Siemens has developed a washing machine that automatically selects the right program for every type of laundry, a feature that reduces water consumption. The appliance — “automaticWascher” — is equipped with smart sensors that recognize how much laundry is in the drum, what kind of textiles the laundry load comprises, and if it is heavily or lightly soiled. Users only have to choose one of two program settings: hot and colored wash, or easy-to-clean fabrics. The machine takes care of the rest.

The sensors determine how much laundry is in the washing machine and which fabric types are to be washed. They do this by measuring the amount of water in the drum and how the textiles absorb the water. The less laundry a drum contains, the less water is needed to fill it up. The level of the water and the water pressure depend on how full the washing machine is. The engineers at Siemens take advantage of this ratio by equipping the washing machine with a pressure sensor and a flow sensor, with the latter measuring the amount of water that is pumped into the drum.

The sensor measurements provide data on how much laundry is in the drum. It also reveals which kinds of fabrics make up the wash load, because every type of textile has its own distinctive absorption properties. Silk, for example, not only absorbs less water than cotton, it does so at a slower rate. This means that every type of textile has a distinctive effect on how the water pressure develops, and the washing machine detects these differences.
The degree of soiling is determined by an aqua sensor that uses a light gate to measure the level of water turbidity resulting from detergent and particles of dirt. The system combines all the data on the amount of laundry, its type and relative degree of soiling, and the washing machine then automatically selects the appropriate wash cycle, which users can follow on a large display. As soon as the water is no longer turbid, the aqua sensor automatically stops the program, ensuring optimum water consumption. (IN 2006.04.2)