The Intelligent Edge: Bringing Transparency to the Factory with Lee Jaderborg (Part 1)
“Quality is never an accident. It is always the result of intelligent effort” – John Ruskin. This rings true in the world of IIoT. For Lee Jaderborg, who wears several hats at FreeWave, from engineering, to quality management and process development, the concept of intelligence-driven quality is what inspired him to learn everything he’s accomplished in his 40-year career, as well as what he’s brought to the future of the factory floor. In our fifth installment of “The Intelligent Edge,” we connected with Lee to discuss his work on the ZumIQ application environment and the purpose of intelligent monitoring. FreeWave: Lee, tell us about your role at FreeWave. Lee Jaderborg: Sure! I don’t have one specific job; I wear five hats. Coming up on my fourth year at FreeWave this April, I’m the manufacturing engineering manager, quality manager, sustaining mechanical support, and I oversee process development and design for new products. I also write SQL for our databases. I manage the procedures for a Printed Circuit Board assembly and Surface Mount Technology (SMT) manufacturing line, ensuring the entire process flows through production to the backdoor to ship. I also handle statistical process control and root cause analysis throughout the manufacturing process, all while monitoring for major operational KPIs. FreeWave: Was IIoT operations always your focus? Lee: No, I began college at age 17 as a drama major. Everything I’ve learned about engineering and management since then has been self-taught. During and after college, I worked in various engineering-type jobs, like designing tools to fabricate jet engine exhausts and helping build Colorado’s Eisenhower Tunnel. Along the way, I became exposed to SQL and got a master’s certificate in 6Sigma for project management. Continuous learning has helped advance me to where I am now. FreeWave: What are you currently working on? Lee: Optimizing FreeWave’s ZumIQ for better data visualizations on the manufacturing floor – a major focus at last year’s annual IMPACT Manufacturing Summit. A panel, which included the director of manufacturing for Rolls Royce, discussed transitioning their workforce to better accommodate millennials, who learn better with visual feedback. So, they put an IO on a light stack – like a stoplight that tells you whether a machine is ready – to give a real-time view of various data points. FreeWave: How exactly would they capture that data? Lee: This is where something like ZumIQ comes in – you need to tie into analog signals to continuously record this data. You do this by having the light stack’s sensor communicate its status to an app programmable device, whose data is then collected by the ZumIQ app environment. ZumIQ gathers and tracks data over time to determine both real-time status and historical trends. This gives a view of the manufacturing floor you can’t get by physically looking down the production line. It determines the collective state and efficiency of each part in the system. Interested in more insights by Lee? We’re continuing the conversation for the next Intelligent Edge blog.
Manufacturing Change through Big Data, Predictive Maintenance & Remote Access
Although the manufacturing industry has seen some troubling times over the past few decades, new technologies are helping it make a resurgence. So what has manufactured this change, you might ask? The rise of automation and robotics across many sectors, and perhaps one of the most significant industrial impacts since the assembly line was created – the Internet of Things. IoT has given rise to advancements in sensor technologies and M2M (machine-to-machine) communications, along with edge computing analytics and business intelligence from big data. These new methods are fundamentally changing the way goods are designed and produced. We recently wrote a blog highlighting some of these impacts and challenges that coming along with it. Below, however, we’ve gathered a handful of recent industry news articles for you to explore and learn how the industrial IoT is changing the manufacturing landscape as we know it. The Hunt for Zero Defective Parts Per Million When it comes to highly scrutinized and regulated industries, automotive manufacturing is near the top of the list. Understandably, then, automotive manufacturers are quite keen on the pursuit of zero Defective Parts Per Million (DPPM). This recent article from Manufacturing Business Technology discusses the driving forces behind this movement, namely the advent of autonomous vehicle technology. While on-vehicle computer systems of the past may have controlled entertainment or emissions systems, in the near future almost every vehicle system will rely on a piece of silicon in one way or another. With the stakes higher than ever, the advanced capabilities of the IIoT are coming into play to drive manufacturing processes. Moving Outside the Plant: Remote Access Is Quickly Evolving Just a handful of years ago, remote access technology was not a standard. However, as noted in this article from Automation World, a recent survey discovered that 72% of respondents are using remote access to monitor plant equipment and data. While the usage of remote access does vary by industry, the growth in this segment of the IIoT has been strong and shows no signs of slowing — and the applications for remote access are diverse. As Matt Wells, GM of Automation Software for GE Digital said, ““Anyone dealing with distributed fleets has a strong demand to be able to see, manage or control it from a remote spot,” he explains. “It all comes down to the difficulty of accessing that remote asset.” Big Data and Shale 2.0 As oil prices seem to have stabilized (for now) at a lower new norm, oil companies are having to get creative to keep margins healthy and profits rising. One of the ways companies are accomplishing this is through Big Data and the IIoT. This article from E&P Magazine highlights some of the challenges and hesitancies that are emerging within the industry, often fueled by cultural difficulties. However, Mark Slaughter — longtime Halliburton employee and current venture capital advisor — believes in just 10 years, smart analytics will give oil companies the ability to produce the most economic barrel of oil. Preventing Machine Failures through A.I. Automotive recalls are a massive expense for car manufacturers, not to mention the significant public relations disaster that can arise. In an effort to avoid this expensive and unseemly events, automotive companies are turning towards next-gen analytics and automation technologies to help prevent this issues before they become widespread problems. This article from IT Brief states that a recent McKinsey study shows that predictive maintenance could save global businesses an incredible $630 billion a year by 2025. In a world where recalls are pricey PR nightmares, this is music to automotive manufacturers ears. The IIoT’s Role in Product as a Service and Predictive Maintenance Models This recent article from Plant Services explores how the IIoT is changing the way equipment manufacturers and service providers approach their business, particularly through Product-as-a-Service (PaaS) and Predictive Maintenance (PdM). PaaS is the idea of charging for the output of a piece of equipment, rather than an upfront fee for the equipment itself. For example, the volume of compressed air generated by an air compressor. With PdM, advanced analytics are used to monitor the various systems in a piece of equipment, and diagnose and fix potential issues before they become larger (and more expensive ones). As the IIoT continues to grow, and more applications become mainstream, it will be interesting to see how manufacturing processes adapt and change. What new manufacturing promise do you think the IIoT holds? Where industry do you see IIoT gaining a foothold in next?
