Abstract:

As maintenance moves more towards a predictive mode of action from a preventative model, a major northern Alberta oilsands mine identified a need for a tool to rank the potential failure risk related to each asset in the mine. Industry is recognizing that in many cases ‘Run to Failure’ may not be the most cost effective strategy considering the fact that aging units often have higher operation and maintenance costs, and undesirable reliability consequences.⁽⁴⁾In industries around the world new challenges are related to extending the life of the main items of facilities or at least, to find the optimal replacement moment that guarantees that the total expenditure (TOTEX) is being optimized.⁽¹⁾Strong Data Management is the first step towards enabling greater sophistication of analysis^{. (3)} Research indicates that industries such as electrical power transmission and generation have approached predictive based maintenance of assets driven by condition monitoring and asset health index (AHI) systems. The aim of the health index is the condition representation of an individual asset.⁽²⁾ The AHI and condition monitoring systems support each other as they each provide a facet for an asset manager to determine maintenance or asset replacement needs based on actual asset condition instead of an arbitrary metric (date, operating hours, miles, etc.) as driven by immediate cost crunch needs. The data inputs for AHI in mining can include the criticality of the asset, condition of lubrication oils as assessed by laboratory analysis, the age of the asset or components of the asset expressed in running hours, magnetic plug inspection results, maintenance backlog, alarm count, and filter cutting analysis results. Applying the weighted AHI and comparing the defined inputs allows for a fair analysis between the failure risk and condition of each asset, even if the assets are of different types. By quantifying the true condition of an asset, maintenance spend decisions and maintenance workforce assignments can be planned and designated to the assets with the highest levels of risk.

Biography of the presenter: I have had a career of 20 years in oilsands mine maintenance with responsibilities including the effective and timely repair of mobile mining equipment such as dozers, graders, and haul trucks. I have gained experience in the technical function of the equipment, reliability best practices, maintenance planning, the implementation of technology to mining and mine maintenance, as well as the importance of 'the right repair at the right time' and how all of it affects mine production in a positive or negative fashion. I continue to explore new concepts and propose new solutions as my knowledge of the correlation between operations, maintenance, planning, and reliability expands and grows.

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Mr. Jory Maccan

Biography