Artificial neural networks

Development of an object identification algorithm for the forging industry based on standard vision systems

by

Development of an object identification algorithm for the forging industry based on standard vision systems Adrian Litwa, Łukasz Madej AGH University of Krakow, Mickiewicza 30 av., 30-059 Krakow, Poland. DOI: https://doi.org/10.7494/cmms.2024.1.0824 Abstract: The work aims to develop an algorithm for identifying objects in a forging plant under production conditions. Particular emphasis is placed on the … Read more

Soft modelling of the shaping of metal profiles in rapid tube hydroforming technology

by

Soft modelling of the shaping of metal profiles in rapid tube hydroforming technology Hanna Sadłowska, Andrzej Kochański Warsaw University of Technology, Institute of Manufacturing Technologies, Warsaw, Poland. DOI: https://doi.org/10.7494/cmms.2022.4.0789 Abstract: The paper presents an approach to the impact of process parameters in innovative RTH (Rapid Tube Hydroforming) technology for shaping closed metal profiles in flexible … Read more

Application of significance analysis to finding root causes of product defects in continuous casting of steel

by

Application of significance analysis to finding root causes of product defects in continuous casting of steel Agnieszka Rodziewicz, Marcin Perzyk Institute of Manufacturing Technologies, Warsaw University of Technology – Narbutta 85, 02-524 Warsaw, Poland. DOI: https://doi.org/10.7494/cmms.2016.4.0588 Abstract: The aim of this paper is to present an application of the input variable significance analysis to finding … Read more

Control method of winding quality in shrink sleeve labels converting process

by

Control method of winding quality in shrink sleeve labels converting process Krzysztof Krystosiak, Wojciech Werpachowski Faculty of Production Engineering, Warsaw University of Technology. DOI: https://doi.org/10.7494/cmms.2015.3.0545 Abstract: In manufacturing practices of most big printing companies there are collected data and records of process parameters. Gathering information from this data in form of developed models and rules … Read more

Artificial neural networks and response surface methodology as a tool for analysis the spindle torque in FSP process

by

Artificial neural networks and response surface methodology as a tool for analysis the spindle torque in FSP process Marek S. Węglowski Institute of Welding, Bl. Czesława Str. 16-18, 44-100 Gliwice. DOI: https://doi.org/10.7494/cmms.2015.1.0504 Abstract: The article presents the effect of rotational and travelling speeds and down force on the spindle torque acting on the tool in … Read more

Extracting knowledge from integrated experimental data on the adi manufacture

by

Extracting knowledge from integrated experimental data on the adi manufacture Barbara Mrzygłód, Izabela Olejarczyk-Wożeńska, Mirosław Głowacki, Andrzej Opaliński AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow, Poland. DOI: https://doi.org/10.7494/cmms.2015.1.0507 Abstract: The problem discussed in this article relates to the integration of knowledge about the design process of products from ADI. Specialised domain … Read more

Ann-based metamodelling with clustering of output values as an approach to robust inverse analysis

by

Ann-based metamodelling with clustering of output values as an approach to robust inverse analysis Grzegorz Gorecki, Łukasz Rauch, Maciej Pietrzyk, Jan Kusiak AGH University of Science and Technology, Department of Applied Computer Science and Modelling, Al. Mickiewicza 30, Krakow, Poland. DOI: https://doi.org/10.7494/cmms.2014.3.0488 Abstract: Inverse analysis, which uses artificial neural networks as direct problem models, is … Read more

Metamodel driven optimization of thermomechanical industrial processes

by

Metamodel driven optimization of thermomechanical industrial processes Jan Kusiak, Łukasz Sztangret, Łukasz Rauch, Maciej Pietrzyk AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków, Poland. DOI: https://doi.org/10.7494/cmms.2014.1.0472 Abstract: The main objective of the paper is presentation of the metamodel driven optimization (MDO) strategy of thermomechanical industrial processes. In this approach, the model of … Read more

Phenomenon of tolerance to damage in artificial neural networks

by

Phenomenon of tolerance to damage in artificial neural networks Ryszard Tadeusiewicz, Izabela Figura AGH University of Science and Technology. DOI: https://doi.org/10.7494/cmms.2011.4.0374 Abstract: Neural networks are computer tools with many advantages. They are powerful because of possibility of complex nonlinear systems modeling and they are user-friendly because of learning abilities. But neural networks have additional advantages. … Read more

Modeling of the oxidizing roasting process of zinc sulphide concentrates using the artificial neural networks

by

Modeling of the oxidizing roasting process of zinc sulphide concentrates using the artificial neural networks Łukasz Sztangret, Łukasz Rauch, Jan Kusiak, Piotr Jarosz, Stanisław Małecki AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków, Poland. DOI: https://doi.org/10.7494/cmms.2011.1.0322 Abstract: The goal of the research is an attempt of development of automatic control system of … Read more