The casino 4.0 - Internet of Things

Predictive Maintenance is the name of the game. Operators maintaining high value assets and perform reliability on a daily basis to ensure critical processes are available while ensuring minimum energy usage presents a clear user / business case: Prevent failures. Save time. Maximize energy efficiency. Billions of dollars are up for grabs when these three key problems are solved, specifically in the brown-field market where millions of assets in operation are wasting time, money, and the environment. These days it seems so easy to solve asset and operational problems in the cloud and even at the EDGE with Digital Twins to apply AI/ML (just Google it!). But for good reasons the core problems have existed for decades. In the IoT Vision (see picture below), published by Gardner, 55% of us are in the game of the 4.0 journey, and most know that it’s riskier to dig in their heels than to gamble on winning the jackpot (The Killer APP). The casino of Internet of Things is now a huge economy. In this case, does the old saying hold true, “The house always wins”? Let’s count our cards…

FOCUS on outcomes

Of course, focus is key to delivering your IoT deployment and winning the business case. It makes the developers life "easy" when you start with a crystal clear use / business case that locks in the WHAT to solve and not the HOW. It’s their job to determine the technology used to solve the problem, not the business individuals. What I have seen evolving over recent years in the space of digital transformation is that there is a common lack of business understanding and people (with all good intentions) are using jargon while not knowing what it means. And that is the #1 error preventing teams nailing down the solution and why tons of Proof of Value trials are failing right in front of your customer, even though the technology stack works and the user interface shines.

Below quote is one that I liked, right here on LinkedIn a few days ago;

"reliability and availability are not the same except in the fantasy world of zero downtime and no failures" - Reliabilityweb

Yes, agreed. In the real world the outcomes of availability (% of time spent) and reliability (% of failure events) are not the same. And for many operators and asset owners, when assets are driven by electrical motors, the asset / system efficiency (% of energy) is another key element to consider. These 3 KPI’s are my favored targeted outcomes to improve and solve customer problems because they deliver attractive ROI's. When you plan to apply AI/ML toolkits to disrupt the industry, focus on the problems to be solved, not the technology to be applied. Where old approaches to Enterprise Asset Management fall short, it will take more than "Intelligent connectivity to the cloud" and "Digital Twins" for your customers to accept your invitation to start the journey of the digital transformation. Often times, those buzz-words end up causing more confusion than benefit.

USE CASES are #1

An inspiring framework, for professionals in the world of reliability, are the Uptime Elements (TM) and it is serving the Culture of Awareness for operators and it scopes the era of technical activities, leadership and the business processes. My professional roots go back some decades into the water industry where for pumps the Life Cycle Cost Analysis is done trough the equation (LCC= Cic + Cin + Ce + Co + Cm + Cs + Cenv + Cd). That all works great and is a tactical solid model as long the data / information accessible, trough high quality of data, consistently logged and teams are engaged. But how does that scale... HARDLY!

In the use cases of a few (low value / non critical) assets that are remotely located or placed in a hazard environment, device connectivity sending device alarms will solve the a problem of AVAILABILITY by lowering the human efforts of routine site visits. It has been around for decades in the complex world of SCADA and today these kind of use cases are easy to solve with a "click to connect" modems, pre-configured applications in the cloud and deliver attractive ROI's. These straightforward IoT technology stacks are architected to scale for those specific use cases. Don't start to gamble and present the same stack to solve the use case of reliability, there is no need to talk about AI/ML, Digital Twins and other hypes while the availability use case is a clear win for everyone.

To solve the use case of RELIABILITY (% of failures) TOGETHER with EFFICIENCY (% of energy used) it becomes more tricky where business understanding (people), application know how (people) and the domain expertise (people) of materials are critical to architect the solution stack. Now the casino is open to play with plenty of "one box solutions" and tool sets on the market place today, from vibration data moved to the cloud generating threshold (false positive) alarms, "SMART wireless sensors" and even tiny boxes with printed labels "AI inside". In case you like to gamble and love to take risks, go ahead, experiment and learn fast, deploy some Proof of Concepts and have fun and pull swing the - one armed bandit -, maybe you are lucky.

READINESS to SCALE

Of course there are products and services available today that deliver the promise to provide early insights on asset degradation and are capable to predict in a very early stage failures and for sure beyond and before a human can do. The use case of solving reliability and efficiency is of course total different from the first use case of availability described before. The good news is that these technologies are already deployed on thousands of critical and high value assets across many industries like for example Utilities, AG, O&G, F&B and Mining. The technology is not the issue anymore, when you stack it correctly. More likely the (short term) challenge is human adoption to scale it into other industries and make it available / affordable for less critical and lower value assets.

Are we ready to "allow" the AI_ML engines to work (with us together), enable the workforce to make proactive decisions for maintenance and improvements based on predictive insights?

If you only like to gamble for fun and rather be safe to win feel free to reach out and I'm open to review TOGETHER your use case.