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

The Zero Defect Manufacturing strategy is based on a framework for multi-stage production that employs technologies such as:
– 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.
Industry 4.0 is the current trend of automation and data exchange in manufacturing technologies. It creates what has been called a “smart factory”. Within the modular structured smart factories, cyber-physical systems monitor physical processes, create a virtual copy of the physical world and make decentralized decisions. Over the Internet of Things, cyber-physical systems communicate and cooperate with each other and with humans in real time, and via the Internet of Services, both internal and cross-organizational services are offered and used by participants of the value chain.
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.

 

 

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 Professional
Global Engineering and EPS Director
Within the GO0D MAN project the great quantity of data coming from internal and external testing measurements will be matched together. Data will be analyzed in order to give adequate reports, anticipating warnings about future problems and proposing right countermeasures.

Fernando Pineu

Volkswagen Autoeuropa
Production System Manager
This project is perfectly aligned with our strategy of high-performance digital productive process and thus towards Industry 4.0 once will allows: to convert some current manual processes to automatically digital ones, to reach a more flexible and adjustable production system and a better way to deal with the increasingly product complexity.

Saverio Zitti

Zannini
Italy R&D Manager
Thanks to GO0D MAN project, real-time detection of deviating processes and self-adjustment of process parameters by means of data and knowledge management tools will be possible and will permit to realize in the practice the Zero Defect Manufacturing target.

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Our Partners 

  • BOC
  • Electrolux
  • IPB
  • Loccioni
  • Nissatech
  • Uninova
  • UNIVPM
  • Volkswagen Autoeuropa
  • Zannini
We join the 4 ZDM Cluster