Also referred to as 3D printing.

Flexible Sheet-to-Sheet (S2S) and Roll-to-Roll (R2R), building in plastics electronics, large volume patterning at nanoscale (photolithography) and new materials and greater use of space on CMOS.

Integration of non-conventional technologies (e.g. laser, ultrasonic) towards the development of new multifunctional manufacturing processes (including in process concept: inspection, thermal treatment, stress relieving, machining, joining

Methods for handling of parts, metrology and inspection require development also to ensure ability to manufacture at scale (volume) with high reliability.

Shaping technology such as forming and machining, to address challenges related to “difficult to shape” materials and to explore new processing methods to achieve nano-sized microstructure components.

See https://www.effra.eu/digital-manufacturing-platforms

The Internet of Things (IoT) is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers (UIDs) and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction.  (from https://en.wikipedia.org/wiki/Internet_of_things)

Production equipment does not yet take full advantage of the benefits that new and advanced materials offer, and factories of the future will need more advanced equipment to meet the requirements for energy efficiency and environmental targets and to meet new demands for a connected world. The future will therefore see modern, lightweight, long-lasting/flexible and smart equipment able to produce current and future products for existing and new markets. There will be a step change in the construction of such equipment, leading to a sustainable manufacturing base able to deliver high added value products and customised production. Increased smartness in the manufacturing equipment also enables a systems approach with machines able to learn from each other and impacting on the human-machine interface.

Continuous monitoring of the condition and performance of the manufacturing system on component and machine level, enables sustainable and competive manufacturing, also by introducing autonomous diagnosis capabilities and context-awareness. Detecting, measuring and monitoring the variables, events and situations will increase the performance and reliability of manufacturing systems. This involves advanced metrology, calibration and sensing, signal processing and model-based virtual sensing for a wide range of applications, e.g. event pattern detection, diagnostics, anomaly detection, prognostics and predictive maintenance.

https://en.wikipedia.org/wiki/Control_system

Control technologies will be further exploiting the increasing computational power and intelligence in order to come forward to the demands of increased speed and precision in manufacturing. Advanced control strategies will allow the use of lighter actuators and structural elements for obtaining very rigid and accurate solutions, replacing slower and more energy-intensive approaches. Learning controllers adapt the behaviour of systems to changing environments or system degradation, taking into account constraints and considering alternatives, hereby relying on robust industrial real-time communication technologies, system modelling approaches and distributed intelligence architectures.

Intelligent components enable the deployment of safe, energy-efficient, accurate and flexible or reconfigurable products and production systems. This includes the introduction of smart actuators and the use of advanced end-effectors composed of passive and active materials. Energy technologies are gaining importance, such as (super)capacitors, pneumatic storage devices, batteries and energy harvesting technologies.

Engineering is the creative application of science, mathematical methods, and empirical evidence to the innovation, design, construction, operation and maintenance of structures, machines, materials, devices, systems, processes, and organizations. (from https://en.wikipedia.org/wiki/Engineering)

Workers must undertake regular training to acquire and refresh the skills that are required due to new procedures. Providing adaptive tools that deal with human variability for training purposes will facilitate the learning process. Mixed Reality (MR) technologies allow the adaptability of training and guidance to changing circumstances (e.g. new devices, new procedures, new workers, workers with different skills, etc.).  (Source)

 

The Social and collaborative operator concept includes, on the one hand, solutions to support participatory design and knowledge sharing and, on the other hand, human-robots collaboration solutions. Knowledge sharing and communication are key aspects in the industrial work context.  (Source)

The Super-strong operator concept involves the usage of wearable apparatus, such as exoskeleton devices, that have the potential to reduce the operator’s physical fatigue, increase their strength, overall safety and productivity
Health and happy operator.  (Source)

The Healthy and happy operator concept can be supported by solutions that monitor physical and mental fatigue, and solutions that give the worker motivating feedback. While many traditional ergonomics and physical safety challenges disappear when operator work becomes knowledge based, new challenges related to cognitive ergonomics may arise as a result of higher mental workload. (Source)

The smart and analytical operator is assisted by an Intelligent Personal Assistant (IPA). This is a software agent or artificial intelligence that has been developed to help a smart operator in interfacing with machines, computers, databases and other information systems as well as managing time commitments and performing tasks or services in a human-like interaction.  (Source)