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Industry case study / AI-assisted engineering

thyssenkrupp

Engineering support on the factory floor.

Based on reporting from Siemens newsroom.

Industrial robot arm, battery-inspection conveyor and a schematic on a control screen

The brief

The challenge.

Complex automation projects require specialist skills, while repetitive programming and configuration tasks take time away from higher-value engineering work.

The work

The approach.

thyssenkrupp Automation Engineering integrated Siemens Industrial Copilot into engineering for a battery-inspection machine. The assistant helps create TIA Portal projects, develop control code and generate machine visualisations, including support for data management and sensor configuration.

Reported outcome

Engineering assistance

control code and machine visualisation within an existing engineering workflow

Siemens reported the battery-machine integration in November 2024 and announced plans for wider use from 2025. The announcement describes an implemented use case and a rollout plan, not a verified company-wide productivity percentage.

Source article (opens in a new tab)

Digitbite perspective

What this means for your project.

Put AI inside the tools specialists already use. Start with repeatable preparation tasks, retain engineering review and validate outputs against real operating requirements before expanding the scope.

Your next step

Have a similar challenge?

Share the workflow or customer experience you want to improve. We will discuss the right scope, the evidence to measure and a practical next step.

What happens next?

  1. Review your priorities

    We review the goal, current tools and the problem you want to solve.

  2. Clarify the right fit

    We follow up to discuss requirements, constraints and open questions.

  3. Agree the next step

    Scope, delivery stages and costs are agreed before implementation.

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