How a Computerized Maintenance Management System Can Benefit Your Lab
CMMS platforms handle all the data associated with asset maintenance, saving lab managers time and effort
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Coordinating maintenance is an essential part of asset management, but keeping track of the operational statuses of the lab’s equipment, associated service providers, calibration schedules, and other factors is a challenge that many labs face. Computerized maintenance management systems (CMMS) programs were designed to clear those hurdles. Greg Lundell, director of asset management at Genesis AEC, shares the benefits lab managers could reap from implementing CMMS programs in their labs. Note: These responses have been edited for clarity and style.
Q: What problems does a CMMS address?
A: CMMS software is meant to manage large quantities of data and provide a compliance solution that ensures preventative maintenance, calibration, spare parts, and other equipment-specific compliance needs are tracked and executed on a pre-determined schedule. The issue with managing assets through other methods, such as the ever-present Excel workbook, is human error. A properly implemented CMMS automates the identification of at-risk assets and ensures that activities required to keep those assets in compliance are flagged and executed.
Q: What are the most important features of a CMMS?
A: Every company’s needs for a CMMS are different, so flexibility is important. Most systems on the market are inflexible, or fully customizable but with a steep price tag. All CMMS solutions offer a similar set of key features. The real question as to key features of a CMMS comes from the user; what features are critical to your operation?
Q: What are the symptoms that indicate a lab has outgrown their current maintenance management solution and needs a dedicated CMMS?
A: Equipment downtime, out-of-calibration events, and data reliability/reproducibility issues are all symptoms that the current method of asset management is inefficient or flat-out not working. Once a lab manager starts to identify these issues as the cause of slowed science or inefficient use of personnel time, it becomes clear that a more sophisticated CMMS system is required. Waiting to see the symptoms to correct the problem is not the best strategy to ensure deadlines and budgets are met for the department.
Q: How can a CMMS be used to make data-driven decisions regarding lab assets? What kind of metrics should a CMMS track and make available?
A: One of the most obvious pieces of data that is mined from a CMMS is reliability. Indeed, there are dedicated individuals who are able to review reliability and make recommendations on equipment upgrades and replacements. Often times the reliability data comes in the form of increased maintenance calls, age of the system or unit, and overall use profile including uptime. In reality, many reliability standards can be defined based on equipment age and capture the majority of reliability issues; a -80°C freezer, for example, typically has a usable life of 12-15 years, so replacement efforts can be timed and funded without complex data mining of the CMMS. One piece missing from many CMMS platforms is actual use data: the number of samples or daily running time of a piece of equipment. That typically lives at the scientist/lab manager level and is oftentimes nebulous. Spot checks can sometimes capture actual use data, but they require an educated staff who understand the equipment and can be in-lab on random days and times to try to extrapolate overall use from a limited data set.
The real question as to key features of a CMMS comes from the user; what features are critical to your operation?
Q: What options exist to integrate a CMMS with the broader lab informatics platform?
A: The most novel idea I have seen for CMMS implementation does not involve integration with other lab informatics platforms, but rather integrates the concepts of a streamlined lab function across multiple departments. In many current research lab setups, each individual department tends to operate somewhat siloed. They buy their own equipment with a budget they individually manage, and their goals may or may not be aligned with other departments, as they all serve different purposes. The issue with this approach is that without cross-department coordination there is a tendency to buy equipment and therefore need lab space for the same functionality, while the equipment sits idle for more than 80 percent of the time. Utilizing a CMMS to manage all equipment in a facility, and not just a department managing equipment on an excel sheet or other method, allows for upper management to review total capability, and therefore equipment utilization. The CMMS can act as the parent asset list to review operational goals, coordinate equipment reduction efforts, and even allow for scientists to “book” time on equipment. Combined with discussions on lab planning, future-proofing, and departmental facility needs, this can lead to great cost reductions and improvements in site efficiency.
Q: Artificial intelligence and machine learning are advancing rapidly. How do you think these technologies will be leveraged in CMMS platforms, if at all?
A: I see a future where service provider scheduling, booking of time on equipment by scientists, and shared reliability data will be the norm. Currently there is a human-level management of these activities; the CMMS alerts the facility manager or other maintenance personnel that an activity needs to be completed on a piece of equipment. That person then needs to schedule resources, cut a PO [purchase order], and otherwise ensure the activity is executed. Imagine if that all happened autonomously. With properly aligned systems and an AI element add-on, the human review of data will become automated and should lead to CMMS management personnel reduction, increased uptime, and decreased costs.
Q: Can you share any insights on effectively training and onboarding new users on a CMMS?
A: Training in a sandbox, or a version of the software outside of the active system, is the go-to for training. Though appropriate for initial familiarity, the true experience of the system is gained through the execution of tasks. I find with any software system, the best way to truly learn the functionality is having a senior user train a new user through the execution of certain tasks. The new user should be in control, and executing the steps, while the more senior staff can provide guidance. This translates well into a classroom setting as well, as long as each individual is driving their own activities and not just watching a presentation or trainer execute the steps.
Q: Do you have any advice for others struggling to manage asset maintenance?
A: It’s understandable that asset management is a struggle for many companies from pharmaceutical giants to biotech startups. Internal employees are often tasked with asset management on top of their existing responsibilities, and even dedicated employees will struggle as assets continue to be added. The continued growth of the industry has created an asset management problem with an unmanageable level of work that leads to missed data entry, lack of executable onboarding processes, and creates the “drowning” feeling that is all too common in today’s scientific workplace. Hiring an outside resource to evaluate current state, execute updates and changes, and even manage the system long term often pays for itself and keeps scientists and manufacturing personnel up and running without worrying about the status of their scientific assets.
As director of asset management for Genesis AEC, Greg Lundell offers more than 20 years of professional experience in laboratory operations management, production facility design and operation, quality and regulatory management, research and development, and product manufacture in various life science fields. His extensive laboratory equipment knowledge is applicable across a variety of industries including diagnostic, pharmaceutical, industrial, biological product development, and manufacturing.