CBM and Maintenance Manager
The vast majority of equipment and machinery for critical applications operate under a preventive maintenance (PM) to improve SLAs and guarantee uptime. In this model, parts replacement is based on usage time and average wear recommendations from the manufacturer, without any indication of premature or late use of any component.
In other words, they are based on average failure periods observed by the manufacturer's engineering department and therefore do not represent any particular operating condition, often leading to unnecessary premature replacements, increasing costs, as well as potential damage to assets during repairs that frequently result in unexpected downtime.
In addition to reducing productivity, unexpected shutdowns cause a significant operational and financial impact, as there is no planning or scheduled interruption of operations. Remediation is conducted through reactive maintenance (RM), that is, based on the immediate and urgent need to replace components to restore operation as quickly as possible. However, immediate repair is not always feasible, either due to a lack of spare parts or the time required to restart the process, which may involve several other assets. In any case, process interruption is a loss that is counted on the clock.
With the emergence of IIoT (Industrial Internet of Things) applications and their ability to monitor asset parameters in real time, the concept of Condition-Based Maintenance (CBM) . CBM is a set of preventive maintenance processes triggered by asset information to ensure that maintenance is performed only when there is evidence of need. Maintenance is then called prescriptive maintenance because it is managed based on the actual need detected by the IIoT monitoring platform. CBM can also be useful in preventing failures, recognizing equipment degradation before a catastrophic failure occurs.
The goal of the CBM model is to move from a preventive maintenance program strictly based on a pre-set schedule to a preventive maintenance program based on the actual condition of the asset, minimizing reactive maintenance. This means that preventive maintenance tasks are scheduled based on the use or condition of the equipment (quantitatively and qualitatively, respectively) and not just on the interval established by the manufacturer.
Another extremely important component for increasing efficiency is the use of a maintenance management module or Computerized Maintenance Management System (CMMS) combined with the CBM model and integrated into the IIoT solution.
The IIoT platform should also include in its maintenance triggering rules the stock conditions of spare parts to generate orders in time to plan and schedule them properly.
Most importantly, the system must function in an integrated and digital way, from detecting abnormalities by reading signals of any kind to sending a workflow directed to the maintenance team and ordering integrated and automated parts. This is the true process that has been called digitization.
Finally, the automated workflow process offers several benefits, including the standardization of repair procedures according to prescribed maintenance, elimination of variations in workmanship quality, and reduced need for staff training.
Optimizing production processes is a complex problem that depends on implementing a system that considers the infrastructure with an integrated vision. To solve this challenge, Bridgemeter offers a turnkey SaaS solution that can be deployed in less than 30 days, depending on the conditions. For a more in-depth view of all these layers and how to solve the problem, read the recently published "IIoT and the Importance of Collaborative Infrastructure
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