Standardizing data collection in breweries

Data collection in breweries is vital for cross-facility digitalization in the brewing industry.

By Martyn Williams July 3, 2022
Image courtesy: Brett Sayles

According to McKinsey & Company, Industry 4.0 can deliver tangible operational benefits for manufacturers, one example being inventory cost savings of 20% to 50%. Breweries are no exception, and are increasingly turning to automation and the Internet of Things (IoT) technologies to become more efficient, lean and scalable in light of increasing production and energy costs.

This is more challenging for brewing companies that operate different sites worldwide. For breweries, as with any type of manufacturer, poor or outdated data management can negatively impact overall equipment effectiveness (OEE), cause unplanned downtime, decrease throughput and ultimately damage the company’s bottom line.

IoT technologies will prove crucial as the beer industry moves into new markets. For example, a large multinational brewer might install sensors throughout its production line to monitor OEE, and upgrade its manufacturing execution systems (MES) to analyze the brewery data collected by these sensors.

This process is where some larger breweries are encountering problems. Managing these large reams of data consistently across multiple international sites simply isn’t feasible without software.

Industrial software can play a vital role in supporting larger manufacturers with data management, making it possible to analyze data more efficiently and effectively within individual plants, and new and legacy systems can be integrated into the software platform to allow overall system improvements.

Take the case of a brewery that, according to a study by the American Council for an Energy-Efficient Economy (ACEEE), was losing up to 10% of its overall product for an unknown reason.

To solve the problem, the brewery used software and installed 40 sensors at key points throughout the production line. It was able to spot exactly where on the production line losses were being made and address the issue. This put an end to the manufacturer’s 10% loss.

Solutions like this rely on better data capture. By linking sensors to software platforms it becomes possible to evaluate the frequency and duration of problems, and source their origin. A brewing company may find that production issues are caused by pressure and temperature imbalances, and resolve these issues accordingly within a predictive maintenance strategy.

Industrial software can also support improvements in production output. A brewery might use digital twinning to compare its actual line capacity, of 100,000 cases of beer a week, against a desired capacity of 2,000 cases. Once the digital simulation has identified performance improvements that can be made to the line, the manufacturer can link its software to an MES and leverage this data to improve its production capacity.

Multisite improvements

Once an individual brewery has used data capture to spot flaws or improvements, this information can be shared with other multinational sites. A zenon analyzer, for example, is able to relay data to operators at other international facilities, who can then investigate if they have the same problems or opportunities.

There is also potential to combine zenon with other management systems, like control charts, to make data management even more integral to the production process.

Brewing companies should turn to industrial automation software to avoid falling behind in the competitive global market. Automated data collection in breweries will be crucial for preventing downtime and managing data across multiple international sites, helping breweries expand globally.

– This originally appeared on Control Engineering Europe’s website. Edited by Morgan Green, associate editor, CFE Media and Technology, mgreen@cfemedia.com.


Martyn Williams
Author Bio: Martyn Williams is managing director at COPA-DATA UK.