The human decision making in the dough mixing process estimated in an artificial sensor system

We consider a problem, that is basic to perception measurement: an artifici al system that mimics the integration of perceptual information into a prop osed framework performed by the human senses. The paper presents a method f or optimising complex information from one single sensor that is indirectly based on the human measurement capability, in the mixing process of dough. We propose a method to measure, analyse and correlate sensor information. This technique is exemplified by an industrial application, where the influ ence of the properties of the human senses on the rheological behaviour of wheat flour dough is estimated and has further been studied in the dynamic mixing process. It is shown that, by dynamic measurements on the mixing mac hine, the complex behaviour of the mixing process could clearly be followed . However, by implementing human knowledge and experience into the sensor s ystem we manage to adapt a process that works with human preferences. The s ystem's ability to optimise various types of bread formulae and different t ypes of wheat flour is also described. An additional benefit is the possibi lity, by calculations, to predict the behaviour of the wheat flour dough pr ocess. (C) 1999 Elsevier Science Ltd. All rights reserved.