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MAINTENANCE PERFORMANCE INDICATORS: AN ANALYSIS IN
THE MINING INDUSTRY
JK Visser & RLM Kotze
Graduate School of Technology Management, University of Pretoria 1
OUTLINE • Introduction • Objectives • Theory and Literature • Research Framework • Methodology • Survey Results • Conclusion
2
INTRODUCTION • Maintenance is an integral part of an
organisation’s long-term profitability • Maintenance can add value through equipment
reliability and therefore availability
• The mining industry is very capital intensive
• Work is often done under extreme conditions
3
Introduction • The mining industry contributes about 6% of
South Africa’s GDP • Mining is still a crucial industry for South
Africa, specially in job creation • South Africa is also a top producer in the
world of many important commodities – Platinum – Chrome – Vanadium
• Maintenance cost 20-50% of production cost 4
Introduction • Various indicators are used for measuring
maintenance performance in mining • However, many managers have a short-term
focus (rat race syndrome) • Some maintenance sections do mostly
breakdown maintenance – not pro-active! • Some managers do not use a structured
process to derive performance indicators • Performance measurement is not always
effective and beneficial for mining companies 5
The Maintenance System
Maintenance System
Inputs Outputs Feedback
Enterprise System
Environment
Materials Labour Spares Tools Money Technology Information Facilities
Capacity Quality System Image Maintainability Availability Reliability Safety Cost
Adjust Calibrate Inspect Repair
Replace 6
OBJECTIVES • Overall objective was to determine whether
maintenance departments at South African mines utilise performance measurement efficiently and effectively
• Sub objectives – Do maintenance departments use a structured
approach to derive MPI’s – Are the MPI’s applied correctly
• Five propositions were defined
7
Research Propositions 1. MPI’s used in mining are not derived or developed from
the maintenance strategy and objectives through a structured process
2. Maintenance performance management is not applied effectively in the mining industry
3. MPI’s used in mining do not address all the important categories of maintenance management
4. MPI’s used in mining maintenance have a high focus on lagging or reactive indicators
5. Maintenance performance measurement is not utilised effectively and efficiently to create value for the mining companies 8
THEORY AND LITERATURE • Various maintenance academic and
specialists have researched maintenance performance in the past decade, e.g. – Wireman (1998 & 2005) – Mather (2005) – Parida (2006) – Tsang (2000) – Dwight (1998) – de Groote (1995)
9
The Balanced Scorecard • The Balanced Scorecard approach takes into
account the fact that companies need to manage intangible assets and not only physical assets
• Indicators should address four perspectives: – Financial – Customer – Internal processes – Learning and improvement
11 (Source: Kaplan & Norton,1996)
Holistic Approach of Tsang • Performance indicators influence what people
do • Indicators are a powerful motivational tool
that drives decisions • To trigger effective change, indicators should
fulfill two conditions: – They should relate to what is controllable by the unit
evaluated – Favorable results on these measures should contribute
to specific business success factors 12 (Source: Tsang et al,1999)
Wireman’s Hierarchical Approach • Performance indicators should highlight
opportunities for improvement • Indicators can identify weak areas and point
to solutions for solving problems • A system of multi-level performance
indicators are proposed • A further classification of eleven categories of
maintenance performance indicators can be used for the selection process
13 (Source: Wireman, 2005)
RESEARCH FRAMEWORK Selection/Identification of
MPI’s
MPI’s for different hierarchical levels
Maintenance categories addressed by MPI’s
Balance of leading & lagging indicators
Purpose of performance management
Importance of CI
Communication/ Explaining of MPI’s
Integrity of maintenance data
Structured process followed to derive MPI’s
Efficient indicators utilised
Effective application of performance management
Performance management utilised effectively & efficiently
14
METHODOLOGY • Survey was targeted at 172 out of a total of
186 mines in South Africa • Commodities investigated
– Diamonds – Gold – Platinum metals group – Coal – Ferrous – Non-ferrous
15
Data Collection • Questionnaire comprised 14 questions • SurveyMonkey internet survey tool was
utilised • E-mail message requesting participation was
sent to engineering managers of 172 mines • 72 responses were received, i.e. 42% return
rate
16
SURVEY RESULTS • The responses to following 5 questions are
discussed in this paper: – What method was used to identify maintenance
performance indicators, if any? – Which indicators, out of a given list of 32, are the
most important? – Which categories of indicators are the most
important? – What are the maintenance indicators used for in the
organisation? – How are the indicators communicated to the different
levels in the organisation? 19
Process for Defining MPI’s • About 75% of the respondents indicated that
some structured process was used to define MPI’s
• About 30% of the respondents indicated that no structured process was followed
21
Most Popular Indicators • The following 6 indicators are used by more
than 80% of the respondents: – Availability – Safety Score (audits) – Reliability (MTBF & MTTF) – Plant/equipment utilisation – Lost time frequency rate (LTFR) – Maintenance cost per unit
23
Categories for MPI’s • Cannot measure a company or division on
financial indicators only • Balanced set of indicators needed (Kaplan & Norton)
• Seven categories of maintenance indicators were presented in questionnaire
• 90% of mines use the following 4 categories: – Equipment/Process – Safety, Health & Environment (SHE) – Cost/Financial – Maintenance Workflow
25
Purpose of Using Indicators • More than 80% of the respondents indicated
that they use indicators for the following purposes: – Declare deviations of operational performance – Identify focus areas for maintenance groups – Monitor progress of and study
27
CONCLUSION
1. MPI’s not derived using a structured process × 2. Maintenance performance management is not
applied effectively 3. MPI’s do not address all the important
categories 4. MPI’s have a high focus on lagging or reactive
indicators 5. Maintenance performance measurement is
not utilised effectively and efficiently 29
REFERENCES • De Groote, P. 1995. Maintenance performance analysis: a practical
approach. Journal of Quality in Maintenance Engineering, 1 (2) pp4-24 • Tsang, A. H. C., 2000. Maintenance performance management in
capital intensive organizations, PhD Thesis. University of Toronto • Mather, D., 2005. The maintenance scorecard: Creating strategic
advantage. New York: Industrial Press • Tsang, A.H.C., 1998. A strategic approach to managing maintenance
performance. Journal of Quality in Maintenance Engineering, 4 (2) p87-94
• Wireman, T. 2005. Developing performance indicators for managing maintenance. 2nd Edition. New York: Industrial Press
30
References (2) • Parida, A. & Kumar, U. 2006. Maintenance performance
measurement: Issues and challenges. Journal of Quality in Maintenance Engineering, 12, (3) p 239-251
• Alsyouf, I. 2006. Measuring maintenance performance using a balanced scorecard approach. Journal of Quality in Maintenance Engineering, 12 (2) p133-149
• Visser, J.K. & Pretorius, M.W. 2003. The development of a performance measurement system for maintenance. South African Journal of Industrial Engineering, 14, (1) p83-97
• Kaplan, R.S. and Norton, D.P. 1996, Using the Balanced Scorecard as a Strategic Management System, Harvard Business Review, 74, (1), p75-85 31
References (3) • Parida, A. 2006. Development of a multi-criteria hierarchical
framework for maintenance performance measurement: concepts, issues and challenges. PhD Thesis. Luleå University of Technology
• Campbell, J.D. & Reyes-Picknell, J.V. 2006. Uptime: Strategies for excellence in maintenance management. 2nd Edition. New York: Productivity Press
• Tsang, A.H.C., Jardine, A.K.S. & Kolodny, H. 1999. Measuring maintenance performance: A holistic approach. International Journal of Operations & Production Management, 19 (7) p 691-715
32