David Baglee Erkki Jantunen Critical Study of Essential Elements linked with the adoption of Condition-Based Maintenance David Baglee Erkki Jantunen University of Sunderland UK VTT Finland

Presentation Outline Aim & overview of research Key findings Next stages Whats new on the horizon for maintenance management?

Where are we?

Who are we? Medium sized University 17.000 students 1500 staff Four Faculties Campus in London Strong reputation in Advanced Manufacturing Strong links with industry

Background to Research UK government report in 2013 suggested Auto-supply chain in UK suffer from high levels of equipment failure Lack of evidence to support General statement (broad brush) Size of supply chain? 12% increase a year in numbers produced from 2009 Small scale research project at Sunderland (Nissan suppliers)

Background to Research cont’d “Quick and dirty” results showed OEE 54% 25 suppliers in different Tier. Discussions with different industries Discussions with colleagues in Europe Spain Italy Finland

Pan-European Approach From a range of industries including auto, aerospace, process, marine and paper, collected & analysed data on different maintenance practices (SME) Discussions Scattered studies Expert opinions literature Do you need to move to an ‘improved’ maintenance strategy i.e. CBM HOW?

CBM Look Listen Smell taste

Benefits of CBM early detection of impending machinery failure to help lower the risk of unscheduled downtime scheduling and utilisation of maintenance resources is more efficient reduced likelihood of ‘maintenance induced’ failures etc etc

Implement CBM Important to use an appropriate method for modelling deterioration, the different conditions and their effects, and the optimal selection and scheduling of inspections and preventive maintenance actions. Failure characteristics often grouped into a number of categories

Bathtub Curves

Which to monitor? Infant mortality, useful life, rapid wear out Rapid wear out after long useful life Gradual wear out after long useful life

Results Industry Country Infant mortality, useful life, rapid wear out Rapid wear out after long useful life Gradual wear out after long useful life Aerospace UK 10% 70% Chemical industry Finland Process industry France 30% Mechanical components Spain 50% Auto 21% 22% 60% 15% Rail 5% Russia 20% Mining industry Canada

Review of Data Expected and ‘unexpected’ differences Majority state “gradual wear out after long useful life” Process industry UK / Sweden High infant mortality, useful life, rapid wear out Rail industry Spain: Rapid wear out after long useful life Process Industry France: 30% all three

Time to reflect

Meaning ‘behind’ the data Wide range of variations in results Lack of ‘credible’ data? Often unknown, why, how, when Lack of Historical data Improper use of equipment Bathtub curve used as a simple method

Conclusion Data from study is ‘generally’ unreliable Although - expected differences and similarities do exist Big difference between countries in same sector Need a new approach to data collection and analyses CBM could be ‘appropriate’ if the above are addressed

Companies Response Not this bad - Blame was passed around

What’s next? Start again- To achieve- Interview again with a different set of metrics Widen the range of companies and staff Different experts from more companies To achieve- Accurate and up to date data Historical trends To understand the how, why and when To help develop a new approach to maintenance

A new approach? What is new in maintenance? 1900-1945: Basic and routine maintenance, reactive maintenance, only repair when broke 1945-1980: Planned preventive maintenance, Time based approach. Total Productive Maintenance (TPM), team based approach to maintenance, examines “culture and people” not systems 1980-Present: Condition monitoring (CM), hazard studies, failure modes and effect analysis. Reliability centred maintenance (RCM) Computer aided maintenance management. Multi-skilled workforce. Emphasis on equipment reliability and availability Present - ?: Self Maintenance systems...

What is the next ‘Big Bang’ maintenance strategy Artificial Intelligence (thinking / smart machines) Augmented Reality New technologies Data collection and analyses Add cost factor to OEE Awareness programmes ??????

Smart system?

Smart systems

Sensors monitoring health Identify and report problems Smart systems Sensors monitoring health Identify and report problems Root cause Future Health Plan production etc

Smart systems

Augmented Reality?

Conclusion Nothing new in maintenance since 1980s? Do we need a new approach to maintenance using technology i.e. AR More needed on the ‘importance of maintenance’ Research into new technologies to support existing systems

Thank you for your attention