Ask Tom
Data Management, Part 3 BY TOM WEBER
T
he following is a recap of the third session in a four-part series surrounding data management. The session, which covered methods, was hosted by your AICC education team and moderated by me. I thought you might find this third recap both relevant and compelling toward finding a better way in 2021 and beyond! The fourth and final session will cover materials and will be recapped in the November/December issue of BoxScore. I encourage you to read ahead by obtaining all four of the recorded versions. The recordings are available through your outstanding AICC education contacts, Chelsea May and Taryn Pyle. To begin our recap of the session on methods, our goal was to gain valuable insights into real and perceived quality issues and to learn how to tell the difference in your operations. The top three methods explorations are listed below, and even more were identified by AICC members during the session. They were explored in some detail by our AICC Associate member panel, which included technical and industry experts from Amtech, Advantzware, EFI, Kiwiplan, and OMP. • Drive continuous improvement in reliability, efficiency, and end-product quality. • Focus on mission-critical methods and reduce costs with key performance indicator (KPI) data. • Analyze huge quantities of data using predictive modeling and analytics.
Drive Continuous Improvement in Reliability, Efficiency, and End-Product Quality Predict problems in advance with machine sensor data that feeds into analytical models. When there is an issue, diagnose it with
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root-cause analysis tools so you can take corrective action quickly and accurately. Don’t expect your machines to deliver top performance without the aid of advanced analytics. For instance, with artificial intelligence and analytics doing the heavy data lifting, a company might analyze profit-per-hour factoring in as many as 1,000 variables and 10,000 constraints to help manufacturers figure out what to buy, what to make, and how to make it to yield the most profit in each period. Worth noting once again: The digital universe is doubling in size every two years. By the end of this year, the data we create and copy annually will reach 44 trillion gigabytes, according to International Data Corp.
Maximize Throughput All methods should be directed toward problem-solving, process improvement, and profit generation. You may get a fresh perspective on a variety of processes or business challenges. Status dashboards and automatic alerts can notify operations staff of impending failures so you have time to correct issues in advance. The use of KPIs and dashboards can move a company toward predictive and preventative maintenance strategies to address known sources of failure without driving up costs. Avoid costly just-in-case strategies by using leading indicators that tell the entire story.
Focus on Mission-Critical Methods and Reduce Costs With KPI Data By offering your employees various methods to test and measure data—and helping them to understand data’s critical importance—you help get them invested in the data-driven culture. A self-service culture of missioncritical data, utilizing KPI dashboards, will present the trends and snapshots necessary to manage your entire conceptto-consumer product delivery process.
Improved Root-Cause Analysis Using Your Machine KPI Data Generation Quickly and accurately identify root causes using your generated data to mine, drill down, and ultimately detect hidden patterns. KPIs will facilitate more data-focused, permanent corrections. This third session recap was intended to create the thought that perhaps there is a better, faster, and smarter way to do tomorrow what we have been asking our most valuable team members to do for our most critical clients each and every day past. If I have piqued your interest, please request the complete session recording from your AICC education team or me. It might well trigger one novel useful thought for you and your team to utilize yet in 2021!
Analyze Huge Quantities of Data Using Predictive Modeling and Analytics When a manufacturing firm adds the right software technology, it can accurately and reliably find patterns hidden in the data that may indicate an impending failure or significant performance degradation. By providing employees the software methods to test and measure data, you, again, help get them invested in this new culture. A self-service culture of data visualization along with KPI dashboards will present the information necessary to manage the entire process.
Tom Weber is president of WeberSource LLC and is AICC’s folding carton and rigid box technical advisor. Contact Tom directly at asktom@aiccbox.org.
