Analysis of Cleaner Production Performance in Manufacturing Companies Employing Artificial Neural Networks
نویسندگان
چکیده
Cleaner production has emerged as a comprehensive paradigm, aiming to reduce, or even avoid, the environmental impact in stage, broad variety of fields. However, great number interacting factors makes assessment efficiency and identification critical pose significant challenges researchers companies. Artificial intelligence and, particularly, artificial neural networks have proven their suitability lead with diverse multi-variable problems, but not yet been applied model systems. In this work, we employ dimensionality reduction combination fully connected feed-forward multi-layer perceptron relation between input (cleaner techniques) output variables performance) subsequently, quantify sensibility different on variables. particular, consider Product Design, Production Processes, Reuse latent variables, whereas Environmental Performance Product, Economic comprises our model. The results, employing data collected from direct survey 205 Brazilian companies, reveal that best configuration for ANN uses eight neurons hidden layer. Regarding sensitivity, obtained results show improving practices poor marks leads higher enhancement figures. since reuse presents mainly low marks, it can be identified an area improvement, order increase overall performance.
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ژورنال
عنوان ژورنال: Applied sciences
سال: 2023
ISSN: ['2076-3417']
DOI: https://doi.org/10.3390/app13064029