For example, in a project the aim was to improve a grease making process. By splitting the investigation into several phases, we managed to develop crucial understanding and quickly scale from laboratory testing to pilot. In the first phase at lab scale we figured out, what was really important in the main chemical process. For this particular grease there had been a long debate about adding water or not, we were able to show that water improved the process, but the amount was not that important. After this we moved to the pilot stage with a much greater amount of grease being produced. We were able to show that the base recipe found in the lab indeed worked as well at that scale. We also proved that there was no influence by the preprocessing of the ingredients and the way the addition of the ingredients was done. When we wanted to then investigate the final stage of the process, the homogenisation, we ran out of base oil and learned that batches of the same base oil might lead to different intermediate outcomes. This meant here we could only use one method of homogenisation of the three available. Again the final product had the same properties as before. But obviously it is crucial to understand this unexpected influence of the base oil on the intermediate product, as this changed the requirements for the homogenisation method. Another important more general learning from this is to understand, if specifications of inputs (materials or data) are actually informative for the challenge at hand. In this case the base oil had physical properties specified, not its chemical properties, which led to the issue.

For projects making use of the structured approach to learning about a challenge we offer fixed prices to understand and structure the task, develop a plan to collect data, and analyse the data. These prices depend on the complexity of the task and the effort in planning and analysis. Typical simple projects require about a week total. If you are interested, please send a request using our contact page.