Long Repair Time (MTTR) Data Deep Dive

This mind-map explores possible investigative dimensions to arrest long lead-times.

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Long Repair Time (MTTR) Data Deep Dive by Mind Map: Long Repair Time (MTTR) Data Deep Dive

1. Inadequate planning

1.1. No inspections are being done prior to services

1.1.1. Check trend of the number of inspections done. Check if there is a downward trend.

1.2. % of notifications created from inspections

1.3. Operator checklist notification close out time

1.4. Planned Maintenance Percentage

1.5. % breakdowns on components on scheduled repairs

2. Workforce discipline

2.1. Mechanical

2.1.1. # boilermaker tasks

2.1.2. # of thread repair work

2.1.3. # pin-and-bush failure

2.2. Damages

2.2.1. Damage prevalence rate

2.2.2. Damages per operator

2.2.3. Damage by temporal factors

2.2.4. Damages per location

3. Aging

3.1. MTTR contrasted by equipment age

4. Skills

4.1. Diagnostics Skills

4.1.1. Repair duration contrasted by repairmen

4.1.2. # of repeat failures

4.1.3. % of spanner time to downtime

4.1.4. repair to fix ratio

4.2. Training

4.2.1. Effectiveness

4.2.1.1. Contrast mttr by training status

4.2.2. Training matrix compliance

5. Spare Parts Availability

5.1. # of stockouts events

5.2. OTIF rate

5.3. Inventory turn-over rate

5.4. Forecast deviation

5.5. % of parts with demand rise of replaced parts

5.6. Part lead-time by usage category

5.7. Fleet failure rate trend

5.8. % Stock below replenishment trigger

5.9. Backlog size as % of turnover

5.10. Rolling Req-toPO time

6. Machine Design

6.1. MTTR contrasted by models

6.2. MTTR contrasted by OEM

7. Lack of labour

7.1. # of open vacancies

7.2. Labour utilization rate

7.3. average time between job cards per labour resource

7.4. Absenteeism rate

8. Equiping and Tools

8.1. MTTR contrasted by workplace location

8.2. Transport vehicle utilization