We obtained a report for the last academic year. A shocking revelation was that the capacity utilization* of lab equipment, laboratories, instruments and machines is only 37%. Everyone seems to be happy with this result, most of the comments are that science can't be lucrative and researchers cannot be forced to work with already existing equipment. If they want to expand research and buy a new machine (even if we have 3 already) that should be allowed. "Your grant your rules".

Is there any organization method to overcome this "abeyance" of overall facilities at faculty?

*Utilization was calculated by time and resources being used, versus number of publications and number of employees (students, professors, researchers).

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    I don't understand this question at all. Your complaint is that some equipment is not utilized as much as you think it should be, and nobody but you thinks this is a problem? Why do you think it's a problem? – ff524 Dec 30 '15 at 7:37
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    If you have data showing that the costs of keeping the equipment in-house (at its current level of utilization) are higher than sending samples out, I assume you must have showed that data to those who find the status quo acceptable. What was their response? You should edit all this information (including the last sentence of your comment) into your question, as it's likely to be highly relevant to any answer you might get. – ff524 Dec 30 '15 at 8:15
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    Your question is fine. I'm also interested in strategies to increase lab efficiency. – Cape Code Dec 30 '15 at 9:23
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    I agree with @ff524 that this question would be much easier and better to answer if you gave more evidence about why you think 37% "utilization" is too low. 37% is just a number - it can be great, terrible, or just usual utilization. Equipment usage depends on many things including (a) whether the machines you have are sufficient for the planned research, (b) how allocation policies etc. currently work, (c) whether the equipment is general-purpose or extremely specific, (d) to what extend your institution is even allowed to use hardware bought with a specific grant in other contexts, etc. – xLeitix Dec 30 '15 at 10:19
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    It's extremely hard to understand what you're saying. There seems to be some calculation where if the equipment is used constantly around-the-clock, but no papers are being published, then this would count as 0% "utilization"? – Daniel R. Collins Jan 10 '16 at 7:39

The U.S. Department of Energy has a system of user facilities. Access to these facilities requires an application and scheduling. Access is typically free. At least some of these facilities reach 100% utilization. Each tool in each facility may have its own rules. These are often listed on websites. Facilities are incentivized to reach their utilization targets with funding.

Example: http://www.anl.gov/cnm/user-information/user-access-program


Unfortunately, the 37% capacity utilization number is essentially meaningless on its own, because it does not directly relate to the actual metric that one might wish to optimize.

When attempting to improve efficiency, it's important to have a precise understanding of what the ultimate metric is that it being maximized. In a university research setting, the metric being maximized is not utilization of equipment, but rather something regarding research being accomplished and effective use of grant money. To maximize such metrics, it's actually important that some equipment be idle some fraction of the time.

The problem is, research projects typically have highly uneven and unpredictable resource utilization profiles. For example, my collaborators will often have 1-2 day bursts of flow cytometer use, in which they use a $200K machine for an hour or so every few hours, followed by a weeks-long gap while they prepare the next experiment. It's very difficult to interleave usage during such bursts without distorting somebody's experimental plans, and an experiment may need to be started several days before the flow cytometer is first run. Counterintuitively, this means that overall experimental efficiency demands that flow cytometers stand idle most of the time.

An even more extreme example is common tools like pipettes or screwdrivers: if anyone ever needs to spend more than a few seconds looking for such a tool, then operations are clearly inefficient. As a professor of mine once told me: "If you can't just reach out and pick up the screwdriver you need, you don't have enough screwdrivers." This means that such common tools must have exceedingly low capacity utilization in order to used efficiently as part of the larger workflow.

That same professor, on the other hand, now runs an operation in which an automated high-throughput mass spectrometer is carefully scheduled to run 24 hours a day, since it is the key high-value bottleneck of an entire pipeline. In that case, efficiency means 100% utilization (but also that when they have grown enough, they will probably add another mass spectrometer).

Bottom line: if you want to improve efficiency, knowing the utilization of equipment is a useful starting point, but it can only be properly interpreted in terms of the larger workflow in which that equipment is used.

  • but what if your lab start to aloud others departments and faculties(unies) to use your flow cytometer? That would increase utilisation ? – SSimon Dec 30 '15 at 15:07
  • research plus educational setting – SSimon Dec 30 '15 at 15:09
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    I think it is important to realize that the costs of not being able to work well is often much more expensive than the instruments. Plus, many instruments wear out rather by abuse and working hours than by standing around unused. – cbeleites supports Monica Jan 14 '16 at 22:48
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    @SSimon: Example 1: One of our students just redid 4 days of experiments because he hadn't realized that one of the shared pipettes he used was not working correctly. A PhD student here in Germany has marginal costs of around 100 - 150 EUR per working day. 4 days equal 2 - 3 new pipettes. Agreed, the student should have checked the pipette before using it. But for shared pipettes, the respective student would need to check it pretty much before every experiment, for your "own" pipettes you know when you need to service them (regularly or because something bad happened). Commercial pipette ... – cbeleites supports Monica Jan 17 '16 at 13:41
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    ... check comes at around 50 EUR. The student can do it, but needs to go another lab for the balance. I don't know exactly, but I'd guess that you don't do it properly below 2 - 3 h for the set of pipettes (all preparations included). Say, over the year 40 h, i.e. one work week can be saved by having "own" set of pipettes for a student who works quantitatively. That is roughly a set of 3 pipettes per year. And this does not include figure in the annoyance it causes if you always need to spend major amounts of time before you can start the "real" experiment. – cbeleites supports Monica Jan 17 '16 at 13:51

Take my advice - invest in human hamster wheels to generate lab electricity, rather than buying it off the grid. So long as you make sure the wheels aren't too efficient, it should be possible to get most if not all of your researchers utilizing the equipment, 24hrs a day, 7 days a week. You may see a slight dip in the utilization of other lab equipment, but the high usage in both number and duration of use of hamster wheels should pull up the whole departmental average.

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I am, of course, being facetious. A lab is not a factory that turns some arbitrary raw material into widgets en masse. Time and motion principles of labour management simply do not apply. If anything you want scientists using equipment less for the same amount of science published. In all seriousness, the only real machine whos utilization is worth tracking would be the coffee machine.

Lab efficiency however is a different ball game. Labs can be more or less efficient, however thats a different question for a different post :)

  • why you think lab is not a factory? It is factory of research articles. How many papers are published and in what journal are published tells directly about lab performance and without good utilisation you cannot have optimal number of publications – SSimon Jan 14 '16 at 11:40
  • Unfortunately we have a difference of opinion about this, so i'm not going to be much help going forward. Perhaps one thing we could agree on is that old, unused hardware isn't doing anyone any favours. One idea would be to donate it to Seeding Labs: seedinglabs.org Dumping your underutilized stock will improve ratings, plus you can pop some blurb into the website about how U. of Z is doing its bit. Most importantly, I think you are one of the few people who would be indifferent enough to the scientist's pro-hoarding protests that you might actually be able to get the job done :) – Wetlab Walter Jan 14 '16 at 12:04
  • I understand you @J.J unfortunately, I think your vision of research and institutions in modern world, are not in touch with reality and current historical modern of developing research. " Researchers are not talented, rather gifted for organisation and planning" – SSimon Jan 14 '16 at 13:22

To complement earlier responses, two types of cost come into play:

  1. context-switching (when you have to go to a different department to use the tool) or re-calibrate whatever tool you use every time you take it from the joint pool;

  2. unpredictability due to use fluctuation. It is known from queuing theory that with queue use approaching full (theoretical) capacity the fluctuations grow significantly. Sometimes not being able to estimate whether a tool will be free to use can hamper your productivity more than the cost of the tool. There is a reason why a rigid scheduling regime is implemented only for really expensive devices.

So, 37% may represent a perfectly good balance for these costs and as measure of utilisation it is not sufficiently informative in isolation.

  • yes, @Captain waist majority of stuff at my inst share your point of view. – SSimon Jan 17 '16 at 4:40

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