Context Sensitive Assistance (CSA)

The »Context-Sensitive Assistance« project was carried out as part of a cooperation agreement between Contact Software GmbH and Fraunhofer IPK. The project proved the feasibility of implementing context-sensitive assistance systems in the field of smart maintenance based on an IoT platform (E4IoT) provided by Contact Software.

Context sensitivity refers to the inclusion of information that specifies the state of individual components, devices, machines or systems and their environment. This context information is stored centrally in E4IoT as digital twins and made available dynamically to mobile assistance applications. The implementation of the assistance system was based on the specific application example of a spindle exchange in order to simulate various process steps that occur during maintenance activities.

The focus was not only on integrating dynamic context information from E4IoT, but rather on providing process models. These should not only reflect the operational view of maintenance processes, but also enable the interface to E4IoT and thus the automatic integration of context information.

The use case was implemented in two different environments. The first environment used Fraunhofer IPK's MO²GO software tool to create the process models and an extension of the existing service case app to visualize the process as an Android application. The second environment is built on the open source tool Camunda BPM. In this environment, both the process modeling and the downstream visualization took place as a web application.

In the course of the use case, so-called process patterns could be developed, which should enable modeling alternative use cases. The development of such process patterns in the field of maintenance is a subject of current research.

Benefit for Industry

Context-sensitive assistance systems offer the following added value to industry:

  • Intercept problems of structural change in society and counteract the shortage of skilled workers.
  • Counter increasing complexity in production
  • Enable language-independent qualification
  • Promote flexibility in the application of know-how and knowledge transfer
  • Supporting an aging society in further training or retraining measures
  • Improve and accelerate processes
  • Support collaborative work through digital tools

In the research project, the assistance systems were generated from process models. The underlying goal is to flexibly create maintenance processes from corresponding models, whereby the processes are represented in mobile applications and interaction with other software is also possible. The focus is thus on process experts who have in-depth technical expertise about maintenance activities, but little programming knowledge to represent this knowledge in the form of a digital application. The solution explored in the project lays the foundation for a no-code platform for generating such digital applications.

Interesting for:

  • Manufacturing companies
  • Machine tool manufacturers
  • Small and medium-sized companies (SME)

You are looking for:

  • Maintenance
  • Smart maintenance
  • Assistance systems
  • IoT
  • Skills shortage

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