Systematic Comparison of Software Agents and Digital Twins: Differences, Similarities, and Synergies in Industrial Production

TL;DR

This paper systematically compares Software Agents and Digital Twins in industrial production, highlighting their differences, similarities, and potential for integration to enhance autonomy and intelligence in manufacturing systems.

Contribution

It provides a comprehensive analysis of how Agents and DTs are used in industry, identifying their roles, capabilities, and the need for standardization to enable synergistic use.

Findings

Agents excel in collaborative planning and execution.

DTs are mainly used for monitoring and information processing.

Combining Agents and DTs can enhance system intelligence and autonomy.

Abstract

To achieve a highly agile and flexible production, it is envisioned that industrial production systems gradually become more decentralized, interconnected, and intelligent. Within this vision, production assets collaborate with each other, exhibiting a high degree of autonomy. Furthermore, knowledge about individual production assets is readily available throughout their entire life-cycles. To realize this vision, adequate use of information technology is required. Two commonly applied software paradigms in this context are Software Agents (referred to as Agents) and Digital Twins (DTs). This work presents a systematic comparison of Agents and DTs in industrial applications. The goal of the study is to determine the differences, similarities, and potential synergies between the two paradigms. The comparison is based on the purposes for which Agents and DTs are applied, the properties and capabilities exhibited by these software paradigms, and how they can be allocated within the Reference Architecture Model Industry 4.0. The comparison reveals that Agents are commonly employed in the collaborative planning and execution of production processes, while DTs typically play a more passive role in monitoring production resources and processing information. Although these observations imply characteristic sets of capabilities and properties for both Agents and DTs, a clear and definitive distinction between the two paradigms cannot be made. Instead, the analysis indicates that production assets utilizing a combination of Agents and DTs would demonstrate high degrees of intelligence, autonomy, sociability, and fidelity. To achieve this, further standardization is required, particularly in the field of DTs.