Siemens Energy: AI and speech recognition in industrial quality inspection
How Siemens Energy used Dropslab’s AI and speech-recognition platform to cut inspection time by 50% and reduce errors by 80% on gas turbine assembly in Berlin.
This case study presents how Dropslab Technologies’ software platform was used for quality inspection at the Siemens Energy gas turbine assembly plant in Berlin. The platform combined artificial intelligence with speech recognition to streamline the process of measuring the distance between the ceramic heat shield plates of the assembled gas turbines.
By replacing the manual recording process with a hands-free digital workflow, Siemens Energy significantly improved the speed and accuracy of inspections — cutting process time in half and eliminating the need for an additional worker.
Results
- 80% — fewer errors
- 50% — process time reduced
- 40% — cost savings
What was achieved
- Hands-free measurement capture via voice, with each value validated against the work instruction in real time
- Automatic transfer of inspection results into the existing quality system — no double data entry
- Faster onboarding for new inspectors, with the AI guide highlighting the next step on the turbine
- Full audit trail for every measurement, including timestamp and operator