Unlocking the Value of Data at Dow

 

At the 2016 Manufacturing Leadership Forum hosted by Northwest Analytics, Jim Peters from the Dow Analytical Tech Center presented on Dow’s efforts to derive greater value from available process data. Most of the manufacturing process data collected are generally underutilized, and sometimes simply ignored, in the archives of various process historians, LIMS or other databases. Enterprise Manufacturing Intelligence (EMI) helps organizations unlock the potential and value of process data by applying analytics in real time and making the results immediately available in context to all levels of the organization for immediate understanding and action. Mr. Peters highlights how Dow is utilizing EMI to better connect analyzed data with the operations to impact production in real-time.
According to Mr. Peters, EMI contextualizes data that is important. When you consider the shear amount of data generated by a piece of equipment, let alone a single operating unit, it becomes clear that a person’s ability to consume that data becomes overwhelmed. Contextualizing the data allows personnel to focus on what is critical to efficient production. It is also important that the information be available in a timely manner.
He made a few key points in his presentation about EMI. One was that end user’s process and approach must evolve. Early analysis may point out certain weaknesses in manufacturing that need focus. Over time, the weaknesses may be addressed and it reveals other weaknesses or priorities change. Another point Mr. Peters made is that alerts must be meaningful. In a manner similar to alarm management, alerts should be targeted to an audience that is expected to act on them. He recommends EMI dashboards be created for specific roles. Someone in Operations will need to focus on different areas than Maintenance or Engineering.
Mr. Peters emphasized the importance of framing the problem first. ARC couldn’t agree more. You must understand the problem well enough to apply an adequate solution. Industry is rife with stories of inappropriately applied technology. If your organization is new to analytics, ARC recommends starting small, but it is important to start. The automation of analytics allows personnel more time to think and act. This additional decision time is crucial to improving efficiency and quality.