 4: Determine likely start/end of impact using MCMC
𝑇𝑠𝑡𝑎𝑟𝑡 ? 𝑇𝑒𝑛𝑑 ?
Metropolis-Hastings algorithms
20000 iterations
Priors for standard delay
e.g., 𝑝0 = (0.94, 0.055 0.005)
and incident-affected delay
e.g., 𝑝1 = (0.93, 0.06, 0.01)
hand tuned on small dataset.
Proposed Approach – Impact Estimation #4
17 Step 4: Determine likely start/end of impact using MCMC
𝑇𝑠𝑡𝑎𝑟𝑡 𝑇𝑒𝑛𝑑
Times at least 50% of the samples
between 𝑇𝑠𝑡𝑎𝑟𝑡 and 𝑇𝑒𝑛𝑑
Proposed Approach – Impact Estimation #5
18 Step 5: Accumulate delay
𝑇𝑠𝑡𝑎𝑟𝑡 𝑇𝑒𝑛𝑑Count fully Discount with prob.Discount with prob.
Evaluation – Case Study in Norway
19
TIOS
BaneData
Save result back
Traffic Control
System
Maintenance
Management
PRESENS-Algorithm
Data
Warehouse
Calculated the impact on delay for
each major incident since 2011
Work
orders
Driving
time
Delay
tagging
Validation
Evaluation – Delay Dashboard
20
Evaluation – Predictive Maintenance
21
• Prediction of "avoided" delay due
to smart maintenance
• Smart monitoring of turnouts
• Justification of investments
• Using the delay effect base on
historical data as proxy
• Not perfect, often rather small data basis
for prediction
• Better than management by `rule of
thumb`
• Explore application on non-infrastructure focussed processes
• Activity-incident relation is less obvious?
• Estimation of `normal` process performance challenging?
• Address the issue of multiple co-occurring incidents
• MCMC would have trouble with multi-modal distributions
• Address non-local knock-on effects on process delay
• Initial solution addresses the problem for single-track railway networks, but difficult to generalise!
• Investigate effects of queues etc. in non-physical processes
• Address the strong dependency on the chosen parameters in the prior
distribution  possible but high computational cost
22
Future work
23
Contact
felix.mannhardt@sintef.no
@fmannhardt
Thanks to BaneNOR which funded part of this research!
Teknologi for et bedre samfunn

More Related Content

What's hot

Acumen Fuse: Datasheet
Acumen Fuse: DatasheetAcumen Fuse: Datasheet
Acumen Fuse: Datasheet
Cisco
 
3 pm3 t_4%20-%20schedule%20development
3 pm3 t_4%20-%20schedule%20development3 pm3 t_4%20-%20schedule%20development
3 pm3 t_4%20-%20schedule%20development
harwoodr
 

What's hot (18)

Pliers
PliersPliers
Pliers
 
The Softer Side of Scheduling
The Softer Side of SchedulingThe Softer Side of Scheduling
The Softer Side of Scheduling
 
Acumen Fuse: Datasheet
Acumen Fuse: DatasheetAcumen Fuse: Datasheet
Acumen Fuse: Datasheet
 
PERT
PERTPERT
PERT
 
Inovaare Webinar - The Importance of A Clean Universe
Inovaare Webinar - The Importance of A Clean Universe Inovaare Webinar - The Importance of A Clean Universe
Inovaare Webinar - The Importance of A Clean Universe
 
PDA-FDA Joint Regulatory Conference - Supply Chain Case Study Rev A Publish
PDA-FDA Joint Regulatory Conference - Supply Chain Case Study Rev A PublishPDA-FDA Joint Regulatory Conference - Supply Chain Case Study Rev A Publish
PDA-FDA Joint Regulatory Conference - Supply Chain Case Study Rev A Publish
 
3 pm3 t_4%20-%20schedule%20development
3 pm3 t_4%20-%20schedule%20development3 pm3 t_4%20-%20schedule%20development
3 pm3 t_4%20-%20schedule%20development
 
6 methods for CAPAs effectiveness verification
6 methods for CAPAs effectiveness verification6 methods for CAPAs effectiveness verification
6 methods for CAPAs effectiveness verification
 
PUG2008 SCHR for Distribution
PUG2008 SCHR for DistributionPUG2008 SCHR for Distribution
PUG2008 SCHR for Distribution
 
Performance improvement in Criminal Justice using Nimbus Control
Performance improvement in Criminal Justice using Nimbus ControlPerformance improvement in Criminal Justice using Nimbus Control
Performance improvement in Criminal Justice using Nimbus Control
 
JP Morgan North American Remote to Core Justification
JP Morgan North American Remote to Core JustificationJP Morgan North American Remote to Core Justification
JP Morgan North American Remote to Core Justification
 
Critical path
Critical pathCritical path
Critical path
 
Docweb Milestone 2 Report
Docweb Milestone 2 ReportDocweb Milestone 2 Report
Docweb Milestone 2 Report
 
Rehab Project
Rehab ProjectRehab Project
Rehab Project
 
Nimbus IP10 CJ Workshop
Nimbus IP10 CJ WorkshopNimbus IP10 CJ Workshop
Nimbus IP10 CJ Workshop
 
Services in detail
Services in detailServices in detail
Services in detail
 
Right-sizing project management and tracking
Right-sizing project management and trackingRight-sizing project management and tracking
Right-sizing project management and tracking
 
Monte Carlo Schedule Risk Analysis
Monte Carlo Schedule Risk AnalysisMonte Carlo Schedule Risk Analysis
Monte Carlo Schedule Risk Analysis
 

Similar to Estimating the Impact of Incidents on Process Delay - ICPM 2019

Project initiation
Project initiationProject initiation
Project initiation
ukrulz4u
 
9 project planning
9 project planning9 project planning
9 project planning
randhirlpu
 
EO notes Lecture 27 Project Management 2.ppt
EO notes Lecture 27 Project Management 2.pptEO notes Lecture 27 Project Management 2.ppt
EO notes Lecture 27 Project Management 2.ppt
yashchotaliyael21
 
8 project planning
8 project planning8 project planning
8 project planning
randhirlpu
 
L05 time management
L05 time managementL05 time management
L05 time management
Asa Chan
 
Lean Six Sigma Green Belt Certification 1
Lean Six Sigma Green Belt Certification 1Lean Six Sigma Green Belt Certification 1
Lean Six Sigma Green Belt Certification 1
Fred Zuercher
 
BA Summit 2014 Predictive maintenance: Met big data het lek dichten
BA Summit 2014  Predictive maintenance: Met big data het lek dichtenBA Summit 2014  Predictive maintenance: Met big data het lek dichten
BA Summit 2014 Predictive maintenance: Met big data het lek dichten
Daniel Westzaan
 
Day 3 Schedule -walaa (3).pptx
Day 3 Schedule -walaa (3).pptxDay 3 Schedule -walaa (3).pptx
Day 3 Schedule -walaa (3).pptx
MohanadRabea1
 

Similar to Estimating the Impact of Incidents on Process Delay - ICPM 2019 (20)

Analysing and Troubleshooting Performance Issues in SAP BusinessObjects BI Re...
Analysing and Troubleshooting Performance Issues in SAP BusinessObjects BI Re...Analysing and Troubleshooting Performance Issues in SAP BusinessObjects BI Re...
Analysing and Troubleshooting Performance Issues in SAP BusinessObjects BI Re...
 
Time --updated 60b084af4f5af-
Time --updated 60b084af4f5af-Time --updated 60b084af4f5af-
Time --updated 60b084af4f5af-
 
Process Cloud Service Deep dive
Process Cloud Service Deep diveProcess Cloud Service Deep dive
Process Cloud Service Deep dive
 
Project initiation
Project initiationProject initiation
Project initiation
 
9 project planning
9 project planning9 project planning
9 project planning
 
AWIN presentation it's only logical-a scheduling overview
AWIN presentation it's only logical-a scheduling overviewAWIN presentation it's only logical-a scheduling overview
AWIN presentation it's only logical-a scheduling overview
 
Introducing "ReNDevoZ"--Work Flow Management software for Renewable projects
Introducing "ReNDevoZ"--Work Flow Management software for Renewable projectsIntroducing "ReNDevoZ"--Work Flow Management software for Renewable projects
Introducing "ReNDevoZ"--Work Flow Management software for Renewable projects
 
Activity planning.ppt
Activity planning.pptActivity planning.ppt
Activity planning.ppt
 
Activity planning.ppt
Activity planning.pptActivity planning.ppt
Activity planning.ppt
 
Sad lecture 4
Sad lecture 4Sad lecture 4
Sad lecture 4
 
EO notes Lecture 27 Project Management 2.ppt
EO notes Lecture 27 Project Management 2.pptEO notes Lecture 27 Project Management 2.ppt
EO notes Lecture 27 Project Management 2.ppt
 
8 project planning
8 project planning8 project planning
8 project planning
 
BPMinDIT-Increasing control in construction processes
BPMinDIT-Increasing control in construction processesBPMinDIT-Increasing control in construction processes
BPMinDIT-Increasing control in construction processes
 
L05 time management
L05 time managementL05 time management
L05 time management
 
Lean Six Sigma Green Belt Certification 1
Lean Six Sigma Green Belt Certification 1Lean Six Sigma Green Belt Certification 1
Lean Six Sigma Green Belt Certification 1
 
BA Summit 2014 Predictive maintenance: Met big data het lek dichten
BA Summit 2014  Predictive maintenance: Met big data het lek dichtenBA Summit 2014  Predictive maintenance: Met big data het lek dichten
BA Summit 2014 Predictive maintenance: Met big data het lek dichten
 
ch13.ppt
ch13.pptch13.ppt
ch13.ppt
 
Project Management
Project ManagementProject Management
Project Management
 
Day 3 Schedule -walaa (3).pptx
Day 3 Schedule -walaa (3).pptxDay 3 Schedule -walaa (3).pptx
Day 3 Schedule -walaa (3).pptx
 
Process Mining and Predictive Process Monitoring
Process Mining and Predictive Process MonitoringProcess Mining and Predictive Process Monitoring
Process Mining and Predictive Process Monitoring
 

More from Felix Mannhardt

Analyzing the Trajectories of Patients with Sepsis using Process Mining
Analyzing the Trajectories of Patients with Sepsis using Process MiningAnalyzing the Trajectories of Patients with Sepsis using Process Mining
Analyzing the Trajectories of Patients with Sepsis using Process Mining
Felix Mannhardt
 

More from Felix Mannhardt (9)

A Taxonomy for Combining Activity Recognition and Process Discovery in Indust...
A Taxonomy for Combining Activity Recognition and Process Discovery in Indust...A Taxonomy for Combining Activity Recognition and Process Discovery in Indust...
A Taxonomy for Combining Activity Recognition and Process Discovery in Indust...
 
Data-driven Process Discovery - Revealing Conditional Infrequent Behavior fro...
Data-driven Process Discovery - Revealing Conditional Infrequent Behavior fro...Data-driven Process Discovery - Revealing Conditional Infrequent Behavior fro...
Data-driven Process Discovery - Revealing Conditional Infrequent Behavior fro...
 
Unsupervised Event Abstraction using Pattern Abstraction and Local Process Mo...
Unsupervised Event Abstraction using Pattern Abstraction and Local Process Mo...Unsupervised Event Abstraction using Pattern Abstraction and Local Process Mo...
Unsupervised Event Abstraction using Pattern Abstraction and Local Process Mo...
 
From Low-Level Events to Activities - A Pattern-based Approach
From Low-Level Events to Activities - A Pattern-based ApproachFrom Low-Level Events to Activities - A Pattern-based Approach
From Low-Level Events to Activities - A Pattern-based Approach
 
Analyzing the Trajectories of Patients with Sepsis using Process Mining
Analyzing the Trajectories of Patients with Sepsis using Process MiningAnalyzing the Trajectories of Patients with Sepsis using Process Mining
Analyzing the Trajectories of Patients with Sepsis using Process Mining
 
XESLite - Handling Event Logs in ProM
XESLite - Handling Event Logs in ProMXESLite - Handling Event Logs in ProM
XESLite - Handling Event Logs in ProM
 
Measuring the Precision of Multi-perspective Process Models
Measuring the Precision of Multi-perspective Process ModelsMeasuring the Precision of Multi-perspective Process Models
Measuring the Precision of Multi-perspective Process Models
 
From Low-Level Events to Activities - A Pattern based Approach
From Low-Level Events to Activities - A Pattern based ApproachFrom Low-Level Events to Activities - A Pattern based Approach
From Low-Level Events to Activities - A Pattern based Approach
 
Decision Mining Revisited - Discovering Overlapping Rules
Decision Mining Revisited - Discovering Overlapping RulesDecision Mining Revisited - Discovering Overlapping Rules
Decision Mining Revisited - Discovering Overlapping Rules
 

Recently uploaded

Gliese 12 b: A Temperate Earth-sized Planet at 12 pc Ideal for Atmospheric Tr...
Gliese 12 b: A Temperate Earth-sized Planet at 12 pc Ideal for Atmospheric Tr...Gliese 12 b: A Temperate Earth-sized Planet at 12 pc Ideal for Atmospheric Tr...
Gliese 12 b: A Temperate Earth-sized Planet at 12 pc Ideal for Atmospheric Tr...
Sérgio Sacani
 
Jet reorientation in central galaxies of clusters and groups: insights from V...
Jet reorientation in central galaxies of clusters and groups: insights from V...Jet reorientation in central galaxies of clusters and groups: insights from V...
Jet reorientation in central galaxies of clusters and groups: insights from V...
Sérgio Sacani
 
Detectability of Solar Panels as a Technosignature
Detectability of Solar Panels as a TechnosignatureDetectability of Solar Panels as a Technosignature
Detectability of Solar Panels as a Technosignature
Sérgio Sacani
 
Continuum emission from within the plunging region of black hole discs
Continuum emission from within the plunging region of black hole discsContinuum emission from within the plunging region of black hole discs
Continuum emission from within the plunging region of black hole discs
Sérgio Sacani
 
Pests of Green Manures_Bionomics_IPM_Dr.UPR.pdf
Pests of Green Manures_Bionomics_IPM_Dr.UPR.pdfPests of Green Manures_Bionomics_IPM_Dr.UPR.pdf
Pests of Green Manures_Bionomics_IPM_Dr.UPR.pdf
PirithiRaju
 
Climate extremes likely to drive land mammal extinction during next supercont...
Climate extremes likely to drive land mammal extinction during next supercont...Climate extremes likely to drive land mammal extinction during next supercont...
Climate extremes likely to drive land mammal extinction during next supercont...
Sérgio Sacani
 
Tuberculosis (TB)-Notes.pdf microbiology notes
Tuberculosis (TB)-Notes.pdf microbiology notesTuberculosis (TB)-Notes.pdf microbiology notes
Tuberculosis (TB)-Notes.pdf microbiology notes
jyothisaisri
 
Quantifying Artificial Intelligence and What Comes Next!
Quantifying Artificial Intelligence and What Comes Next!Quantifying Artificial Intelligence and What Comes Next!
Quantifying Artificial Intelligence and What Comes Next!
University of Hertfordshire
 

Recently uploaded (20)

Molecular and Cellular Mechanism of Action of Hormones such as Growth Hormone...
Molecular and Cellular Mechanism of Action of Hormones such as Growth Hormone...Molecular and Cellular Mechanism of Action of Hormones such as Growth Hormone...
Molecular and Cellular Mechanism of Action of Hormones such as Growth Hormone...
 
WASP-69b’s Escaping Envelope Is Confined to a Tail Extending at Least 7 Rp
WASP-69b’s Escaping Envelope Is Confined to a Tail Extending at Least 7 RpWASP-69b’s Escaping Envelope Is Confined to a Tail Extending at Least 7 Rp
WASP-69b’s Escaping Envelope Is Confined to a Tail Extending at Least 7 Rp
 
Gliese 12 b: A Temperate Earth-sized Planet at 12 pc Ideal for Atmospheric Tr...
Gliese 12 b: A Temperate Earth-sized Planet at 12 pc Ideal for Atmospheric Tr...Gliese 12 b: A Temperate Earth-sized Planet at 12 pc Ideal for Atmospheric Tr...
Gliese 12 b: A Temperate Earth-sized Planet at 12 pc Ideal for Atmospheric Tr...
 
Jet reorientation in central galaxies of clusters and groups: insights from V...
Jet reorientation in central galaxies of clusters and groups: insights from V...Jet reorientation in central galaxies of clusters and groups: insights from V...
Jet reorientation in central galaxies of clusters and groups: insights from V...
 
Ostiguy & Panizza & Moffitt (eds.) - Populism in Global Perspective. A Perfor...
Ostiguy & Panizza & Moffitt (eds.) - Populism in Global Perspective. A Perfor...Ostiguy & Panizza & Moffitt (eds.) - Populism in Global Perspective. A Perfor...
Ostiguy & Panizza & Moffitt (eds.) - Populism in Global Perspective. A Perfor...
 
Film Coated Tablet and Film Coating raw materials.pdf
Film Coated Tablet and Film Coating raw materials.pdfFilm Coated Tablet and Film Coating raw materials.pdf
Film Coated Tablet and Film Coating raw materials.pdf
 
Detectability of Solar Panels as a Technosignature
Detectability of Solar Panels as a TechnosignatureDetectability of Solar Panels as a Technosignature
Detectability of Solar Panels as a Technosignature
 
Continuum emission from within the plunging region of black hole discs
Continuum emission from within the plunging region of black hole discsContinuum emission from within the plunging region of black hole discs
Continuum emission from within the plunging region of black hole discs
 
RACEMIzATION AND ISOMERISATION completed.pptx
RACEMIzATION AND ISOMERISATION completed.pptxRACEMIzATION AND ISOMERISATION completed.pptx
RACEMIzATION AND ISOMERISATION completed.pptx
 
GBSN - Microbiology Lab (Microbiology Lab Safety Procedures)
GBSN -  Microbiology Lab (Microbiology Lab Safety Procedures)GBSN -  Microbiology Lab (Microbiology Lab Safety Procedures)
GBSN - Microbiology Lab (Microbiology Lab Safety Procedures)
 
Pests of Green Manures_Bionomics_IPM_Dr.UPR.pdf
Pests of Green Manures_Bionomics_IPM_Dr.UPR.pdfPests of Green Manures_Bionomics_IPM_Dr.UPR.pdf
Pests of Green Manures_Bionomics_IPM_Dr.UPR.pdf
 
GBSN - Microbiology (Unit 7) Microbiology in Everyday Life
GBSN - Microbiology (Unit 7) Microbiology in Everyday LifeGBSN - Microbiology (Unit 7) Microbiology in Everyday Life
GBSN - Microbiology (Unit 7) Microbiology in Everyday Life
 
INSIGHT Partner Profile: Tampere University
INSIGHT Partner Profile: Tampere UniversityINSIGHT Partner Profile: Tampere University
INSIGHT Partner Profile: Tampere University
 
Climate extremes likely to drive land mammal extinction during next supercont...
Climate extremes likely to drive land mammal extinction during next supercont...Climate extremes likely to drive land mammal extinction during next supercont...
Climate extremes likely to drive land mammal extinction during next supercont...
 
Tuberculosis (TB)-Notes.pdf microbiology notes
Tuberculosis (TB)-Notes.pdf microbiology notesTuberculosis (TB)-Notes.pdf microbiology notes
Tuberculosis (TB)-Notes.pdf microbiology notes
 
Mining Activity and Investment Opportunity in Myanmar.pptx
Mining Activity and Investment Opportunity in Myanmar.pptxMining Activity and Investment Opportunity in Myanmar.pptx
Mining Activity and Investment Opportunity in Myanmar.pptx
 
Gliese 12 b, a temperate Earth-sized planet at 12 parsecs discovered with TES...
Gliese 12 b, a temperate Earth-sized planet at 12 parsecs discovered with TES...Gliese 12 b, a temperate Earth-sized planet at 12 parsecs discovered with TES...
Gliese 12 b, a temperate Earth-sized planet at 12 parsecs discovered with TES...
 
Lec 1.b Totipotency and birth of tissue culture.ppt
Lec 1.b Totipotency and birth of tissue culture.pptLec 1.b Totipotency and birth of tissue culture.ppt
Lec 1.b Totipotency and birth of tissue culture.ppt
 
Constraints on Neutrino Natal Kicks from Black-Hole Binary VFTS 243
Constraints on Neutrino Natal Kicks from Black-Hole Binary VFTS 243Constraints on Neutrino Natal Kicks from Black-Hole Binary VFTS 243
Constraints on Neutrino Natal Kicks from Black-Hole Binary VFTS 243
 
Quantifying Artificial Intelligence and What Comes Next!
Quantifying Artificial Intelligence and What Comes Next!Quantifying Artificial Intelligence and What Comes Next!
Quantifying Artificial Intelligence and What Comes Next!
 

Estimating the Impact of Incidents on Process Delay - ICPM 2019

  • 1. ESTIMATING THE IMPACT OF INCIDENTS ON PROCESS DELAY Felix Mannhardt, Petter Arnesen, Andreas D. Landmark
  • 2. 2
  • 5. 5 Railway Traffic Logs – Example Process Model
  • 6. What is process delay? 6 Definition A Expected/Scheduled vs. Actual Performance Definition B Normal performance vs. Actual performance
  • 7. What is known about incidents? 7 Image sources: banenor.no
  • 8. What is known about incidents? 8 Incident Log Issue registered Mover/motor turnout km 453 Work order created Repair Process Work Order DB Manual registration Manual registration Registered? Work started? Contractor notified? When was it fixed?
  • 9. The Problem – Linking Incidents to Delay 9
  • 10. • Internal performance factors • Alignments to project performance information • Identification of slow variants / combination of attributes • Identification of slow resources • Prediction of performance • Remaining time to completion • Some work considering inter-case parameters • Visualisation of performance • Dotted chart • Others: Process Profiler, Performance Spectrum etc. 10 Existing work None is addressing the linking/estimation challenge!
  • 11. Proposed Approach – Assumptions #1 11
  • 12. Proposed Approach – Assumptions #2 12 Resource required for trains to pass station Støren! Image sources: banenor.no
  • 13. Proposed Approach – Impact Estimation #1 13 Step 1: Collect performance information from event log Case 5262 took about 460s for activity LMO-STØ (single track) Approx. time for incident on turnout XYZ 𝑇𝑖𝑛𝑐𝑖𝑑𝑒𝑛𝑡
  • 14. Proposed Approach – Impact Estimation #2 14 Step 2: Determine normal process performance
  • 15. Proposed Approach – Impact Estimation #3 15 Step 3: Classify activity instances into three classes
  • 16. Proposed Approach – Impact Estimation #4 16 Step 4: Determine likely start/end of impact using MCMC 𝑇𝑠𝑡𝑎𝑟𝑡 ? 𝑇𝑒𝑛𝑑 ? Metropolis-Hastings algorithms 20000 iterations Priors for standard delay e.g., 𝑝0 = (0.94, 0.055 0.005) and incident-affected delay e.g., 𝑝1 = (0.93, 0.06, 0.01) hand tuned on small dataset.
  • 17. Proposed Approach – Impact Estimation #4 17 Step 4: Determine likely start/end of impact using MCMC 𝑇𝑠𝑡𝑎𝑟𝑡 𝑇𝑒𝑛𝑑 Times at least 50% of the samples between 𝑇𝑠𝑡𝑎𝑟𝑡 and 𝑇𝑒𝑛𝑑
  • 18. Proposed Approach – Impact Estimation #5 18 Step 5: Accumulate delay 𝑇𝑠𝑡𝑎𝑟𝑡 𝑇𝑒𝑛𝑑Count fully Discount with prob.Discount with prob.
  • 19. Evaluation – Case Study in Norway 19 TIOS BaneData Save result back Traffic Control System Maintenance Management PRESENS-Algorithm Data Warehouse Calculated the impact on delay for each major incident since 2011 Work orders Driving time Delay tagging Validation
  • 20. Evaluation – Delay Dashboard 20
  • 21. Evaluation – Predictive Maintenance 21 • Prediction of "avoided" delay due to smart maintenance • Smart monitoring of turnouts • Justification of investments • Using the delay effect base on historical data as proxy • Not perfect, often rather small data basis for prediction • Better than management by `rule of thumb`
  • 22. • Explore application on non-infrastructure focussed processes • Activity-incident relation is less obvious? • Estimation of `normal` process performance challenging? • Address the issue of multiple co-occurring incidents • MCMC would have trouble with multi-modal distributions • Address non-local knock-on effects on process delay • Initial solution addresses the problem for single-track railway networks, but difficult to generalise! • Investigate effects of queues etc. in non-physical processes • Address the strong dependency on the chosen parameters in the prior distribution  possible but high computational cost 22 Future work
  • 24. Teknologi for et bedre samfunn

Editor's Notes

  1. Bildet illustrerer:  ·        bredden  i SINTEFs ekspertise, fra havrom til verdensrom. ·        hvilke områder og bransjer vi jobber innen for å realisere visjonen Teknologi for et bedre samfunn.   Bildestilen er basert på stikkordene fremtidsrettet, teknologi og norsk natur (naturressurser). SINTEFs visuelle univers er utviklet for SINTEF av Headspin Productions AS.