Defining the Digital Twin
From the Circuit Board to the Board Room
The Foundation for Digital Transformation
“A digital twin is a real world instance of a digital model. A digital model is the as-designed representation, while the digital twin is the as maintained representation, as manufactured.”
-Diego Tamburini
Principal Industry Lead-Azure
Microsoft
Decoding how buzzwords actually translate to business use cases can be difficult. The digital twin is one of these popular buzzwords, even though it represents the foundation of digital transformation for electronics manufacturers. With Diego’s definition of a Digital Twin in mind, let’s look at some categories, values, and use cases of Digital Twins for electronics manufacturing.
There are many categories of Digital Twins, each with their specific value. These include component, asset, system, process, or an entire manufacturing plant. The Digital Twin of each of these categories can include data from other categories; for instance, the Digital Twin of an Asset includes data from Components, and can include assembly information from System.
- Component/Part: The basic building blocks of electronics: transistors, resistors, capacitors, regulators, etc. These can be serialized or (more typically) non-serialized
- Asset: A serialized unit which performs a discrete function in and is an integral piece of a higher level assembly. An example would be a printed circuit board (PCB).
- System: A serialized unit that is comprised of multiple constituent assets. There can be many system levels and genealogy (for instance, a higher level assembly can be made of several assemblies, each of which is made of several assets). An example can be a aircraft engine control system.
- Process: The steps and procedures taken during a unit’s lifecycle, each of which comprises one or multiple events. Manufacturing is one example, MRO is another.
- Manufacturing Plant: The location where manufacturing processes are located. These include test, assembly, rework and other related processes.
In discrete manufacturing of complex electronics, a system digital twin is the most useful approach to optimize manufacturing efficiency, throughput, and product quality. The major challenge of developing a system digital twin is the convergence of information across many complex enterprise information sources, including product design, ERP, test, MES, supplier quality, and service into a single source of truth.
Digital Twin Use Cases in Electronics Manufacturing
With Diego’s definition in mind, what is the relevance of the digital twin to modern electronics manufacturing, and how can we apply it?
To put it succinctly, it means having the data of the as-built and as-maintaned object from all areas where data can be gathered, and (perhaps most importantly), making the data analyzable and useful to drive better business outcomes.
At a corporate level, executive decisions on cycle time and utilization rates help drive overall profitability and success. By linking data from each manufacturing stage and event in the same normalized data warehouse, users can have two key deliverables: how a metric (like cycle time or utilization rates) is performing and trending, and the underlying reasons why that metric is performing the way its. The latter deliverable gives technical users and engineers the data and tools they need to investigate, resolve and/or prevent the former deliverable.
These deliverables (executive decisions on KPIs with root-cause workflows) rely on a system that can provide a foundation for the Digital Twin. IntraStage BlackBelt Fusion leverages a web enabled architecture based on Microsoft Azure technologies, as well as a purpose built manufacturing data model that ultimately enables distributed data democratization.
Let’s examine a few examples of IntraStage customers using that Digital Twin foundation and data democratization to identify and resolve some key performance indicators.
Click on the images below to explore Digital Twin use cases including PPM/DPMO, Heatmap Overlay, As-Built/As-Maintained/As-Is, and OEE/Cycle Time.
PPM and DPMO
Drive to Optimal PPM on a Global Scale
OEE and Cycle Time
Improve Manufacturing Throughput and Efficiency
Heatmap Overlay
Rapid Rework Insight and Resolution
As Designed, As Built, As Maintained, As Is
Full Traceability and Genealogy