Your Maturity Result: 1
At this moment, things could be looking better. Limited digital processes are in place, there is restricted access to the data generated from the machines and processes. Additional sensors and improvements to the operational/information technology infrastructure need to be made. There is a limited willingness towards the digital transformation from the management side. No data-driven maintenance strategies utilized for analytics.
There is a lot to be improved, but fear not, taking the first step towards data-driven maintenance is always the hardest.
Level 1: Basic
- SOP’s, Checklist, Manuals
Level 2: Aware
- SOP’s, Checklist, Manuals
- Automation
- Reactive Maintenance
Level 3: Compliant
- Asset Visibility
- Periodic Maintenance Plan
- Process Excellence-Asset Category, Comparison
- Asset Strategy/ Roadmap
- OEE Measurement
- Enterprise Aligned Metrics
Level 4: Evolving
- Asset Data Collection & Reporting
- Condition based/Predictive Maintenance
- Error Proofing
- OEE Monitoring
- Plant Simulation
- Integrated Supply Chain
- Decision Support
- Energy Management
Level 5: Execution Excellence
- Asset History at Floor
- IIOT / Connected Assets
- Pro-Active Maintenance
- Systematic Framework for CI
- OEE Drill-down & Live Data
- AR (Augmented Reality) in Training & Service
- Focus on reliability
- Asset Life cycle focus and impact
- Inbuilt Intelligence
How You Benchmark Against the Industry
Looking at the Scale of the Basics of Cbm and Pdm to Advanced Implementation, We Can Distinguish Four Different Levels
Level 1: Visual Inspections
Periodic physical inspections, where conclusions are solely based on inspectors’ expertise.
Level 2: Instrument Inspections
Periodic inspections, where conclusions are based on a combination of inspectors’ expertise and instrument read-outs.
Level 3: Condition Monitoring
Continuous real-time monitoring of assets where alerts are given based on pre-established rules of critical levels
Level 4: Big Data/Advanced Analytics
Continuous real-time monitoring of assets, with alerts sent based on predictive techniques and predicting future events.
Market Position
Looking at the market, there is no shortage of ambitions, ambitions are high. A majority of companies is planning to use data-driven predictive maintenance at some point in time. Where one in three companies (33%) wants to do something within the next 5 years. However, currently two thirds (66%) are still at level 1 or 2. Another 23% is at level 3, already continuously monitoring asset conditions in real-time. Only 11% has achieved level 4, monitoring assets in real-time and predicting future events.
Predicting Future Events
Governance
Technology
Value Creation
Competence
Benefits
Organizations With Data-Driven Maintenance Maturity of Level 4 and Higher Benefit From:
- Reduction of asset shutdown time 25%
- Maintenance cost reduction of 20%
- Reduction of safety, health, environment & quality risks of 14%
- Lifetime extension of ageing asset 20%
- Increase of average asset durability of 80%
- Factory output increase 5-200%
- Productivity increase 5-160%
- OEE increase 3-50%
- Quality cost reduction 5-90%
- Product cost reduction 5-40%
- Energy efficiency 2-50%
- Inventory reduction 10-90%
- Lead time reduction 10-90%
- Change-over shortening 30-70%
- Lot size reduction 50-90%
Give the Next Step Towards Data-Driven Maintenance
Book a time to discuss with any of our consultants how we can help you to improve your maintenance maturity and be ready for data-driven maintenance.