Twin reality: the next frontier in digital manufacturing

The manufacturing industry requires significant change, driven by the rapid evolution of AI and its adoption in multiple processes in manufacturing – from the design and engineering of greenfield plants to operational efficiencies like waste reduction and quality improvements. Additionally, let handling issues and challenges associated with ongoing capital projects be a thing of the past, with the advent of simulated digital twins.

Optimizing capital spend in manufacturing, supply chain and operations

Traditional approaches to managing the often-spiraling costs of capital projects have included leveraging various discrete event simulation (DES) tools. While DES tools help with the optimization and assist with many trade-off decisions around automation and flow, the nature of issues faced by manufacturers today requires dynamic simulations, bi-directional operational connectivity and scenario planning.

Many of the challenges in these programs range from new greenfield builds to brownfield modernization projects. These projects, while substantial, often face challenges such as delays and budget overruns due to limited collaboration among internal functions (from design and engineering to production and testing), right through to external suppliers of equipment/ parts.

Especially in an existing facility, a project for a process automation – like a robotic cell addition – may cause adverse disruptions to the existing production schedule. Further delays in execution may even render the program obsolete.

These workflows infused with AI simulations can enable accuracy and collaboration. Bi-directional connectivity on a single platform has the potential to substantially deliver reduced capital spend – resulting in on-spec delivery of equipment and achieved targeted production/ throughput rates.

Evolution of digital twins

At the core of this revolution is the digital twin, a virtual replica of a physical system or process, that provides a dynamic and real-time view of an asset’s health, performance and other key metrics. This technology, developed on NVIDIA Omniverse, with workflows conceptualized and built by Accenture, helps manufacturers predict and fix possible problems, improve processes, and make better decisions. By embracing digital twins, manufacturers can streamline operations, improve product quality and ultimately, gain a competitive edge.

Yet, there can be challenges associated with digital manufacturing. The cost of implementing and maintaining digital systems can be a significant barrier, particularly for smaller manufacturers with more nimble supply chains. A shortage of skilled talent with the expertise to operate and manage advanced technologies presents another challenge. Digital technologies often require big changes to current processes and workflows, which can be difficult for employees to keep up with, resulting in a slower rate of technology adoption for the enterprise overall. Finally, concerns about cybersecurity and data privacy must be addressed to ensure the responsible use of data, AI and gen AI, within the community.

Creating the next frontiers in industrial digitization and physical AI with NVIDIA

Accenture and NVIDIA are collaborating to develop compelling solutions to many of these manufacturing industry challenges, offering a powerful platform and unique advantages. At the heart of this is the NVIDIA Omniverse platform, used for developing tools and applications to operate and interact with digital twins. These digital twins let manufacturers create precise simulations of their physical production lines and warehousing operations in real-time. They capture behavioral models and precisely accurate details of operating equipment, process conditions, and human interactions/ flow.

What distinguishes the solutions from Accenture and NVIDIA in the market is their tailored industry approach. By combining technical know-how and manufacturing domain expertise, Accenture and NVIDIA can streamline and enhance operational efficiencies. The solutions take Accenture's deep roots and understanding of industry practices, augmented by NVIDIA’s advanced visualization technology, to deliver comprehensive analytics and performance insights. Moreover, Accenture acts as a conduit to facilitate adoption, enabling manufacturers to integrate automation with minimal disruption. This harmonious blending of innovative engineering and deep sector expertise delivers successful and streamlined processes.

Opex-focused initiatives (operational expenditure) provide the flexibility for ongoing enhancements. Unlike capex projects (capital expenditure), which often entail prolonged commitments, opex improvements can be swiftly materialized and fine-tuned based on real-time insights and feedback. This agility empowers manufacturers to quickly adapt to market shifts, embrace emerging technologies and adopt procedural enhancements without the constraints of long-term investments.

Let us illustrate this with a practical example. Picture a manufacturing site that's brought to life with real-time monitoring of its processes through the clever use of sensors and Internet of Things (IoT) devices. The data streaming in from these sensors is like a digital mirror, a twin, reflecting the facility's every move. Engineers can then, from a distance, spot bottlenecks and fine-tune the production flow.

Case Study: Reinventing Operations with KION

KION GROUP AG, working with Accenture and NVIDIA, is reinventing supply chain and warehouse operations using artificial intelligence (AI) and digital twins. This project utilizes “Mega,” an NVIDIA Omniverse Blueprint, to develop digital twins of industrial environments, enabling the simulation and optimization of operational scenarios such as layout planning, robot interactions, and workforce management.

These digital twins act as a virtual testing environment where operations of autonomous warehouse robots can be simulated, validated, and adjusted according to changes in demand and inventory, enhancing operational flexibility. By testing various configurations in physically accurate simulations, KION identifies the most efficient strategies before implementing them in real-world facilities, improving performance metrics like throughput and task completion times.

The use of AI and digital twins is leading to more autonomous and efficient warehouse operations, reducing the need for manual intervention and allowing for quicker adaptations to operational changes. This approach has streamlined warehouse management, minimized disruptions, and increased overall efficiency, demonstrating a practical application of operational excellence principles in a manufacturing environment.

Digital twins and their impact on opex

Digital twins are the virtual representation of physical assets, processes or systems. Within manufacturing, they can be fashioned for singular machines, complete production lines or even entire facilities. These digital models are perpetually refreshed with live data from sensors, empowering manufacturers to oversee and scrutinize their operations in real-time, pinpointing areas for enhancement.

The allure of digital twins lies in their potential to yield significant opex savings. By pinpointing inefficiencies, choke points and areas of excess, digital twins empower manufacturers to streamline their operations, and avoid unnecessary costs.

The upshot? Manufacturers can identify and implement enhancements that were previously out of reach, culminating in heightened productivity and efficiency.

The potential for digital twins to transform the manufacturing landscape is vast. This innovative approach equips manufacturers with robust tools for real-time monitoring, in-depth analysis and the optimization of their operations, without undertaking the unknown risks inherent in capital projects with overrunning costs and schedules. The result? Marked improvements in operational efficiency, productivity and cost-effectiveness.