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Optimizing Laboratory Operations

Asset Utilization Monitoring Captures the Data Necessary to Improve Instrument Uptime and Lab Productivity.

by Keith Martinko
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To optimize lab operations, several questions must first be answered. How can you adjust service levels based on usage? How can you trigger preventive actions prior to failure? How effective are you at utilizing your assets? These questions can be easily answered by implementing an asset utilization monitoring solution. Such a solution provides laboratories with knowledge of how instruments are used throughout the laboratory, and can significantly help labs optimize operations, drive cost savings, and improve productivity. It also empowers lab managers to make smart operational decisions based on real instrument and equipment usage information.

Asset utilization monitoring delivers significant benefits, including the ability to eliminate unnecessary capital expenditures and reduce laboratory downtime. It helps laboratories reduce downtime and service costs through proactively adjusting the delivery of planned services (e.g., preventive maintenance, operational qualification), allowing laboratories to match actual instrument usage to optimize service levels. In addition, the data can be leveraged to balance workloads and reduce downtime risk through redeploying instruments and equipment from areas of low utilization to high utilization. Asset utilization data enables laboratories to optimize return on current investments and eliminate unnecessary future capital expenditures. Labs can make better strategic decisions by factoring current instrument utilization into capital purchase and disposition decisions.

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Implementing an asset utilization monitoring solution in a laboratory consisting of instruments and equipment purchased from multiple manufacturers, comprising different scientific techniques, and controlled by different instrument software, can be extremely challenging. At a minimum, data such as sample run times and instrument reset times (time for the instrument to return to a starting point to run the next sample) must be captured across each instrument to give a true reflection of actual instrument usage. Data should be collected at least once per day, to ensure that utilization data is not skewed by explainable events that are missed (e.g., repairs, sample delays, power failure, researcher time off).

Laboratories have attempted to deploy both automated hardware and software solutions to meet these challenges, with varying degrees of success. Hardware solutions typically consist of a sensor (e.g., voltage, current) to capture a physical event on the instrument and log the time of the event and the time between events. These types of solutions can be difficult and expensive to implement and support, sometimes requiring physical modifications to the instrument itself. A more effective approach is to use a software solution to either monitor for creation of instrument data files or read instrument-generated logs and/or results files to capture sample acquisition times and instrument reset times. No matter what approach is chosen, it is important that it is easily scalable regardless of the manufacturer, technique, or instrument control software, and does not interfere with instrument functionality or research productivity. This allows the laboratory to keep its existing technology and software infrastructure in place, protecting the lab’s investment in instrumentation and operator training.

Automated collection of sample run and reset times is an important first step in generating useful utilization information for the laboratory. Additional process factors must also be considered to truly transform this data into valuable information and knowledge to drive decision making. For example, an accurate utilization calculation should take into effect the intended hours of operation for the instrument within the lab (e.g., 10 hours per day, 5 days a week versus 24/7) and adjust for periods of inactivity due to preventive maintenance and repairs that were performed during the monitoring period. Applying these types of corrections to the raw utilization data provides a more accurate account of instrument usage within the lab.

Having accurate utilization information does not provide enough knowledge on its own to drive actions that increase instrument uptime and lab productivity. In order to adjust preventive maintenance (PM) schedules based on instrument usage, for example, it is necessary to completely understand the number of hours of operation that are acceptable before performing a PM. Typically, this information can be obtained from the manufacturer or your existing service provider, and should be adjusted (either higher or lower) depending on the specific application and sample matrix used on the instrument. Over time, the combination of actual utilization information, instrument performance, and service history can be used to fine-tune this information for each specific instrument in the lab. Similarly, quantitative limits that define low utilization (e.g., less than 25 percent) and high utilization (e.g., greater than 70 percent) must be established for each instrument and/or lab area. Using these limits, a lab can easily identify areas of high utilization and potentially redeploy existing, or purchase new, instruments to balance the workload and reduce downtime risk. An expert multi-vendor service provider or consultant can often provide significant value to this process by standardizing reporting of asset utilization data and offering productivity recommendations based on the data.

Implementing a comprehensive asset utilization monitoring solution within a laboratory consisting of instruments from multiple manufacturers can be challenging, but recent advances in technology and service methodology now make it possible to implement a streamlined solution, and much easier for labs to take advantage of this valuable data. Development of a road map and an execution and support strategy can help ensure a successful rollout of the solution. Careful consideration to the method and frequency of utilization data capture, inclusion of process factors to create actionable utilization information, and application of this information against PM and utilization level limits can significantly improve instrument uptime and lab productivity. Knowledge is power.

Keith Martinko is developer of Unity™ SmartCapture asset utilization monitoring and global product development manager for Unity Lab Services, Thermo Fisher Scientific.He can be reached at or by phone at 608-273-6819.