The LCAMP Observatory seeks to provide up-to-date and user-friendly information on the current skills trends, gaps and skills prediction in Advanced Manufacturing.
Industry 5.0 paradigm is emerging in Europe towards a more human-centric, resilient and sustainable industry.
Transformations are not technology-driven but simultaneously technology and human-centric.
The EU’s investment in research and innovation programmes, emphasizes the need for digital skills of students and workers as well as the adoption of new technologies to adapt to the changes brought by Industry 4.0.
The application of Artificial Intelligence (Al) techniques in manufacturing has made it possible to formalise complex multivariate knowledge of machine and process conditions. These tools enhance the work of the operator, which also increases his value as a technician. The massive generation of data through Internet of Things (loT) is giving Al a huge boost in the industrial sector.
Collaborative robots (cobots) and autonomous mobile robots (AMR) have already changed the way humans and machines work together, but the use of Cyber Physical Systems (CPS) will take this to a new level. Increased interaction between the worker and the technological environment enhances safety by reducing risk and preventing accidents.
By incorporating ergonomic principles and digital technologies into vocational education, students learn to thrive in a rapidly changing manufacturing landscape.
This includes training in ergonomics, human factors and digital technologies, as well as getting hands on experience with digital workstations and equipment.
The Advanced Manufacturing sector is facing a green transition, including energy efficiency, energy neutrality and ecological emphasis. Green skills and circular economy concepts must be included in all the training programmes. Therefore, Green skills need to be defined.
Learning analytics is the opportunity to identify potential gaps in an organization’s skill set and to develop training programmes to address those gaps. Additionally, analytics provide valuable data to help companies assess the effectiveness of their training programs and make necessary adjustments. It is rarely used in Vocational Education and Training (VET) centres.
The resource efficiency in terms of material saving and reduction of wastes make metal forming processes an attractive alternative for producing complex parts. Furthermore, the improvement of quality and efficiency due to digitalization increases this methods opportunities.
Metal additive manufacturing, concretely Selective Laser Sintering (SLS), is a growing and developing technology that requires specific skills and knowledge to design parts and operate equipment. The shift to automated manufacturing processes such as SLS requires retraining of existing staff in order to remain employable.
The creation phase of predictive models, which is fully automated, in many cases encourages companies to engage in predictive maintenance.
A culture for Lifelong Learning is not developed enough among students and workers. VET centres and companies must place mechanisms towards strengthening Lifelong Learning pathways.
A global deployment of 5G technology eliminates the need for distributed edge computing, enabling lower costs for data mining and management on servers in the cloud. 5G enables better communication and supports the maturity levels in digital transitions of companies
Cybersecurity is of strategic importance for SMEs as a result of the in-depth digital connectivity of all the value chains.
3D scanning is a core element in reverse engineering and requires specific equipment and software that needs to be made more affordable to Vocational Education and Training (VET) Centres which are incorporating 3D scanning training programmes into their courses. This requires more collaboration between trainers and the industry to keep such crucial training processes going.
Collaborative immersive virtual environments are a safe and useful tool for training on complex or risky processes and establishing useful digital twins in advanced manufacturing. In addition, new solutions simplify the process of creating teaching materials, giving teachers and trainers a leading role.
Digital twin (DT) technology is an emerging valuable tool for Vocational Educational Training (VET) as it is used to create digital replicas of physical assets and processes that are monitored and analysed in real time.
Ai Ml Big DataEdge Cloud Blockchain QuantumRobotics AutomationDigital TwinsIndustrial MaintenanceSensor EngineeringAutomation RoboticsQuality ControlIndustrial OperationsData Analysis
