Retrofit Concept for Textile Production

Abstract

In production, an intelligent analysis of the data provided along the production line bears huge potential for increasing process efficiency and reducing production costs. The (continuous) collection of relevant data is a crucial precondition for every Industry 4.0 or smart technology. While new machines have internal controllers and sensors to meet those requirements, this is usually not the case for machines being already in use. Especially in the textile industry, it is often standard to keep old machines since the manufacturing methods themselves haven't changed significantly over the past decades. Hence, the successful exploitation of digitalization advantages requires these companies to first develop and implement a digitization strategy. In this paper we present a concept which allows to develop modular, scalable, flexible solutions considering the whole digitization process from data acquisition to storage. The concept is complemented by a guideline for its application in industry. Experience from a prototypical application in a textile company is described. The concept enables companies to determine the various conditions and requirements for digitization, to analyze different possibilities and to deduce scenarios that lead to a solution for the effective utilization of Industry 4.0 technologies.

Retrofitting-Based Development of Brownfield Industry 4.0 and Industry 5.0 Solutions

“…The first step in brownfield development is enhancing the data acquisition from dated equipment that often has varying degrees of instrumentation and automation and can be categorized by deploying the additional sensors in the first level of the IoT reference model. Legacy machines lack ways to monitor their processing parameters [22]; fortunately, sensor technologies nowadays are well-advanced for that purpose [53]. In many cases, additional actuators are added to enhance the automation at the field level and replace the human manipulation [54].…”

“…In the context of a textile retrofitting project [22], the authors could not utilize the cloud solution in the concern of data security but a centralized server instead. This problem raises the fact that a full-scope IoT architecture may not apply to every legacy system without considering its intrinsic characteristics.…”

“…A good agenda with the concurrent-engineering approach allow the retrofitting team to understand the digital transformation, clearly define their system to support their tasks, and build up solution [58]. Discussions within the team are vital for the retrofitting project in particular, but also for a successful digitization process in general [22]. Other requirements can be gathered by interview or questionnaire as proposed in Ref.…”

“…[76], vital process parameters affecting product quality should be considered first. In the textile industry, parameters such as yarn tension, surface quality, temperature, humidity need to be measured [15], [22]. For food industries, the precise temperature is a special requirement for various chemical reactions; thus, temperature sensors should be deployed [73].…”

“…The most challenging obstacle of a retrofitting project is that in a legacy system, there are machine tools from different manufactured times, thus having different communication protocols [21]. Due to the lack of sensors and actuators, process control needs to be conducted manually by observing, sensing, estimating, and adjusting the machine parameters [22]. Together they formed a system with minimal connectivity that is not suitable for IoT and data-driven management approaches, which need data collection and analysis as prerequisites [23].…”