Predicting when tools need calibrating improves quality—and saves rework and money By Eric Fetters-Walp and photos by Bob Ferguson Boeing jetliners are packed with high technology and cuttingedge design, but it still takes torque wrenches, screw guns and other relatively low-tech tools to put them together—along with mechanics who use the tools. And the quality of Boeing products depends, in part, on making sure these tools are properly maintained. On the 787 program, for example, 57 different tools that are especially critical to the final assembly of the Dreamliner are calibrated every three to four days to minimize tool-related risks. While inspectors and extensive Quality Assurance processes catch work performed with tools out of calibration, preventing it from happening saves time and money. To that end, teams in Commercial Airplanes and Engineering, Operations & Technology have developed a predictive analytics program to keep tools better calibrated and working well, which prevents costly rework that can slow production. In less than a year, the program has identified dozens of “significantly out of tolerance” (commonly referred to as SOOT) tools in Boeing’s factories and helped predict when others need to be calibrated. “By applying the analytics model, we were able to ‘pull ahead’ a number of our out-of-tolerance tools that would have taken months to find,” said Martin Ohman, SOOT mitigation leader for Fabrication. “This saved the programs potentially millions of dollars in rework tools if the tools had been used to their full calibration cycle.” The program analyzes rafts of data on the tools—how they are used and when they are prone to slip out of calibration or just wear out. In simpler terms, it builds on a concept that has proved successful in Major League Baseball. The book and film Moneyball tell the story of how the Oakland Athletics’ general manager used empirical analysis of player statistics, especially statistics and data patterns that previously were undervalued by other teams, to predict a player’s future performance. The Athletics have built winning teams as a result. Boeing continues to expand its use of predictive and other advanced analytics into new areas where they might be useful, explained Paul Ortman, Manufacturing Operations Advanced Analytics manager in Commercial Airplanes. Boeing has reams of data available, and within Commercial Airplanes, it is his team’s job to figure out how to use it productively. His team worked with an Information Technology team in Huntington Beach, Calif., to create and apply specialized analytic formulas. “They previously had no way to proactively prevent SOOTs before they PHOTOS: (Far left) Commercial Airplanes’ Paul Ortman, from left, Tracie Wingrove, Alan Davis and Bobby Lohnes review tools tagged for repair or for being out of tolerance. (Above) Davis displays a nut runner. Frontiers May 2014 17
Frontiers May 2014 Issue
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