{"id":2174,"date":"2025-07-11T14:20:56","date_gmt":"2025-07-11T04:20:56","guid":{"rendered":"https:\/\/buenoanalytics.com\/?post_type=case-study&p=2174"},"modified":"2025-10-20T16:00:42","modified_gmt":"2025-10-20T05:00:42","slug":"woolworths-case-study-refrigerant-leak-detection","status":"publish","type":"case-study","link":"https:\/\/buenoanalytics.com\/us\/case-study\/woolworths-case-study-refrigerant-leak-detection\/","title":{"rendered":"Woolworths Group | Refrigerant Leak Reduction"},"content":{"rendered":"
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Woolworths \u2013 37% Refrigerant Leak Reduction Across 1,200 Stores\n\n<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Woolworths Group, one of the world\u2019s largest grocery retailers, operates more than 1,200 supermarkets across Australia. As sustainability targets and refrigerant compliance obligations increased, the need for early, proactive leak detection became mission-critical\u2014not just to cut emissions, but to avoid costly service visits, preserve food safety, and protect system performance.<\/p>

Partnering with Bueno, Woolworths has deployed predictive refrigeration analytics at national scale, transforming leak detection from a reactive process to a strategic advantage.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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The Challenge \u2013 Invisible leaks driving costs and emissions\n<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Refrigerant leaks are among the most difficult faults to detect and the most costly to ignore. Traditional alarms were no longer sufficient for a network of this size. Woolworths needed to shift away from reactive callouts and toward predictive, data-led maintenance that could deliver environmental, operational, and financial returns.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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The Journey Begins \u2013 Predictive leak detection across 178,000 connected devices\n<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Using Bueno\u2019s Refrigeration Management module, Woolworths connected over 178,000 pieces of equipment across its store network. With data captured every 5 minutes<\/strong> from racks, cases, and controller logic, the platform identified leak signatures before traditional alarms would typically trigger\u2014allowing targeted responses, fewer truck rolls, and more accurate emissions reporting.<\/p>

Key elements of the solution included:<\/p>