Additional information
by Tobias Wigand (Author), Ram Dhiwakar Seetharaman (Author)
While rule-based automation follows predefined instructions to perform repetitive tasks, AI agents act autonomously and are able to make decisions in complex, dynamic situations. This book shows how to build AI agents for product development, particularly hardware development. It is aimed at development engineers, designers and engineering managers.
The book covers the following topics:
- Basic principles and architectures of agentic systems
- Technological components of agentic systems: frameworks and patterns for designing agents as well as interfaces to CAx, PLM, and ERP systems
- Governance, change management, and role responsibilities
- Outlook: vision of a future engineering organization
Step by step, the book demonstrates how AI agents can be developed by using low-code platforms. It also considers Multi-Agent Systems (MAS). MAS go one step further by combining several AI agents that interact with each other to achieve common or individual goals. The book provides criteria for selecting pilot projects and guides you through the project phases of the implementation. Use cases from the industry--from automotive tier suppliers to consumer goods OEMs up to engineering service providers--provide valuable practical insights from engineering leaders at companies such as NASA, Miele, IMS Gear or ARRK Engineering. They show how AI agents can reduce costs in product development and provide a competitive advantage through shorter time-to-market cycles.
