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Aims & Goals

Sectors such as aerospace, automotive, wind power, capital goods are characterized, on the one hand, by complex products and small scale production that require high flexibility and on the other hand by an increasing pressure to raise productivity rates. Furthermore manufacturing systems need to deal with an ever-changing environment due to short term changes caused by human or production related variability or long term changes caused by market`s demands and company’s strategy, technology advancements and demographic trends. In this context assembly systems need to put together humans and automation taking advantage of each other’s strengths.

A4BLUE aims at the development and evaluation of a new generation of sustainable, adaptive workplaces dealing with evolving requirements of manufacturing processes, and the introduction of automation mechanisms that are suitable for flexible and efficient task execution in interaction with human workers by optimizing human variability through personalised and context aware assistance capabilities as well as advanced human-machine interfaces. The proposed solution will be instantiated in two real industrial scenarios (AIRBUS and CESA) and two lab scenarios (IK4-TEKNIKER and RWTH Aachen) that have been selected according to their representativeness and impact.
To support this objective the main goals to be achieved by A4BLUE are:

  1. adaptability by providing an open, secure, configurable, scalable and interoperable adaptation management and assistance system (A4BLUE adaptive framework) that allows effortless integration of heterogeneous hardware and software components and is able to adjust the behavior of workplace parts according to changes;
  2. interaction by providing a set of safe, easy to use, intuitive and personalized and context aware multimodal human-automation interaction mechanisms;
  3. sustainability by providing methods and tools to determine the optimal degree of automation of the new assembly processes that combine and balance social and economic criteria to maximize long term worker satisfaction and overall performance.