Agent Oriented Zero Defect Multi-stage Manufacturing
The quality of products is a key factor for success in manufacturing industry along with the reduction of material waste, re-works, rejects and stocks, leading to a demand for the development of zero-defect manufacturing strategies at system level.
GO0D MAN project constitutes a real world implementation of the Industry 4.0 paradigm, through the integration and convergence of technologies for measurement and quality control, for data analysis and management, at single process and at factory level.
The ultimate goal is to develop a production strategy that can guarantee high quality of products without interfering, actually improving, the production efficiency of the entire system.
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The Zero Defect Manufacturing Strategy
– Integration of process control and quality control by using an agent-based CPS architecture.
– Smart inspection tools designed to exhibit at local level real-time adaptive behaviors to keep measurement uncertainty under control even in case of variations of process/product parameters, pre-process data to derive synthetic quality indicators, implement self-diagnosis and self-calibration to maximize the confidence level of the sensors output.
– Data-driven approach supported by advanced ICT and big data analytics tools for real-time data processing and analysis by data mining at both local and global levels.
There are 4 design principles in Industry 4.0. supporting companies in identifying and implementing Industry 4.0 scenarios:
Interoperability The ability of machines, devices, sensors, and people to connect and communicate with each other via the Internet of Things (IoT) or the Internet of People (IoP).
Information transparency The ability of information systems to create a virtual copy of the physical world by enriching digital plant models with sensor data. This requires the aggregation of raw sensor data to higher-value context information.
Technical assistance First, the ability of assistance systems to support humans by aggregating and visualizing information comprehensibly for making informed decisions and solving urgent problems on short notice. Second, the ability of cyber physical systems to physically support humans by conducting a range of tasks that are unpleasant, too exhausting, or unsafe for their human co-workers.
Decentralized decisions The ability of cyber physical systems to make decisions on their own and to perform their tasks as autonomously as possible. Only in the case of exceptions, interferences, or conflicting goals, are tasks delegated to a higher level.
Industry 4.0 Clusters and Projects
Agent-based CPS architecture
The solution is able to implement process and quality control at local and global levels in multi-stage manufacturing, to achieve modularity, to develop adaptation and reconfigurability whilst reducing complexity.
Smart inspection tools
Keep measurement uncertainty under control, even in case of variations of production parameters, pre-process data to derive quality indicators, implement self-diagnosis and self-calibration to maximize the confidence level of the sensors output.
Data-driven approach
Enable real-time and early detection of production quality deviations and trends, establish correlations between upstream and downstream process variables, allow updating downstream process parameters and acceptance thresholds for quality checks.
Case studies
Quotes from the use case

Stefano Rossi
Electrolux ProfessionalGlobal Engineering and EPS Director

Fernando Pineu
Volkswagen AutoeuropaProduction System Manager

Saverio Zitti
ZanniniItaly R&D Manager