How to build DT:
Building a digital twin for a refinery process requires a combination of expertise in
engineering, data science, and software development. Here’s a high-level guide on how to
approach building a digital twin for a refinery process:
1. Define Objectives and Scope
Identify Use Cases: Clearly define what the digital twin will achieve (e.g., process
optimization, predictive maintenance, energy management). Understanding the
specific challenges or goals helps determine the scope.
Determine the Assets to Model: Choose whether the digital twin will cover specific
equipment (pumps, compressors, etc.), an entire process unit (distillation, cracking),
or the whole refinery.
2. Collect and Integrate Data
Sensor Data: Gather real-time data from sensors (temperature, pressure, flow rates,
etc.) placed on refinery equipment.
Historical Data: Use historical data from the Distributed Control System (DCS),
SCADA systems, and other operational logs for model training.
Engineering Design Data: Collect the initial engineering designs and specifications
(e.g., P&IDs, flow diagrams) to accurately represent the physical assets.
External Data: Integrate external factors like market demand, feedstock quality, and
environmental data (e.g., weather, emissions regulations).
3. Select Software and Tools
Simulation Platforms: Use process simulation software like AspenTech’s Aspen
HYSYS or Honeywell’s UniSim to model the refinery’s processes.
IoT Platforms: Select platforms like Siemens Mindsphere, GE Predix, or Microsoft
Azure IoT that can handle sensor integration, cloud storage, and data analysis.
AI and Machine Learning Tools: Implement AI models to predict performance and
provide optimization recommendations. Tools like Python (with libraries like
TensorFlow, PyTorch), MATLAB, or specialized AI platforms can be used.
4. Develop the Virtual Model
Process Modeling: Use the data collected to create a virtual model of the refinery
process. Software like Aspen HYSYS or UniSim can help simulate thermodynamics,
chemical reactions, and flow.
Equipment Modeling: Simulate the behavior of individual assets (pumps, reactors,
etc.) using real-time sensor data and historical performance metrics.
System Integration: Ensure that all models are interconnected and can simulate the
refinery's overall process flow.
5. Implement Real-time Data Integration
IoT and Edge Computing: Use IoT devices to feed real-time data into the digital
twin, allowing it to simulate real-world conditions. Edge computing can be used for
processing data locally before sending it to the cloud.
Data Pipelines: Set up data pipelines that can efficiently transmit, store, and process
large volumes of operational data in real time.
6. Deploy Predictive Analytics and Machine Learning
Predictive Models: Use predictive analytics to forecast equipment failure, process
deviations, or energy inefficiencies.
Optimization Algorithms: Implement algorithms to optimize refinery operations
(e.g., optimizing distillation column performance or reducing flaring).
Training AI Models: Train AI models using historical data and real-time sensor data
to improve predictions and optimize operations continuously.
7. Test and Validate the Digital Twin
Simulation Testing: Run simulations of the digital twin in different operating
conditions (e.g., varying feedstock quality, equipment malfunction) to validate its
accuracy and reliability.
Comparison with Physical Performance: Compare the digital twin’s outputs with
the real-world performance of the refinery to ensure that the model accurately reflects
physical processes.
8. Deploy and Monitor the Digital Twin
Real-time Monitoring: Once deployed, continuously monitor the digital twin’s
performance and update it with new data. Implement dashboards and visual tools to
track KPIs and generate insights.
Feedback Loops: Create feedback loops that allow the digital twin to influence real-
world operations by providing recommendations or directly adjusting process
variables.
9. Continuous Improvement
Model Updates: Refine the digital twin model as new data becomes available or as
refinery configurations change.
Feature Expansion: Add new capabilities over time, such as new equipment,
additional analytics features, or deeper integration with control systems.
Key Players in Digital Twin Development for Refineries:
Software Vendors: Companies like Siemens, GE, AVEVA, Honeywell, AspenTech,
and Schneider Electric offer platforms for building digital twins for industrial
applications.
Consultants and Systems Integrators: Firms like Accenture, TCS, or Infosys can
help design and implement digital twin solutions tailored to refinery needs.
In-house Development Teams: For a customized approach, refinery owners can
develop their own digital twin systems by hiring experts in software development,
process engineering, and data science.
By following these steps, you can build an effective digital twin that optimizes refinery
processes, improves decision-making, and reduces operational risks.
28th Feb’2024
In a significant move aimed at modernizing Varanasi’s infrastructure and tackling urban
challenges, Prime Minister Narendra Modi has commissioned Genesys International
Corporation, a prominent mapping and geospatial company, to develop a 3D Digital Twin of
the city. Leveraging Genesys New India Map stack, the project marks a pivotal step towards
the digital transformation of Varanasi, the Prime Minister’s constituency.
Under the collaboration between Genesys and Varanasi Smart City Limited (VSCL), the
ambitious initiative will entail the creation of a precise 3D replica spanning an extensive area
of 160 square kilometers. With an order value of INR 7 crores, the project aims to
capture Varanasi‘s physical features, processes, and relationships in intricate detail.
Sajid Malik, CMD of Genesys International, highlighted the project’s significance: “Our 3D
city data will be integrated into various development schemes and projects. The simulation
capabilities offered by the Digital Twin will aid urban planning efforts, allowing predictive
visualization of infrastructure projects such as flyovers, foot over bridges, and road-
widening.”
The endeavor aligns with India’s broader urban development goals. In November, Survey of
India (SOI) and Genesys International Corporation Limited had announced a partnership to
develop GIS-enabled Digital Twins for major Indian cities and towns. This initiative aims to
empower government authorities and city planners in designing sustainable and resilient
urban environments.
Also Read | PM Modi inaugurates 74 Revamped Railway Stations in Uttar Pradesh
Commenting on the initiative, Malik emphasized, “The highly accurate geometrical data will
help develop a host of high-end applications, enabling flagship government schemes such as
SVAMITVA, Smart Cities Mission, and PM GatiShakti.”
Furthermore, Genesys has already completed street imaging programs for approximately
1500 towns and cities and collaborates with Google Maps for the same, underscoring its
commitment to building smarter and more resilient urban centers across India.
June,17th 2022
Digital twins in demand
AI, Internet of Things sensors and remote site monitoring with drones present a virtual
replica of a real world, improving time and efficiency.
By integrating manned aerial LiDAR mapping, terrestrial mobile LiDAR, and 360-degree
street panoramic imagery, the project ensures a high level of accuracy and detail in the city
model. The Genesys constellation of sensors is creating a nationwide urban Digital Twin.
What is LiDAR technology used for?
Lidar technology is an ideal way to examine the surface of the earth. Assessing information
about the ground, creating a digital twin of an object, or detailing a range of geospatial
information. Laser scanning solutions harness this technology, using LiDAR data to create
3D models and map digital elevation.
Use of Digital Twins in Urban Development
The 3D Urban Spatial Digital Twins and its corresponding
spatial databases can be used to locate, identify, visualize
and inspect the location of critical infrastructure such as
roads, bridges, railway lines, hospitals, public amenities
etc.
Government agencies can use this information to improve
the delivery of public services by identifying areas where
additional resources are needed and by monitoring the
progress of development projects.
Additionally, geospatial technology can also be used to
support disaster management efforts by providing real-
time information on the location and status of critical
infrastructure and resources, as well as the location and
movement of evacuees.
In urban planning, engineering-grade geospatial data can
be used to create detailed 3D digital maps of cities and
towns, which can be used to identify areas that need
development and plan infrastructure projects such as
transportation and housing.
Furthermore, this technology can also be used to improve
the delivery of public services such as citizen safety and
security, healthcare, and education. Upcoming
infrastructure and projects can be digitally modeled and
inserted into the existing city.
Simulations can be run to understand how the proposed
infrastructure interacts with and affects the current city
and town infrastructure.
Digital India Mission’s Progress
Geospatial technology is critical to the Digital India Mission
as it enables the collection, analysis, and visualization of
geographic data, which can help in taking informed
decisions and improve the delivery of government services.
This directly ties in with the Indian government’s vision of
achieving Sustainable Development Goals (SDGs).
Amaravati, the capital of Andhra Pradesh, too is already
being built as a Digital Twin. Genesys has, so far, built
‘Digital Twins’ of Ayodhya, the Dharavi slum cluster of
Mumbai, Kochi and Kanpur.
Opening up data sets to the private sector follows from the
government’s 2022 National Geospatial Policy that was
cleared by the Union Cabinet last December. One of its
stated goals is to bring out a high-resolution topographical
map of “every inch” of India by 2030 and make Digital
Twins of India’s major cities and towns by 2035.
The twin-digital copy of physical assets has the potential to
help policymakers understand how infrastructure will
function in different situations such as high-footprints
events, increase of population, and disaster management.
Oct,18th 2024
Gati Shakti Digital Twin to Support Both Greenfield and Brownfield
Projects.
The newly launched geospatial platform under the PM Gati Shakti Master Plan will facilitate the
planning of new projects and the upgrading and expansion of existing infrastructure. Surendra
Ahirwar, Joint Secretary for Logistics and Trade at the Ministry of Commerce and Industry, explained
that the platform contains comprehensive data on the country's infrastructure assets, including their
geospatial coordinates.
This data is crucial for planning future projects and using digital twins to support project expansions,
addressing any existing infrastructure gaps. Ahirwar noted that a key challenge in implementing PM
Gati Shakti has been ensuring last-mile connectivity, which the digital twin technology aims to resolve
in the future.
Prime Minister Narendra Modi emphasized that the PM Gati Shakti National Master Plan (PMGS-
NMP) is a transformative initiative poised to revolutionize India’s infrastructure, promoting faster and
more efficient development across multiple sectors. He described PM Gati Shakti as a holistic
approach to economic growth and sustainable development, driven by seven engines: railways,
roads, ports, waterways, airports, mass transport, and logistics infrastructure.
Modi highlighted that the seamless integration of various stakeholders has improved logistics,
reduced delays, and created new opportunities. He stated, “Thanks to Gati Shakti, India is adding
speed to fulfill our vision of a Viksit Bharat. It will encourage progress, entrepreneurship, and
innovation.”
Union Minister of Commerce and Industry Piyush Goyal added that by streamlining logistics and
enhancing connectivity, this groundbreaking initiative ensures quicker and more efficient project
implementation.
Coursera:
HBR article:
https://hbr.org/2024/09/digital-twins-can-help-you-make-better-strategic-decisions?
utm_medium=paidsearch&utm_source=google&utm_campaign=intlcontent_strategy&
utm_term=Non-
Brand&tpcc=intlcontent_strategy&gad_source=1&gclid=Cj0KCQjwm5e5BhCWARIs
ANwm06g4rIIBRo8uw48aMEgaQmWsaO2Um5BZFYdGKp5dcrtlRGPtqG2RBWQaA
iBaEALw_wcB
Research paper:
https://www.sciencedirect.com/science/article/pii/S277266222300005X
