Lab Automation and Robotics Control

A specialized control interface for robotic workstations, specifically focused on automating PCR (Polymerase Chain Reaction) setup. The client was Qiagen, a global provider of biotechnology solutions. The platform was designed for highly qualified laboratory personnel. The goal was to empower these scientists to execute complex automation workflows without needing advanced programming skills.

PCR preparation requires extreme precision, moving microscopic amounts of DNA and reagents between hundreds of tubes. The previous manual scripting process was slow and error-prone. My goal was to translate these complex biological protocols into a collision-free, drag-and-drop interface that scientists could trust.

Designing for a lab isn't like designing a website. I couldn't start with wireframes. First, I had to understand the biochemistry behind the machine and the hardware limitations of the robot. My strategy was to build the "Core Experience" first, ensuring that a basic user could run a PCR test safely, and only then expand to advanced features like the Protocol Editor or Calibration.

Thinking like a scientist: Before designing, I had to learn the basics of laboratory work. I underwent biochemical training to understand what "PCR" actually is and why precision matters. I conducted interviews with lab technicians to map their daily routines. The goal was to understand not just how the machine works, but what the users are actually trying to achieve.

Selecting the right hardware: Unexpectedly, the project required selecting the physical touch screen for the machine. I had to quickly research and choose a display that met strict technical parameters—resolution, responsiveness, and durability for a lab environment. This ensured that the UI I was about to design would be perfectly legible and responsive on the final device.

From chemistry to flowcharts: I took the specific biochemical processes identified in Phase 1 and mapped them into logical steps. Working with experts, I prioritized which processes were critical for the launch. We dissected every action, from heating to pipetting, to understand how to visualize them on a screen without overwhelming the user.

Design and Validation weren't separate stages - they were a continuous cycle. Given the high stakes of controlling physical machinery, I couldn't wait until the end to test the designs. Instead, I implemented a tight feedback loop focusing strictly on the Core Experience. I would design a critical part of the flow, validate it immediately with scientists to catch logic errors, and then refine it. This ensured the foundation was solid before we added any additional features.

Mapping the journey from setup to success: I focused exclusively on the most frequent user scenario: setting up and running a PCR test. I designed the end-to-end flow, starting from Protocol Selection, through the physical Deck Setup (guiding users where to place tubes), to the final execution. I used a system of clear, color-coded components to create a "digital map" that mirrored the physical machine, ensuring users always knew the system's status

Testing for safety, not just preference: Immediate validation was key. Once a part of the "Run" flow was designed, we tested it with real lab technicians. We weren't just asking, "Do you like this color?" We verified safety and logic. We checked if the on-screen instructions correctly guided their physical actions (e.g., did they instinctively put the reagent in the correct slot?). This allowed us to spot potential hardware collisions and user errors early in the process.

Beyond the "Start" button. Once the Core Experience was secured, I expanded the system to support "Power Users" and maintenance staff. Since the UI language and component library were already established in the previous phase, building these modules was faster and more consistent.

The Advanced Modules:

Workflow Editor: A drag-and-drop tool allowing senior scientists to build and save their own biochemical templates.

Calibration & Maintenance: Precise tools for engineers to fine-tune the robot's coordinates.

Reporting: Automated post-run reports summarizing the experiment results.

Support beyond the design file: Since the hardware was already established, the focus was purely on implementing the new interface. After delivering the tested designs, I worked closely with the developers and the lead engineer.

Clarifying the Logic: The implementation team had numerous technical inquiries regarding the documentation and complex edge cases. My role was to be available to answer these questions immediately, ensuring that the logic was fully understood and correctly applied to the machine without delays.