CBM and Maintenance Manager
The vast majority of equipment and machinery used in critical applications operates under a preventive maintenance (PM) to improve SLA and guarantee operation. Under this model, parts are replaced based on age and the manufacturer's average wear recommendations, without any indication of premature or late wear of any component.
In other words, they are based on average failure periods observed by the manufacturer's engineering and therefore do not represent any particular operating condition, often generating unnecessary premature replacements, increasing costs, as well as possible damage to assets during repairs that often result in unexpected shutdowns.
In addition to reducing productivity, unexpected shutdowns cause significant operational and financial impacts, as there is no planning or scheduled interruption to operations. Remediation is conducted through reactive maintenance (RM), which is based on the immediate and urgent need to replace components to restore operations as quickly as possible. However, immediate repairs are 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 interruptions are a significant loss.
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 now called prescriptive maintenance because it is managed based on the actual need detected by the IIoT monitoring platform. CBM can also be useful in failure prevention by recognizing equipment degradation before catastrophic failure occurs.
The goal of the CBM model is to move from a preventive maintenance program strictly based on a pre-established calendar to one based on the actual condition of the asset, minimizing reactive maintenance. This means that preventive maintenance tasks are scheduled based on the equipment's use or condition (quantitatively and qualitatively, respectively) and not solely 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 with the IIoT solution.
The IIoT platform must also include spare parts inventory conditions in its maintenance trigger rules to generate orders in time for appropriate planning and scheduling.
The most important thing is that the system must function in an integrated and digital manner, from detecting abnormalities by reading any kind of signal to sending a workflow to the maintenance team and ordering integrated and automated parts. This is the true process known as digitization.
Finally, the automated workflow process offers several benefits, including standardizing repair procedures according to prescribed maintenance, eliminating variations in labor quality, and reducing the need for team training.
Optimizing production processes is a complex problem that requires the implementation of a system that encompasses the infrastructure with an integrated perspective. 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 look at all these layers and how to solve the problem, read the recently published "IIoT and the Importance of Collaborative Infrastructure
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