Through a data-driven approach, organizations can efficiently integrate future generations of skilled maintenance personnel by equipping them with the complete history of each critical asset. Smart sensors, like the GraceSense™ Vibration & Temperature Nodes, continuously monitor critical assets, record trends, and trigger alerts when irregular thresholds are met. Advancements through the Industrial Internet of Things (IIoT) are paving the way for a safer, smarter, and more productive digital workplace.
Digital transformation for maintenance teams has made planning easier and more efficient than ever. When maintenance needs are scheduled out in advance through early insights into their equipment health, technicians are better equipped to prepare for the task at hand. As opposed to reactive maintenance where the pressure is high to get everything back online as quickly as possible.
Equipment uptime directly impacts plant productivity and output. The age-old practice of route-based vibration analysis can fail to provide sufficient early indication of problems because data is not collected continuously and is neither provided remotely nor in real-time.
An unplanned shutdown due to a failure of improperly maintained equipment, such as motors and rotating equipment, is among the highest risk and most expensive scenarios an organization and its maintenance teams can endure. To curb this potential major economic loss, integration of a wide array of maintenance methods is essential as condition-based monitoring will spot equipment failure before it occurs and automatically alert personnel.
The next generation of college graduates who once would line up to fill these skilled maintenance positions is starting to lean more towards innovative fields and are less inclined to take up traditional maintenance positions. As a result, it's important to attract new talent with technologies to take up the mantle and allow organizations that are losing skilled maintenance personnel to augment and replace some of their expertise with IIoT technologies.
Anytime you have legacy equipment upwards of 50-60 years old that is still running in your facility, there's going to be a constant need for maintenance. If IIoT can eliminate the route-based inspections of that legacy equipment and bring about route prioritization it can have a high-value proposition for organizations.
There is a massive potential in the automation space for IIoT. It can serve to bring value by reducing unexpected downtime, but it can also be used to help augment the widening gap in the skilled maintenance workforce that's been created as more and more skilled maintenance personnel are retiring.
Above all else, the most important aspect we should value is safety enhanced through IIoT analytics that provides better planning and a proactive approach to maintenance.
Unlike the run-to-failure method, both preventive and predictive maintenance methods fall under the proactive maintenance category. Though the preventive and predictive methods share a common category; the principles, strategy, and implementation methods are different and, in some cases, a bit complex. A robust and reliable maintenance program will include elements of both preventive and predictive maintenance tools. This eBook explains how to equip yourself with the right tools for "A Proactive Approach to Electrical Maintenance".
Register for Upcoming Webinar: Facilities around the globe are experiencing a major generational shift in terms of how they operate and maintain their equipment. Increased productivity pressures and high uptime demands of equipment combined with a shortage of qualified maintenance personnel are driving facilities to rely more than ever on predictive maintenance tools (PdM). But how can you ensure confidence in your integration?
This session will explore the need for the Industrial Internet of Things (IIoT) in industrial environments and will highlight the importance of predictive maintenance (PdM) tools over preventive maintenance methods. Topic discussions will include why early IIoT attempts have failed, challenges involved with IIoT, and the four key elements for successful IIoT implementation.
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