Cyber-Physical Systems in textile production – the next industrial revolution?

Cyber-Physical Systems in textile production – the next industrial revolution?

Yves-Simon Gloy, Anne Schwarz, Thomas GrieInstitut für Textiltechnik, RWTH Aachen University, Aachen, GermanyCorresponding Author. Email:


Germany claims the fourth industrial revolution. The evolution towards Industry 4.0 is mainly based on digital technologies. Basic ideas and concepts of Industry 4.0 will be presented, including aspects like horizontal integration through value networks, end-to-end digital integration of engineering across the entire value chain and vertical integration and networked manufacturing systems. Opportunities for a realisation of Industry 4.0 within the textile industry are described. In addition also textile products such as smart textiles can lead to Industry 4.0 and will be herein presented.

Keywords: Industry 4.0, Digital technologies, Cyber-Physical Production Systems, textile industry

1. Introduction

Germany’s industries are highly productive. Also, Germany is one of the global leaders in the manufacturing equipment sector. One reason for this is Germany’s specialisation in research and development. Also production of innovative manufacturing technologies and the management of complex industrial processes are well established in Germany.

Germany’s strong machinery and plant manufacturing industry, its globally significant level of IT competences and its know-how in embedded systems and automation engineering mean that it is extremely well placed to develop its position as a leader in the manufacturing engineering industry.

Germany is thus uniquely positioned to tap into the potential of a new type of industrialization: Industry 4.0 [1].

2. Industry 4.0

According to the German secretariat of the “Platfom Industrie”, and its report “Recommendations for implementing the strategic initiative INDUSTRIE 4.0”, one major innovation of Industy 4.0 will be the integration of so called Cyber-Physical Production Systems (CPS), see figure 1. CPS will use real-time capable sensors, actors and cognition. Also the use of the Internet of Things is important for Industry 4.0. All this will have impacts on the value creation, business models, downstream services and work organization. Following features of Industry 4.0 will be implemented

  • Horizontal integration through value networks
  • End-to-end digital integration of engineering across the entire value chain
  • Vertical integration and networked manufacturing systems [1].


Horizontal integration through value networks

The main question of the horizontal integration through value networks is “How can companies’ business strategies, new value networks and new business models be sustainably supported and implemented using CPS?”. In addition to “business models” and “forms of cooperation between different companies”, it becomes also necessary to address topics such as “sustainability”, “know how protection”, “standardisation strategies” and “medium to long-term training and staff development initiatives”.

End-to-end digital integration of engineering across the entire value chain

The major question for this is “How can CPS be used to deliver end-to-end business processes including the engineering workflow?” The appropriate IT systems should be deployed in order to provide “end-to-end support to the entire value chain, from product development to manufacturing system engineering, production and service”. A “holistic systems engineering approach is required to span the different technical disciplines”.

Vertical integration and networked manufacturing systems

The question to be raised for this is “How can CPS be used to create flexible and reconfigurable manufacturing systems?” In tomorrow’s smart factories, “manufacturing structures will not be fixed and predefined”. Instead, a” set of IT configuration rules will be defined to be used on a case-by-case basis to automatically build a specific structure (topology) for every situation, including all the associated requirements in terms of models, data, communication and algorithms”.

As an example, the application for the reduction of the energy consumed by a vehicle body assembly line while it is not in use will be described. Currently, many production lines, or parts thereof, continue running and consuming high quantities of energy during breaks, weekends and shifts where there is no production. Tomorrow, robots will be powered down as a matter of course, even during short breaks in production. During longer breaks in production, they will enter a kind of standby mode known as Wake-On-LAN mode. The extractors will use speed-controlled motors that can be adjusted to meet requirements instead of motors that cannot be controlled in this way [1].


Another example application can be demonstrated by looking at custom manufacturing and how an individual customer’s requirements can be met. Today’s automotive industry is characterized by static production lines (with predefined sequences) which are hard to reconfigure to make new product variants. Software-supported Manufacturing Execution Systems (MES) are normally designed with narrowly defined functionality based on the production line’s hardware, and are therefore equally static

Tomorrow vehicles become smart products that move autonomously through the assembly shop from one CPS-enabled processing module to another. The dynamic reconfiguration of production lines makes it possible to mix and match the equipment with which vehicles are fitted; furthermore, individual variations (e.g. fitting a seat from another vehicle series) can be implemented at any time in response to logistical issues (such as bottlenecks) [1].


3. Textile Machines with Cyber-Physical Systems

Textile process chains in high-wage countries like Germany are described by many companies along the production chain. In order to get these textile process chains on level of Industry 4.0, information flows through all levels of an enterprise needs to be connected to other member of the textile process. This enables a flexible and fast production, feasible to deal with an order of a lot size. In markets like automotive, many of these ideas are already realised.

Also for internal company logistics, use of digital technologies and CPS do show potential to improve productivity of companies. Machine can communicate to each other and the operators. They can inform about their status and upcoming problems such as maintenance. In this case, the factory will reconfigure itself in order to fulfil the customers production order. Textile machines with open interfaces will be highly flexible and able to independently adapt status based on an overall information platform. Can, Core and warp beam and fabric will become carriers of information. This will lead to an autonomic textile process chains.


A main aspect of the production in the future will be the human-machine interaction. The use of smart personal devices, such as smart phones, tablets or head mounted display, do offer a huge potential for innovation. Smart personal devices can be used to make production more transparent by providing relevant production key parameters in a sophisticated way. In addition, guidance programs can lead to optimise production, or faster act in case of machine break downs. Also aspects of tele-maintenance, such as repair of machine supported by the machine produces are easier possible.


Self-Optimisation of textile machines is one path to Industry.4.0. Self-optimisation of the warp tension by using digital technologies has been investigated at ITA. The aim of this work was to enable the loom to set the warp tension automatically on a minimum level without reducing the process stability. First step of self-optimisation is to model the process. Therefore a method was developed within the cluster of excellence „Integrative Production Technology for High-Wage Countries“. Consequently, an automated sequence routine was created with the help of regression models for the model-based setting of the loom, and implemented in the weaving process. Thus, the loom was able to create its process model for a given process domain independently. Therefore, the machine ran an experimental design, and automatically determined at respective test points the warp yarn tension. The operating point was determined with the aid of quality criterion, such as that the warp tension becomes minimal. A system test within ITA, as well as a field test in industry demonstrated the functionality of the system, where warp tension was reduced within the self-optimised operating point [2].


In addition, further sensors are developed and integrated in the weaving process. A prototype system for automatic in-line flaw detection in industrial woven fabrics is presented. Where the state of the art systems operate on low-resolved (≈ 200 ppi) image data, we describe here the process flow to segment single yarns in high-resolved (≈ 1000 ppi) textile images. This work is partitioned into two parts: First, mechanics, machine integration, vibration cancelling and illumination scenarios are discussed, based on the integration into a real loom. Subsequently, the software framework for high precision fabric defect detection is presented. The system is evaluated on a database of 54 industrial fabric images, achieving a detection rate of 100% with minimal false alarm rate and very high defect segmentation quality [3].


4. Textile Products as Cyber-Physical Systems

Also textile products can act as CPS, in this case the products can be described as smart textiles. Textile touchpads, shirts with integrated electrodes and mattresses monitoring your sleeping quality are just a few examples of smart textiles. Smart textiles are a growing and fascinating field with enormous potential. The market of smart textiles looks extremely promising; experts forecast a double-digit growth within the next years.

However, success can only be guaranteed if we have reliable and up-scalable production technologies. To serve this need we at ITA explored various textile production processes and investigated their suitability for smart textile production.


The most explored textile technology for smart textiles is weaving. Due to its versatility and flexibility, weaving has been explored to produce textile-based sensors and transmission lines. It is possible to process a variety of functional yarns and yarn-like structures, such as stainless steel yarns, metal-coating yarns and metal wires, as well as optical fibres.


Embroidering is an attractive alternative for smart textiles as it can produce textile in 2D and 3D shapes. Especially with the Tailored Fibre Technology it is possible to generate complex forms of smart textile designs and handle even brittle materials. Especially when talking about textile electrodes, the moss stitching is an attractive technique, as it generates patterns sticking out of the fabric surface, hence, ensuring a good contact with the human skin.


For applications close to the human body, where comfort and breathability are very crucial properties, knitting is the perfect technology of choice. We investigated the knitting of silver coated yarns to shape textile electrodes in shirts monitoring, the heart rate, as well as the hydration status of a person. Major problems presented the damage of the coating layer on the yarn by the knitting needles and vice versa.


This technology is of special interest when it comes to structural health monitoring of ropes. We integrated monitoring systems into ropes to improve functional reliability by showing the actual load case of the ropes. To identify the optimal moment to replace the ropes, the grade of occurred damages and the expectable service life were displayed. For the future, we envisage to design and develop a collaborative tool consisting of software design tools, coupled to a digital dispenser printer allowing to create smart textiles by printing. This will enable to collaboratively design, layout, visualize, simulate and produce smart textiles. 2.

5. Conclusions

Use of digital technologies, and in a world of smart things, will change the way we produce textile. Machine with additional sensors, actors and cognition acting in a network can lead to the fourth industrial Industy 4.0. In addition, textile products will be enhanced by sensors and actors to smart textiles, and also communicating with the world. But aspects of security, especially on information, need to be taken into account. Still, some experts claim: “it’s already all available, we just have to use it”. 3.

6. Acknowledgement

The authors would like to thank the German Research Foundation DFG for their support of the depicted research within the Cluster of Excellence “Integrative Production Technology for High-Wage Countries”.


  1. Secretariat of the Platfom Industrie, Recommendations for implementing the strategic initiative INDUSTRIE 4.0 – Final report of the Industrie 4.0 Working Group, Frankfurt 2013,
  2. Gloy, Yves-Simon Modellbasierte Selbstoptimierung des Webprozesses, Aachen, Shaker, 2013 ; Zugl. Aachen, Techn. Hochsch., Diss., 2012
  3. Schneider, D.; Holtermann, T.; Neumann, F.; Hehl, A.; Aach, T.; Gries, T.: 2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA 2012). Proceedings Pages: 1494-9 Published: 2012 DOI: 10.1109/ICIEA.2012.6360960

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