Every day, in countless laboratories, scientists rely on automation to manage samples, run assays, and capture data from their experiments. So naturally, when their systems stop working, they need to solve the problem quickly and get back to work. In this post, we look at some problems that can come up with automated setups and offer some suggestions for how to troubleshoot them.
Why lab automation fails
Automation can fail for several reasons. Some common issues include:
- Damaged equipment: Broken or damaged parts can stop systems from functioning properly. For example, mobile robots may not be able to navigate their surroundings if their sensors are faulty.
- Misaligned equipment: The parts may work properly independently, but are unable to work together for some reason.
- Combining legacy and new automation infrastructure: When systems are incompatible and unable to communicate, the equipment may not work as it should.
- No power: An unplugged cord or damaged wires in the plug can prevent power from reaching the system.
- Human error: Scientists may not be properly trained on the equipment and could be using it incorrectly.
Why troubleshooting lab automation errors can be difficult
Figuring out exactly why automation fails to perform as expected can be challenging. Labs can have multiple workstations, mobile robots, and scientists running experiments and transporting samples at the same time. With so many moving parts, identifying and solving problems takes time. In some cases, there may be multiple errors triggering the system’s breakdown.
Another challenge is that automation problems may be due to simple mistakes that have nothing to do with the equipment. Mislabeling samples, inputting the wrong sample measurements, entering the wrong command into their automation software, and contaminating samples while moving them are all sources of human error that have nothing to do with the hardware and software.
How to effectively troubleshoot automation problems
Being proactive and having a detailed error-handling strategy in place minimizes downtime when mistakes happen. Outlined below are some components that can be part of a comprehensive automation troubleshooting strategy.
- Identify and define the problem: The first step is to recognize that something is wrong. Then figure out if the problem is due to human error or equipment failure, as this will determine the direction of the troubleshooting strategy.
- Ask questions and gather data: Collect as much information as possible about the problem, when it started, and the circumstances around it. Review activity logs and metadata about experiments and samples. If possible, run the workflow again to see if the issue recurs and collect more data.
- List possible reasons for the problem: Come up with a list of likely and unlikely explanations for the problem. Use a process of elimination to run down the options and check them off the list.
- Run diagnostics: Conduct a complete review of all the systems used in the workflow and every step of the experiment, including the consumables and reagents used, where samples were stored prior to use and how they were handled, as well as any points of human interaction.
- Ask other scientists for help: Depending on the problem, colleagues in online forums can be great resources as some of them may have worked through similar issues.
- Evaluate the results: Consider the outcomes of the troubleshooting process. Ideally, the system will be functioning normally again. It’s helpful to keep a list of the suggested solutions so that if one approach does not work, the next option can be tested.
- Ask the experts: When all else fails, check in with the automation provider and ask for help. They may already be aware of the problem and have a solution ready to go. Vendors can also run a more thorough systems check and make any needed upgrades. Most quality vendors have dedicated service teams ready to assist and get the system up and running quickly.
What if I can’t fix the problem?
All systems will fail at some point. Having a troubleshooting strategy in place reduces confusion,provides concrete guidance for dealing with equipment failure, and helps improve the overall usability of your lab equipment for the long haul. If all attempts at a resolution fail, it may be time for a more complete system overhaul where automation experts physically take apart the equipment to get at the root cause of the problem. It is important to let experts such as automation engineers, who know these systems inside and out, handle this level of investigation. They’ll be able to diagnose the issue quickly and make the necessary repairs to get the system back online — without creating new problems along the way.