| Organisation: | ALMA MATER STUDIORUM-UNIVERSITA DI BOLOGNA |
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Flexible manufacturing is a growing request that often in conflict with the need of massive production and high-quality standards. To improve automation capabilities is a possible way to fulfill all these goals at once and achieve strategic autonomy.
Increasing autonomy in manufacturing automation is a goal that should be pursued in order to implement the main principle of human-centered Industry 5.0. Increasing autonomy and adaptation of machines, possibly with an interaction among different machines, would give humans the possibility to move to more intellectual tasks.
The remaining challenge is to develop new methods for optimizing processes by combining standard control approaches with data-driven AI tools.
Remanufacturing is fundamental for circularity but a big part of the problem is in materials, product design and production processes.
Pushing toward a highly connected and distributed intelligence can improve scalability of manufacturing technologies while ensuring zero-defect solutions thanks to the shared processing of a larger number of data.
The remaining challenge is distributed on-edge computing and intelligence.
Optimal manufacturing can be achieved by pushing toward optimization approaches that take into account data by exploiting novel AI approaches. However, formal verification of the data-based AI tools is mandatory.
Trusted AI and digital twins are important tools but for sure not the only one needed to face the problem.
The remaining challenge is to combine model-based optimization and control approaches with AI tools to increase trustworthiness.
We suggest adding “trusted and human-centric AI” in the title.
New solution in the Industry 5.0 paradigm need to allow humans to extend their capabilities in interaction with machines and environments. This is possible by designing new virtual prototyping and augmented reality solutions.
We suggest adding “inclusive, human centric and socially sustainable manufacturing”.
Remaining challenge: machine and robotic simulators with advanced capabilities.
There are many manual activities in production that can benefit from cognitive augmentation to be more inclusive, to decrease workers cognitive stress and then decrease the impact of human errors.
We suggest adding “inclusive, human centric and socially sustainable manufacturing”.
Actual production is mostly based on raw materials availability and does not consider reusability in the design of products and production processes. A big impact can be generated if new products will be designed starting from end-of-life products and facilitating the reuse of the materials at end-of-life.
Remanufacturing is fundamental for circularity but a big part of the problem is in materials, product design and production processes.
Pushing toward a highly connected and distributed intelligence can improve scalability of manufacturing technologies while ensuring zero-defect solutions thanks to the shared processing of a larger number of data.
The remaining challenge is distributed on-edge computing and intelligence.
By increasing autonomy and by adopting optimization strategies, production technologies can take into account constraints by design and be more responsive to changes.
To achieve these goals simultaneously represents a serious challenge because it requires to foresee market requirements and understand how production technology can influence the sustainability of the value network.