As with any digital transformation process, the devil is in the details, and there are many potential pitfalls that can derail projects.
The bane of modern engineering is complexity. One promise of artificial intelligence and machine learning is helping engineers to use complex tools and harness vast data sets effectively.
Technology came to the aid of Detroit Tigers management when they hoped to recapture some of the magic of the 1968 Detroit Tigers’ World Series-winning season. The 50-year anniversary celebration, held September 7-9, 2018, included on-field festivities in which the 16 surviving members of the 1968 team were presented with replicas of the World Series’ trophy.
Until just a few years ago, if a vehicle maker wanted to test the process for making a newly designed composite part at full scale, the company’s R&D engineers would call one of its Tier Ones and ask to schedule a trial run on the composites fabricator’s machines during off hours.
Fostering human-centered innovation by developing powerful, easy-to-use tools is at the heart of the new products, enhancements and services showcased during the Siemens Digital Industries Software 2020 Media & Analyst Conference, a two-day virtual event hosted by the Plano, Texas-based company on June 16 and 17.
When designers at Siemens started using virtual reality (VR) to quickly evaluate early-stage ideas, the usually slow and costly design-and-iteration process went from days and hours to minutes.
The institutes that make up Manufacturing USA need to move at the speed of business, considering that the endeavor represents the U.S. government’s biggest investment in the digitization of manufacturing to date.
Manufacturers who have deployed the digital or smart factory have put down their pencils, found new uses for their clipboards and closed their spreadsheet programs in favor of using real-time data gleaned from condition monitoring of their machinery.
Metrology-grade laser scanners are expanding their range of applications. New users are finding the main attractions of laser scanners—speed and ease of use. What prevented more widespread use in the past were laser scanners’ perceived tradeoffs. Using one usually meant sacrificing accuracy or working with noisy data.
Information technology and operations technology are unlikely candidates for a successful marriage. But to ensure that manufacturers thrive in the digital age, OT and IT must find ways to work together—or to at least, as on Tinder, swipe right to indicate interest.
