Digital transformation is the only way for companies to survive and continue to innovate in the new normal against the backdrop of the coronavirus pandemic. They must now accelerate their digitalization processes and finally arrive in Industry 4.0. To this end, digital solutions should be anchored at the core of the value chain in order to fully develop their transformative effect.

Industrial companies should use technologies such as artificial intelligence, the cloud and the Internet of Things in parallel. This is because it results in benefits such as optimized business processes, greater efficiency in value creation and improved employee productivity.

At the heart of these technologies is the digital twin. It is a digital mirror image of physical plants, processes, personnel, systems and devices. The digital twin maps real-time information from these connected systems, providing a deep insight into the efficiency of various processes and accelerating automation. In industry, digital twins are currently being used to digitally test new systems and processes, train employees or optimize ongoing operations.

The digital twin in action

The digital twin enables predictive maintenance.

© Aveva

The market research institute IDC estimates that spending on digital transformation will reach 2.3 trillion US dollars by 2023. To unleash its true potential, digital transformation must be implemented as a holistic strategy across the entire company. The digital twin can be the vehicle that shows the company a plan for transformation, synchronizes business and operational goals and ultimately delivers optimal results.

In manufacturing, a digital twin can track the effectiveness of plant, machinery and other equipment on the factory floor in real time. The combination with machine learning and IoT capabilities provides a holistic view of the plant and enables predictive maintenance. This means that unplanned downtime can be avoided. For example, the virtual simulation allows measured values for system temperatures, power consumption, pump pressure and flow rates to be monitored in real time. This allows engineers to model the system for optimum performance and adjust it accordingly.

As a representation of a supply chain, the digital twin can provide end-to-end transparency so that manufacturers and customers always know exactly where a delivery is, which route it has taken and when it will arrive at its destination.

Employees receive comprehensive information about current operations at a glance. This makes it easier to make optimizations. As a result, companies can increase their business value and have room for innovation. Predictive analytics leads to improved operating and maintenance processes and generates cost savings in the billions, either directly or by avoiding downtime. Current safety and regulatory requirements can also be integrated into the system. Scenarios can also be modeled with the digital twin. The digital twin thus becomes the key to Industry 4.0.

A virtual 3D system

Vanessa Erickson is a Capital Project Portfolio Expert at Aveva.

© Aveva

Chemical company SCG, one of the largest petrochemical companies in Thailand, has developed a Digital Reliability Platform (DRP) with a partner. This is a complete APM (Asset Performance Management) solution for predicting asset health, monitoring performance and enabling advanced maintenance across the entire operation. The digital twin used supports SCG in its goal of generating no unplanned downtime.

The digital twin is integrated into the DRP as a virtual, three-dimensional plant. The virtual planning solution provides an immersive and touch-based visualization that enables interdisciplinary collaboration and quick access to asset information through Aveva Asset Information Management, Aveva 3D Asset Visualization and a range of different dashboards for asset status, alarms and health status. All machine information is displayed in the model, allowing management to efficiently plan work and respond to emergencies.

"Together with Aveva, we have successfully merged big data, AI, machine learning and predictive analytics into a solution that supports our employees and improves our performance," explains Mongkol Hengrojanasophon, Vice President - Olefins Business and Operations, Chemicals Business, SCG.

Four steps to the digital twin

The digital twin uses a four-stage strategy to contextualize new and existing data. This creates new insights that help companies to continuously improve processes without taking any risks.

1. Implement a Digital Twin based on accurate data feeds to determine current asset performance and establish key data checkpoints.
2. Simulations and predictive analytics to identify the potential value gains from operational or process improvements and risk control.
3. Develop a digital twin strategy that maps program and project planning for digital transformation.
4. Implementation of this strategy to map relationships between current and future developments and determine how the company or project responds to internal or external changes.