Harnessing data to deliver more sustainable manufacturing
Manufacturers are continuously redesigning and adjusting their production lines to produce goods specific to clients’ requirements, and to ensure optimal use of resources. However, not all factories are able to make full use of all the data being generated, due in part to technical complexity and cost. “A key aim of the i4Q project was to develop tools capable of capturing and managing factory data,” explains project coordinator Georgia Apostolou from the Centre for Research & Technology Hellas (CERTH) in Greece. “We wanted to develop simulation and optimisation tools that create an integrated approach to zero-defect manufacturing.”
Digital tools
The i4Q project worked with manufacturers to identify and understand key production processes, and to pinpoint where production line problems occurred. This led to the development of user-friendly tools based on five key data issues: sensing where problems occur; communication of these problems in real time; computer analysis and simulation; data storage; and optimisation. “Each manufacturer has its own problems,” says Apostolou. “By applying internet of things (IoT)-based reliable industrial data services and AI, we wanted to create tools that would be easy to use and adaptable to specific challenges.” A suite of 22 tools was created, each of which can be tailored to the needs of specific manufacturers. The tools cover the data life cycle, from collection and storage through to analysis and distribution. Web-based software tools to help manufacturers visualise information were also developed, with a key emphasis on user-friendliness.
Real-world trials
The suite of tools was installed, tested and validated in six factory production lines. These factories produce industrial metal equipment, specialised wood equipment, white goods, metal machining tools, ceramics and plastics. The trials provided invaluable feedback, helping the production team to make improvements as the project advanced. “Take the ceramics manufacturer, as an example,” adds Apostolou. “The production process involves shaping clay into plates, putting them through an oven, and applying a liquid glazing material. A common problem is that sometimes too much liquid is applied to each plate. This creates an uneven surface that doesn’t look appealing, leading to wastage.” An inability to predict, monitor and verify glazing in real time can lead to hundreds of plates having to be destroyed, costing the manufacturer time, material and money. To counter this, the i4Q project installed sensors at critical stages of the production line. Data was analysed in real time, and alerts sent to machine operators if a potential error was detected. This enabled production to be immediately paused and to optimise the process.
Power of big data to reduce waste
The i4Q team is currently commercialising several of the more advanced data tools through the creation of project-related start-ups – such as CDXi solutions – and marketplaces, such as the i4FS platform. This enables project partners to promote their tools and connect with potential customers. “Some industrial project partners also want to continue using the tools beyond project completion, and have identified the need for extra features, something that we are currently working on,” says Apostolou. The i4Q team believes that harnessing the power of big data will help industrial manufacturers to reduce waste, improve product quality, optimise energy use and achieve more sustainable production. Ensuring the tools are easy to use will be critical for encouraging their widespread adoption among businesses looking to upgrade their production lines. “Moving towards greener manufacturing with less waste is essential,” remarks Apostolou. “Innovations from the i4Q project will keep shaping the smart manufacturing field. These advancements are expected to lead to fully integrated, defect-free production environments, enhancing competitiveness and sustainability in the manufacturing sector. By showing the benefits of working with data, we hope to get more companies on board.”
Keywords
i4Q, manufacturing, data, IoT, AI, factory, waste, ceramics, zero-defect
