Preventive Lab Automation Mistakes to Keep an Eye On

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.

Before Reading: Find Out Which Rulebook to Follow

The guide refers to “the FDA” as if one set of rules covers every lab. It does not. What governs your automation cell depends on what the lab’s records are used for, so settle this before you read any vendor checklist, this one included.

If your lab…	Framework that typically applies	What is asks of the automation
Runs nonclinical studies that support FDA submissions	21 CFR Part 58 (Good Laboratory Practice)	Equipment used to generate, measure or assess data must be of appropriate design and capacity (§58.61), and inspected, maintained and calibrated under written procedures with records (§58.63)
Makes or tests drug products	21 CFR Parts 210 and 211 and FDA’s data integrity guidance	Data that is attributable, legible, contemporaneous, original and accurate (ALCOA)
Keeps any FDA-required record electronically	212 CFR Part 11	Validated systems, limited access, secure time-stamped audit trails (§11.10)
Does discovery research that produces no FDA-required records	Often no FDA rule applies directly to the cell	Your institution’s or sponsor’s quality requirements govern; confirm with your quality or regulatory lead

This article covers US FDA frameworks only. Clinical diagnostic labs and non-US regimes have their own rules.

What the Content Actually Covers

Pitfall One: Flexibility has a Regulatory Price

The guide splits flexibility into scale (one system, many sample sizes) and software (connecting to other instruments and migrating to new development environments). Both matter. What the guide leaves out is that in a regulated lab, every change to a qualified system goes through change control, and some changes trigger requalification.

Under USP <1058>, the framework most labs use for instrument qualification, the user rather than the supplier owns design qualification by writing the user requirements specification. Qualification then runs from that document through installation, operational and performance qualification. Relocating an instrument is treated like a new installation, which repeats the full IQ–OQ–PQ sequence. USP <1058> addresses analytical instruments, so treat it as a model for a multi-instrument robotic cell and confirm the scope with your quality group.

Ask the vendor: For each change made to the system, which can you make inside the existing qualification, and which trigger requalification?

Pitfall Two: Test the Audit Trail, not the Brochure

The guide recommends an audit log of code and parameter changes. For electronic records under Part 11, the requirement is more specific. Section 11.10(e) calls for secure, computer-generated, time-stamped audit trails that independently record the date and time of operator entries and actions that create, modify or delete records. Changes must not obscure previously recorded information, and the trail must be retained as long as the records and be available for FDA review. Sections 11.10(d) and (g) add limited system access and authority checks on who can alter a record.

The gap the guide does not raise is that a robot controller’s log is one piece of a chain. A typical cell also involves a scheduler, instruments and a data system, each recording its own events. Chain of custody is only as strong as the weakest log and your ability to line the logs up. FDA’s 2018 data integrity Q&A guidance also ties audit trail review to review of the underlying record, so a log nobody reviews does not help you.

Ask the vendor: who can edit or disable the log? Are time stamps system-generated? Can the robot’s log be exported and reconciled with your data system’s? During the demo, have them change a parameter live and show you the entry, including the prior value.

The guide warns that an untraceable step may mean re-certifying the system. The practical cost is requalification and lost time, plus open questions about the data already generated.

Pitfall Three: Underestimating Reliability Requirements

The guide’s strongest point is that a robot built to run for ten years needs a vendor that will still support it in year ten. No salesperson can answer “will you be around?” in a way you can rely on, so ask for commitments instead: a written notice period before a model or part is discontinued, a stated period of spare-parts and service availability after end of sale, and a software support window.

Also ask whether a like-for-like replacement part counts as a change under your own change control. Maintenance is a compliance matter as well as a cost. For GLP studies, equipment that generates, measures or assesses data must be inspected, maintained and calibrated under written procedures, with records of routine work and of non-routine repairs after a failure (§58.63). Your maintenance plan is therefore an auditable document.

The guide also suggests choosing equipment that monitors its own condition. Ask the vendor: What condition data does the controller expose, in what format, and can you can store and trend it? Data you cannot capture will not prevent a failure.

Pitfall Four: Plan the Environment Around Your Decontamination Cycle

The guide uses vaporized hydrogen peroxide (VHP) to show how regulation shapes the environment, and the example is a timely one. In January 2024, FDA announced that it considers VHP an established method (Category A) for sterilizing medical devices, which changes what device makers must submit in 510(k) sterility information. That puts VHP in the same category as moist heat, dry heat, ethylene oxide and radiation, and it reinforces the guide’s advice to settle the environment before choosing equipment.

What matters for your cell is whether the robot’s materials, seals, cabling and electronics tolerate your site’s decontamination cycle, repeated as often as your procedure requires. If your process sterilizes health care products with VHP, the process standard is ISO 22441:2022, which governs the sterilization process itself.

Ask the vendor: for a written compatibility statement covering your agent, your cycle and your number of cycles, and for which components were actually tested.

The guide’s point about operator readiness is also a compliance control. Part 11 §11.10(i) requires you to determine that people who develop, maintain or use electronic record systems have the education, training and experience for their tasks. Ask vendors for training material you can fold into your SOPs, and for how competence is assessed.

Pitfall Five: Skipping Comprehensive Testing

The guide recommends grippers that adjust programmatically to different labware, which is sound. The detail a buyer needs is where standards help and where they stop. The ANSI/SLAS microplate standards define footprint, height, bottom outside flange, well positions and well bottom elevation. The footprint standard sets 127.76 × 85.48 mm with a tolerance of ±0.5 mm overall, so two plates that both conform can differ by up to 1 mm in length.

Those standards address microplates. Vials, tubes, tip racks and reservoirs fall outside them, and those are the formats where programmable adjustment matters most.

Ask every vendor: put every labware item you plan to use into acceptance testing, including your supplier’s alternates, with plates drawn from more than one lot. Specifying to one vendor’s labware and discovering the mismatch during validation is the failure the guide describes, and this is the cheapest way to find it first.

On security, the guide’s advice to use access control and encryption is right. Part 11 gives it a basis: §11.10(d) limits system access to authorized individuals, and §11.10(g) requires authority checks so that only authorized people can alter a record or perform an operation. Ask whether the controller supports individual accounts with role-based permissions, and whether the validated program can be locked so that changes require authorization.

Two Pieces of Advice Worth Testing

“Dedicate a robot to one process.” The guide says this is usually more efficient and more accurate, but it offers no data. The case for it is real: a narrower validation scope and failures that stay contained. The case against is also real: more capital, bench space, interfaces and spares, and more systems to qualify and maintain. We found no published benchmark that settles this either way, so treat it as engineering judgement. A reasonable rule is to dedicate a robot when processes differ in validation status, contamination boundary or throughput peaks, and to share one when steps run in sequence on the same labware and the robot would otherwise sit idle. Test that rule against your own utilization figures.

“Choose the vendor at the forefront of advancement.” Newer releases bring new capability, and in a validated environment they also bring change control. Weigh innovation against a stable, documented release history and a clear upgrade path, and ask how much of a typical update is covered by the vendor’s own regression testing.

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.

RBTX Learn recommends this guide specifically for lab teams that are defining project scope rather than teams already in deployment. Read Epson’s guide for its structure. Its four-step planning checklist and its ten scoping questions are a useful starting point that we have not repeated here. 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.