Abstract
With the rapid development of science and technology, digital technology has brought the world economy and management into a new stage. Collaborative design can realize product design process by cross-regional and cross-industry designers and share and exchange product information through network. With the rapid development of big data and artificial intelligence, knowledge services have gradually developed into multirole collaborative design activities based on artificial intelligence decision support. Traditional manufacturing industry has gradually transformed into modern manufacturing service industry after integrating information technology means such as Internet, communication, computer, and modern management methods. This article focuses on artificial intelligence decision support systems and the complex product manufacturing industry. We present a detailed analysis of how to integrate the knowledge generated by the product life cycle in the era of big data. We calculate the influence coefficient and sensitivity index of four different industries and propose a metadata architecture to improve the value of products as a whole. The findings of the research study imply that a knowledge-based collaborative platform should be designed by the enterprises and industries and a platform-based construction approach for economical, practical, and reliable production. We also present a detailed discussion about other factors such as the network cost of symmetric services, raw data and forecast data, and the number of nodes and the processing complexity.
Highlights
-In the 21st century, science and technology are developing rapidly, especially artificial intelligence and big data technology due to the digitization of the industries and the advancement of the Internet, which brings the economy and management of today’s world into a completely new stage [1]. e task of process planning is often accomplished by a group of experts with different domain knowledge distributed in different process design departments, because of the progress in the fields of information technology, especially the rapid development of computer and communication technology [2]
Collaborative design based on artificial intelligence decision support system enables the product design process to be coordinated by designers across regions and industries and to share and exchange product information through the network [4], thereby achieving the purpose of improving design capability, reducing product development costs, and shortening product development time
Scientific Programming manufacturing industry has gradually transformed into a modern manufacturing service industry. e manufacturing method has gradually evolved from large-scale production line to personalized, customized, and digital [6]
Summary
-In the 21st century, science and technology are developing rapidly, especially artificial intelligence and big data technology due to the digitization of the industries and the advancement of the Internet, which brings the economy and management of today’s world into a completely new stage [1]. e task of process planning is often accomplished by a group of experts with different domain knowledge distributed in different process design departments, because of the progress in the fields of information technology, especially the rapid development of computer and communication technology [2]. E transformation to a new technology service mode has become an important strategic component of manufacturing industry [11] It is the potential value of manufacturing industry, and the powerful pillar of technological innovation and enterprise value added. Stepping out of the constraints of traditional manufacturing technology service thinking, the technical service model will be transferred to a more convenient and superior network environment, giving full play to the enormous intangible value of knowledge management theory [14]. It is the inevitable way out for the development of manufacturing technology services. It is the inevitable way out for the development of manufacturing technology services. is article analyzes artificial intelligence decision support systems and focuses on the complex product manufacturing industry and the integration of the knowledge generated by the product life cycle in the era of big data. e analysis and application of the knowledge big data formed after integration is taken into account, and the impact of product life cycle on resource consumption and environment is considered in the design stage. e aim is to help design and develop complex product lifecycle design, big data integration, and application systems
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