Production Optimization

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.

Client

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

Results

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.