Paving the way to Industry 4.0 for SMEs
Industry 4.0 and digital tools have so far been used relatively little in small and medium-sized enterprises (SMEs). There are many reasons for this, ranging from a lack of personnel capacity or a lack of employee know-how for realisation and implementation to scepticism about the added value of digital solutions. The WIN4KMU project therefore aimed to develop practical solutions that would introduce SMEs in particular to Industry 4.0 easily and cost-effectively in order to strengthen and maintain their market position and competitiveness.
Digitalisation and the emerging platform economy are opening up new opportunities for industry to develop innovative products, services and business models. One enabler of this transformation is the seamless digitalisation of production along the value chain. Basically, this involves connecting machines and systems across locations and companies in such a way that industrial processes can be automated end-to-end and the data obtained can be used to generate value. While an important component of this “economy” has already emerged in the form of cloud-based Industrial Internet of Things (IIoT) platforms, data integration and its direct use in production is only progressing slowly.
The WIN4KMU project therefore focused on a standardised and universal cloud connection of SMEs to IIoT platforms via 5G, the development of flexible standards for cross-manufacturer data extraction from machines and the low-cost extraction of data from machines and its transmission to a cloud.
The most common network protocols were first evaluated for a standardised and universal cloud connection. Building on this, a start was made developing a suitable infrastructure for transmitting data from the machine to the cloud, with transmission via the 5G mobile network being tested. In this way, the data flow was taken into account in the event of poor network infrastructure via intermediate storage at the connector or edge device level. This allowed the data to be stored even if the connection was interrupted and transferred consistently after the connection was re-established, enabling secure and stable data transfer to the cloud.
© IKVThe project then focused on the development of standards and options for cross-manufacturer data extraction, known as integration service devices. In addition to identifying relevant measured variables and their measurement precision, a demonstration sensor system was developed for this purpose. This sensor system enables low-cost data extraction from the machine. By implementing the system in the environment of the Plastic Innovation Center 4.0, the system could be tested.
The test provided key findings and identified challenges for implementation in the SME-dominated plastics industry: The initial implementation and configuration of the system, including the necessary mapping of the available data points for standardised variables, is usually carried out manually. Another challenge is mapping the machine parameters to the standardised service parameters. This can either be solved by creating machine templates or by using standardised machine interfaces such as EUROMAP77 or asset administration shells in plastics processing.
In order to enable low-threshold access to the developed solution, a concept for a minimal viable product based on the containerization solution Docker was developed. This enables implementation or depolyment in four, modularly usable services that can be configured centrally (Fig. 1). This allows the following scenarios to be instantiated as required:
- No existing system: all four services (database, connector, back-end and front-end)
- Central SQL database available: only connector, backend and frontend
- Data collection in place: only back- and frontend
Funding and project data
Project title: Paving the way to Industry 4.0 for small and medium-sized enterprises
Short title: WIN4KMU
Project duration: 07/2021 – 09/2024
Project partners: SHS plus GmbH (SHS), Teleport Köln GmbH (Teleport), Chair of Production Systems (LPS) at the Ruhr University Bochum
Project funding by: Ministry of Economic Affairs, Innovation, Digitalisation and Energy of the State of North Rhine-Westphalia as part of the Leading-Edge Cluster for Industrial Innovation (SPIN), funding code EFO 0015A-E