Reducing maintenance costs through predictive fault detection
In the mining industry, maintenance is a key priority and a major expense. As mining equipment is large in scale, high in cost, and difficult to tow, it is key to maintain equipment on a timely basis. Breakdown in -40°C or away from a maintenance station can cause great costs in repair as well as lost production.
It has often been quoted that about 5% of the North American production is lost every year due to unscheduled downtime. About one-third of the downtime is attributable to equipment failures. From this fact alone, it is evident that proper equipment maintenance can add tremendous value to the bottom line.
As organizations and equipment become more sophisticated, maintenance expectations begin to evolve. This evolution can be traced through three generations:
The first generation (1940–1950): A “fix it when it broke” attitude prevailed during that time, mostly because the industry was not highly automated.
The second generation (1950–1980): Automation and mechanization of the industry increased. The industry now was dependent on machines performing the majority of the work. Preventive maintenance (overhauls at fixed intervals) appeared as the first maintenance practice. Maintenance costs started to rise rapidly.
The third generation (1980–): Assets become more complex. Failure modes are better understood and computerized maintenance methods are becoming mainstream. Condition-based maintenance (CBM) starts to gain ground as a cost-effective alternative, replacing the fixed interval overhauls. As corporations amalgamate and market places are becoming more complex, multi-functional teams become responsible for maintenance.
At the beginning of the third generation, maintenance organizations began embracing technology to provide efficiencies in maintenance management. A strong push was made to transition from reactive maintenance to proactive maintenance. At the forefront of this push is condition-based maintenance.