Asset Performance Moving Beyond Just Reliability Because of Industry 4.0

The good news is that organizations don’t need to take on a massive redesign or make huge investments to achieve value from pursuing APM 4.0.

Posted: August 30, 2018

Asset Performance

Asset Performance Moving Beyond Just Reliability Because of Industry 4.0

For the last couple of decades reliability-centered maintenance (RCM) has been considered the pinnacle of maintenance philosophies. Although almost ½ of all companies today still have reactive (or break-fix) maintenance as their dominant approach to maintenance, the prevalence of preventative maintenance (PM), predictive maintenance (PdM) and condition-based maintenance (CBM) techniques is fast becoming the norm. For many companies the shift to PdM or RCM is viewed as state-of-the art maintenance. However, LNS believes this takes too narrow a view of the benefits of digital transformation. The reality is that if you are pursuing Industry 4.0 or Smart Manufacturing or more broadly, digital transformation, and relying on Smart Connected Assets to drive your business forward then reliability is but a stepping stone to the real benefits of asset performance management (APM) 4.0 level performance.

In the past maintenance has frequently been seen as a cost of doing business and an opportunity area for cost savings. Some more enlightened organizations have adopted RCM driven programs that focus on reliability and downtime reduction, but success has often been measured by savings, not overall profit improvement. However, organizations that have committed themselves to Digital Transformation can pursue loftier goals. LNS Research has crafted an APM 4.0 framework, and in this framework, the value delivery object of APM is overall performance, not simply reduced costs or downtime.

foundational technologies

APM 4.0

In the APM 4.0 model, reliability is only one factor of value. Profits, quality, employee and customer satisfaction, sustainability and other factors are all improved when a suite of tools can operate together, processing a diversity of information across the entire value chain. That information might be structured (i.e. from a business records database), semi-structured (historian data) or unstructured (images, text documents, media feeds, or vibrational spectral data). This applies whether the data is coming from devices on the plant floor, at a corporate location or from the cloud. It may be traditional IT type information, or it might be OT data at the edge.

The key to deriving value from this diverse data is to use multiple tools ranging from AI and Machine Learning to First-Principles-based models, incorporating financial data and taking a systemic view of the opportunities. In the past, the trend has been to focus on a single problem area. For instance, focusing on the reliability of a specific piece of equipment. These failure-prone and production-impacting elements were treated as the “bad actors” and the focus was on preventing their failure.

However, many firms found that despite reducing the frequency of failure on a specific piece of equipment, maintenance costs are as likely to go up as they are to decrease, and overall plant profitability may not even change. This can happen when the particular bad actor was throttling the production flow and hiding more fundamental flow issues. Or, it could be the activity to address the bad actor took critical resources or skills away from other critical process elements.

Leveraging the Digital Twin

The key to realizing the maximum potential from your plant is a robust and comprehensive digital twin. A digital twin is the tool that you leverage to not only better understand what is happening in your plant but the implications of future decisions. It is the digital twin that takes an organization to the next level of analytics – prescriptive analytics (RxM) where operational alternatives are presented with all their implications, so operations can make the best-informed decision on how to manage operational risk, improve profitability and drive stakeholder returns. The foundational technologies, data and the seven pillars of APM 4.0 described in the figure are the essence of the digital twin.

The good news is that organizations don’t need to take on a massive redesign or make huge investments to achieve value from pursuing APM 4.0. In many cases portions of the technology pillars are already part of a plants portfolio today. Investments in replacement technology often bring in new foundational capabilities such as the IIoT by default. All that is really needed to get started pursuing APM 4.0 is the vision, a defined architecture that supports APM 4.0 and the decision to make future technology investments that align with that architecture.

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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