Smart factories are characterized by smart processes and smart manufacturing systems that involve interlinked smart machines, smart tools, and smart products as well as smart logistics operations. These generate large amounts of data, which can be used for analysis and fault prevention, as well as for the continuous improvement of both manufacturing processes and products. However, a major challenge for manufacturing is the quality and reliability of data. To address the challenge of data reliability, the sensors, actuators, and instruments used at various levels of integration in the manufacturing process – need to provide adequate levels of data accuracy and precision. Measurement traceability should ensure optimal manufacturing quality. DAT4.ZERO aims to develop and implement a Digitally enhanced Quality Management (DQM) system, characterized by real-time feedback and feed-forward loops using robust, quality assured data that offers a huge potential for the advancement of the Zero-Defect Manufacturing (ZDM) paradigm. At the heart of DAT4.ZERO is a DQM System that gathers and organizes data from a Distributed Multi-sensor Network, which, when combined with a DQM Toolkit and Modeling and Simulation Layer and further integrated with existing Cyber-Physical Systems (CPS), offers adequate levels of data accuracy and precision for effective decision-support and problem-solving – utilizing smart, dynamic feedback and feed-forward mechanisms to contribute towards the achievement of a near zero-defect level of manufacturing in smart factories and their ecosystems. This shall be achieved through the following objectives:
1) To develop and demonstrate an innovative DQM system and deployment strategy for supporting European manufacturing industry in realizing a near-zero defect level of manufacturing in highly dynamic, high-value, high-mix, low-volume production contexts.
2) The effective selection and integration of sensors and actuators for process monitoring and control within intra- and inter-organizational production processes, systems and networks.
3) Developing a DQM platform with an architecture that provides reliable and secure data management and knowledge extraction to ensure integrity of data.
4) Creating strategies for advanced, real-time data analysis and modelling – exploiting artificial intelligence (AI) and CPS capabilities combined with smart human-in-the-loop technologies for rapid qualification, configuration, adaptation, and reconfiguration of multi-stage process chains within and across organizational boundaries.
5) Five industrial pilots; developing optimized metrology and control strategies applicable to multiple domains/sectors, demonstrating first pass yield improvements, improved product quality and improved data reliability.
Overall, DAT4.ZERO will support the European factories of the future by increasing equipment productivity through rapid detection and correction of product- and process errors, reducing ramp-up time, decreasing time-to-market of existing and evolving high-value products and increasing product quality, also reducing quality costs, scrap, and rework.
