Wednesday, February 13, 2019

Intro to timeseries features - getting started on a DrivenData competition


We're really excited to launch our latest competition! In addition to an interesting, new prize structure, the subject matter is at the intersection of sustainability and industry. Improvements to these kinds of processes can have upside for both a business and the planet.

The presence of particles, bacteria, allergens, or other foreign material in a food or beverage product can put consumers at risk. Manufacturers put extra care into ensuring that equipment is properly cleaned between uses to avoid any contamination. At the same time, the cleaning processes require substantial resources in the form of time and cleaning supplies, which are often water and chemical mixtures (e.g. caustic soda, acid, etc.).

Given these concerns, the cleaning stations measure turbidity during the cleaning process. Turbidity quanitifies the suspended solids in the liquids that are coming out of the cleaning tank. The goal is to have those liquids be turbidity free, indicating that the equipment is fully clean. Depending on the expected level of turbidity, a cleaning station operator can either extend the final rinse (to eliminate remaining turbidity) or shorten it (saving time and water consumption).

The goal of this competition is to predict turbidity in the last rinsing phase in order to help minimize the use of water, energy and time, while ensuring high cleaning standards.


DataTau published first on DataTau

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