Food Manufacturer Resolves Quality Problem and Saves $1million p.a. on Production Line Using New CAMO Multivariate Data Analysis Software

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Nidar AS, the largest chocolate and sweets manufacturer in Norway, recently used new CAMO multivariate data analysis software and design of experiments to resolve a product quality problem in one of their process lines.

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This project has saved the company $1 million USD per year on one production line alone.

Despite deep experience and heavy investment in their manufacturing and quality control processes, Nidar were unable to identify the cause of the problem which resulted in significant waste, downtime, energy usage and re-work costs.

Because chocolate manufacturing is a complex process with many variables, Nidar required more powerful analytical tools than traditional Statistical Process Control (SPC) to understand the relationships between product variables.

Therefore, the company turned to The Unscrambler® X multivariate data analysis program by CAMO Software, which enabled them to identify and understand the complex process variables causing the problem, as well as to quantify the ‘gut feel’ of the Production and Quality teams.

Nidar undertook a 3-step process beginning with analyzing historical data using multivariate models, followed by the application of Experimental Design in full scale production, and finally implementing changes in the process settings.

The analysis revealed that the process of making the chocolate could not be viewed as an isolated event. For example, the speed at which the process was running was important for the production volume. Furthermore, the process settings when filling and cooling the product had interactions with the storage conditions such as temperature, time and humidity.

This project has saved the company $1 million USD per year on one production line alone. Additionally, the knowledge gained has been transferred to other production lines resulting in improvements across the business.

Paal Braathen, CEO of CAMO Software, says, “This illustrates how multivariate data analysis solutions give organizations greater insights from their R&D, production and quality control processes, enabling them to realize significant cost savings and quickly get a large return on investment.”

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Nathan Bray
Camo
(+47) 223 963 00
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