Turbocharge your predictive maintenance KPIs with higher accuracy predictions
Plant operators and maintenance teams spend a significant amount of time setting, measuring and analyzing key equipment performance metrics around availability, efficiency, reliability and quality, all with the goal of improving operations over time. Because today’s plant operators are also challenged by the business to improve performance, savvy ones are turning to predictive maintenance (PdM) solutions to drive better performance on KPIs.
Regardless of where you are on your PdM journey, the more accurate your system predictions, the more positive impact they will have on your performance KPIs. PdM alone will positively affect performance KPIs, but more accurate predictions can have an exponential impact on improvement. Here are some ways higher accuracy PdM can turbocharge important KPIs for plant operators.
Measuring Overall Equipment Effectiveness
At the top of the list of ways to measure success is Overall Equipment Effectiveness (OEE). Often considered the gold standard KPI for plant operators, OEE is somewhat tricky to measure as it involves several variables but when evaluated correctly, it provides an informed, data-driven picture of how effective maintenance processes are.
OEE also sheds light on an important question: are you spending time making revenue – or simply fighting the revenue bleeding? The fact is, a majority of plants are running at suboptimal efficiency. In one recent survey, 60 percent of those surveyed experienced overall OEE levels that underperformed. PdM plays a significant role in improving OEE by addressing such critical factors as availability, performance and quality of equipment. Let’s explore these in closer detail.
PdM improves the availability of equipment by anticipating when a component may fail. The upside to this foresight is the ability to have more control and schedule maintenance at a more opportune time. A successful PdM program will see unplanned equipment downtime inch closer to zero hours. Getting to this mark sounds out of reach, but higher predictability provides the valuable lead time required to manage maintenance weeks or months in advance.
General performance is also equally important. PdM helps ensure equipment operates at its optimal level by evaluating the overall health of each asset. Mean Time Between Failures (MTBF), the elapsed time between failures of a system during operation, is a way to quantify an asset's reliability and predict future performance, which is especially critical for essential pieces of equipment.
Plant operators can optimize PdM schedules by tracking MTBF and the associated metrics – such as downtime, uptime and number of failures – to avoid unexpected losses and reduce the risk of performing unnecessary maintenance on equipment. The higher the PdM predictability, the better the understanding of MTBF and therefore a longer runway to schedule and perform maintenance at a time that will not impact availability.
Drilling down a bit deeper, high accuracy in PdM significantly impacts KPIs in other areas. One such area is the percentage of maintenance hours spent on planned compared to unplanned maintenance. A ratio of 80 percent planned to 20 percent unplanned is considered ideal, compared to a typical average of 55 percent or less. However, higher accuracy in predictions can easily push this number over 90 percent.
Mean Time to Repair
Mean Time to Repair (MTTR) is another metric used by maintenance departments to measure the average time needed to determine the cause of failure and repair the equipment. The only way to improve this KPI is by alerting the maintenance team to identify both the problem and the course of action needed to bring the asset back online quickly. This is a KPI where predictability and accuracy are equally essential.
Manufacturing safety is a crucial component to the success of any business, and this includes the maintenance function. The most common KPI in health and safety has been accident and incident rate. PdM can help provide valuable insights to better arm maintenance teams so they can plan maintenance and repair at optimal times, such as when a work crew is well-rested or adequately staffed to perform the function. This in turn reduces the potential accident risk rate.
The one metric that rules all other KPIs is the return on investment (ROI). The financial benefits of a PdM installation must be measured against the costs of implementing the system. This goes beyond the economic costs of the technology system to include training, ease-of-use, and the quality of insights, including the level of predictability. The higher the predictability a PdM system has, the higher the positive impact and the faster the ROI.
The Novity TruPrognostics engine is the leading PdM platform that can reduce unplanned downtime with 90 percent or better predictive accuracy, often providing months of advanced notice before failure. However, Novity’s goal is to provide both prognostics and full-spectrum visibility that deliver actionable insights to substantially improve business functions.
Want to know how Novity can help you reach zero unplanned downtime? Sign up for a demo of the Novity TruPrognostics platform today.