There is increasing momentum in industrial practice to improve the development process itself. One of the key factors to do so is the desire for the profit made per appliance. The second reason is increase of the development oriented companies and with this also fierce competition in the global market. Development of the appliance lasts from the first idea about the product till the end of production. In between that time a lot of activities take place in order to achieve the success on the market. But because, as we know from the other fields, of more competition, the terms for success get stricter. This means that equally progressing companies can't make a significant competitive advantage on the market. If there is too much resources applied in the development phase it later shows on the price of the product itself. If there is too less resources assigned to it could happen the product is qualitatively not sufficient and therefore market rejects it. Therefore optimum development would be to minimize resources to the minimum necessary quantity with preserving quality of the end product. In this article there is suggested a method for helping the appliance developers, which based on existing knowledge foresees potential solutions with new challenges. To implement the system there were data collected from various beverage appliances. The main methods within the system were neural networks so the acquired data were set as a base for creating supporting neural networks. System was tested with the data that were previously not included into learning patterns. Results show the method to be suitable during new appliance development. System itself predicted expected solutions well enough to confirm usability for development purposes. References[1] Brglez, Š., Dolšak, B. (2016). A necessity-based method for product requirement elicitation and classification,
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