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A digital twin is a dynamic, virtual representation of a physical asset, product, process, or system. It digitally models the properties, condition, and attributes of the real-world counterpart.
Using data from multiple sources, a digital twin continuously learns and updates itself to represent the current working condition of the object or process.
Decision-makers gain deep understanding, which they apply to improve and optimize the performance of the modeled asset and the larger systems it interacts with.
This far-reaching innovation expands the concept of digital twins to provide an integrated understanding of production as a whole. An Operational Digital Twin blends and correlates real-time streaming IoT data together with other inputs. It then applies machine learning, AI, and advanced modeling techniques to create a dynamic virtual representation of the entire plant. For the first time, manufacturers gain full visibility into the manifold and multi-layered interdependencies among assets, processes, and operations.
These unprecedented
insights unlock the full business value of manufacturing analytics, enabling:
Operational Digital Twins are extremely complex and challenging to create and refine. Unlike Asset Twins, they require the blending of thousands of data sources that come in myriad formats, including real-time streaming input. The only way to ingest, correlate, and integrate such diverse datasets at scale is with AI and machine learning — techniques that have only lately attained the right level of maturity for the job.
These are vendor-specific models of a single asset or machine, which tap into operational data for the purpose of asset optimization.
They can be used for:
While asset twins provide a window into single components, they offer no visibility into the intricate and all-important relationships among machines, workflows, and parts or batches.
To date, the absence of these foundational insights has prevented manufacturing analytics from delivering more than a fraction of its potential production impact.
This limitation has only recently been overcome, through a groundbreaking advance in digital twin technology.
The Sight Machine platform is a pioneering system that is purpose-built to create Operational Digital Twins.
It leverages AI to automate the process of digitally representing any manufacturing machine, line, facility, supplier, part, or batch.
Our patented AI Data Pipeline integrates algorithms, expert-systems learning, and continually advancing techniques for ingesting, transforming, and combining streaming data from thousands of sources and assets.
The outcome is a digital twin that delivers profound actionable insight into all layers of the manufacturing environment, from individual sensors to entire supply chains.
Enabled by pre-configured manufacturing-specific data models
AI and machine learning quickly create digital twins from unstructured data
Real-time streaming data ingestion, processing, and transformation, fully optimized for manufacturing
Out-of-the-box manufacturing analysis and visualization tools for unlocking the value of your Operational Digital Twins
A factory digital twin is a dynamic, virtual representation of a physical asset, product, process, or system. It digitally models the properties, conditions, and attributes of the real-world counterpart.
A digital twin is a dynamic virtual copy of a physical asset, product, process, or system that looks and acts like its real-world counterpart. A digital twin ingests data and replicates processes so you can predict and test possible performance outcomes and issues that might occur on the production floor.
Digital twins are highly effective tools for optimizing manufacturing processes. Utilizing a digital twin can drive a lot of value for manufacturers across sectors, from predicting quality in real time to removing the necessity for costly physical tests.
Creating new or updated products often involves long periods of trial and error in a traditional manufacturing model. Now with digital twins, we can create a simulation to design and test products. This allows you to test various scenarios and find ways to reduce costs in production.
Digital twin technology can be applied to various industries such as manufacturing, engineering, and construction.
Sight Machine is a pioneer in building and deploying digital twins in the manufacturing industry through its groundbreaking manufacturing data platform.
For more information, download this white paper from ARC Advisory Group on enabling operational intelligence with Sight Machine-generated digital twins.
