by Brandon Most, Portfolio Director
This is Part 1 of a two-part series; check back in a few weeks for Part 2!
Effective asset management delivers many benefits. Keeping close tabs on asset health prevents failures, reduces unplanned outages, and helps operations managers get the most out of scheduled maintenance windows. Effective asset management delivers capital benefits too, by extending useful equipment lives and improving overall ROI. In addition to these, close monitoring of assets improves workplace safety, reduces risks, and increases service quality.
The global economic downturn of the past half-decade or so has put additional pressure on asset-intensive companies to wring more value from their infrastructure assets. Companies increasingly view asset management as table-stakes for survival, and it now looms large in management strategies and corporate cultures. Effective asset management will drive more effective performance from equipment.
Given the extremely large asset inventories that make up large infrastructures, data-driven asset management approaches have proven a boon for companies in power, water, communications and other asset-intensive industries. By methodically streaming sensor and other device and system data to asset management solutions, numerous companies and organizations have transformed operations, applying technologies such as performance benchmarking and advanced pattern recognition to a monitoring and diagnostics culture previously defined by alarms, reactive remediation, and crisis management.
Reactive or proactive?
A natural extension of data-driven asset management, predictive analytics constitutes the next stage of evolution for infrastructure operations management. Where software-enabled monitoring and diagnostics benefit operations through techniques such as automated filtering and advanced pattern recognition, predictive analytics layers additional value in the form of machine learning, artificial intelligence, and other techniques for predicting future outcomes, time frames, and impacts.
How different is predictive analytics from monitoring and diagnostics? Massive. Monitoring and diagnostics help engineers repair assets after an issue occurs; predictive analytics, on the other hand, predicts when an asset will likely fail, in what time frame, and at what cost impact to the operation. Predictive analytics allows you to proactively fix issues before assets fail, before workers sustain injury, and even before alarms thresholds get breached.
Do predictive analytics solutions necessarily replace time-based maintenance? Not necessarily. Few organizations have embraced predictive approaches to this level so far. Can predictive analytics complement time-based maintenance? Absolutely. We’ve seen numerous examples of this hybrid approach – along with significant material benefits – in our customers’ operations. Operations engineers frequently maintain their monthly site inspection schedules well after implementing digital asset management solutions.
Ready for the Next Stage
Is your organization ready to advance from a reactive to a predictive mode? Metaphorically speaking, if a tree falls in your operations forest, would you rather wait to hear the crash or predict the collapse ahead of time and make proper preparations? Equipment failures can happen at any time of the day. A growing number of operations leaders have determined they can no longer afford to rely solely on reactive measures. Given its advantages – improved risk management, operational efficiency, quality of service, and asset ROI – embracing predictive analytics technologies is a matter of when, not if.
The time to formulate your proactive strategy for critical infrastructure asset management has arrived.
For more information, visit our Monitoring & Diagnostics product page.
Check back for Part 2 of this series, which will post in a few weeks. It will discuss how there is a better way to manage your critical infrastructure assets using advanced pattern recognition and predictive monitoring.