RBTXpert Debrief: Five Lab Automation Mistakes Worth Knowing Before You Start
Partner Resource: Epson Robots — The Top 5 Laboratory Automation Pitfalls and How to Avoid Them
Content Type: Technical Guide
Best For: Lab managers, life sciences engineers, and operations leaders planning or evaluating their first laboratory automation project
Why We Are Sharing This
Laboratory automation sits at the intersection of two demanding environments: the precision requirements of scientific processes and the compliance requirements of regulated industries. That combination makes lab automation projects uniquely unforgiving when something goes wrong. A mistake that costs a general manufacturing operation a few days of downtime can cost a life sciences lab months of recertification time and significant budget.
Epson’s pitfall guide draws on over 40 years of robotics development experience and addresses the mistakes labs make before any equipment is installed. Axis is sharing it because forewarned buyers ask better questions, scope projects more accurately, and avoid the delays that make lab automation projects earn a reputation for being harder than they need to be.
What the Content Actually Covers
Pitfall One: Locking In a System That Cannot Adapt
The first pitfall covers flexibility, and it appears first for good reason. A lab automation system specified too tightly for current conditions cannot adapt when protocols change, sample sizes shift, or the project scales from bench to production. The guide identifies two distinct flexibility gaps that trip up labs. Scale flexibility determines whether a system handles multiple sample sizes and applications without requiring new equipment. Software flexibility determines whether the robot can connect to other instruments, accept updated programming, and migrate to new development environments as the project evolves. Either gap, discovered after installation, generates costly workarounds or outright replacement.
Pitfall Two: Untraceable Process Steps
Traceability is a regulatory requirement in life sciences, not a documentation preference. The FDA requires a clear chain of custody from sample preparation through data analysis. Any step that lacks documentation creates a compliance gap that may require full recertification of the automation system. Beyond regulatory risk, poor traceability removes the ability to identify when, how, and by whom a process change was made. The guide recommends an audit log covering all code and parameter changes from the outset. In practice, labs that build traceability in during design spend far less time proving compliance than labs that retrofit it after deployment.
Pitfall Three: Underestimating Reliability Requirements
Reliability in a lab automation context means two things: equipment uptime and vendor longevity. The guide makes a point most buyers overlook entirely. A robot designed to run for 10 years requires a vendor partner who will still support it in year 10. A vendor that exits the market or discontinues a product line mid-lifecycle forces a complete restart with a new supplier, new certification, and new integration cost. Beyond vendor selection, the guide covers equipment monitoring as a proactive reliability tool. Systems that report condition data continuously allow maintenance before failure rather than after it.
Pitfall Four: Environments That Are Not Ready
Lab environments impose requirements that standard manufacturing environments do not. Temperature, humidity, lighting, and sterilization method all affect which robot is appropriate and how the workspace must be configured before installation begins. The guide specifically calls out VHP sterilization as an example. Vaporized hydrogen peroxide is widely used in pharmaceutical and medical device environments, and the FDA has specific guidelines for equipment used in VHP-exposed environments. A robot not rated for VHP exposure cannot operate in that environment regardless of its other capabilities. Beyond chemistry, the guide addresses operator readiness as part of environmental preparation. The right equipment in an environment where operators lack the training to use it safely produces the same outcome as the wrong equipment.
Pitfall Five: Skipping Comprehensive Testing
The final pitfall covers testing and debugging, and it surfaces two specific gaps that affect lab projects more than general automation. Labware standardization is the first. Different labware vendors produce vials, trays, and plates that vary in dimension. A gripper or handler specified for one labware format may fail on another. The guide recommends planning for dimensional variability from the start rather than specifying to a single labware format and discovering mismatches during validation. Security is the second gap. Lab automation systems handle sensitive research data and controlled processes. Unauthorized access to robot programming can compromise result integrity and trigger regulatory review. Access controls and encryption belong in the design specification, not in a post-deployment remediation plan.
The RBTXpert Take
The value of this guide sits in its sequencing. Each pitfall it covers is most expensive to address after the system is installed and certified. Flexibility gaps require hardware changes. Traceability gaps require recertification. Reliability assumptions require vendor renegotiation. Environmental mismatches require cell redesign. Testing gaps surface during validation when schedule pressure is highest.
Axis recommends this guide specifically for lab teams that are defining project scope rather than teams already in deployment. Reading it before scoping means the questions it raises get answered during design rather than during commissioning. That shift alone is worth the time the guide takes to read.
Access the full Epson laboratory automation pitfalls guide Here.