Gearing up for the future of food production

Last week we had three “fruitful” days at the INC Online Conference, where the global fruit and nut industry was online in full force. We got the chance to introduce our new machine, the Qcifeye, and discuss the future of food production with professionals from all over the world. Here’s some of the trends that are shaping the future of food production, and how Qcify is helping to lead the way:

Labor redefined

As we’ve been saying for years, to keep improving food processing and quality control, we have to become less reliant on human labor. Not only is it more inconsistent, prone to error and time-consuming, it is a major expense for food companies. The COVID-19 brought these issues into stark relief as employee absences and employee safety became huge obstacles to overcome in providing business continuity.

We’ve always been huge proponents of fully automating food processing lines, and with every new development in technology we’re getting closer to doing it. From the start our tech has used 3D imaging to capture the way humans see objects. While our first machines were most easily used in the quality control lab, we’ve since moved on to machines that are fully integrated into production lines, from collecting samples to returning them to the lines. This means quality control can be carried out without the line skipping a beat, completely free of human intervention.

The new Qcifeye can be integrated into existing lines, reducing the overall investment. Because so many customers wondered if we could also pick out the foreign objects or flawed product while we were detecting them, we’ve also made that possible with our Qcifeye AI sorter which combines our cutting edge sensors with inexpensive compressed air technology to remove unwanted elements. The sorter can be added on to the Qcifeye sensor at any point to make the quality control and sorting process run seamlessly 24/7.

Getting the most out of our data

We need big data in order to make food production and processing more efficient, safer and more reliable. This doesn’t just mean collecting an avalanche of data points via sensors, but rapidly analyzing information to adjust and improve. It all begins with accurate and objective reporting that is fully automated. Qcify started off with conventional vision algorithms, but we’ve since moved on to AI and deep learning.

AI allows us to precisely label each type of object so that we can get the maximum amount of information about what the sample contains. This way we assure the highest and most consistent quality available. Everything our machines learn about what’s in the samples is shared across our network, so that a machine in California could learn from a new defect found in Australia. Our machines also integrate with ERP systems so that all the information is automatically transferred. By automating in-line monitoring, we can capture more data to help optimize the processing line to make it as safe and efficient as possible.

From support to success

Mind you, we’re not doing all this optimizing and innovating just for fun (though we do enjoy it). We do it for our customers. We apply the same data-driven approach to our company as we do to our machines: by automating our own processes and constantly monitoring what we’re doing, we constantly adjust and improve. Essentially the way we approach customer support comes down to a mindset of being proactive rather than reactive. We don’t wait for problems or complaints to fix: we try to be three steps ahead of these. For this we use our QCentral system which collects and analyses data from all our systems. The better the versions of ourselves we can be, the better solutions we can come up with for our customers.

As John Carter from confectionary giant Ferrero pointed out during the conference, the future of food production rests on the ability to understand in real time what customers think. So while historically companies have tried to measure customer satisfaction after the fact, now it’s about shifting to real-time conversation you can monitor on the internet: being able to sift through and use that data is key to getting further.

Consumers are driving the push for more transparency, traceability and sustainability. Companies have to meet this need while being able to pivot quickly to meet changing consumer behavior when unexpected things like the COVID-19 happen. While AI is becoming ever more sophisticated, we fell back on the good old human mind to make calls about how to adjust quickly in the face of crisis. Now we have an opportunity to collectively learn from this world-altering experiment to make our industry smarter, more connected, and stronger than ever.