Maximilian Kemper

Weaving machine as cyber-physical production system: Multi-objective self-optimization of the weaving process

Real (physical) objects melt together with information-processing (virtual) objects. These blends are called Cyber-Physical Production Systems (CPPS). The German government identifies this technological revolution as the fourth step of industrialization (Industry 4.0). Through embedding of intelligent, self-optimizing CPPS in process chains, productivity of manufacturing companies and quality of goods can be increased. Textile producers especially in high-wage countries have to cope with the trend towards smaller lot sizes in combination with the demand for increasing product variations. One possibility to cope with these changing market trends consists in manufacturing with CPPS and cognitive machinery. This paper focuses on woven fabric production and presents a method for multi-objective self-optimization of the weaving process. Multi-objective self-optimization assists the operator in setting weaving machine parameters according to the objective functions warp tension, energy consumption and fabric quality. Individual preferences of customers and plant management are integrated into the optimization routine. The implementation of desirability functions together with Nelder/Mead algorithm in a software-based Programmable Logic Controller (soft-PLC) is presented. The self-optimization routine enables a weaving machine to calculate the optimal parameter settings autonomously. Set-up time is reduced by 75 % and objective functions are improved by at least 14 % compared to manual machine settings.

Self-optimizing Production Technologies

Customer demands have become more individual and complex, requiring a highly flexible production. In high-wage countries, efficient and robust manufacturing processes are vital to ensure global competitiveness. One approach to solve the conflict between individualized products and high automation is Model-based Self-optimization (MBSO). It uses surrogate models to combine process measures and expert knowledge, enabling the technical system to determine its current operating point and thus optimize it accordingly. The objective is an autonomous and reliable process at its productivity limit. The MBSO concept is implemented in eight demonstrators of different production technologies such as metal cutting, plastics processing, textile processing and inspection. They all have a different focus according to their specific production process, but share in common the use of models for optimization. Different approaches to generate suitable models are developed. With respect to implementation of MBSO, the challenge is the broad range of technologies, materials, scales and optimization variables. The results encourage further examination regarding industry applications.

Magnetic weft insertion for weaving machines

The common methods of weft insertion in weaving machines are shuttle, rapier, air jet, water jet and projectile insertion. During weft insertion in the weaving process, a variety of demands are to be fulfilled. Besides transportation of the weft yarn, three of the most relevant demands are energy efficiency, productivity and flexibility. These demands are only partially met by the common methods of weft insertion. This paper describes the investigation of a novel method of weft insertion, which combines the advantages of common insertion methods whilst avoiding their deficits. The developed weft insertion is based on the principle of a magnetic force for the controlled transport of the weft yarn. The new method allows a potential energy saving of about 60% compared to a conventional air jet weaving machine. At the same time, industrially experienced weft insertion rates of about 2000 m/min are within reach.

Individual customizable in-store textile production

The target of every company is to satisfy customer demands. Especially the clothing industry has to serve individual customer requirements. Textile products always have been and still are the defining attributes of people’s appearance. Consumer’s demands towards commercial clothing companies have been changing rapidly during the recent years. Two global megatrends have supported this change: Individualization and digitalization. Individualization created demand for frequent collection changes, while still keeping availability high. Digitalization supported the quick distribution of new trends and forced a higher amount of request during peak periods. This paper outlines how a highly individual and customizable fashion product can be produced in a store environment. It focuses on the conceptual design, taking into account the interdisciplinary approach combining production technology with IT-systems, but also addresses the economical challenge with help of a value stream analysis.

The future of textile production in high wage countries

It is undisputed that smart production in the context of industry 4.0 offers significant potential for industrial production in Germany. Exploiting this potential provides an opportunity to meet the growing competitive pressure for textile production in high-wage Germany. The complete cross-linking of textile mills towards Textile Production 4.0 means substantial savings. However, currently there are still some challenges that have to be overcome on the long way to Textile Production 4.0. This paper initially reflects the particular challenges of textile production in high-wage Germany. Later, the vision of the future of smart textile production will be outlined. In addition, first pilot solutions and current research approaches which pave the way for Textile Production 4.0 are described.

Process analysis of an in store production of knitted clothing

In the textile and clothing industry, global value-added networks are widespread for textile and clothing production. As a result of global networking, the value chain is fragmented and a great deal of effort is required to coordinate the production processes [1]. In addition, the planning effort on the quantity and design of the goods is high and risky. Today the fashion industry is facing an increasing customer demand for individual and customizable products in addition to short delivery times [2]. These challenges are passed down to the textile and clothing industry decreasing batch sizes and production times. Conventional clothing production cannot fulfill those demands especially when combined with more and more individual or customizable designs. Hence new production concepts have to be developed.