It’s Time to Level Up The Maintenance Role

AI and machine learning will impact maintenance, reliability, and operations at levels that will be hard to fully comprehend their impact. ChatGPT has taken the world by storm, and technologies driven by sophisticated artificial intelligence (AI) and machine learning algorithms can now tap into terabytes of data, creating original content as never seen before. Experts in just about every industry see the potential: AI can now write academic papers, pass the Medical Licensing Board Exam, perform research, and write legal briefs faster than humans. I believe that millions of jobs are at risk.

Yet, this is not a novel occurrence. History will repeat itself. With each new era comes a new generation of how we work. As business processes become more effective and efficient, thousands of low-skilled jobs disappear and are often done better and faster by machines or automation. However, I believe this will again shift industry’s focus to employee education and training, helping those in the workforce upskill for higher-level jobs, which then boost both wages and standards of living.

Unlocking the Potential of Data

This call to embrace AI and machine learning technology like ChatGPT is reaching maintenance, reliability and operations as well. We are at the cusp of a new generation of how we work in our factories, in our healthcare facilities, on our farms, and in the world as a whole.

I believe the key to making the shift successfully is unlocking the power of data that is already being generated at unprecedented rates. Maintenance teams now have access to more IoT, ERP, and technical data than ever before. Yet, this data is not shared across platforms or teams but remains siloed and fragmented across different systems. The result? Misaligned perspectives, priorities, and decisions across the entire business.

The problem is that without the right infrastructure, this data problem will be rapidly compounded over the next five years. Analysts predict that IoT devices alone will transmit more than 73 zettabytes of data during this time, representing a 422 percent increase. Without effective use of all this data, we will be holding ourselves back from the next evolution of how we should be working.

We need to find a solution to this problem of explosive, yet siloed data, in order to tap into the power and potential of AI and machine learning technologies like ChatGPT. We need to automate away those low-skill, low-paying skills and open opportunities for our employees to level up to better jobs–jobs that require critical thinking and creativity. When we do this, we can expect to make greater strides in reliability, safety and the understanding of the criticality of assets. 

Asset Operations Management

The first shift must be how organizations view maintenance, reliability and operations. They can no longer be three different teams each working on their own unique goals. Instead, there must be a movement to a single team focused on common goals around your asset operations management.

To achieve this, organizations must create an integrated and centralized data ecosystem that can effectively collect and extract data from all business applications, sensors, and PLCs. Then, they must be able to rapidly standardize all this data that comes from different sources into a common data model with customized metrics. And finally, they must be able to load the resulting asset data into business critical systems to support real-time business decisions.

By having this vast amount of data at hand, I believe that not only will AI and machine learning technologies like ChatGPT be able to find more ways to support business growth and evolution through automation, but our human teams will be able to elevate the work they do from completing unconnected tasks to adding value, generating revenue, and supporting growth for the entire organization.