Quality and consistency are two of the most important characteristics of any successful roastery. Given the broad range of variables that roasters need to control and maintain, however, it’s not always so easy to balance both. On top of managing many areas of their business – including wholesale clients or upgrading their facilities – staying on top of quality control needs to be a priority.
Just like in many other parts of the supply chain, AI technology can help roasters with their efforts to maintain coffee quality and consistency. At the same time, more advanced and intuitive machine features can improve operational efficiency – benefitting roasters in a number of ways.
So it’s fair to say that AI has changed coffee roasting for the long term, but how could it evolve even further? To learn more, I spoke to Lorenzo Mosca, production engineer at IMF Roasters.
You may also likeour article on what roasters need to know when upgrading their facilities.
The rise of AI in the coffee industry
Automation isn’t a new concept, even in the coffee industry. Simple automated technology has been used for years for some repeatable and simple tasks – especially by producers who use mechanical harvesters to pick coffee cherries.
AI, however, is a much more modern addition to the coffee sector. While automation ultimately relies on humans to make decisions and implement workflow for machines, AI (or artificial intelligence) technology can be programmed to use information about certain repeatable tasks to improve efficiency and achieve a desired outcome.
This level of problem-solving has opened up many new possibilities across the coffee industry to minimise the potential for human error. In fact, a recent study shows there is a 50% chance AI could automate all jobs in 120 years.
Of course, this would result in significant implications for coffee professionals the world over. But when AI is used in conjunction with human-driven actions and decisions, it can massively optimise performance, as well as improve coffee quality and consistency.
For instance, in coffee production specifically, industry professionals use AI technology to:
- Set up weather insurance and climate adaptation systems
- Predict coffee prices
- Generate specific data for EUDR compliance
Coffee shops have also embraced AI to improve efficiency and assist staff in their job roles. The most prominent example is robot barista concept stores, with many of them able to prepare a variety of drinks. This allows café staff to spend more time focusing on other tasks, such as interacting with customers and stock management.
How has AI technology changed roasting?
We’ve seen AI used at every level of the coffee supply chain to improve quality and streamline operations. The area that has seemingly adopted this technology the most, however, is roasting.
Lorenzo Mosca is a production engineer at IMF Roasters, a roastery equipment manufacturer in Italy.
“AI technology enhances the consistency and reproducibility of many roasting processes,” he says. “Traditionally speaking, roasting coffee means adhering to a predefined roast curve, which dictates parameters like optimal temperature and total roast time to achieve desired flavours and aromas.
“But when AI is integrated into roasting equipment, it can continuously monitor key parameters such as temperature, airflow, and drum speed throughout the entire process,” he adds. “So when there are deviations from the specified roasting curve, AI systems can autonomously adjust variables in real-time.”
Although this level of AI isn’t widely used in the coffee industry yet, more and more roaster manufacturers and other companies have started to invest in this technology. With machine learning, AI could understand more about different variables that impact how we roast coffee – including origin, bean density, and processing method – and develop roast profiles which produce better results.
Consistency is key
Consistency is a key part of this, as Lorenzo explains: “AI can help produce desired flavour profiles batch after batch, irrespective of variations in roasting variables.”
Other machine features can also assist with this. For instance, IMF roasters include 12 preset inlet temperature points and extensive control over air and drum rotational speeds.
“Roasters can precisely adjust parameters to match specific requirements of different coffee beans, which ultimately leads to greater consistency,” Lorenzo says.
When quality is maintained through the roasting process, customers can experience coffee closer to its peak flavour potential. This allows roasters to highlight the exceptional characteristics of the coffees they source, and keep refining their menu and brand identity.
Other ways for AI to improve roasting
Better quality control and repeatability are certainly two of the most beneficial implications of AI roasting technology. But there are several other key ways that AI can support roasters.
Data collection and analysis are some of the most important. “IMF software captures critical information throughout the roasting process, including the weight of green and roasted coffee, temperature, and total roast time,” Lorenzo explains. “This data is logged in real-time and provides an accurate record of production.”
Managing green coffee stocks is another way. Smart software can track inventories and inform roasters about whether they need to order more of a particular coffee. IMF Roasters’ silos, for instance, include integrated software which monitors the weight of the green beans stored inside, as well as other key data points.
Similarly, AI systems can also control the movement of coffee around a roastery, whether between storage silos and destoners or roasters and packing stations. This not only helps increase efficiency, but can also allow staff to find ways to improve the workflow of a roastery.
Leveraging the power of AI
Whether a small business or a large-scale operation, AI technology can be a useful tool for many coffee roasters. And as a business grows, AI-driven management solutions can help owners streamline processes.
“As roasters scale, they may face challenges in managing larger volumes of beans, orders, and customers,” Lorenzo says. “Software management provides the tools and resources to remain efficient and maintain consistent quality.”
Moreover, there are many aspects of production roasting that are repetitive, and roasters can therefore use machine learning to their advantage. By transitioning from human to AI-driven actions, this inevitably frees up employees to focus on other areas of the business. Over time, this could yield significant dividends for roasters who need to stay beside their machines, or inventory managers who spend hours each week monitoring stock levels.
Looking ahead
The future also holds plenty more potential for better leveraging AI technology in roasting.
“In the years to come, AI software could continue to advance coffee roasting by using machine learning algorithms to adapt and optimise roast profiles based on an even wider range of variables,” Lorenzo says. “These could include specific bean characteristics, environmental conditions, or even customer preferences.”
Theoretically, this means roasters could improve and experiment with roast profiles even more – allowing them to customise sensory profiles and showcase the full spectrum of coffee flavour.
Preserving coffee quality and maintaining consistency are vital to the success of any roastery. In time, AI software and machine learning will become increasingly integral parts of these processes.
Ultimately, using AI in conjunction with in-depth knowledge and expertise will help propel the coffee industry forward even further. And in the coming years, we can expect to see more and more roasters leverage the power of AI-assisted technology to achieve the best results they can.
Enjoyed this? Then readour article on why roaster manufacturers need to provide global support services.
Photo credits: Viva Sara, Bell Lane Coffee, Amokka Nordic Roasters, IMF Roasters
Perfect Daily Grind
Please note:IMF Roasters is a sponsor of Perfect Daily Grind.
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