IoT in the Café
/By Kaleb Leach
IoT (Internet of Things) is not new, and it has been in place in residential equipment like refrigerators and TVs for some time. Manufacturers have been trying to find ways to get feedback from the equipment to improve reliability and understand how end-users interact for a long time. Based on what I have read, the closest use case to how we as technicians would use IoT data from equipment is being done by the automobile industry. Because cars are connected to provide entertainment or navigation, the manufacturer can receive data from the on-board computer to assess usage and calculate failures. Aside from runtime, mileage, etc., the error codes that cars put out help the end-user, mechanics, and the manufacturer.
Even though they can be somewhat vague or ambiguous, we know that they often point to a problem, especially if you can pinpoint by connecting all the different data points at the moment that caused the error.
Coffee equipment is becoming more digital every year.
The error outputs have been integrated into brewers and espresso machines for some time, at least on the user interface side. If nothing else, user messages have provided instructions that give the end-user a task or a description of a type of problem to pass off to the technician when the machine is broken. Flow errors, level errors, drawer or funnel missing are terms that are ambiguous with coffee equipment. These messages provide information about how to interact with or repair a brewer. These messages are the start of delivering IoT data output but not the end.
The first time I remember using a computer to interact with an espresso machine was in the early 2000s; it was a line of super automatics that made both commercial and domestic machines. As a service provider/distributor, we had to purchase the software and digital interface. It looked like this:
Different models had different connectors and interfaces, and it was kind of a pain. The machines had to speak through an outboard user interface that was much like an old-school automotive code reader. Still, you could connect through the interface and into a laptop, and the user interface on the computer was more intuitive. Ultimately, the output was not much more robust than what we could get from the UI. It was nice to get the service codes and a self-diagnosis for the customer, and it could track the work done, which meant you had a digital copy to review if you saw the machine again. You could record the SN of the device, date, and there were a bunch of service codes you could input into the machine based on the job you did. We were supposed to upload the information to the manufacturer's servers once a month. I don't think we got as much value out of the tool as the manufacturer did, but it was good to be current with technology at the time.
The IoT of today is much different. In some cases, you can already get real-time data streamed from a machine you are working on:
We are not far from a time that all machines will be able to connect through a secured connection. The most likely scenario is that manufacturers will offer an extended warranty if you are willing to connect to their cloud or an extended service that the customer can add to the machine's purchase. Connecting to the cloud allows the manufacturer to help keep your machines healthy and prevent downtime. Using IoT data, the manufacturer will see how many times the valves on the groups have been activated over time or how many hours a pump motor has run. Flowmeters can give an output of how much water has passed through the groups or through the inlet of the machine for total water usage. Outputs are easy to capture. All that is needed is to make calculations on what 'output' means. Manufacturers have a lot to gain from this information: For example, (1) they can see how a machine is used between different customers; (2) they can use the information to understand warranty claims; (3) they can use it to root out manufacturing problems and how they affect the machine's overall health on a large scale.
Ultimately, they can help techs troubleshoot an individual machine by looking at the real-time data outputs.
What does this mean for techs?
I still think that the manufacturer will lead the space in development for IoT because they have the best platform to build it in the design. However, I see a world where techs certified by the manufacturer could have access to a dashboard of information that helps them diagnose and repair the machine remotely. In some cases, a tech might use the information to help a customer over the phone and save some money and time for both parties. For instance, if a customer calls in that the machine is not hot.
The tech could open a dashboard and look at the machine's data if the machines have been refilling consistently in 5 seconds until the refill time slowly went up incrementally for a week or two. The dashboard shows multiple flow errors and fill-errors. In that time, the tech might be able to conclude that the water filter before is clogged or there is a water supply issue. This information can help the tech troubleshoot with the customer and prepare for the service call. Yes, this scenario might lead to a few different problems, but the outcome is the same. The boiler takes longer to fill every day until it gets a fill-error and shuts down for safety. The IoT data will provide this aggregated information to a tech in detail, which would give the tech direction for diagnosis and a way to confirm any fix they put in place has worked. If the customer says, let me change my filter and call you back, the tech can confirm that the machines have gone back to standard fill times.
What does the future look like?
Let's take this a little further and say that every time this scenario plays out in the data, the result is a service call. The problem and solutions may vary, but every time this calculation in data happens, it leads to a service call. Why not have the machine create the service call before the hard-down event. This will result in reduced customer downtime and the frustration that come along with it. We will still have a preventive maintenance model, and you will still have to change group gaskets, overpressure valves, steam valves, etc. But we will also have a predictive maintenance model, a model that lets the customer know they will be expecting a hard-down event if they do not call their service provider.
As a tech, I would much rather plan time with a customer that is not losing money because their machine is down. As a café owner, I wouldn't want to put that hardship on the people trying to serve customers or upset my customers because we couldn't make their order.
How does the end-user access and use IoT?
There's a lot of potentials for end-users to get value out of equipment IoT. When it comes to them, they might want to see all of the business's equipment on one dashboard. The outputs are specific to the users' needs in these use cases but consider, instead of checking temps in a fridge, the dashboard could track and monitor temps and alert to low or high temps when needed. Café owners could get accurate data letting them know when cleanings have been performed on the coffee equipment, average shot extraction times from espresso machines— keeping an eye on quality and consistency for training and accounting. Warnings from the filtration system that the pressure is getting low and they either need to change the filters or have a tech out—built-in troubleshooting for different issues.
Ultimately IoT has several possibilities that add value on many different levels, including research and development, repair and maintenance, user experience, and more that we don't understand yet. For a nerdy look into the sci-fi-future, imagine techs using VR to check and inspect a machine remotely before they walk into the café, but that's probably just me being crazy. Regardless, all equipment/machines will have some form of IoT outputs in the future, and we will interact with it in some form or another. The systems that we build out now will help inform how future techs will interact with equipment and a computer or mobile device with another tool in the tool bag in the future.