Skills Composition Framework for Reconfigurable Cyber-Physical Production Modules

TL;DR

This paper introduces a framework using behavior trees for skill composition in reconfigurable cyber-physical manufacturing modules, enabling rapid reconfiguration and better integration of control systems.

Contribution

It proposes a novel distributed behavior tree framework for skill composition in reconfigurable manufacturing, integrating low-level device control with AI-based task management.

Findings

Framework supports rapid reconfiguration of manufacturing modules

Implementation with IEC 61499 controllers demonstrates practical applicability

Enhances modularity and integration in cyber-physical production systems

Abstract

While the benefits of reconfigurable manufacturing systems (RMS) are well-known, there are still challenges to their development, including, among others, a modular software architecture that enables rapid reconfiguration without much reprogramming effort. Skill-based engineering improves software modularity and increases the reconfiguration potential of RMS. Nevertheless, a skills' composition framework with a focus on frequent and rapid software changes is still missing. The Behavior trees (BTs) framework is a novel approach, which enables intuitive design of modular hierarchical control structures. BTs have been mostly explored from the AI and robotics perspectives, and little work has been done in investigating their potential for composing skills in the manufacturing domain. This paper proposes a framework for skills' composition and execution in skill-based reconfigurable cyber-physical production modules (RCPPMs). It is based on distributed BTs and provides good integration between low-level devices' specific code and AI-based task-oriented frameworks. We have implemented the provided models for the IEC 61499-based distributed automation controllers to show the instantiation of the proposed framework with the specific industrial technology and enable its evaluation by the automation community.