{"id":74489,"date":"2024-05-31T07:57:54","date_gmt":"2024-05-31T05:57:54","guid":{"rendered":"https:\/\/intellias.com\/?post_type=blog&p=74489"},"modified":"2024-07-12T13:37:27","modified_gmt":"2024-07-12T11:37:27","slug":"industrial-metaverse-the-next-stage-of-the-manufacturing-industry","status":"publish","type":"blog","link":"https:\/\/intellias.com\/next-stage-of-the-manufacturing-industry\/","title":{"rendered":"Industrial Metaverse: The Next Stage of the Manufacturing Industry"},"content":{"rendered":"

Industrial metaverse<\/em>. When leaders in the industrial sector hear this phrase, they picture semi-autonomous conveyor belts, employees designing product<\/a> mockups in virtual reality, and sustainable resource management.<\/p>\n

Many industrial automation projects face cultural resistance. Employees are disgruntled with cameras invading their privacy. Labor union leaders lament robots taking over humans\u2019 jobs, while stakeholders view proposed innovation skeptically due to unclear return on investment (ROI). In reality, all sides are experiencing tunnel vision.<\/p>\n

We\u2019re still in the Industry 4.0 era \u2014 a period of rapid adoption of emerging technologies, from cloud and edge computing<\/a> to machine learning (ML) and artificial intelligence (AI)<\/a>. In recent years, manufacturing leaders have built a solid technological foundation to support their operations. Now, they\u2019re eager to scale the available technology stack to support new use cases.<\/p>\n

\"Industrial<\/p>\n

Source: Deloitte \u2014 Exploring the industrial metaverse<\/a><\/em><\/p>\n

Unpacking the industrial metaverse: Key technology components<\/h2>\n

The metaverse isn\u2019t a singular technology but a collection of building blocks organizations can use to replicate physical environments.<\/p>\n

At Intellias, the industrial metaverse combines industrial digital twins with AR\/VR capabilities powered by advanced analytics and artificial intelligence<\/strong>.<\/p>\n

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IntelliTwin Platform<\/p>\n

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Transform your infrastructure with the data-driven IntelliTwin platform powered by Intel SceneScape<\/div>\n <\/div>\n <\/div>\n Learn more<\/span>\n\t\t <\/a><\/div>\n

Let\u2019s look at the role and value of each technology.<\/p>\n

Digital twins<\/h3>\n

A digital twin is a virtual replica of equipment, an ecosystem, or a facility that emulates its physical characteristics using real-time data. Digital twins<\/a> synchronize the physical and digital worlds, offering a 360-degree view of an asset\u2019s condition, performance, and other characteristics. They can include data points like motion, temperature, vibrations, or energy consumption captured with modern connectivity technology.<\/p>\n

Thanks to these characteristics, digital twins can support various use cases<\/a> across sectors: predictive equipment maintenance, optimized energy management, product process simulation, surgical training, precision farming, and more.<\/p>\n

In the manufacturing sector, 71% of leaders said their enterprises already used digital twin technology in 2023 according to an Altair survey<\/a>. Among adopters, 94% said that digital twins improved new product development<\/a>, while 62% cited maintenance and warranty cost optimization.<\/p>\n

Digital twin technology adoption<\/h4>\n

\"Industrial<\/p>\n

Source: Altair \u2014 2023 Global Digital Twin Survey Report<\/a><\/em><\/p>\n

Intel has been progressively digitizing its factories since the early 2000s. Its facilities can be operated remotely via Remote Operation Centers (ROCs), allowing engineers to monitor and control operations from any location via a software platform.<\/p>\n

The company also relies on digital twins<\/a> to model and analyze complex factory operations, evaluate the risks of process changes, and train staff. For example, using a digital twin of the Automated Material Handling System (AMHS), Intel engineers can remotely monitor performance, identify problems early, and accurately predict production metrics. With digital twins, Intel increased productivity and reduced unit throughput time while maintaining product quality despite complex manufacturing procedures.<\/p>\n

Siemens<\/strong>, a leader in developing and implementing digital twin solutions, recently launched<\/a> a new digital twin module to create 3D simulations of CFD thermal environments. Electronics manufacturers face heat dissipation challenges due to miniaturization and increasing processing demands. Complex IC package architectures like 2.5D, 3D IC, and chipset-based designs bring complex thermal management challenges. Siemens\u2019 thermal twin enables high-fidelity 3D thermal analysis and secure model sharing.<\/p>\n

Today, most companies rely on descriptive or informative digital twins<\/strong>:<\/p>\n