The future of manufacturing is iterative, collaborative, and data-driven

Data Driven Transformation

Another key digital transformation approach is to integrate artificial intelligence (AI) and machine learning (ML) to automate, or at least streamline and simplify, product development. At Raytheon, teams leverage model-driven engineering to predict complex fluid, structural, and thermal interactions in rocket systems so engineers can better understand how a product will behave. at supersonic speed. But any industry can use AI and ML to help teams make better and smarter design choices and ultimately create better products and experiences for customers and users. last.

For example, natural language processing, a branch of AI that trains machines to understand human speech and writing, could improve everything from customer support to product descriptions. ecommerce. AI and ML can also be used to streamline and automate warehouse operations as well as data entry and processing. In the early days of the pandemic, a number of banks relied on AI-powered robotic process automation to respond to the large number of Paycheck Protection Program applications and rapid submissions. The U.S. government.

A central goal of many digital transformations is to connect stored data across the organization, making it easier to discover, access, and leverage. This is often achieved through federated data modeling, an approach to data management that creates a centralized view of an organization’s data, even though it is located in different locations. By aligning previously stored data, while storing it at its source, data binding provides simple access to up-to-date data, allowing different teams to collaborate throughout the process. development, production and testing.

At companies like Raytheon, where security and safety are a top concern, data must be organized and firewalled to ensure that only those with the appropriate access rights can view the information that has been received. classify. But once implemented, the modern data architecture has also helped Raytheon’s teams navigate the global supply chain that continues to face challenges posed by the pandemic and ongoing political conflict.

“We have stored data in multiple systems. There is data in our procurement system and data in our risk management system. There is data stored in the master schedule of each show,” says Gundrey. “Our supply chain team can now bring all this data together and use AI and ML to better predict material lead times and help us better plan for its program activities”.

All of these transformative technologies and critical data can be linked through a “digital chain,” a communication architecture that runs throughout the manufacturing process. By collecting and streaming data throughout the product lifecycle, the digital chain integrates various digital technologies in one holistic view. Of course, people and processes remain at the heart of this transition. As Gundrey says, “I wanted people to know that when we built this digital chain, it was all about the people and the workflow that went with it.”

The benefits of digital transformation

For companies today, the benefits of digital transformation are enormous. In addition to connecting and speeding up product development cycles and providing teams with richer and more relevant data, it can also help reduce risk.

At the individual enterprise level, this means reducing the risk of disappointing end users as the agile approach has helped teams identify potential problems early in the design process. Using these iterative and collaborative approaches gives teams the ability to solve complex design problems in the first place, preventing costly rework later, and giving managers have a greater vision of how separate components will work together.

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