An O&M guide to Maintenance 4.0

ML predictive maintenance for O&M professionals

The next normal has accelerated industrial digitalization processes despite economic downturn and continued supply chain disruptions. While adoption is rising, for many organizations investment in these solutions is still fraught with uncertainty. What should you be doing to reduce investment risk?

In the midst of a global pandemic, O&M professionals found themselves dealing with an additional operational challenge. As executives began to grasp the savings and efficiency opportunities of Maintenance 4.0 technologies, O&M professionals found themselves in the middle of discussions about innovation, possible technology providers, and the monetary or operational value these solutions could provide. 

Though the timing was not ideal for many O&M departments, the switchover to Maintenance 4.0 technologies was never going to be seamless. If Industry 4.0 is truly an industrial revolution, then history teaches us to expect a rise of new centers of power at the expense of old elites, with O&M departments forced to quickly adapt to new ways of working and expectations. In this article, we will explore how Maintenance and Reliability professionals can not only survive this tumultuous period but also thrive in the IIoT era. 

Our recommendations are based on the assumption that although change is inevitable, the contours of the digital factory are not yet set.  With IIoT, Operations and Maintenance (O&M) activities will gain more visibility at an executive level. Our message to those most impacted: Understand the change, make yourself indispensable and protect your domain. 

#1 Ignore the Hype  

It seems that overnight a cottage industry of thought leaders has sprouted up.  The reason is simple.  According to estimates, the market for Industry 4.0 is expected to reach $214 billion by 2023.  Many within the investment community recognized the economic potential early on, as investment capital was channeled to technology startups.   Not to be outdone, industry behemoths have invested significantly in Industry 4.0 R&D. 

Why is it important to ignore the hype? Much of the hype is fueled by third-party analysts and experts that stand to benefit from corporate sponsorship or consulting fees.  The interests of these parties are not necessarily aligned with those of the industrial plant. 

Next, tune out the noise and recognize that it is very unlikely that your job is at risk.  The futuristic scenario that AI, robotics, and drones will complete replace humans is unlikely to occur during your working life.  

The best way to manage the change is to own it by protecting your territory. The Chinese character for crises is comprised of “danger” and “opportunity”.  As solutions flood the market, the biggest danger is the role of outsiders in your decision-making process. 

#2 Own the Change 

The Maintenance and Reliability professional is the custodian of an organization’s industrial assets. Management will be inundated by well-funded sales and marketing messaging, and various stakeholders within the organization will likely be targeted by conflicting messaging.  

The path ahead is not simple. 

It is important that O&M be integral to the development of an Industry 4.0 roadmap and the vendor selection process. Unless the voice of O&M is included in business and functional specifications for IIoT solutions, their interest will be ignored.  This means actively engaging with management to reinforce the messaging that O&M is the brains of the plant’s industrial assets.  

#3 Learn to Think and Talk Like a CFO 

CFO’s are considered the stewards of a company’s financial statements. 

Historically, there is a perception that CFO’s consider O&M activities as a cost line item with limited strategic value.  These opinions were likely based on outdated views of the O&M role and CFO’s limited operational insights. 

Deloitte reports that CFO’s face relentless pressure to pressure to “grow revenue, cut costs and ensure control.”  As IIoT becomes more critical to an organization’s strategic goals and significant investments are made to support IIoT infrastructure, the O&M function is likely to mirror the views of the CFO. 

Instead of being pigeonholed as a cost center, O&M will be on the radar of senior management that recognize the opportunity to improve the financial performance and reduce the downtime cost in the following ways: 

Revenue increase.ARC Advisory Group estimates that the global processing industry loses $20 billion a year due to unscheduled downtime. As industrial plants use IIoT to reclaim a significant part of this lost production, the incremental revenue directly impacts the bottom line. 

Reducing maintenance costs.When machinery breaks down unexpectedly, repair crews are taken off their current jobs and need to travel to the site where the failure has occurred. Often, there is a need to wait for parts to be ordered and arrive.  This inherent inefficiency can be minimized when alerts of evolving failure provide sufficient warning time for parts to be ordered and maintenance scheduled for convenient time periods. 

Reducing CapEx.The average age of industrial equipment in the US is close to the highs experienced at the end of World War 2. When a production plant is alerted to evolving failure, it can remediate the problem before it occurs.  By reducing workloads before further damage occurs, assets can be repaired in an optimal environment.  Extending the useful asset life of machinery delays the need for capital replacement.  

Lowering insurance costs.A paper delivered at First World Congress on Engineering Asset Management explains that premiums for Boiler and Maintenance Insurance (BM) and Business Interruption Insurance (BI) change based on a company’s asset maintenance practices.  The “insurance industry is vitally interested in technologies which reduce the risk of interruption to plant and processes”.  

By improving O&M practices, insurance premiums are reduced which lowers the cost of capital. 

Without negating KPI’s such as Overall Equipment Efficiency, Maintenance and Reliability professionals need to adopt the language of finance and accounting.  The move from cost center to revenue producer is more than just semantic.  With the right level of executive support, O&M should gain the organizational recognition that it deserves. 

#4 Don’t be Intimidated by AI or Big Data 

Let’s look at this issue – Artificial Intelligence – in more detail. 

Until recently, there was no reason for Big Data to be on the radar of most O&M professionals.  However, with Machine Learning being applied to Predictive Maintenance, the topic is unavoidable.  There is an important role for Big Data.  Machine generated sensor data can be analyzed to detect evolving machine failure using advanced Artificial Intelligence.   The science behind it is complex and based on new research. 

Maintenance and Reliability professionals cannot be expected to become experts in this field.  The challenge for them is to understand how Big Data can be used without gaining direct discipline expertise.  We cannot speak for all solution providers, but at SKF Enlight AI all the analysis of the sensor data is performed offsite using a cloud-based solution.  We do not expect technicians to become proficient in Machine Learning.  Instead, we provide alerts for evolving asset failure and leave O&M professionals to do their work. 

How does an O&M professional thrive without becoming an expert in Big Data science?  By defining the business goals and technical functionalities of an IIoT Predictive Maintenance solution, you stay in the driver’s seat for adopting new technologies.  

Summary and Conclusion 

Many solutions will over-promise and under-deliver and it is incumbent upon O&M to prevent the procurement of the wrong technologies.  Claims of “seamless” integration and “zero touch deployment” need to be evaluated carefully.  If hardware is purchased for a new solution, does it require a new skillset to operate?  What type of integration is necessary? 

Today one needs to understand the topography of vendor solutions, without understanding the nuances of Machine Learning science.  If you ignore the hype and focus on aligning the ML/Big Data solutions with your plant’s strategy, you can thrive in the new IIoT era.