Every stage in a manufactured product’s life involves data, from its initial design and modeling through production to validation testing and inspection, usage, monitoring and servicing. In the pre-digital era, the data associated with each of these stages was managed separately, in isolation from one another.
Today, integrating this data together has played a vital role in the long-term competitiveness of manufacturers, especially those deploying additive manufacturing (AM) because it is one of the most inherently digital processes.
In this article, we will explore:
Conceptually, a digital thread is an integrated repository of all the data associated with a manufactured product, spanning end-to-end across the life of that product.
While traditional manufacturing systems approach each step as a discrete operation that may or may not be connected to the others, a digital thread gives manufacturers visibility to all of the data from every step and feed it back or forward to gain new insights, enhance the operation, and manage the complexities of AM.
A digital thread integrates data across four major phases:
A digital thread begins at the design phase, where a particular part to be manufactured is first imagined and the designer’s concept becomes a 3D model using CAD tools. Designers may also use 3D scanning to start with the model of an existing part.
The model is then subject to finite element analysis (FEA) to establish its structural and thermal characteristics or computational fluid dynamics (CFD) to examine fluid flow. A feedback loop helps ensure the model meets specific performance requirements. In AM workflows, this phase also involves algorithmically driven design techniques that create shapes that are impossible to manufacture through conventional subtractive means.
AM parts may also be subject to advanced modeling and build process simulation in order to optimize part orientation, supports and other factors that ensure high-quality results in 3D printing.
Based on everything learned in phase one, the 3D model of the part is transformed into output instructions for a 3D printer.
Many software tools use the .STL file format, which was originally developed for stereolithographic printing. However, converting complex models using implicit modelling into STL format raises data integrity risks and results in extremely large file sizes which requires excessive computational power to manipulate in AM build preparation tools.
Modern tools, including 3DXpert, perform build preparation directly from CAD files with no need for transformation or file conversion.
Next comes 3D printing, which fabricates the part. In addition to the machine instructions there may be alerts and actions taken based on monitoring of real-time sensor data coming from the printer. Finally, post-processing or finishing steps are completed, including the removal of support structures, curing, heat treating, machining, or surface treatment.
This phase includes part inspection, typically via nondestructive evaluation (NDE) technologies such as X-ray, CT scanning, liquid penetrant or UV dye, and ultrasound, among others. It also includes data verification and “digital twinning” that collect all of the data produced in a digital thread to date, including information about the build process, validation testing and inspection results, and an updated CAD model.
In highly regulated industries, such as aerospace & defense, medical devices, and energy, all of this data will be needed to meet traceability requirements and industry standard quality requirements. Such industries also require compliance with security certifications that prove the information is protected through industry-standard best practices.
The final phase occurs when the part goes into service. This may include field service sensing and inspection, using sensor data to continuously update the digital twin and gain insights that can improve the next generation of the part or product.
The Manufacturing OS creates a complete digital thread
The foundational value of a digital thread is visibility to all the data associated with a manufactured part, end-to-end, across its life. There are many reasons why manufacturers need full visibility of this information.
All of these value elements combine to increase scalability of the manufacturing process, and ultimately reduce cost and lead time.
There are two key enablers of the digital thread. One is the model-based approach used to characterize every step in the AM process and how those processes and systems relate. Another is interoperability, which connects systems in such a way that the data in the digital thread will be accessible, readable and usable in any phase of workflow. This allows data to flow freely between and among various product models and processes, regardless of format.
In addition to these enabling concepts, the digital thread depends on several specific technologies:
The cloud gives manufacturers instant, highly scalable access to the computing power required to analyze 3D models in the design phase, prepare complex build files in the build phase, and extract insights from the digital thread. Similarly, cloud storage makes it possible to manage very high data volumes in a flexible way that allows all stakeholders to access it securely.
The connected ecosystem of sensors and devices sharing data about how parts are printed and how they perform in service is called the Internet of Things (IoT). Real-time sensor data enables more efficient part fabrication and gives manufacturers a window into long-term performance, fatigue and failure rates, and maintenance needs.
This refers to the digital models of physical manufacturing operations, inclusive of all parts, products, processes and sensor data in the digital thread. The digital twin helps ensure a single source of truth for all AM stakeholders and allows them to analyze current and historical data as well as run accurate simulations to better understand and optimize all four phases.
It should be clear that implementing a digital thread for AM is a complex and intricate endeavor. Overall, there are three primary challenges manufacturers will face.
A digital thread requires significant computing power and data storage capacity to run modeling, simulation and other software used to optimize AM processes. Complex supply chains will drive the need for a robust data warehouse. To solve these issues, manufacturers will likely turn to cloud-based solutions that offer tremendous flexibility and scalability.
Changing how each phase of the product life cycle connects with every other phase can be disruptive. Design and development must be prepared to collaborate closely to analyze and optimize AM designs and printing. Incorporating advanced modeling and simulation tools will likely affect how well-established design processes are conducted. Manufacturers may want to consider a manufacturing operating system that is specifically designed to accommodate complex AM workflows inclusive of diverse machines and applications.
Workforce development and training will need to be a key priority as AM continues to evolve and new technologies arise. Success will depend heavily on a workforce that is prepared to learn continuously and adapt to change. Choosing software that both supports the digital thread and is relatively easy to configure and use will be important.
While some manufacturers currently use additive technology primarily for rapid prototyping during design, a digital thread enables them to scale AM workflows to the industrial level.
Organizations can design higher quality and more effective parts, improve efficiency, collaborate more easily and think more strategically about how AM can serve their business in the long term – all thanks to a digital thread.
Oqton’s Manufacturing OS creates a digital thread throughout the entire manufacturing process. Find out how we can help you trace, track and analyze your 3D files with our MES solution for additive manufacturing.