Experts: Daniel Liebhart (ZHAW), Philipp Schmid (CSEM)
Connected machines are a potential game-changer in the manufacturing industry because they enable new production processes and business models. The concept requires improved flows of information and data between the individual components and systems within production processes. For a high-wage country like Switzerland, the networking of machines will develop into a key technology. For this to succeed, there is a need for specialists with knowledge and skills in ICT, as well as in mechanical and systems engineering.
Picture: Lucian Alexe, Unsplash
In the "connected machines" or "networked production" approach, machines and production systems are interconnected, such that they exchange data and information. Ideally, the individual machines and systems are connected to form an overall system, a smart factory, which relies on continuous flows of data and information, and adjusts production in response to environmental influences. Another conceivable application is the connection of spatially separate machines, enabling both production advantages and new services.
In a way, the connected machines approach is an industrial version of the Internet of Things (IoT), also called the Industrial Internet of Things (IIoT). The challenges for IIoT applications are different to those for conventional non-industrial IoT applications. They reside in the capture and mapping of the production process (see article Digital twins) and thus not in power supply, data transmission or safety, as with conventional IoT applications. Applications in the field of connected machines enable the automation and optimisation of processes, but extend, at least in theory, to concepts like predictive quality, which assumes that the quality of the goods produced can be estimated in advance and improved if all relevant parameters are known.
Connected machines can be used in all areas of the manufacturing industry and at many points along the value chain: in the processing of raw materials and primary products, in the assembly of products from components and in logistics, but also in services and support, such that new business models at the user end arise from the networking of machines and devices. Such digitalisation of production processes also makes it possible to optimise existing workflows. Inline quality control is conceivable, which means that quality control of components and goods is undertaken during each production step – rather than as a downstream step after production, as in traditional approaches. Connected machines also enable smart maintenance. This means that maintenance strategies and predictions of possible breakdowns emerge on the basis of conditions indicated by data.
In terms of the development of individual technologies, Switzerland is in a good position. Universities and industry are both pushing ahead with technology development. However, commercialisation of approaches from the field of connected machines is only just beginning. According to one estimate, only 10–20 percent of companies in the manufacturing industry have piloted or carried out trials with regard to networking their production.
The digitalisation of production with connected machines will become a key technology for industries in high-wage countries like Switzerland. Clever use of such connected machines would improve the quality, the efficiency and thus the sustainability of production. Alongside reduced costs, improving the flexibility or even the robustness of production processes is also a conceivable goal of the digitalisation of production processes. If this is achieved, customer satisfaction will increase because products will be of higher quality, cheaper or available sooner. Predictive quality assumes that the quality of the goods produced can be precisely adapted to customers’ needs if all the parameters relevant to the quality of a product are known. This requires the possibility of controlling the corresponding processes and all relevant parameters in a targeted manner.
In the manufacture and commercialisation of connected machines, challenges are emerging on two levels: The individual machines and their components must be connected to form an intelligent overall system that reacts quickly to changes in production. This requires that the collected data is of sufficiently high quality and can be transmitted and assessed correspondingly quickly.
All universities and research institutes are conducting activities in this area. Some large companies are also active in the field of connected machines. However, there is a need for action in academic teaching and the vocational training of specialists. Knowledge and skills must be cultivated – especially at the intersection between ICT, mechanical and systems engineering, and specific knowledge from the respective sectors in which connected machines are used. This is because machines can only be meaningfully networked and put to use if all three of these areas of knowledge and competence are covered.
