INCLUSIVE
Smart and Adaptive Interfaces for INCLUSIVE Work Environment
Key Info
Basic Information
- Duration:
- 01.10.2016 to 30.09.2019
- Research Area:
- Sociotechnical Systems and Human-Machine Interfaces
- Status:
- Closed
Further Information
Contact
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- +49 241 80 99494
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Synopsis
Modern production systems require a high production rate combined with high quality and flexibility. The increasing complexity can be countered by the increased use of digital networked technologies. Despite the increasing level of automation of machines and robots, humans remain at the center of manufacturing, as they are still responsible for controlling and monitoring production processes. Humans interact with machines and robots through human-machine interfaces (HMI). With the implementation of new functions in the production system, there is also a wide range of operating modes and commands. A possible approach to improving the usability of complex production systems can be driven by a paradigm shift from “learning to operate the machine” to “adapting the machine to human capabilities and skills”.
Addressing this issue, this project did research into adapting the interaction between man and machine based on ergonomic concepts of information processing. This was realized by adapting the HMI to the characteristics of the respective employees and thus adaptively considering their individual abilities and skills. Furthermore, the development of an online and offline training platform supported workers in their independent machine operation.
Challenges
The INCLUSIVE project focused on the implementation of three interactive pillars: "Measure", "Adapt" and "Teach". The first pillar, Measure, determined the characteristics of employees and their limitations in processing information caused by mental stress during human-machine interaction. The identified parameters served as the basis for the interface adaptation, Adapt, which adapted to the previously identified personal profiles by adjusting the information output accordingly and providing additional interaction aids. Finally, the system provided each user with an individual training platform, Teach, e.g., to support unskilled or inexperienced workers.
Within this scenario, users often had difficulties interacting efficiently with the machine. This was especially true either for middle-aged individuals who felt uncomfortable interacting with a complex computer-based system or for young inexperienced or performance-challenged individuals who, among other things, also exhibited difficulties in dealing with such systems. Based on this adaptive interface, the consideration of specific target group persons such as older, performance-challenged or unskilled work persons proved to be another challenge that can be overcome.
Goals
The objective of the project was to create an integrative working environment that ensures high user acceptance and productivity with regard to automated production systems. Within the framework of the INCLUSIVE project, an innovative adaptive human-machine interface was developed, which reacts flexibly to the different prerequisites of the users. The interface compensates for possible limitations of the user in order for them to be able to optimally use their existing abilities. The aim was to develop a system that records the mental strain of a worker in real time during the operation of machines and evaluates it on the basis of a defined effort level. This system had to be able to adapt to the different production processes as well as to the workload of a worker in order to be able to provide support especially in critical moments. Furthermore, the system had to be able to support users with less experience and, above all, to train them in dealing with complex automated tasks. The objective of the project was to create an integrative working environment that ensures high user acceptance and productivity with regard to automated production systems. Within the framework of the INCLUSIVE project, an innovative adaptive human-machine interface was developed, which reacts flexibly to the different prerequisites of the users. The interface compensates for possible limitations of the user in order for them to be able to optimally use their existing abilities. The aim was to develop a system that records the mental strain of a worker in real time during the operation of machines and evaluates it on the basis of a defined effort level. This system had to be able to adapt to the different production processes as well as to the workload of a worker in order to be able to provide support especially in critical moments. Furthermore, the system had to be able to support users with less experience and, above all, to train them in dealing with complex automated tasks.
Methodology
During the implementation phase, the project had three application cases at industrial partner companies within Europe, which were part of a highly automated operation and would be where this kind of HMI interface would be used:
| Case 1 |
Woodworking machine for small workshop, typically run by older employees |
| Case 2 | Automated robotic cell, mostly operated manually, for bending sheets and used in companies in developing countries |
| Case 3 | Industrial plant for bottling and labeling |
First, a needs analysis was carried out. This was then used to create a conceptual design of a modular interface concept for stress measurement. Within the framework of a proof-of-concept study, the measurement methods determined were examined for their suitability for recording mental stress in the context of machine operation. The subsequently developed prototype was then evaluated at the three partner companies.
Results
Within the project, a prototype of a human-machine interface was developed that reacts adaptively to mental stress in real time by using eye-tracking and EDA sensor technology. Furthermore, online and offline training platforms were realized, which enabled the people in the respective target groups to intuitively learn how to operate the machine in a self-determined manner.
Funding
The project was funded by the European Union as part of the Horizon 2020 funding program.
Project Partners
|
Rheinisch-Westfälische Technische Hochschule Aachen (RWTH), DE |
|
Centralny Instytut Ochrony Pracy – Państwowy Instytut Badawczy (CIOP-PIB), PL |