Irrespective of the type of industry, the goal of any maintenance program is to increase uptime, eliminate unexpected failures, and maximize asset utilization while taking care of the health and safety of employees. Reliability Centered Maintenance (RCM) is a strategy that can help attain the aforementioned goals while maximizing availability and improving overall equipment efficiency (OEE). RCM also reduces the total cost of ownership (TCO) of plant machinery, equipment, and other assets.
Primarily, there are four different approaches to maintenance viz., Reactive, Preventative, Condition Based, and Predictive maintenance. The most appropriate choice of course would depend on several factors such as the type of plant machinery or equipment in use, the criticality of the process, and the service conditions.
Reactive Maintenance is generally suitable for equipment that is small, low in power (KW) rating, non-critical applications, and in processes where (i) sufficient redundancy is built into the system, (ii) failure will not lead to serious disruption to production, and (iii) the consequential effects of failure will be minimal and not result in a major loss.
Preventative Maintenance approach, on the other hand, is adopted to lessen the likelihood of unexpected failures and works best for plant and equipment whose failure pattern is well established by user experience or by the manufacturer and where effective service life is based on the hours of usage or distance travelled in the case of automobiles and other mobile equipment.
Condition Based Maintenance, as the name suggests, is based on the actual condition of the equipment. It is adopted for plant machinery and equipment whose effective life cannot be predicted accurately based on usage data but depends more on the conditions of service and could face random failures. This approach requires an initial investment in setting up an infrastructure for monitoring the operating parameters of the plant machinery using sensors and deploying personnel with expertise in interpretation of the collated data. But with the advent of remote monitoring technology using IOT, organizations are offering this service on a subscription basis and can be accessed without having to commit a huge financial outlay for setting up.
Predictive Maintenance approach is one where techniques such as Failure Mode Effects and Analytics (FMEA) and Root Cause Failure Analysis (RCFA) are applied to predict the time before failure. Maintenance work is planned and undertaken based on these predictions. Quite obviously, this approach involves substantial initial investment for monitoring equipment; software; infrastructure for collection, storage, and analysis of data; and personnel specialized in the analytical and prediction techniques. Therefore, this approach is applied to plant and machinery that are critical to the process and whose failure could have serious disruption, consequential losses, and sometimes result in catastrophic incidents jeopardizing the health and safety of the wider populace.
Some of the methods adopted for Predictive Maintenance overlaps with that of Condition Based maintenance; for making accurate predictions one needs to assess the condition of the equipment. The condition of the equipment is determined by continuously monitoring certain operational parameters such as the ultrasonic noise, vibration, and operating temperature in the case of rotating machinery, and NDT methods are employed for the evaluation of others.
The idea behind RCM is to fine-tune the maintenance approach to the needs of the plant and equipment, its application in the industry, the duty cycle, and other such factors rather than following a one-size-fits-all approach. The organization should keep this in mind and choose an approach that renders well to meet its goals and objectives. A well thought out and customized maintenance approach will optimize OEE, aid in reducing costs, and lead to increased profits. RCM is an effective maintenance strategy that has been widely adopted by leading industries and has proven to boost reliability, improve customer confidence, and satisfaction.
