Objectifying Machine Setup and Parameter Selection in Expert Knowledge Dependent Industries Using Invertible Neural Networks

Lecture notes in mechanical engineering, pp. 293–300

Abstract

Abstract The textile industry is one of the oldest and largest industries in the world. The fields of application for textile products are diverse. Although the technologies for manufacturing textiles are extensively researched, the industry is still highly dependent on expert knowledge. To date, manual process- and machine adjustments and quality control are the norms rather than the exception. Heat setting is used in the process chain to dissolve or selectively introduce tensions from the weaving or knitting process and to prepare the products for digital printing. The correct setting of the machine depends on a large number of different materials-, processes- & environmental parameters. For each product, the machine has to be set up again by an experienced textile engineer. To ease the training for new workers and shorten the machine setting process, this study aims to use machine learning to facilitate and objectify the setting of the heat-setting process. Machine parameters are generated using an invertible neural network (INN) based on pre-defined target parameters. The results can be used to identify trends in machine settings and respond accordingly. Thus, a reduction of machine setting time could be realized.

Authors 4

1. Kai Müller corresponding Aachen Institute for Textile Technology

   RWTH Aachen University

   Affiliation as printed

   Institute for Textile Technology (ITA) of RWTH Aachen University, Otto-Blumenthal-Street 1, 52074, Aachen, Germany

2. Andrés Felipe Posada-Moreno Aachen Institute for Data Science in Mechanical Engineering

   RWTH Aachen University

   Affiliation as printed

   Institute for Data Science in Mechanical Engineering, Dennewartstr. 27, 52068, Aachen, Germany

3. Lukas Pelzer Aachen Institute for Plastics Processing in Industry and Craft

   RWTH Aachen University

   Affiliation as printed

   Institute for Plastics Processing (IKV) in Industry and Craft at RWTH Aachen University, Seffenter Weg 201, 52074, Aachen, Germany

4. Thomas Gries Aachen Institute for Textile Technology

   RWTH Aachen University

   Affiliation as printed

   Institute for Textile Technology (ITA) of RWTH Aachen University, Otto-Blumenthal-Street 1, 52074, Aachen, Germany