Mechatronics

Mechatronics, which is also called mechatronic engineering, is a multidisciplinary branch of engineering that focuses on the engineering of both electrical and mechanical systems, and also includes a combination of robotics, electronics, computer, telecommunications, systems, control, and product engineering. (From https://en.wikipedia.org/wiki/Mechatronics)


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.
  • Smart and functional materials Smarter equipment and manufacturing systems with self-diagnosis (temperature, vibrations, noise) and embedded sensing, memory or active architecture, with functional materials allowing them to adjust work processes and operations to variances in structure, shape and material composition (right first time manufacture).. Capture of machine data through this inherent ‘smartness’ for communication between machines (for M2M), at factory level and through supply chains for a systems approach to manufacturing and meeting customer demand. New equipment components taking advantage of new designs and advanced materials (e.g. gears and transmissions providing longer lifetime of equipment, active surfaces that can embed and release lubricant when needed (higher pressures or temperatures))

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)

  • System modelling, simulation and forecasting

    Simulation (often referred to as digital twins) is the imitation of the operation of a real-world process or system. The act of simulating something first requires that a model be developed; this model represents the key characteristics, behaviors and functions of the selected physical or abstract system or process. The model represents the system itself, whereas the simulation represents the operation of the system over time. (from https://en.wikipedia.org/wiki/Simulation)