The traditional Industry 4.0 use cases have matured in the industrial sector, with digital solutions leveraging the Industrial Internet of Things (IIoT), big data, cloud, industrial automation, and robotics. This has enabled use cases such as inventory and asset tracking, predictive asset maintenance, and mitigating equipment failure and downtime for enterprises. As Industry 4.0 continues to progress, the convergence of multiple digital technologies, such as AR/VR, IIoT, and AI, is paving the way for advanced digitalization, which is defined as the application of advanced models, technologies, and frameworks like digital twin, digital thread, and generative AI, to transform business processes and operations. This research byte outlines what industrial enterprises should do to achieve advanced digitalization, building on Industry 4.0 principles.
With a challenging macroeconomic environment, supply chain disruptions, and a tight labor market, the focus has shifted toward adopting smart manufacturing practices through advanced digitalization. Here, we cover two key areas—the industrial metaverse and generative AI—showing how advanced digitalization is poised to disrupt the world of smart manufacturing, the need for IT-OT integration, and the role of platform-based solutions.
Industrial Metaverse Enables Real-time Collaboration and Connectivity
In response to increasing customer demand, manufacturers are harnessing advanced digital and immersive solutions to further improve factory efficiency and streamline processes. The industrial metaverse, defined as a blend of physical and digital worlds within industrial environments aimed at driving process and operational efficiencies and enabling real-time collaboration and connectivity, has been quickly gaining traction. The industrial metaverse can be applied to areas such as production-level simulation and R&D collaboration. The figure below highlights some of the key use cases within the industrial metaverse gaining traction among enterprises.
Digital twin technology is rapidly reshaping design and engineering processes and serves as the foundation for industrial metaverse applications. It helps replicate physical objects, assets, processes, and environments in real time with high accuracy and therefore has the potential to significantly enhance product and system design, prototyping, development, and collaboration. It involves the convolution of multiple technologies, including AR/VR, IIoT, and AI, to build and scale virtual environments. Businesses leverage big data analytics to extract valuable insights from digital twins and facilitate continuous, real-time monitoring and operational enhancements within manufacturing processes, empowering plant operators to take actions that improve productivity and quality. This convolution of digital technologies in the form of a digital twin goes beyond a specific production environment or system to link multiple environments, enabling enterprises to develop a connected network of multiple digital twins, forming a digital thread.
Generative AI Improves Production Efficiency and Quality Control in Manufacturing
Industrial enterprises are already using AI-powered technology to enhance product quality, plant safety, and equipment maintenance. The latest innovations in the generative AI space can enable manufacturers to expedite the shift toward smart manufacturing, further improving productivity, cost-efficiency, and quality control, as noted in Avasant’s research article Generative AI: A Catalyst for Transforming the Manufacturing Industry. Generative AI brings high benefits in:
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- Accelerating product design and development by, for instance, converting text prompts into images and creating design sketches based on engineering constraints.
- Optimizing production processes through, for example, automating production monitoring by analyzing vast sensor data from production lines.
- Improving quality control via, for instance, analyzing data from sensors and devices and identifying manufacturing defects in real time.
For both industrial metaverse and generative AI applications, a key requirement is to unify disparate data sources for tapping into vast data repositories and generating real-time data insights.
IT-OT Integration is the Key Success Factor in Achieving Advanced Digitalization
While embracing advanced digitalization is appealing, the path to Industry 4.0 transformation presents several obstacles. One of the key challenges remains how to increase connectivity and build a data foundation to enable better information-sharing and collaborative operations that require interoperability between production and operational processes, people, and systems. Organizations have traditionally kept information technology (IT) and operational technology (OT) as distinctive entities, with IT managing information systems and OT handling production equipment. The absence of an interconnected infrastructure and remote operability diminishes the overall scalability and flexibility of industrial operations.
The following are key considerations in driving IT-OT integration to enable advanced digitalization:
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- The first step toward achieving IT-OT integration is setting up instant connectivity across systems and touchpoints leveraging technologies like cloud and IIoT, which use sensors, connected devices, and machines to collect and unify real-time data from frontline equipment, processes, and the edge. This would also include implementing backend data integration across factory floors, production equipment, and the systems for ERP, product design, and product life cycle management to create a unified data model/platform using cloud data stacks.
- The collection and transference of data from equipment and integration with the digital system itself are not sufficient for achieving advanced digitalization; it also needs to be stored and made accessible, with a well-defined access control system and governance model that can facilitate a seamless exchange of data. This will ensure the data is used ethically, securely, and in compliance with regulatory requirements.
This serves as the bedrock for advanced technologies and models like generative AI, digital twins, and digital threads.
Driving IT-OT integration requires building a unified data model and seamless data flow across systems and applications with the right access controls that serve as the foundation to run industrial metaverse and generative AI use cases in manufacturing. For this, technology vendors, such as AWS, PTC, and Secureworks, that have solutions in edge, IoT, IT-OT integration, data management, and industrial security are playing a key role. Furthermore, service providers with deep domain expertise and their own platform-based solutions for IT-OT integration and management and implementation of advanced digitalization use cases like digital twin and generative AI, which actively collaborate with the right ecosystem partners, are becoming pivotal. They help manufacturing enterprises solve the challenges related to IT-OT integration, assisting them by picking the right areas and use cases to target and reap the benefits of advanced digitalization.
Birlasoft Analyst and Advisor Day 2023
At the recent Birlasoft analyst and advisor event at their Pune campus on September 6, 2023, the Group CFO Kamini Shah and CTO Ganesan Karuppanaicker, along with the business leadership teams, weaved together several of these areas, covering how to harness emerging and disruptive technologies like generative AI and the industrial metaverse to transform operations and processes for manufacturing and industrial clients.
As part of the CK Birla Group, 40% of the IT company’s revenue is driven by the manufacturing industry. As the newly appointed CEO, Angan Guha, sets his eyes on making Birlasoft a billion-dollar company in the next three years, the manufacturing vertical is expected to grow from $286 million to $500 million in revenue.
It aims to achieve this target by driving a domain-centric focus on industrial, high-tech, life sciences, and energy and utilities sectors. It leverages digital twin, which is a key enabler of Industry 4.0, to drive the following transformational agendas for its customers:
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- Medical device manufacturers use the design digital twin to accelerate product launches by reducing the cost of product prototype design and test iterations. This enables them to meet product performance and compliance requirements, efficiently handle engineering and manufacturing processes, and streamline change management and product variant management.
- Birlasoft implemented the Supply Chain Digital twin for a wood processing company to optimize its supply chain processes and improve the traceability of wood products, benefiting suppliers, manufacturers, warehouse operators, and logistics providers. It also allowed the customer to identify bottlenecks and non-value-added activities to improve decision-making on route planning, resource allocation, and inventory safety stock to achieve on-time delivery and cost optimization.
- A cement manufacturing company partnered with Birlasoft to implement the process digital twin, which detects process anomalies in real time, offers dynamic root cause analysis, and helps perform closed-loop actions to optimize energy consumption. It has enabled the customer to improve process quality, performance insights, and operational efficiency.
Additionally, Birlasoft implemented its “Plants of the Future” solution, incorporating a unified performance model that provides real-time visibility into factory, asset, and energy consumption. This integrated system offers actionable insights and is enhanced with an AI/ML-based IntelliVision solution, providing guided assistance for quality inspection, testing, and maintenance operations and ensuring worker safety. This comprehensive approach contributes to end-to-end operational improvements for a global engine manufacturer. In 2023, it established a Generative AI CoE in collaboration with Microsoft. Through this center, it aims to enhance product design processes, optimize manufacturing processes, improve quality and defect detection, enable predictive maintenance, and implement digital twins, with a focus on the manufacturing sector.
Birlasoft has taken a partnership route to rapidly address changes in the industry. It leverages its partnerships across the IT-OT landscape to support its digital platforms and application strategy. It has strategic partnerships spanning manufacturing applications (for example, Siemens and SAP), smart factories (Dassault Systems and RealWear), and connected products (for instance, Rockwell Automation and PTC) to address evolving client needs and accelerate value creation.
The Road Ahead
The manufacturing sector’s pursuit of advanced digitalization in the context of Industry 4.0 is poised to bring profound changes. Innovative technologies such as the industrial metaverse and generative AI offer exciting opportunities to enhance collaboration, productivity, and efficiency. These advancements are shaping the future of manufacturing and the industrial sector at large. However, challenges like IT-OT convergence persist, mandating that manufacturing enterprises build a unified data model that effectively leverages both historical and real-time data and handles challenges such as data inaccuracies, intellectual property infringement, and data security. It is important to go one step at a time, focusing on the right use cases that entail lower risk. Service providers, with their combined digital and domain expertise and joint collaboration with external vendors, play a crucial role in reaping the true benefits of Industry 4.0.
Gaurav Dewan, research director; Shwetank Saini, associate research director; Chandrika Dutt, research leader and Premal Shah, lead analyst at Avasant, attended Birlasoft’s Analyst and Advisor Day on September 6, 2023, in Pune, India.
