VP Operations

Ashe Menon

In the last article I wrote about the Internet of Really Old Things (IoROT^TM), I specifically addressed how we need to remember that we have many plants in the US that have really old machines. We have to make sure that “no machine gets left behind” in this Digitization revolution, or at least, that no plant with old machines gets left behind. For this article, I want to focus on the people who run those machines. During early periods of Covid, while a majority of us were at home, there were a lot of factory workers that were classified as essential workers, so they could come in to work and make the products that we all needed. Many of us retooled our facilities to make ventilators and masks, and needed workers to come in to make them. This article is focused on the human being(s) operating the machine and maintaining the machines. I have coined the term IoTaB – the Internet of Things and Beings, and what I mean by this is that we have to build systems that don’t just include the human, but keep it at the center and use AI and ML to Augment the Human mind. A paper written by JCR Licklider in 1960 talked about how the two should work together. When we think of all the work done by Steve Jobs, as much as he was a technologist, I think he was best at understanding how humans would interact with technology. And everything is about the simplicity of the use of the “tech”. 

When we think about manufacturing technology, the real insight is provided by the Front Line Worker - they create the final product and that is the tip of the spear for any company. While we all want to focus on OEE, Overall Equipment Effectiveness – the combination of Availability, Performance and Quality - the focus has to be the people that make that happen.  Those people being the mechanics who make sure that equipment is available and the operators who make a quality product, on time. The systems shouldn’t be dashboards that show what they should do better, but instead should really focus on identifying the root causes that stop them from doing better. The systems that we build now should be about listening to the pain points to address the bottlenecks that exist between the carpeted floors and the concrete floor. 

You can’t be online these days without getting bombarded by ads for Machine Learning, AI or “learn Python” classes. The reason for this is that there is a shortage of Data Scientists and Data Analysts to analyze all the data that is being created by these disparate systems. While the rest of the world fights for these expensive resources, there is a huge opportunity for the technologists of today to build systems that can leverage the substantial supply of the determined and driven youth who aren’t in college or the military. The advantage is that the youth of today come pre-trained in the latest technologies, and are not afraid to use technologies like AR & VR. These are the technologies that we should use to bridge the gap that exists due to their lack of experience. The excuse of too little experience should be a thing of the past when we have as much technology as we do. Additionally, the fantastic article in Manufacturing Insights by Hao Dinh really addressed the future state of our factories and not on the automation-side, but on the people-side. The way we hire the next generation of employees can influence the culture of the plant for the future generations, and the “growth mindset” employees can fuel the acceptance and propulsion of new digital technologies. 

The goal is to leverage technologies to help us innovate, and I feel that innovation happens when people are allowed to “think” as well as “do”. Young people with the growth mindset without the baggage of “that’s how we have always done it”, can help companies come up with new and creative ways to build things faster, better, and cheaper. What this does is address three of the four foundational elements for manufacturing excellence - Efficiency, Quality and Cost. This same approach can be used to address Safety. Too often we look at Safety as an afterthought. People in operations and maintenance typically behave around Safety personnel like I do when I see a cop on the freeway. I tense up a little, ease up off the gas, look at the speedometer and check my rear view mirror to make sure he is still where I last saw him (or her). So instead of a similar reactive approach, it would be better to be proactive and just set the cruise control to the speed limit. We should a similar approach to being safe, we should analyze all the historical data on recordable, and use machine learning to identify any patterns that can point to some root causes, and leading indicators to consequently create an environment for safe behavior. We essentially poka-yoke the operation to be safe. As we create a culture of Continuous Improvement, we must ask them for ideas to improve as we arm them and ourselves with data and latest technology. This, in my opinion, is how we lay the foundation for a safe and profitable enterprise. This case has been proven in facilities across the US during the depths of the downturn in the oilfield and retested during the pain of Covid. 

I’d like to conclude this article the way I started, by thanking and expressing sincere appreciation to the people who make the things we buy, and show our gratitude by involving them in the conversation about how to build better systems that they will end up using.