Production optimization at Foods Manufacturer

Consumer Packaged Goods

Real-time data extract from the production line was used to rapidly generate fact-based operational insights and drive business process changes. This resulted in a consistent increase in machine availability and daily average production within a few months.


  • Natural and Functional food manufacturer based in the Pacific North West
  • Publicly traded company (NYSE) with market cap of US $300M
  • Manufactures powdered and liquid creamers, and hydration products

Business Challenge

  • Client has been expanding rapidly and was finding it increasingly difficult to make production meet increased demand
  • At the same time, they wanted to ensure that the challenges of rapid growth did not result in decreased quality or increased rework, since they pride themselves on quality
  • To further complicate matters, some essential production and quality monitoring and metrics (such as OEE) were virtually non-existent or difficult to get hold of
  • This meant that ensuring production & quality standards, performing root cause analysis on key issues and driving continuous improvement weren’t an integral part of the organization

Our Approach

  • We started by interviewing key stakeholders and holding workshops to identify the most pressing issues in Production and Quality departments
  • Next, we setup tracking, storage and display of real-time pouch weight data directly from the production line
  • This enabled us to quickly collect baseline numbers for key metrics such as machine Availability (uptime), Rate (production speed) and Quality (rework)
  • We worked closely with the production & quality teams to identify root causes of downtime, slowdowns and underweight bags, and setup procedures to consistently address key issues
  • The team, in conjunction with client SMEs, started collecting additional sensor data to perform machine learning to identify potential sources of weight fluctuations (underweights and give-away)
  • Finally, we performed advanced data analytics on the data collected to identify potential adjustments to machine set-points to reduce rework


  • Increased machine availability by 24% - $1.35M annualized
  • Sustained average daily production increase by 32% - $2.67M annualized

Key Takeaways

We setup a real-time data extract from the production line. Capturing this data in a time-series historian, we built a custom dashboard that was used to rapidly generate fact-based operational insights. The team subsequently used these insights to drive business process changes that ultimately generated operational benefits such as a consistent increase in machine availability and daily average production, in less than six months.

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