At LNS Research we are excited as to what 2017 will hold! We recently published a blog post to revisit our 2016 predictions, review how we did, and what it means going forward for Asset Performance Management (APM). Now as 2017 is upon us, we would like to discuss our predictions about what we expect to take hold for the year to come.
Our basis for making these predictions is the depth and breadth of our survey research, customer meetings, vendor solution direction briefings, and intuition. Last year was all about the blurring lines between APM and Industrial Internet of Things (IoT), the selling of capacity over assets, and augmented reality. This year we expect to witness new ways to jump into APM and take advantage of multiple solutions and data sources to innovate going forward.
As IIoT platforms begin to take hold in the APM space, we need to go beyond IIoT thinking and bring the platform to being “what’s of value in connections in the first place, the asset’s information.” It’s not just about connecting an asset, adding more sensors, or enabling Predictive Analytics; it’s about creating as many connections to that asset throughout its entire asset lifecycle and using the data to create information.
This means connecting assets, services, workforce, suppliers, manufacturers, sales & marketing, operations, and maintenance together on one platform; with the ability to mashup many applications that span specific users or use cases, to enterprise apps for many.
We foresee two opportunities for the materialization of mashup applications in APM in the near term. The first is prescriptive maintenance. We spent much of last year hearing vendors tout their Predictive Analytics offerings. These are an important part of the journey towards Prescriptive Maintenance. Taking predictive tools, with IIoT data and Analytics and merging with APM applications such as EAM, ERP, and Knowledge Management can create an innovative mashup application for prescriptive maintenance.
This type of mashup application will help organizations move beyond the identification of a problem or future problem to making recommendations on the best path forward based on inputs from the entire business.
A Digital Twin mashup application is more than just a digital copy of a physical asset. It’s the virtual and augmented model, that can is manipulated at a higher level. For example, in Refining, the digital twins of the Distillation Tower, Cracking Units, Reformers and Alkylation Units can be combined to simulate, visualize and monitor the performance of the entire system throughout the asset lifecycle.
This digital copy of the physical asset can be used for various purposes in Asset Performance Management. For example, these twins can be used to view and understand the status of an asset and the sensor data from the asset can be used to update the digital twin in real-time.
The APM space has been the poster child for the opportunity in IIoT. As you can see from the chart below, we expect this trend to continue for the next year, and more than likely beyond. Because of this, we anticipate an emergence of two or three APM tools to emerge that may or may not have their traditional roots in APM. These new tools will be formalized to allow users to extract the value the promise of IIoT creates, on the cheap, for very specific issues.
For example, understanding and gaining insight as to why an asset breaks down too often. Now, choosing a tool to support finding the answer to this problem can come from many different directions, IT, APM, or Automation solutions. Each, more than likely, will provide a Predictive Analytics engine to support improving asset reliability.
Businesses are facing vexing problems demanding immediate solutions. Utilizing an easy to install and manipulate solution can be an option to deal with fixing issues in the short term. We expect these solutions to be deceptively simple while getting the job done effectively. These tools should be viewed as ways to prove that implementing APM can support the organization. When organizations find, they are reconfiguring the tool to address a new problem; they might heed this as a warning to begin looking at broader capabilities that work at an enterprise level and offer a range of out of the box functionality.
In asset-intensive organizations, the operations and maintenance teams live in a world that is highly complex. As the great crew change continues to drain knowledge from these industries, it will force organizations to look at ways to simplify this complexity. This is where AR/VR lives at a plant level; not just an asset view has potential.
This will not be full on wearable tech that was discussed and popularized late last year by Samsung. And we don’t expect the experimentation to explode to mainstream in short order. The expectation is 5-10% of organizations pilot and explores how this approach can create value through workforce training, planning, and execution of complex projects and the skills that should accompany them.
A good example of a use case for experimentation of AR/VR is around shutdown/turnaround activities. To work, organizations can create an interactive model, using the Digital Twin, to create an interactive model that provides mobile capabilities and is easy to interact with. Having the maintenance teams work out their approach to the shutdown/turnaround virtually, with their predefined set of tasks, they can train less skilled workers, increase the chances the project runs smoother, increase safety, and reduce risk. Any issues can be uncovered, integrated into the simulation and then gone through again to test for improvement.
As 2017 unfolds while working with end-users and vendors, our eyes will not only be in our predictions but what else continues to shape the APM space. We look forward to providing insights and analysis from our surveys and market dynamics as they progress. You should expect to see deliverable research on each of these topics this year that will help define and execute best practices strategies.
And as we did last year, we will be grading ourselves on our APM predictions at the end of the year. Although we hope we are spot on, we will always be interested in how things turn out regardless of being right or wrong, as long as APM landscape continues to innovate and evolve.
LNS Research Analyst, Joe Perino, presents learnings from his latest APM and risk management research.
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