Digital Twin Technology
A Creator's Tool
What is DT & Why?
Digital twin technology promises to transform the design and give engineers, manufacturers and businesses a 360-degree view of products and systems throughout the entire lifecycle.
Armed with an enriched pool of data provided by the Internet of Things (IoT), the design technology stands poised to deliver previously impossible opportunities. But, there’s a catch: A key capability is missing from conventional modelling and simulation tools.
For the technology to deliver on its promise, it must be able to run analytics in real-time or faster, provide a high degree of prediction accuracy and integrate data from a collection of disparate and often incompatible sources.
Digital Twin Technology - Applications
Power-generation equipment
Large engines — including jet engines, locomotive engines and power-generation turbines — benefit tremendously from the use of digital twins, especially for helping to establish timeframes for regularly needed maintenance.
Healthcare services
Just as products can be profiled through the use of digital twins, so can patients receiving healthcare services. The same type system of sensor-generated data can be used to track a variety of health indicators and generate key insights.
Structures and their systems
Big physical structures, such as large buildings or offshore drilling platforms, can be improved through digital twins, particularly during their design. Also useful in designing the systems operating within those structures, such as HVAC systems.
Automotive industry
Cars represent many types of complex, co-functioning systems, and digital twins are used extensively in auto design, both to improve vehicle performance and increase the efficiency surrounding their production.
Manufacturing operations
Since digital twins are meant to mirror a product’s entire lifecycle, it’s not surprising that digital twins have become ubiquitous in all stages of manufacturing, guiding products from design to finished product, and all steps in between.
Urban planning
Civil engineers and others involved in urban planning activities are aided significantly by the use of digital twins, which can show 3D and 4D spatial data in real-time and also incorporate augmented reality systems into built environments.
Roles & responsibilities
As a Technical Lead, I undertake activities like gathering requirements from varied Digital Twin creators, research on information architecture, User research, Low-fi wireframes, Hi-fi Wireframes, Prototyping, Testing and front end development (in Unity), provide backend team with technical details.
Product's Goal
Achieve Development of fully extensible, cross-functional, collaborative (Creator tool) to forge Digital Twins. Aspects like version controlling, Importing ontologies (varied formats) from different sources, CRUD operations of DTDL (language) from UI, Publishing the finished contents to the Azure backend with ease. It is sophisticated software accompanied by a straightforward user experience that promotes the creation of digital twins through 3D representation.
Research& Methodlogy
Understanding User Needs
Personas
User Pain points
Ingestion of source files with Microsoft's standard DTDL (Digital Twin Definition Language) received from different sources in varied formats. The process starts with automatic validation of the imported data before conversion. A simplified UI helps ameliorate the JSON files to guarantee data quality, focused analysis of individual elements within an asset to study the properties of the data syntax, and employment of backend technology of the Azure to publish Digital Twin on the cloud. The tool provides capabilities for authentication and approval before releasing the digital twin.
Ingestion of source files with Microsoft's standard DTDL (Digital Twin Definition Language) received from the IoT sensors to control data configuration. The process starts with automatic validation of the imported data before conversion. A simplified UI helps ameliorate the Jason files to guarantee data quality, focused analysis of individual elements within an asset to study the properties of the data syntax, and employment of backend technology of the Azure to publish Digital Twin on the cloud. The tool provides capabilities for authentication and approval before releasing the digital twin
Based on the discussion and interviews conducted with varied Digital Twin creators, to import and stitch multiple Ontologies functionality is a challenging task and ability to import Ontologies from multiple sources. It is crucial to have a structured approval process and diversified personas (based on the organizational hierarchy).
Persona 4 - Reader
It is read-only access, restrained from CRUD operations, and assisted with notifications of the incorporated changes.
Persona 3 - Contributor
The contributor is confined to read/write/modify/update (basic CRUD) operations, dispatches these updates. The dashboard displays the approval notifications.
Persona 1 - Owner
Owner persona would have complete access to the resources. The role involves the right to delegate access, restrict users to approve and publish the final DTDL files to the cloud. The owner dashboard displays updates and navigation to relevant projects.
Persona 2 - Admin
Admin functionalities include adding/removing, approve and publishing content in the designated project. The admin dashboard displays summary of the assigned project
01
Converting all ontologies to DTDL
02
Cloud Save of all Projects
03
Hard to work with typical DTDL JSON
04
Very complex to keep multiple versions.
Inference and Implementation
The Most important feature that DT creators needed was Importing ontologies from different sources in varied formats, Publish the created contents (DTDL models) to Azure Digital Twin Instance with ease, Ability to keep Different DTDL versions, Compare the local files against the cloud files, Simplify reading DTDL files through UI.
The items that are implemented in product design are, Create/Edit DTDL files using UI, Publish the DTDL contents to Azure with single button press (Owner and Admin persona), Contributor persona will be able to send updated/modified files for approval, Created a comparison view to compare files, Created a cloud import button and created a list view to see all different ontology from different sources, Convert all standard ontology formats to DTDL, Keep all versions of DTDL models
Affinity Map
Findings
Node based DTDL editing is good.
Customizable UI
Easier navigation & Intuitive tools
Appealing visual design
Observation
Good Visualization of DTDL
Need based tool options
Create Azure resources in editor
UI based approach to Edit DTDL
Confusion
Confusion - model graphs & nodes
More info on query language
More info on Azure resources
Can try diffeent theme options