Neuro-fuzzy Modeling of an Eco-friendly Melting Furnace Parameters using Bio-fuels for the Agile Production of Quality Castings
نویسندگان
چکیده
In this paper neuro-fuzzy technique is used for the first time in modeling eco-friendly furnace parameters to predict the melting rate of the molten metal required to produce homogenous and quality castings. The relationship between the process variables (input) viz. flame temperature, preheat air temperature, rotational speed of the furnace dome, percentage of excess air, melting time, fuel consumption and melting rate (output) is very complex and is agreeable to neuro-fuzzy approach. The neuro-fuzzy model has been developed out of training data obtained from the series of experimentation carried out on eco-friendly self designed and developed 200 kg capacity rotary furnace using bio-fuels. The results provided by neuro-fuzzy model compares well with the experimental data. This work has considerable implications in selection and control of process variables in real time and ability to achieve energy and material savings, quality improvement and development of homogeneous properties throughout the casting and is a step towards agile manufacturing.
منابع مشابه
Optimizing Process Parameters of Rotary Furnace using Bio-fuels: An Interactive ANN Approach
This paper deals with a novel interactive approach of Artificial Neural Network (ANN) as an optimization tool for optimizing process parameters of rotary furnace. This approach solves a very challenging problem in the area of rotary furnace i. e. selection of optimal process parameters for producing homogenous quality castings. Rotary furnace involves several critical parameters like flame temp...
متن کاملDynamic Modeling of a Robot Manipulator for Opening the Tap Hole of an Electric Arc Furnace
The electric arc furnace (EAF) is used to produce high quality steel from steel scraps. The EAF uses plasma arc to generate heat for melting scarp or direct reduced iron (DRI). The liquid metal should be drained from the tap hole. Manual tapping operation of the EAF in the hot environment around the furnace is a potentially dangerous and time consuming task for the workers. Therefore, it is ess...
متن کاملDetermination of water quality parameters and nutrient level with an Adaptive Neuro- Fuzzy Inference System
In this research, the physico-chemical water quality parameters and the effect of climate changes onwater quality is evaluated. During the observation period (5 months) physico-chemical parameterssuch as water temperature, turbidity, saturated oxygen, dissolved oxygen, pH, chlorophyll-a, salinity,conductivity, and concentration of total nitrogen (nutrient level) as main pollutant factor have be...
متن کاملModeling of Weld Bead Geometry Using Adaptive Neuro-Fuzzy Inference System (ANFIS) in Additive Manufacturing
Additive Manufacturing describes the technologies that can produce a physical model out of a computer model with a layer-by-layer production process. Additive Manufacturing technologies, as compared to traditional manufacturing methods, have the high capability of manufacturing the complex components using minimum energy and minimum consumption. These technologies have brought about the possibi...
متن کاملModeling and Simulation of a Side-Port Regenerative Glass Furnace
ABSTRACT:A mathematical model for the performance prediction of an industrial glass furnace with six ports on each side was developed. This model comprises of two main sub-models for the combustion chamber and glass-melting tank. The first sub-model consists of the models for the combustion and the heat transfer model including, radiation, convection and conduction. The fuel combustion in a...
متن کامل