The software that handles a mixed product range, logs every record for audit, and runs the robot you may already own.

For manufacturers running end-of-line functional testing on electronic components, the path to automation is rarely linear. Most engineering teams find themselves caught in a cycle of failed pilots. Commercial robot cells look flawless when handling a vendor’s uniform reference parts, but they halt production when introduced to real-world geometric variations, mixed product runs, or conditional test sequences that depend on a previous step's result.

When automation stalls, manufacturers fall back on manual testing. This transition drives up operational expenses and creates a direct regulatory liability. Under quality frameworks like IATF 16949, AS9100, or FDA 21 CFR Part 11, a manual logbook or a missing test record constitutes a documented audit finding.

€195K Saved with Zero Cloud Floor Dependency

N-iX partnered with an electrical equipment manufacturer to completely replace manual intervention at the end of their line. We developed a custom robotic manipulator tailored specifically to their fluctuating product geometries and compliance demands.

The system operates near-continuously through scheduled maintenance windows, completely automating €195K per year in manual testing costs. Hardware represents only 30% of an automation solution; the remaining 70% relies on software integration. This system connects directly to the client’s Manufacturing Execution System (MES), handles conditional test logic on the fly, and uses a local single-board computer to execute AI tasks without requiring an active internet connection on the floor.

The Webinar Agenda

  • The Structurally Broken QA Labor Market: Analyzing the 2026 manufacturing data and calculating the financial exposure of manual compliance logging.
  • Case Walkthrough (Electrical Equipment Manufacturer): A deep look into what the client tried first, why their initial automation attempts failed, and the blueprint of the working custom system.
  • The Optics and Hardware Stack: Why a single camera could not solve the positioning problem, requiring a dual-camera system paired with LiDAR sensors.
  • Market Benchmarks: An objective comparison of current industry deployments and where standard setups fall short on custom software integration and ERP connectivity.
  • The Operational Outcomes: How the system functions without human involvement, writing serial numbers, dates, and test results directly to AWS S3 to ensure tamper-proof audit trails.
  • N-iX Demo: A practical overview of our prototyping and design solutions for custom lines.

Who This Is For

This technical session will be especially relevant for Engineering, Manufacturing, QA, Operations, and IT leaders working in regulated production environments and looking to scale testing throughput without increasing headcount.

The Speakers

  • Dmytro Humennyi, Engineering Manager, N-iX — a hands-on engineer who designed the motion planning algorithms, specialized end-effector hardware, and computer vision systems for this project.
  • Taras Petriv, Engagement Director, N-iX — host of the session, bringing market context shaped by years of experience across industrial, robotics, and embedded domains.

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About N-iX

N-iX is a global technology partner for Pragmatic AI Software Engineering, the practice of measuring what AI tools actually deliver on your codebase with your engineers before scaling them. With over 2,400 engineers across Europe, the Americas, and APAC, we work with Fortune 500 companies and enterprise technology leaders across finance, manufacturing, supply chain, and retail. For over two decades, we have built and measured software that runs in production. Our services cover software engineering, AI consulting and implementation, cloud migration and managed services, data platform engineering, application modernization, and cybersecurity. We hold AWS Premier Tier Services Partner status and AWS AI Services Competency, and maintain an established, certified partner ecosystem with Microsoft, Google Cloud, Palantir, Snowflake, and SAP.

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