Achieving Maintenance Reliability from Data

Expensive critical equipment generates overwhelming volumes of data. Maintenance personnel try repeatedly, with little success, to interpret that data so as to predict when and where failure will next occur. Yet the maintenance engineer lacks systematic techniques with which to reduce vast amounts of data to clear confident maintenance decisions. Although maintenance technology vendors have long promised this capability so far none have delivered it.

The solution does in fact exist. Merely an incomplete understanding of the nature of data has impeded resolution of a central problem. The fundamental problem in maintenance is uncertainty in the prediction of failure. As a result of misunderstanding of the key role of maintenance data, vital failure mode instance attributes have eluded capture by conventional enterprise asset management (EAM) procedures.

The course “Achieving Reliability from Data” will impart to each trainee a comprehensive framework for acquiring data of adequate analytical quality. And then to extract the decisions from that data.

The three day “Achieving reliability from data” training course addresses the subject of uncertainty in maintenance thereby empowering trainees to make decisions based on statistical confidence. The course imparts a thorough treatment of RCM methodology with which to establish an initial maintenance plan. However, the course goes further by extending RCM methods to daily work order related activity. The “living” RCM process accomplishes two important goals that have been neglected in current maintenance practice. The first goal is to ensure dynamic update of the RCM knowledge base. Experience of new failure modes and effects evolve, as does operating context. A living RCM process keeps the knowledge synchronized with reality. Secondly course participants will learn how to ensure that analysable work order data is transferred accurately and completely from the field or shop to the EAM. Finally, the course will provide the trainee with Reliability Analysis tools and skills with which to transform data into practical decision models that they will verify as having improved reliability, availability, and profitability within their enterprise.

Each participant will gain permanent access to a thorough set of slides and supporting text as well as educational versions of software that they will have used in the course exercises.

Top Learning Objectives

  • Overcome the natural uncertainty of the failure process
  • Learn what data is relevant and how to verify that it is accurate enough for predictive performance
  • Know how to transform the historical database from a black hole into which work order data is lost to analytic scrutiny into a knowledge resource for optimizing specific maintenance tactics
  • Apply reliability theory to practice in such a way as to achieve verified optimal performance from day to day maintenance decisions
  • Use RCM knowledge skills when transmitting field observations made during the execution of maintenance so as to continually improve the current maintenance plan
  • Construct an analysable data set for predictive modelling
  • Transform information from your maintenance information management EAM/ CMM database
  • Use the RCM methodology to configure a defensible initial maintenance plan.
  • Update the RCM knowledge base in a living process so that the maintenance plan continuously reflects new experience and deepening understanding of the asset’s condition and age-based failure mode behaviour.
  • Perform Reliability Analysis and build practical CBM decision models
  • Assess proposed projects with life cycle cost RAM analysis

Who Should Attend?

VPs, Directors, Division Heads, Managers, Superintendents, Specialists, Leaders, Supervisors, Foremen, Planners, Technicians, & Engineers from the following departments:

  • Maintenance
  • Engineering
  • Reliability
  • Preventive Maintenance
  • Predictive Maintenance
  • Shutdowns & Turnarounds
  • Condition Monitoring
  • Rotating Equipment
  • Static Equipment
  • Mechanical Engineering
  • Asset Management
  • Asset Integrity
  • Operations
  • Plant
  • Production
  • Process
  • Inspection

From industries including but not limited to:

  • Oil & Gas, Mining, Utilities, Manufacturing, Construction, Petrochemicals/Chemicals, Manufacturing, Transportation & Rail, Pharmaceuticals & Healthcare, Food & Beverages, etc.
  • All other industries that see leadership skills and physical asset management as a factor to business success such as facilities management and operations

Outcome of this Workshop

By attending this course, you’ll be able to understand how RCM can be used to:

  • Reduce routine planned maintenance work
  • Increase equipment operating performance (output, product quality, customer service) at the same time
  • Improve understanding, motivation and teamwork

By the end of this 3-day master class, delegates will learn key steps to use RCM, RCFA, FMECA, and Reliability Analysis tools in order to optimize the current maintenance regime. They will be able to take back with them immediately applicable skills and a practical action plan with which to achieve measurable results:  more effective plant maintenance, increased operational efficiency, lower operating costs and improved plant availability.

Trainer's Background

The trainer innovates in Maintenance Engineering, Management and Consulting particularly in using Maintenance Data to achieve Reliability. He founded and operated the world’s first web expert-system based commercial oil analysis laboratory. As a principal consultant at PricewaterhouseCoopers’ Centre of Excellence in Physical Asset Management he specialized in Condition based Maintenance Optimization. He leads projects in condition-based maintenance optimization that achieve safe increased equipment availability while minimizing life cycle cost. He founded Optimal Maintenance Decisions (OMDEC) Inc, a software and consulting company dedicated to strategic reliability information and knowledge management. As VP of Technology at OMDEC he introduced the revolutionary principles of “Living RCM” to the Canadian Armed forces, as well as to mining and metallurgy, cement, and process industries around the world. He holds a B. Eng. Mech. degree from McGill University. He has conducted highly regarded training programs in many countries, including the physical asset management certificate course at the University of Toronto.

Some of the organizations that have benefited from the trainer’s expertise include:

  • Schlumberger
  • Shell
  • Rolls Royce
  • Kuwait Oil Company
  • Petronas Gas
  • Petronas Refining
  • Centrica
  • Petroleum Development Oman
  • Total
  • National Semiconductor
  • Hitachi Rail
  • Alcan Rolling
  • Dofasco Steel
  • DuPont
  • Gassco
  • GlaxoSmithkline
  • Rayong Refining Company
  • Texas Utilities
  • The Royal Navy
  • EDF Energy
  • ExxonMobil
  • Heinz
  • Single Buoy Mooring
  • New Brunswick Power
  • Western Geco
  • Pemex
  • Royal Air Force
  • Irish Water
  • Bausch and Lomb
  • Cereal Partners
  • Pedigree Petfoods
  • BAPCO
  • Statoil
  • Pfizer
  • British Army
  • Guinness
  • Bombardier
  • Iron Ore Company of Canada
  • UK National Grid
  •  Guinness
  • Texaco
  • Pirelli
  • Mass Transit Rail (MTR) (Hong Kong)
  • SMRT Corporation
  • Shotton Paper
  • Corning
  • ConocoPhillips
  • Ford of Europe
  • Nissan
  • Volvo Cars
  • Acordis
  • Agrium
  • BP Chemicals
  • British Chrome and Chemicals
  • Rhodia
  • British Nuclear Fuels
  • Hong Kong Electric
  • ESB
  • Landsvirkjun
  • EON UK
  • Interbrew
  • Heinz
  • Kellogs
  • Mars Group
  • Alcan Recycling
  • Qatar Petroleum
  • Pilipinas Shell Petroleum Corporation
  • BP Exploration
  • AstraZeneca
  • Kodak
  • Domtar Paper
  • SCA Hygiene
  • Hofincons

Event Details

6th – 8th July 2020
Ho Chi Minh, Vietnam


“Our reliability department realized 90% of our expectations from the trainer’s reliability training.”

Meg Energy
Ron Kornelson, Reliability Manger