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Rising labor costs and increased instances of plant downtime present significant facility maintenance challenges for owners of industrial plants. While downtime costs increase due to the more interconnected nature of plant infrastructure systems, the steady dispatch of maintenance personnel to plant sites drives up energy costs and adds to an organization’s carbon footprint.
Rising labor costs and increased instances of plant downtime present significant facility maintenance challenges for owners of industrial plants. While downtime costs increase due to the more interconnected nature of plant infrastructure systems, the steady dispatch of maintenance personnel to plant sites drives up energy costs and adds to an organization’s carbon footprint.
In addition, issues like deferred maintenance, which serve as a band-aid to reduce operational costs, cause the plant or facility to run less efficiently, again driving up energy costs and carbon footprint. Industry statistics show that running a piece of equipment to the point of failure could cost up to 10 times as much as a more pre-emptive maintenance approach. Fortunately, these challenges can now be addressed through the deployment of condition-based maintenance programs supported by analytics.
Many manufacturers are reevaluating their current plant critical infrastructure maintenance plans. One area garnering closer scrutiny is the plant electrical distribution system. Fortunately, recent breakthroughs in digitization technology allow for critical electrical assets to participate in remote, ongoing health checks that help to anticipate problems before they manifest themselves into unplanned downtime.
In the case of industrial electrical systems, devices such as low and medium voltage circuit breakers and relays, low and medium voltage panels, medium voltage switchgear cubicles, transformers, Uninterruptible Power Supplies (UPS), drives, and electric motors are subject to wear. By observing changes in the temperature and humidity profiles of such devices, for example, a condition-based maintenance approach, supported by analytics, can now enable facility staff to detect early signs of wear and aging. This allows maintenance teams to react before any unanticipated system failures occur.
In fact, according to the U.S. Department of Energy, such predictive maintenance approaches have proven to be highly cost-effective, saving roughly 8% to 12% over regularly scheduled preventive maintenance, and up to 40% over reactive run-to-failure maintenance approaches.
Field deployments highlight condition-based maintenance benefits
Customers who deployed the service derived some significant benefits. In one case, a global leading global chemical firm used the service to better maintain electrical distribution equipment and their motor control centers (MCC). By remotely monitoring motor voltage quality, they were able to avoid past catastrophic failures. In another case, a leading global food and beverage manufacturer, thanks to Schneider Electric Connected Services Hub alerts, have been able to react and avoid three unplanned outages that would have amounted to losses of US$1.2 million in production. They fully trusted Schneider Electric, implementing 100% of recommendations made, including correcting a serious transformer temperature anomaly which helped them avoid the loss of up to two years of transformer lifetime.
Such digital service contracts have helped support plant maintenance staffs in three important ways:
- Remote monitoring – The ability to monitor electrical infrastructure devices presents several advantages. If short on maintenance staff, the plant can rely on vendor experts to provide continuous screening of asset health. The service tracks both short-term (increased temperature or humidity) and long-term (computation of wear and aging) behavioral anomalies, computed by analytics, and alerts are generated that are analyzed and prioritized by remote experts. In that way, unanticipated instances of downtime are avoided.
- Issue identification – When critical alarms are generated, the Schneider Electric Connected Services Hub experts, who are on call 24 x 7, contact the end user with a diagnosis of the situation. The experts perform a remote diagnosis using advanced analytic tools. They also apply the performance data collected from the power distribution systems to identify issues impacting uptime. With this consistent health diagnosis in place, the plant staff can confidently push out the traditional plant shutdown maintenance cycle of once every three years to once every five years on average. This reduces costs and improves safety through fewer business process disruptions.
- Problem resolution – The experts who manage the Schneider Electric Connected Service Hub have access not only to the performance and maintenance data being gathered at the customer site but also to a data pool of thousands of global sites that have similar electrical distribution installed. This allows the experts to issue high credibility recommendations for when and how to prioritize and resolve issues that are identified. In fact, service hub experts rely on the maintenance index computed by the EcoStruxure Asset Advisor platform to allow the customers to make sound tactical and strategic maintenance decisions. Also, in some situations where an on-site fix is required, experts can remotely and visually guide the individual on-site, through the use of a tablet device (the expert sees what the person in the electrical room is seeing via a camera in the device supported by augmented reality), to troubleshoot and fix issues that require on-site work. This saves the expense, the travel time, and the sustainable impact of having to fly in experts and specialists for on-site diagnosis and repair.
For more information
To learn more about conditioned-based maintenance and how Schneider Electric EcoStruxure Service Plan Electrical Asset Management can help your organization reduce maintenance costs while improving safety and sustainability, visit our power services website.
