Fuzzy Decision Support System for the Calibration of Laboratory-Scale Mill Press Parameters

Chemical analyses of iron ore samples are crucial to identifying the characteristics being mined and processed by mining industries. Moreover, reliable content results fundamental optimizing plant operation correctly pricing final product. An industrial laboratory usually performs hundreds per day requires a certain amount equipment increase capacity. However, parallel chemical approach demands proper calibration avoid result variability due use different equipment. This paper proposes method help operators select correct mill press parameters during calibration. First, we apply design experiments (DoE) technique determine parameter that affects result. Then, decision support system (DSS) is developed based on fuzzy logic adjust parameters. Results with real data show proposed reduces standard deviation concentrate grade (%Fe ) up 65.01% silica (%SiO2) 60.81%.