5 Steps to Implementing Intelligent Asset Strategies (Part 4): Threat Detection
You've got your devices connected and generating your data, which you've used to prioritize work and analyze risk. Now let's jump on threat detection.
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Green means “go.”
Red means “stop.”
Yellow falls somewhere in between, right?
This tri-color scheme is familiar to many of us in our everyday lives. It can also apply to industrial organizations managing massive amounts of data. But it’s not just about being alerted to a “red” indicator or an emerging threat on a particular asset, it’s also about what to do next or how to act proactively to prevent asset failures. That’s where intelligent asset strategies enable organizations to take all of their asset data and bring it together to get an overall view of asset health and continuously monitor for excursions and anomalies.
By establishing an overall asset monitoring program, based upon failure risks, organizations are able to observe and keep watch over changing business conditions, equipment health, regulatory requirements and other aspects that might impact your business. Once an emerging risk is detected, actions can be implemented to proactively manage potential unexpected events such as equipment downtime or non-compliance situations. This type of monitoring, Step Number 4 in our intelligent asset strategy implementation process ensures long-term benefits to your business.
Going Beyond Alerts and Advisories with Intelligence
As discussed previously in this blog series, implementing an optimized asset strategy can provide great initial benefits such as reduced maintenance spend and lower risk of asset failure. However, a key consideration that needs to be accounted for is the initial creation of a strategy is a ‘point in time’ decision based upon currently conditions and other assumptions. As we know, Industrial environments are dynamic; business objectives change, equipment ages, asset health degrades, process conditions flex, maintenance and inspection activities are performed and each one of these elements components can negatively impact the value of a ‘point in time’ or ‘static’ strategy. We believe the key to truly optimizing asset performance and getting long term value from an asset strategy is to connect the risk of failure to these dynamic elements, monitor emerging threats in near real time and drive proactive action when increased risks are detected. We call these living strategies which are a key characteristic to an intelligent asset strategy.
Intelligent asset strategies provide organizations with alerts and advisories via condition monitoring data, engineering or design data, safety and compliance data, process condition data and maintenance history data. But we’ve also placed intelligence behind those alerts and advisories (health indicators) through the concept of policies. Policies are a very robust way of combining human knowledge, industry standards, and compliance standards into one solution and having them work effectively for your organization. Policies integrate the strategy definition, appropriate input data sources, the analytical routine to determine the appropriate proactive action and automatically drive implementation processes.
As sensors and monitoring systems have become more prevalent, one of the more popular use cases for a living or dynamic asset strategy is driving condition based maintenance (CBM) programs. We have seen many customers use the policy capability, within GE Digital's APM solution, to take very simple conditional inputs such as vibration levels or flow rates, assess against known failure risk thresholds and automatically drive proactive maintenance activities to optimize maintenance resources and minimize downtime. However, intelligent asset strategies go beyond CBM approaches and our customers continue to amaze us with many forms of intelligent asset strategies, other examples include:
- Dynamically measuring integrity operating windows against risk-based inspection damage mechanisms to detect if process excursions have shifted integrity risk or require an adjustment in inspection plan to comply with regulations
- Ensuring key strategy recommendations (such as maintenance or inspection activities) are not sitting in an EAM execution backlog thus creating another hidden risk to the business
- Automatically detecting machine start and stop events to more accurately measure equipment downtime and potential production plan impacts
- Leveraging smart instrumentation to measure, in real time, the integrity of safety systems
These are just a few examples of implemented intelligence and one of our customers recently shared with us that they have implemented over 10,000 intelligent asset strategies in their organization! We believe one of the key reasons for the diversity and scale of intelligent strategies with our customers is why we designed the Policy application for direct use by equipment experts in a very intuitive environment. GE Digital's APM provides the integrated view of key asset data and with Policies, we have given the resources that understand the asset, potential risks, detection methods and the appropriate mitigation plan the tools to define and implement the intelligence without having to really on software programmers.
Intelligent Asset Strategies in Action
At Meridium Conference 2016, Rio Tinto Kennecott (Rio), a major U.S. copper producer, presented on how they’ve adopted this approach to better manage their assets. Rio took data from their process historians, computerized maintenance management system (CMMS), production loss accounting tool, operator rounds, analytics, lab data, and tribal knowledge, and rolled all the information into their APM solution.
With all the data in one place, Rio decided to group all health indicators into three groups:
- Performance- or process-related
- Age- or design-related
Then by weighting each asset based on its asset criticality score (Step #2 blog post), known failure modes, and domain expertise of operators, inspection and maintenance teams, Rio generates policies that create properly weighted and prioritized asset health indicators.
This provided Rio’s team with a single source of truth for asset health. All of the data coming in from various sources was rolled into dashboards for operators, analysts, and management to drive corrective actions when risk arises. Benefits Rio is now seeing with this approach include enhanced work prioritization, capacity assurance as well as the ability to forecast the remaining useful life of critical assets.
By having one “source of truth” for your asset data and then enabling the intelligence behind that asset data, your organization can become aware of asset failures ahead of time and you can act proactively on those threats to ensure you’re maximizing uptime and minimizing unplanned events that can occur.
Published at DZone with permission of Joe Nichols, DZone MVB. See the original article here.
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