New Belgium Brewing uses MES data to improve operations

Using data from its Wonderware MES, New Belgium Brewing is in the process of digitally transforming its business to understand and eliminate production constraints and grow its business.

New Belgium logo
New Belgium logo

The digital transformation of business has been widely discussed for years now. While perspectives on this industry-changing evolution vary, a few facets of it are becoming more clear as companies increasingly apply digital technologies to improve specific aspects of their operations. Many of the steps taken by New Belgium Brewing serve as good examples of how this is happening.

New Belgium Brewing is the fourth largest craft brewer in the U.S., producing 850,000 barrels of beer a year with distribution in all 50 states. But in 2011, the company ran headlong into a major constraint. The new bottling line it installed in 2007 to accommodate the company’s double digit growth hit capacity.

With the line running 24 hours a day, seven days a week, the company initially thought it would need to buying another, expensive new bottling line to accommodate for its continued growth. But it decided to take a closer look at equipment data first.

Ray Matthews, manager of production applications at New Belgium Brewing, said, “We began to look at what our bottling line capacity really was, and we realized that people were calculating it differently. So we decided to approach it from a basic engineering viewpoint [to establish a baseline]. Since the botting line could fill 700 bottles/minute, and we were running it 24/7, that meant we should be producing 294,000 cases per week. Knowing this, the question then became: Why is our biggest week producing just 150,000 cases?”

To better understand what was happening, New Belgium Brewing began speaking to its operators in more depth and discovered that there were numerous and varied perceptions about the causes of downtime and operating speeds. This led them to look deeper into the pieces of equipment that were causing the downtimes and what the root causes for those downtimes were. “This is when we realized we needed more information to know what to solve,” said Matthews.

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