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4 Jan 2022

This is the first of a two-part blog detailing the value of digital twins and robust IIoT platforms that mirror shop-floor operations and boost productivity, improve maintenance and speed time-to-market.

Part 1 focuses on digital twins and the Virtual IoT Maintenance System. 
Part 2 will focus on the selection process for the optimal IIoT platform.

First coined in 2012, the term Industry 4.0 captures the diversity of new technologies and digital innovations that are transforming manufacturing by connecting the physical and virtual worlds. While progress has been steady, many companies have been slow to build robust digital ecosystems of their manufacturing operations that align Industrial Internet of Things (IIoT) platforms with digital twins of manufacturing equipment and production lines.

That’s about to change as the pace of adoption picks up as the value becomes apparent. One market report projects investment in IIoT platforms and digital twins will grow at over 30% a year for the rest of the decade. The application leading the way is predictive maintenance.[1]

IIoT platforms use sensors, artificial intelligence (AI) and machine learning (ML) to collect and analyze data from industrial equipment. There are various sensors to collect the data: machine IoT sensors and industrial systems such as programmable logic controllers, enterprise resource planning systems, supervisory control and data acquisition systems. A digital twin is a virtual representation of a system, such as a process like product design or a piece of manufacturing equipment, a production line or an entire factory. Together, they improve operational performance, optimize maintenance and repairs and create new revenue opportunities from innovative digital services.

A robust digital twin requires a massive volume of data from many sources to create a representation that mirrors the physical entity. Just as important, the digital twin must model the behavior of the individual physical components and their interactions with other components and digital twins. Augmented reality (AR) and virtual reality (VT) tools permit remotely controlled, optimized predictive maintenance.

To remain competitive in the coming years, manufacturers must renew their commitment to invest in IIoT platforms that acquire and analyze data, and digital twins that use the data to monitor, maintain and innovate manufacturing operations.

To this end, Capgemini Engineering is spearheading the Virtual IoT Maintenance System (VIMS) project, a European research program funded by the European Commission’s Community Research and Development Information Service. The VIMS project integrates IIoT platforms with digital twins to develop new digital ecosystems for industrial and manufacturing maintenance systems. [2]

Capgemini Engineering is working with VIMS industry participants Airbus Operations SL and F. Hoffman-La Roche AG to develop IIoT-digital twin solutions for their operations. The Airbus VIMS use case aims to reduce downtime and improve production efficiency in the drilling process of several aircraft parts. Using data from vibration and acoustic sensors, an ML algorithm determines the beginning and end of the drilling process and if it has been performed correctly. The Roche VIMS use case implements predictive calibration of IIoT sensors that digitally monitor the state of sensors and counters on production lines. The digital twins in both use cases improve the control and efficiency of their respective manufacturing processes.

The VIMS digital twin is an industry-ready, highly scalable solution that brings Industry 4.0 capabilities to traditional industrial manufacturing. It uses a cloud-based IIoT platform and includes information monitoring applications and specialized training for operators and remote assistance.

Creating digital twins requires developing high-fidelity virtual models of the physical environment that change in real-time as the physical environment changes. The digital twin architecture has three levels:

  1. Unit level: A digital twin of a single piece of equipment, such as a robotic arm.
  2. System level: A digital twin of multiple pieces of equipment, such as all the robotic arms, machine tools and conveyor belts in a production line.
  3. System-of-systems level: This is the most complex level of digital twins that includes all the equipment in all the production lines in the factory.

VIMS focuses on developing shop-floor digital twins that provide a detailed visualization of the manufacturing process at all three levels, from a single component to the whole factory. It is an ambitious project that brings digital twins and IIoT closer to the production line and offers possibilities that are only now starting to emerge. Digital twin technology is poised to be a must-have asset for businesses on the Industry 4.0 journey that want to digitalize, optimize and manage their factories in a smarter, more efficient way.

Capgemini Engineering is looking forward to supporting Airbus, Roche and other companies as they take full advantage of IIoT and digital twin technology as the VIMS projects expand and Industry 4.0 becomes a reality.

Part 2 of the VIMS blog explores the selection process for the IIoT platform that optimizes the performance and value of VIMS digital twins

[1] “Digital Twin Industry Was Valued at $3.6 billion in 2019 and is Forecast to Reach $73.2 Billion by 2030” Research and Markets, Jul 21, 2020

[2] Virtual IoT Maintenance System (VIMS) fact sheet, Community Research and Development Information Service, European Commission


    IOT AND HARDWARE EXPERT, CAPGEMINI ENGINEERING Francisco has an MSc in Telecommunication Engineering with communications and electronics specialties. For 15 years, he has been designing and developing embedded devices based on microcontrollers, most of them battery powered. Francisco has worked with a wide array of technologies: GPRS, Bluetooth, Wi-Fi, LED lighting, GNSS, ARM coding, and has developed different custom protocols in ISM 433 MHz and 868 MHZ bands MQTT. For over five years, he has developed many embedded sensor devices for smart cities (i.e., devices that measure electricity consumption from anywhere in the city and regulate public street lighting). The sensor information is sent to a centralized server or an IoT platform. Currently, Francisco is developing a digital-twin solution for the Capgemini Engineering Virtual IoT Maintenance System (VIMS) project using IIoT platforms to manage data flow for digitalization and optimization of the project’s use case processes.

    IOT AND ROBOTICS CONSULTANT, CAPGEMINI ENGINEERING Alejandro has a degree in Electronics and Robotics Engineering and has worked with a wide array of technologies in his three years as an engineer. He began his career as an Unmanned Aerial Systems developer, providing custom solutions for clients needing UAV technology in their projects. As a consultant at Capgemini Engineering for over two years, Alejandro has been working in the fields of robotic automation, sensor connectivity and communication, and indoor positioning algorithms. For the VIMS project, he is developing a digital-twin solution using IoT platforms to manage data flow for digitalization and optimization of the project’s use-case processes.

This was first published on the Capgemini Engineering website.