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Monitoring laser filtration with the DesignSpark ESDK

Background

Hello everyone! I'm Zak, one of the coordinators at Blueprint, the Palmerston North City Library Makerspace. As part of the library, our goal is to provide access to tools, equipment and expertise so that members of the community can work on their ideas and projects.

We have a broad range of equipment, but I joined the Environmental Sensor Development Kit (ESDK) beta test aiming to get a bit more insight into the air quality in our laser room. This is particularly important to us, as we're in a unique position on the ground floor of the library building with only one side of our space facing the outside. Combined with the library building being heritage listed, this means we've not been able to exhaust the smoke produced by our laser cutters; instead, we have to filter the output and recirculate the filtered air into the room.

The filtration is done by one of these units which are connected to the laser by 100 mm tubing:

Annotated image showing a three-stage fan filter unit. Air is pulled from the bottom of the unit upwards through each filter stage.

The fan at the top of the unit sucks the dirty air from the laser and then up through a stack of three filters - first a piece of fibreglass wool, then a large paper-filled cartridge, and finally a smaller cartridge filled with activated carbon. As you can see in the comparison of a new and week-old wool filter, there's a lot of dirt and soot produced:

A new fibreglass wool filter. It is bright white in colour.

A wool filter after a week of laser cutting. Dirt is clearly visible and the filter is brown.

Project aims and setup

There were two main questions I wanted to answer during my time with the ESDK:

  1. Is the filter unit working? That is, can it keep the air quality in the room at or close to the baseline while the laser is running? Although this might seem easy to answer, we don't have a lot of information on the unit and its filters, and while it has a display for pressure and airflow, the numbers don't make a lot of sense. For example, it often displays an airflow of 2 m3/hr, but performance while displaying this is often variable - sometimes it will be working fine, and other times it will be unable to exhaust any smoke from the laser.
  2. Can we use the air quality data to predict when a filter change is needed? The carbon and paper filters are expensive to purchase due to their size and weight, and it would be great to know that it's time to change them rather than change on a strict schedule.

Once we received the ESDK (no mean feat considering it had to get to the other side of the world during a global shipping crisis), the documentation made it very straight forward to assemble and get working. I chose to locate the kit close to the laser, but on the opposite side of the room from the filter unit so the kit didn't get odd temperature readings from the warm air that's exhausted by the filter:

A picture of our laser room. Left-to-right, there is the filter unit, the laser itself, and the computer used to operate it. The ESDK is just above and to the left of the computer monitor.

The typical readings at the end of a day of laser use:

Close-up picture of the ESDK. Readings are (clockwise from top-left): temperature 24.8℃, humidity 46%, VOC index 235, CO2 799 ppm, PM1-10 18/19 µg/m3

Once I received the credentials for DesignSpark Metrics, I was able to get a lot more context for these sorts of readings. Let's take a look at the data!

A typical week

We can start by looking at a typical week. I've chosen 10 - 14 May (we're open Wednesday to Saturday) to illustrate what we've started to see as 'normal'. Besides the screenshots below, I've also made this week of data available as a snapshot from the DesignSpark Metrics site, which is probably easier to view.

Screenshot of the DesignSpark Metrics dashboard, showing temperature, humidity, CO2 and VOC.

Second screenshot of DesignSpark Metrics dashboard, showing particulate matter readings.

Straight away, we can see when the laser's in use, with the background readings for particulate matter sitting in the 1-3 µg/m3 range and spiking up to 30/40 µg/m3 when the laser's in use. Interestingly, all of the particulate matter readings are very close together - obviously, the laser produces smoke particles that vary evenly in size across the range that the sensor can detect.

CO2 rises consistently throughout the day, which is to be expected as most of our patrons use the laser to cut and engrave plywood and acrylic, both of which produce CO2 when burnt. Since the filter doesn't remove CO2, this is recirculated around the room and the concentration rises pretty steadily over the course of a day before falling at night as the air in the room exchanges with the air in the rest of the space. The TVOC index seems to mostly follow the CO2 concentration, though I'm still trying to get a handle on whether the TVOC index changes depending on what material is being cut.

How important is the filter?

One of the benefits of the Metrics platform is that we're able to go back and look at the data after an event very easily. This was really useful when on 30 April, a patron started a laser job without turning on the fan. The impact of the filter is pretty obvious in this screenshot (dashboard snapshot available here):

Graphs of particulate matter during incident where patron left filter off. All values spike over 1000 ug/m3

Every particulate matter value spiked over 300 µg/m3 within 15 seconds of the job starting and then increased to over 1000 µg/m3 - a 20-fold increase over the worst values we typically see! Importantly, the ESDK detected this happening well before others in the space noticed, as it took us a couple of minutes to detect (aka smell) and realise what had happened. Fortunately, once the filter was turned on things returned to more normal levels within a few minutes.

Conclusion and next steps

Overall, I feel that the data above gives us a good answer to my first question. While the filter isn't able to keep the particulate matter from the laser at a very low background level, it is able to keep the PM10 (coarse particle) concentration mostly below the WHO air quality guideline value of 45 µg/m3 (the recommended maximum for a 24 hour period). However, the filter isn't able to achieve the guideline values for the PM2.5 (fine particle) concentration, where the guideline values are significantly lower. This indicates that we should consider additional measures to protect against these such as providing suitable dust masks - something we already do for patrons who use our workshop for woodworking. Despite this, the filter is clearly a lot better than running the laser without it as is demonstrated by the second set of data!

I don't yet have a concrete answer to my second question about predicting when filters need to be changed, as within the data there was a lot of variation depending on the time of day, what material was being used, and the type of job (engraving vs cutting) being run. I think achieving this goal may require a lot more experimentation, possibly using consistent 'baseline' jobs and brand-new filters. For now, the project I'd like to work on next is an alert beacon, perhaps using an LED strobe light, for situations where the laser has been started without the filter being turned on. This would allow patrons and staff to react faster as the ESDK can clearly detect such an incident far more quickly than we can; it took us far longer than 15 seconds to notice something was wrong!

Overall, working with the ESDK has been a great experience. It's taken something that was very much a black box (literally and figuratively!) and given us an appreciation for what it can and can't do. More importantly, it's given both the workers and patrons at Blueprint a chance to monitor the air quality of their environment and take control of an aspect of workplace health and safety that is often invisible without expensive, specialist equipment. Thank you to DesignSpark and RS for the chance to participate in this beta!

I help maintain and run the equipment at a library makerspace. Outside work, I like playing with electronics and enjoy running as well.
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