Profitability Management is Possible - Thanks to Digital Transformation

The key to being successful with APM 4.0 is to take a systems perspective

Posted: August 27, 2018

Asset Performance

Profitability Management is Possible - Thanks to Digital Transformation

For several decades there has been a lot of discussion on shop-floor to top-floor information integration, executive dashboards (so management can get a snapshot of business performance) and enterprise manufacturing intelligence (EMI) solutions that give a holistic view of the business.  All of these approaches have focused on trying to get someone access to information about process performance, so they can better manage operations. 

The problem with all these approaches is they rely on human intervention to interpret the information displayed, decide upon a corrective action and execute that action.  In some cases, this might be the appropriate way to address a problem. However, if every deviation from the intended business operational course requires human intervention, this also poses a risk. If people become so overloaded, it becomes difficult to identify the critical few among the clutter.  One way to address this is to leverage technology available today to put business processes under closed loop control.

Does Digital Transformation Enable Change?

The business press, the Twittersphere and LinkedIn and other blog sites are all ripe with content touting digital transformation. The premise is that by adopting the core technologies associated with digital transformation a company will be able to prosper in the face of the disruptive forces that will inevitably be aligned against it.  Most often digital transformation is focused on six key technical trends 

  • Big Data and Advanced Analytics
  • Artificial Intelligence (AI) and Machine Learning (ML)
  • The Industrial Internet of Things (IIoT)
  • Mobility
  • Augmented Reality and Virtual Reality (AR/VR)
  • The Digital Twin

By adopting a combination of these technologies, the hype promises, businesses can avoid being disrupted, change their business model and continue to prosper for the next decade.  The implication is that by leveraging technology businesses can enable change. 

Typically, in asset intensive industries or those with asset centric manufacturing plants, the proof of concept (POC) project for digital transformation an asset performance management (APM) implementation. The typical POC project leverages IIoT sensors, Big Data & Analytics and potentially AI or ML to improve the reliability of the plant through condition-based maintenance (CBM) practices, or depending on the needs of the plant, predictive maintenance (PdM) or reliability-centered maintenance (RCM).

While this targeted approach provides benefits, it also has potential pitfalls. The problem with this approach is that the emphasis is solely on the technology or digital part of digital transformation. This only reflects best practice maintenance philosophy that has been in place for more than a decade.  So, while the promise is that digital transformation enables a change the reality is that with this approach it just makes doing the right thing affordable and somewhat easier. 

What Real Change Might Look Like

LNS believes that in those industries where APM is considered a key pillar of operational excellence, that if one takes the same view of the production plant and focuses on Smart Connected Assets the same way Industry 4.0 is focused on the design and manufacturing of Smart Connected Products, a concept we call APM 4.0, that businesses can do much more.  Specifically, using the technologies described above, and combining them with advanced simulation and modeling to facilitate AI and ML, assets can be managed to not only improve reliability, but also drive higher profitability.  Businesses can expand from just looking at how to avoid machine failure to understanding how to drive optimal business performance that really effects change.  The key to making this change is to expand the use of analytics from a backwards looking descriptive and diagnostic approach to a forward looking predictive and prescriptive approach.

APM1

Rather than having to set an alarm threshold indicating that a piece of equipment may have exceeded an operating condition that in the past was a precursor to a failure, APM 4.0 empowers operators to take a different approach. Operators can use Big Data Analytics to paint a picture of the entire environment that existed prior to the failure, then with AI and ML technologies consider how they might operate equipment differently to still meet production, quality and profitability goals, all while avoiding failure.  Alternately, if the analytics tell you that the best solution is to affect a repair to maintain schedule, quality and profits then take that approach.

The key to being successful with APM 4.0 is to take a systems perspective.  Instead of looking at just the asset look across the entire value stream of the process to understand the best approach.  Then as confidence in the ability of the technology to provide profitability guidance grows, start automating the application of those decisions.  When companies start to use technology to automate optimizing at the corporate strategy level rather than just automating basic control functionality they are truly transforming their business holistically, not just digitalizing individual functions.

To learn more about how APM is evolving and your company can get the most from analytics and increase your profitability watch the On-Demand webinar with LNS Research sponsored by AVEVA

 

author
Written By
Dan Miklovic

Dan Miklovic is a Research Fellow with LNS Research; he primarily focuses on industrial operations, asset management, and energy management, with collaborate coverage across the Industrial Internet of Things (IIoT), paper and packaging, mining, metals processing and other industry verticals served by LNS Research. Mr. Miklovic is a Lean Sensei with more than 40 years’ experience in manufacturing IT, R&D, engineering, and sales across several industries, and has held key positions with companies like Emerson Electric, Mallinckrodt Chemical, Weyerhaeuser, Scott Paper, Aspen Technology. He is a fellow of the Industrial Computing Society and past leader in ISA, TAPPI and SME, and held an adjunct faculty position at Central Washington University for 16 years. Mr. Miklovic holds a BS in Electrical Engineering from the University of Missouri and earned a Masters of Science in Management from the University of Southern California.

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