Optimation Blog

In the brave new world of the Industrial Internet of Things (IIoT), many companies are discovering that they have better connectivity and access to a wide variety of data generated by their business and manufacturing computing systems.  This digital information is a product of databases used to order products, manufacture them, and even ship them.  With all this information at hand, manufacturers are beginning to ask how the data could be used (mined) to improve a whole host of company metrics, like lead times, yields, supply chain efficiency, etc.  With most businesses that utilize computers across their product delivery stream, the key is to cull out the valuable information from the massive amounts of less valuable data at hand.  As you might imagine, this becomes a daunting challenge.

As a process and product engineer for a fortune 100 company that manufactured high value chemical products, my job involved analysis of a tremendous amount of process and product information.

At one point, Kodak continuously evaluated over two hundred thousand process and product parameters for all production orders in the worldwide film supply chain. The parameters being evaluated included: key process parameters, such as chemical reactor feed flows and temperatures; product release parameters, such as number of defects in a 10,000 ft master roll of coated film, and the condition of critical process components, such as pump vibration level, heat exchanger approach temperatures, motor current draws and control valve positions. Automatic alerts are generated to alert maintenance when parts need to be replaced or operations when a product just made needs to be held and not released to downstream operations. How did Kodak accomplish this level of aggressive monitoring in a global supply chain with flexible manufacturing systems and thousands of product recipes? In short, the answer is Process Monitor.

Recently a team of Optimation’s web conveyance experts teamed up with a pair of Eastman Kodak’s IT experts to create a means to demonstrate the power of applying a process monitoring tool to a known but illusive problem.  The demonstration involved using Optimation’s Thin Web Rewinder, one of the pilot machines located in our Media Conveyance Facility, and Kodak’ proprietary Process Monitor software.  We elected to use roller traction as the parameter of interest, because it is a functional attribute that is subtle, making it challenging to measure and status over time.

When you stop and think about it, what control system integrators are brought in to deliver is some specific capability with our expertise and experience that ensures the safe and efficient accomplishment of the mission. If the client’s own internal experts, or certified integrators, are not able to do the job, then other resources (uncredentialled, unverified) might be asked to do the work, jeopardizing the processes, procedures and qualitative metrics.

During the past decade, the Internet of Things has been steadily advancing and becoming a part of our lives.  We get texts from our cars when the tire pressure is low or suggesting we should stop and buy another gallon of windshield washer fluid.  We can turn on the oven or close the garage door at home from our office.  These opportunities are supported by small amounts of data and provide simple solutions. 

Industry 4.0 and the Industrial Internet of Things (IIOT) promise to make more data and better analytic applications available for industry.  Driven by high powered analytics, including machine learning and artificial intelligence engines, both promise operational benefits including lower costs through improved Key Performance Indicators (KPI), such as First Pass Yield, Non-Standard Downtime or Overall Equipment Effectiveness. 

An interesting manufacturing tool is emerging as more companies seek to mine, or take advantage, of the process data their production systems generate.  The tool, called Process Monitor (PM), uses statistical analysis methods to crunch the manufacturing process data, and predict whether or not the production system is operating within preset control limits that indicate an acceptable product outcome. 

The Internet of Things is revolutionizing all areas of our lives.  Manufacturing Industry 4.0 is a revolution as transformative as the first industrial revolution that began nearly three hundred years ago.  Over the past few years major manufacturers of industrial control products, as well as smaller software companies and start-ups, have been developing and introducing software and software tools to provide analytics and artificial intelligence to improve both manufacturing processes as well as products manufactured.  Advancements in manufacturing analytics are coming fast and furious.