AWS for Industries

Monitor factory operations using digital twins from AWS and Matterport

Digital twins are used across the whole manufacturing lifecycle, from designing and planning to monitoring facilities. A digital twin is a virtual model of a physical object. It uses real-time data to simulate the behavior of the object. Digital twins can replicate many real-world items, from single pieces of equipment in a factory to full installations, such as wind turbines and even entire cities.

In this blog, we will describe how digital twin technology is helping manufacturers monitor the operations of a complete factory or remote facility by using AWS IoT Twinmaker with AWS Partner Matterport.

AWS IoT TwinMaker is a solution from Amazon Web Services (AWS) that makes it easy for industrial companies to create digital twins of real-world systems, such as buildings, factories, industrial equipment, and production lines.

Matterport is the leading spatial data company focused on digitizing and indexing the built world. The Matterport 3D data platform enables anyone to turn a space into an accurate and immersive digital twin, which is used to design, build, operate, promote, and understand any space.

Business problem

To ensure profitability and stay competitive in the market, manufacturers are forced to find the best ways to improve operational effectiveness, asset utilization, sustainability, and employee safety.

Enterprises expect an approach that can simplify the core challenges of creating the digital twin: 1) creating the 3D model of the physical environment without spending much time and money, and 2) getting real-time data from plant equipment/remote facilities.

Solution – digital twin technology

A Digital Twin is a living digital representation of a physical system, process, and complete business operation. They dynamically update it to mimic the structure, state, and behavior of the physical entity to drive business outcomes. We built digital twins to remotely access the facility operations, whether it’s a wind farm, offshore drilling, or extreme temperature operations.

Adapting digital twins with real-time visualization on the data adds more value for the business. Data coming from PLCs, SCADA, MES, and historians in a factory will give deep insights on how to speed the manufacturing process and reduce downtime time. Besides that, it also helps to calculate the Overall Equipment Efficiency (OEE) and predict equipment failure in advance.

With AWS IoT TwinMaker and Matterport integration, developers leverage this technology to combine the data from the manufacturing floor with the 3D models of the factory. This helps to create a fully integrated digital twin of the factory or remote facility. All of this is done in a short period of time and at a low cost, giving the customers the spatial data insights they need to monitor and manage their operations more efficiently than ever before.

Levels of digital twin technology

There are four different levels of digital twin technology:

  • L1 Descriptive – Engineering design and visual
  • L2 Informative – Integration of IoT, asset history, and maintenance data
  • L3 Predictive – Predictions of unmeasured quantities and future states based on continued operations
  • L4 Living Digital Twin – Updatable models to drive actionable insights

Components of a Digital Twin

Digital twins are built out of several components:

  • Model Builders – Create entities to virtually represent the physical system
  • Data Connectors – Access data from diverse sources
  • Scene Composer – Combine 3D visual models with real-world data
  • App Toolkit – Integrate digital twins into 3D applications

Digital Twin Benefits

Boost efficiency and safety through:

  • Increase the productivity of a plant
  • Improved safety by defining the geo fencing
  • Immersive user experience for service operators.The anomalies were identified and corrected on time.

Revolutionize the customer experience with:

  • A focus on product innovation
  • Guidance for remote troubleshooting
  • New digital business models, like product as service

Streamlined processes and data reliability are achieved through:

  • A digital thread that enables insights into business operations
  • The traceability of the data for any abnormalities that occurred in the past

Enhance enterprise digital culture through:

  • A clear vision for the stakeholders
  • An improved way of training the new workforce

System Architecture

  1. Data Capture: Data from desperate sources, either real-time IoT sensor data, video feeds, or manufacturing process data, is securely fed into the AWS Cloud via AWS IoT Sitewise. This data contextualization helps to take straightforward business actions.
  2. Create 3D model: Matterport services, SDKs, and devices will help to create an immersive 3D model of the physical environment. Once you create the mode, you import it into the AWS Cloud to make it available for AWS IoT Twinmaker scene creation.
  3. Combine data and 3D Model:  The data from the manufacturing floor or the remote facility is overlayed into the immersive 3D model. We track the real-time operating condition of the physical equipment and its health status in a centralized place.
  4. Visualization: The maintenance engineer or shift in charge can monitor the operations from a centralized control room and take preventive action before the machine or equipment goes down.

Digital Twin Use Cases

Use case 1: Monitor factory/remote facility

The following dashboard created I Matterport with AWS IoT TwinMaker shows real-time conditions and performance of a factory in 3D view.

Use case 2: Predictive maintenance

Using digital twin technology, you can measure and get alerts on the health index of the equipment, which gives an indication of RUL (Remaining Useful Life).

Use case 3: Measure equipment utilization

The below dashboard explains how the OEE calculation is calculated and acts upon the lower utilization. These examples provide an example of how you can visualize the complete factory with the most important key performance indicators.

In this blog, we learned: 1) what a Digital Twin is and its components 2) How to use AWS and Matterport to build digital twins in your factory. 4) Use cases that enable you to monitor factory operations with key performance indicators.

Suresh Kanniappan

Suresh Kanniappan

Suresh is an AWS Solutions Architect handling Manufacturing customers in the southern part of India. He is passionate about cloud security and Industry solutions that can solve real world problems. Prior to AWS, he worked for AWS customers and partners in consulting, migration and solution architecture roles for over 9 years.

Gurumoorthy Krishnasamy

Gurumoorthy Krishnasamy

Gurumoorthy is a Sr. Solution architect focused on Industrial IoT in Amazon Web Services Pvt Ltd, India and he is responsible for developing and supporting Smart factory/Industry 4.0,Digital twin and video analytics solutions to the customers.