The food and beverage industry still relies on principles and technology developed in the 1880s to manage clean-in-place (CIP) operations. While conductivity meters have long been the industry standard for monitoring CIP, they often lack the sensitivity and accuracy needed to identify optimization opportunities without compromizing cleaning effectiveness.
Recently, a global beverage plant, with a $4 billion revenue and a beverage bottling network serving a population of over 600 million people across 12 countries, set out to reduce its water consumption while maintaining production efficiency. To achieve their goal, they turned to deep-tech company Collo's process intelligence. The company installed two Collo analyzers at one of their plants to optimize over 160 complete CIP cycles across production lines for six weeks.
"Collo uses radio frequency to analyze the entire composition of a liquid, whether milk, soft drink or jam, in real time," says Jani Puroranta, CEO at Collo. "Combined with machine learning, the analyzers reveal properties that current solutions relying on optics or conductivity overlook. The deep tech transition moves factories away from reactive, manual lab-testing toward an adaptive, data-driven production that continuously learns what normal liquid looks like and flags deviations instantly."
Market leaders such as Coca-Cola, Danone and Valio are already using Collo’s technology.