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.
Swiss-style machine tools can be a good choice for making complex parts. On the downside, however, Swiss machining itself has a reputation of being complex—and, therefore, more difficult to master than standard machining.
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.
Abrasive machining is a tried-and-true technology for meeting exacting tolerances and producing superior finishes. Manufacturers continue to develop new capabilities.
An Israeli company has developed new artificial intelligence technology that promises to dramatically change how original equipment manufacturers and their suppliers conduct quality control inspections.
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.