AI in human-centred manufacturing

Background and Problem

The WASABI project is developing intelligent digital assistance solutions that enable small and medium-sized enterprises (SMEs) to recruit new employees more quickly and to train and upskill them efficiently, with a focus on the activities of skilled work. These solutions are intended to allow employees to interact with complex software using natural language and thus to meet the requirements placed on them. In addition, users are enabled to build up and expand their knowledge intuitively through dialogue and in their preferred language, and to improve their competences in the areas of human–AI collaboration and digital media through training offers provided via a Digital Innovation Hub network. In doing so, the WASABI solutions support tasks such as situation analyses, needs identification, the planning and delivery of continuing training measures and the evaluation of their impact.

A central component is the digital intelligent assistant (DIA) – an anthropomorphic, task-oriented, conversational AI based on Mycroft and Rasa. Access to these digital assistance solutions will be as simple as selecting and configuring apps from an online store. The interoperability of the solutions minimises dependence on any one provider and maximises the use of information. In addition, new AI-focused training services will be available to employees, enabling them to familiarise themselves with the solutions and to learn more about the opportunities, risks and limits of AI in manufacturing. A particular focus of the project is on ensuring that the digital assistance solutions are integrated into the emerging European legal framework for AI and that they are affordable and user-friendly for small manufacturers too.

Research question

• According to the Technology Acceptance Model (TAM), how do perceived usefulness and ease of use influence the acceptance of voice assistance systems in small and medium-sized enterprises?

• What effect does the perceived adaptability of voice assistance systems have on acceptance and willingness to use them among different employees at shop-floor level?

• Which success factors for the use of voice assistance systems in SMEs can be identified?

Approach

In the context of the project, questionnaires are being developed, among other things, and distributed to employees. This will provide initial findings for the assessment of the perceived usefulness and ease of use of the voice assistance system. In addition, semi-structured interviews are being conducted with employees of the participating SMEs. The aim is to build an understanding of the social influences and subjective norms that may affect the acceptance of voice assistance systems. It is also being examined how much weight these concerns carry compared with other factors such as usefulness and ease of use, and what measures can be taken as the project progresses to dispel these concerns and increase acceptance. Alongside this, a quasi-experimental study is being conducted with a demonstrator. Here, employees first solve a task conventionally, without the use of an assistance system. In a second step, the tasks are then solved with the help of the voice assistant. The aim is to gain insights into efficiency and acceptance in direct application.

Results

The interviews are intended to provide detailed insights into individual and collective perceptions of, and expectations towards, new technologies in general and a voice assistant in particular. The complementary analyses of the survey results are intended to yield conclusions about the acceptance of voice assistance systems and the factors influencing the use of the assistance solutions. Ultimately, the results are intended to identify ways and opportunities for deploying voice assistance systems, and the benefits they offer, in the context of skilled work.

Dissemination and Transfer Activities

• Presentation and paper at the 18th Annual Conference of the Ingenieurpädagogische Wissenschaftsgesellschaft, 2024

• The underlying didactic concept for the voice assistance system (COALA) is listed as a key innovation in the European Union's Innovation Radar.