Previously in Part 5 of our Artificial Intelligence (AI) blog series, we examined the key challenges to implementing AI and how to overcome those barriers. Now, let’s explore the immense value AI promises to bring to industrial sectors—both today and into the future.
Digital Continuity & Digital Twins
Digital continuity is about creating an environment where all information from every phase of a product or asset’s lifecycle – from concept to disposal or reuse – is captured in real time and transformed into actionable insights.
Manufacturers have long wanted this kind of full lifecycle visibility, but they have been frustrated by either siloed data, or data deserts (nonexistent data for certain objects and events). Now, enhanced data access technologies and sensor-based IoT connectivity can deliver the comprehensive data and data views needed.
What’s more, a “digital twin” of a physical process, product, asset or environment can provide a unique, authoritative and consistent referential for this lifecycle data. For instance, a 3D CAD model of a product can provide a referential to which data can be linked from conception through to design, engineering, manufacturing and post-sales service.
Going a step further, a simulation-capable twin like Dassault Systèmes’ 3DEXPERIENCE twin provides more than just a consistent, “single-version-of-the-truth” referential. It is an extremely powerful tool for iterating through scenarios and options for everything from design to fabrication to maintenance and repair, for continuous improvement and innovation. And the more real-world data the digital model is fed, the more accurate and valuable are the simulations it supports.
The Right Digital Collaboration Infrastructure
Digital transformation requires a general foundation of social, mobile, cloud and Internet technologies. Connecting people, places, and objects, and enabling anywhere, anytime collaboration, is at the heart of the digital age.
For digital continuity and the proper functioning of digital twins, a business platform with integrated search capabilities is a requirement. This type of platform can connect to or crawl all relevant internal and external resources, and provide unified views of both structured and unstructured information across these silos. With the right platform, these views can include dashboard metrics and recommendations based on advanced analytics.
Part 2: Industrial applications of Artificial Intelligence and Machine Learning
Part 3: Differentiating Between Artificial Intelligence, Machine Learning and Deep Learning
Part 4: Benefits of Machine Learning in Industrial Contexts
Part 5: Key Challenges of Artificial Intelligence in Industrial Sectors
Part 6: Realizing the Value of Artificial Intelligence in Industrial Sectors
Part 7: Artificial Intelligence and Machine Learning at Dassault Systèmes
to stay on top of the latest industry news, ask questions and collaborate with peers:
- EXALEAD Sourcing & Standardization Intelligence User Community
- 3DEXPERIENCE Marketplace | PartSupply User Community
- NETVIBES Public Community
Learn more about EXALEAD on the 3DEXPERIENCE platform.
Karin is a brand content creator on the NETVIBES Marketing team.