AI based System of Systems Lifecycle Management of Digital Threads

ver the past two decades, our understanding of product devel-
opment has changed fundamentally. Disciplines that were once
clearly distinct from one another, such as mechanical engineer-
ing, electrical engineering and software development, have now
become increasingly intertwined. Products are no longer isolated
objects, but rather nodes in a network of systems, data and pro-
cesses. In this environment, it is no longer enough to manage indi-
vidual data sets – they must flow, remain consistent and be avail-
able to the right people at the right time. The AI-based lifecycle
management system of Digital Threads (Digital Thread for short)
has therefore established itself as the backbone of modern sys-
tem engineering. Early approaches to product data management
(PDM) focused on the central storage of CAD data and the man-
agement of versions and approvals. However, with the advent of
complex mechatronic systems, networked vehicles and modular
plants, it became clear that this approach was not sufficient. Com-
panies began to realise that it was not enough to simply store ge-
ometries; they needed a system that mapped the entire lifecycle
of a product – from the initial requirement through development
and production to operation and decommissioning. Today, Digital
Threads’ AI-based lifecycle management system acts as a digital
nervous system that connects disciplines such as mechanics, elec-
tronics, software and simulation. While system engineering pro-
vides methodical approaches for structuring requirements and ar-
chitectures, Digital Thread ensures that the associated data is find-
able, traceable and up to date. This object-oriented approach cre-
ates transparency and enables end-to-end traceability, which is a
key requirement of modern systems engineering. Another feature
of modern digital thread approaches is the seamless integration of
models and product data. Changes in one discipline – for example,
in design – can automatically detect and forward all affected areas
such as requirements, tests and functions. This promotes the con-
tinuous flow of information and prevents unnoticed consequences
of changes elsewhere in the system. The close link between AI-
based lifecycle management systems for digital threads and system
engineering goes beyond technical necessities and promotes cul-
tural change in companies.