Asset Monitoring in the Life Sciences: Do Labs Need To Keep a Closer Eye on Their Instruments?
Industry Insight Jul 01, 2020 | by Ruairi J Mackenzie, Science Writer for Technology Networks
In the day-to-day of research science, the acquisition of a new piece of equipment is a momentous occasion that will elicit different reactions from each member of the team. Whilst researchers grin as their heads buzz with novel experiments, technicians groan at the prospect of yet another instrument monitoring protocol and lab managers despair at the thought of negotiating new maintenance contracts. With this in mind, an equally momentous occasion could be the implementation of an asset monitoring software, which will help the lab save on money, time and help more research get done using that new purchase. We spoke to Agilent’s Marc Boreham to find out more.
Ruairi Mackenzie (RM): What kind of efficiencies can be achieved by monitoring instruments?
Marc Boreham (MB): Measuring asset (instrument) utilization is critical for an effective asset management program. These programs are used to help optimize capital expense spending, increase workflow throughput, balance workflows, pinpoint workflow bottlenecks and quite a bit more.
Agilent’s early work with its customers shows only 3% of lab managers today use utilization data for decision making and that instruments on average are utilized only 35% of the time. This translates into potential for at least 15% cost savings in every lab
Monitoring laboratory instruments in this way makes capital expense planning decisions much more fact based, showing how much each instrument is utilized and balancing that information against the rest of the fleet to be able to understand where you might have too many or too few of a particular instrument. In fact, some organizations are now required to present utilization data to accompany a justification for a new instrument purchase request. On the workflow question asset management programs can identify bottlenecks in the process and help laboratory managers to understand how sharing instruments or redeploying like-instruments to different parts of the lab or site, can improve the throughput of the instrument as well as overall workflows.
With these capital expense decisions and workflow improvements, you can look at cost savings associated with a reduction in the fleet i.e., better preventive maintenance planning; optimizing service contract coverage, consumables, power and gases and daily maintenance; and of course, with larger companies, reduction in required lab space and the associated facility costs, as well as the improvements in the throughput, better planning of optimal maintenance times, improved instrument sharing schedules and many other improvements.
RM: What types of information can a monitoring system provide users with? What would a report might look like if the asset monitoring software built into Agilent's CrossLab capability was asked to assess the performance of, for example, an NMR spectroscope?
MB: Let’s say we have a lab with five NMRs and have collected several months of utilization data. In reviewing the dashboards, we note on one of our dashboards all instruments are in use during the period, and the NMR fleet may have redundancy as 60% of NMRs are in use on an average day, and 80% on the busiest day. So, of the five, only four are peak requirements. If methods are transferable between the instruments, we would recommend reviewing service entitlements for OpEx reductions, that is, remove the extra capacity, or the one NMR unit, which in turn removes associated maintenance, service contracts, lab real estate, consumables, power and probably a few more things. We also notice on the workload distribution dashboard heatmap it indicates that Thursdays have the least number of instruments in use, followed by Mondays; this tells us any scheduled maintenance should be done on these preferred days to reduce interruption to operations. The impact of carrying out this level of asset monitoring once applied across multiple labs and instrument fleets, is really significant and leads to great gains.
RM: What is involved in the process of “hooking up” individual instruments to a monitoring software platform?
MB: Once we understand the specific goals for lab improvement, we analyse the instrument inventory to better understand the IoT sensor best suited to the task. A conversation is then typical with the customer’s IT organization to explain the requirements of the Asset Monitoring service and the data privacy and security guidelines that must be followed. Depending on the selected sensor technology deployed, an expert from the field service team may be required to install some light hardware, and then a remote team takes over to configure the system to get utilization data moving through the solution and into the customer viewable dashboards.
RM: Is there any limit to the number of instruments that can be monitored?
MB: For Agilent’s solution, there is no limit to the number of instruments that can be monitored. The sensors that are used can connect to individual instruments as well as those residing on networks. Great gains in understanding instrument usage can be realized especially by reading the operational data from large deployments of Chromatography Data System networked instruments or a content management system such as our OpenLab ECM. Monitoring equipment can provide rich metadata, and other sensor capabilities also allows us to measure everything else in the lab.
RM: Are monitoring software platforms such as that used by Agilent CrossLab vendor agnostic?
MB: I believe that what differentiates our solution is our selection of sensor technology which can monitor almost any instrument across any lab including chromatography, mass spectrometry, spectroscopy, liquid handlers, plate readers, flow cytometry, centrifuges, NMR, sequencers, PCRs and nearly anything else you can name. The multiple IoT sensors that are deployed and the supporting AI engine behind the solution allows the Asset Monitoring service to connect to every instrument in the lab and collect utilization data. Although the data collected may be represented in different ways depending on the instrument source, Agilent’s solution normalizes this usage data across the fleet and creates dashboards providing a consistent view that provides insights for the usage across the lab.
Marc Boreham was speaking with Ruairi J Mackenzie, Science Writer for Technology Networks