Five Engineering Strategies to Enhance Software-Defined Product Development Efficiency
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- AutomationWorld.com
Manufacturers are facing new challenges in engineering as software-defined products evolve and development cycles shorten. Engineers are reportedly spending about half their workday on documentation and information searches, leading to a global productivity loss of $39 billion annually, according to Accenture. To adapt, manufacturers can implement five key engineering strategies: enhancing traceability, integrating verification processes, utilizing AI for simulation, and optimizing workflows.
The importance of traceability has increased significantly as software and data define product features. BMW's Mobile Data Recorder, which tracks over 10,000 signals from 3,500 development vehicles, exemplifies this need. Additionally, Daiichi Elektronik's integration of PTC’s Codebeamer into its workflow has reduced implementation time from nearly a year to just two months, showcasing the benefits of early verification and compliance.
Siemens Energy's engineering digital thread has enabled rapid design iterations, resulting in the world's first 100% hydrogen gas turbine system. ABB Robotics' RobotStudio demonstrates how AI can enhance product development, achieving a 99% simulation-to-real correlation and significantly reducing deployment costs and time. No further timeline was disclosed at the time of publication.
Original report
5 Engineering Strategies To Accelerate Software-Defined Product Development
AutomationWorld.com · Sam PaulThis briefing is an independently written summary based on publicly available reporting and is provided for industry information and news discovery. The original report and source publication are credited and linked where applicable. RobotToday does not claim ownership of third-party source material.
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