Food Industry Case Study
Reducing Quality & Waste Losses by 70%
With Automated Root Cause Analysis
About the company
Company size: 4,200 employees over 38 sites worldwide
Annual Turnover: €1.2 billion
Industry: Food & Beverage
Focused on a baked goods production line in western Europe
Want to predict & prevent quality and waste production losses?
The Challenge
Persistent quality & waste production losses
The company had identified significant process-driven
losses in quality and waste at their toasted bread line.
Problems contributing to these losses included:
- Rejects due to weight – particularly net weight underweight
- Burned or over-toasted bread
- Size & shape variability
Manual investigations by their process experts – including
the use of an advanced self-serve analytics platform –
could not locate the root-cause of the problems. In most
cases where losses occurred, no clear process inefficiencies
were apparent, and the data tags they investigated
appeared to be operating within the permitted ranges.
The Solution
Identifying & preventing the hidden causes of production losses
Using the Seebo solution, the company’s process experts were able to identify the hidden causes of their production losses, and gain clear recommendations as to how to prevent those process inefficiencies. Furthermore, production teams received real-time alerts as soon as those inefficiencies were detected – enabling them to prevent losses before they occurred.
The Results
70%
reduction in quality & waste losses
138
new insights learned about their process
~€1 million
in savings on a single production line
The company achieved annual savings of nearly €1 million on this single production line by significantly reducing losses in quality and waste using the Seebo solution. Moreover their manufacturing teams learned 138 totally new insights about their process – enabling them to effectively understand and master their processes in the long-term.
For example, the rate of waste due to underweight was cut from 7.4% to just 3.2% – a vast improvement.
This also enabled the company to increase production capacity, by eliminating waste and optimizing their production processes.
Just as importantly, their manufacturing teams gained a far deeper understanding of their production processes. Seebo’s AI insights discovered no less than 138 new
insights about their production processes that their teams had not been aware of.
These insights were then turned into concrete metrics to measure important decisions against. This in turn greatly increased productivity, as process experts and engineers no longer had to spend countless hours discussing and investigating theories and engaging in guesswork.