Consulting

Andrew Jardine is regularly called upon to provide expert testimony in court cases or to assess a company’s current practices in asset management.

Over 30 years’ experience in the field of Reliability Engineering

Assignments with organizations around the world

Representative Consulting Cases

The following examples are representative rather than exhaustive. For more information, contact Professor Jardine directly at jardine@mie.utoronto.ca.

Operating, Maintenance, and Administration (OM&A) Estimates for a Five-Year Planning Horizon

This project, undertaken for an electrical transmission and distribution utility in North America, asked for a forecast of the company’s OM&A costs related to the upkeep of a fleet of physical assets, in this case, transformers. Professor Jardine discovered that existing forecasts of costs in the near term closely matched the results obtained by modelling, over-estimated costs in the following year and would likely come close to the modelling results in later years. He was able to attribute the jump in cost for one year to costs associated with work required to refurbish a certain transformer class.

Maintenance Assessment of Five Petrochemical Plants

A Middle Eastern company with five petrochemical plants wanted to improve its organizational performance through the effective management of its physical assets. Given the nature of the industry and the consequences of potential events, the company had to manage the risks in designing, building, operating and maintaining its plants. As a government owned company, its objectives and constraints were significantly different than a privatized company, presenting both challenges and opportunities. Working his way through the elements of the Uptime Pyramid, Professor Jardine gave the company concrete suggestions for improvement, including pointing to the need for higher levels of consistency and greater clarity of definitions across operating practices.

Arbitration on Liability Payment

Arbitration on Liability Payment

Professor Jardine served as an expert witness in arbitration proceedings on liability payment for electricity. In 2010, the state-owned power company Meridian Energy and Rio Tinto’s New Zealand Aluminium Smelters Ltd. (NZAS) ultimately negotiated a settlement over a 2008 power outage. The outage, caused by a transformer failure, cut electricity demand and aluminium output by a third at Rio Tinto’s Tiwai Point smelter. It took about four months before the smelter was up and running at full production.

Assessment of Equipment Maintenance Program

Professor Jardine was an expert witness in a dispute between a South American mine and its maintenance contractor. The case involved both a warranty compliance issue and the implementation and performance of an equipment maintenance program. To make such assessments, he typically considers the following factors: strategy, people, work management, maintenance tactics & basic care, materials management, performance management, management & support systems, asset-centric approaches, team-based methods, and process optimization. Each element identified in the asset management pyramid is examined to establish its state of health, resulting in an assessment of the maintenance maturity of the organization.

Asset Management: Maintenance Optimization

A large North American oil and gas utility company with close to two million residential, industrial and commercial customers was interested in determining the total cost of ownership and repair decisions vs. replace decisions for its underground pipes. To answer these questions, Professor Jardine examined data stored in the company’s systems and augmented these data with tacit knowledge gained through “knowledge elicitation” from experts in operations, maintenance, engineering and finance. His analysis focused on: Life Cycle Costing (LCC); Repair vs. Replace Decisions; Optimization of Maintenance Tactics; and Maintenance Levels vs. Life Cycle Expectations. In each of the four areas, he was able to give concrete suggestions for improvement.

Performance Gap Determination for a World Class Asset Management System

Professor Jardine examined a Chilean mining company’s mobile asset management practices and infrastructure and interviewed members of the maintenance workforce, professional, support, and management staff. Based on the information received and using the Uptime Pyramid, he recommended a prioritization of asset management initiatives consistent with the company’s corporate goals as it proceeds on its journey to asset management excellence.

Assessment of a Study on Reliability and Risk Reduction

Professor Jardine was asked to provide an overview and assessment of a study suggesting viable options to address problems in a central heating and cooling plant from an operational reliability perspective. The study sought ways to improve reliability to reduce risk. Operational reliability determines how well systems perform on an ongoing basis to meet the needs of their users. Overall, equipment reliability rests on four primary factors: the suitability of the asset for its intended use; how well the asset is installed; how well it is operated; and how well it is maintained. Professor Jardine underlined his concern that dependencies could be introduced into otherwise independent systems in the detailed design, negating the redundancy in the initial design.

Failure Behaviour Analysis

Analysis of Failure Behaviour to Optimize Preventive Maintenance

In this project, a mining company wanted to understand the failure behaviours of certain assets (scoops and trucks) to be able to optimize preventive maintenance intervals. Professor Jardine analyzed failure frequency, failure downtime, and costs associated with all components. Graphical tools (Pareto histograms and Jackknife scatter plots) revealed important information about costs and priorities. Following the graphical analyses, he performed reliability trend analysis on the age (failure) data to see if the failure of a component had a significant reliability trend (either growth or deterioration). By applying these optimal intervals in its maintenance plan, the company could minimize the total cost of maintenance (corrective and preventive) of these components.