Optimizing Product Development and Innovation Processes with Artificial Intelligence

The rapid advancement of artificial intelligence (AI) has created new avenues for enhancing the design and innovation phases of product development. This dissertation aims to provide a comprehensive and analytic examination of the usage of AI tools to assist different aspects of the product development process. The objective is investigating the way in which AI technologies can improve the productivity, effectiveness, and competition of product development teams, while addressing the risks and challenges related to their deployment. The process of product development and its phases are introduced in the very first chapter, which covers planning, concept development and system-level design along with detailed design, testing and refinement and production ramp-up. The discussion then focuses on the application of operation research to product development and examines different reasoning techniques, like deductive, inductive and abductive reasoning, common sense reasoning, monotonic and nonmonotonic reasoning and probabilistic reasoning. The chapter concludes with a review of cognitive activities in product development, concentrating on their correlation with the various stages of the process. The second section offers a thorough introduction to recent advancements in AI, covering various subfields and branches like machine learning, neural networks, evolutionary computation, computer vision, robotics, expert systems, speech processing, natural language processing, planning, and large language models. The exploration is a starting point for learning how AI technologies might be employed in product development. The third chapter examines the relationship between AI and product development, showcasing the potential uses and applications of AI technologies in supporting the design and innovation process. This chapter combines AI and cognitive science to illustrate just how AI tools can augment cognitive tasks in product development, resulting in far more efficient and effective processes. The chapter showcases commercial software incorporating AI technologies and shows the practical application of AI in product development. The fourth chapter examines the risks and challenges of utilizing AI, including bias propagation, legal issues, data storage, data security, social impact, and integration issues. The discussion stresses the need for balancing the advantages of AI with the risks and challenges it entails, so that AI is utilized efficiently and responsibly. This thesis provides an in-depth analysis of the application of AI tools in product development and innovation. Product development teams can make educated decisions regarding how to incorporate AI into their workflows and processes by knowing the different technologies, their challenges and applications. The use of AI in product development will only grow as AI evolves and matures, creating exciting opportunities for innovation and change in the industry.