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Google Cloud Platform > Case Studies > AB InBev: Optimizing Beer Manufacturing with Machine Learning
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AB InBev: Optimizing Beer Manufacturing with Machine Learning

Technology Category
  • Analytics & Modeling - Machine Learning
  • Functional Applications - Manufacturing Execution Systems (MES)
Applicable Industries
  • Packaging
  • Retail
Use Cases
  • Chatbots
  • Predictive Maintenance
Services
  • Cloud Planning, Design & Implementation Services
  • Data Science Services
The Challenge
Anheuser-Busch InBev (AB InBev), a global corporation known for its popular beer brands like Budweiser, Corona, and Stella Artois, was facing challenges in optimizing its beer filtration process. The filtration process, which is crucial for achieving the best beer taste and meeting brand-required turbidity levels, involves many unpredictable variables. The existing technology could only handle basic logic, using meters to monitor and react to adverse conditions such as a change in pressure. AB InBev recognized the potential of machine learning (ML) and artificial intelligence (AI) in leveraging a larger dataset to better predict and prevent potential issues during filtration. However, the company needed a partnership and provider that could enable them to deploy ML quickly and effectively.
About The Customer
Anheuser-Busch InBev (AB InBev) is an international corporation with global headquarters in Belgium. Founded in 2008 from the merger of InBev and Anheuser-Busch, AB InBev's global beer brands include Budweiser, Corona, and Stella Artois. The company is committed to embracing the future and innovating to stay competitive. As part of this commitment, AB InBev partnered with Pluto7, a technology solutions provider, to optimize its beer filtration process using machine learning and artificial intelligence.
The Solution
AB InBev partnered with Pluto7, a technology solutions provider that uses Google Cloud services to improve operations at manufacturers and other companies. Pluto7 developed a prototype solution that enabled AB InBev to optimize the beer filtration process with much greater accuracy. The solution combined TensorFlow, Cloud Machine Learning Engine, Cloud SQL, and BigQuery. Working with Pluto7, the AB InBev team evaluated six months of manufacturing data from its Newark, New Jersey brewery. The data was fed into a TensorFlow ML engine run through Google Cloud. Through this process, they identified more than 50 specific parameters that displayed potential predictive ability, which were then used to revolutionize their system. Currently, AB InBev is working with Pluto7 to scale the solution to multiple brewery locations, with plans to deploy the solution at all K Filter and similar filtration systems globally.
Operational Impact
  • The implementation of machine learning and artificial intelligence in the beer filtration process has not only improved the efficiency and cost-effectiveness of the process but also ensured the best possible beer taste. The success of this initiative has gained attention, with AB InBev being showcased at the 2018 Google Cloud Next conference in San Francisco and selected as a Finalist for the Supply Chain Breakthrough of the Year awards at Gartner's 2019 SCM World conference. The company is now working on scaling the solution to multiple brewery locations, demonstrating its commitment to continuous innovation and improvement.
Quantitative Benefit
  • Increases the barrelage per run by 60% through longer filter runs
  • Reduces costs of filtration
  • Increasing the length of each filter run by 40% to 50%

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