Artificial Intelligence in the Manufacturing Industry

Robotics and Computer-Integrated Manufacturing, 1988

Artifical intelligence is a discipline engaged in the development and application of methods, tools and techniques for solving logically complex problems. These tools and techniques are now becoming accepted in computer applications in general and their use is proliferating rapidly in areas other than computer science. This paper reviews part of the existing artificial intelligence technology with a special view toward potential applications in manufacturing systems. The review includes automatic planning, learning, programming by examples, qualitative modelling and AI programming languages.

International Journal of Manufacturing Technology and Management

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems.

The universal praise subsequently can lead to the questions about the importance of AI. This essay aims to define AI, explain why it is lauded and show its transformative nature via its application in the manufacturing sector.

Since the release of Artificial Intelligent manufacturing like China proposes "Made in China 2025",Germany proposes "Industry 4.0",U.S. Proposes "Design Innovation and Digital Manufacturing", UK proposes "leading technology network sand and innovation", Netherlands proposes "high-end technology strategy" and others related countries are proposed in different areas, and the traditional manufacturing industry has accelerated the pace of transition to Artificial intelligent manufacturing, which has caused tremendous changes in the entire product life cycle of design, production, management, and service in the manufacturing industry. The Artificial intelligent manufacturing space characterized by information perception, network collaboration and human-machine integration will promote the development of Artificial intelligent manufacturing. Keywords:-Artificial intelligent manufacturing, which has caused tremendous changes in the entire product life cycle of design, production, management, and service in the manufacturing industry.

IFAC Proceedings Volumes, 1988

Being understood as a new generation production systems, computer integrated manufacturing (CIM) should comprise artificial intelligence (AI). However, studies in the field of CIM do not centre around any overall concept of AI. Still, it is important to view AI as a CIM-oriented structure. The rapid development of knowledge-handling tools and systems may soon bring the appearance of numerous "islands of automation" in the factory, that will be difficult to integrate. These considerations motivate the present study, starting from a multy-layer and a multy-aspect functional CIM-model with given properties. In general, two points are considered: the application of existing AI-forms in the structure of CIM, and the problems of the development of the necessary distributed and integrated knowledge-handling computer environment for the factory of the future. As a result, principles are defined that may guide the development, delivery and implementation of AI in CIM.

Robotics, 1985

The activities involved in manufacturing a product include part design, process design, and process execution. While conventional techniques of scientific computation and data processing are indispensable when automating each of these stages of manufacturing, there are a number of manufacturing problems for which these conventirnal techniques are ineffectual. The solution to such problems has normally been the responsibility of human engineers, but the magnitude and complexity of these problems in the manufacturing environment of today threaten to overwhelm human reasoning capabilities. Fortunately, a new set of computational techniques is under development and promises to have broad applicability to automating the solution of some of these difficult problems. In this paper, an abstract model of manufacturing is presented to highlight problems which are not amenable to conventional computational techniques. Then, a set of computational techniques which shows promise for solving these problems is described and a number of applications of these techniques to manufacturing problems are given.

Artificial Intelligence applied to the development of the Metalworking Industry, 2024

"Artificial Intelligence Applied to the Development of the Metalworking Industry" by Maximiliano O. Zárate explores the transformative potential of AI in the metalworking sector. The book serves as a practical guide for industry professionals, detailing how AI can enhance operational efficiency, quality, and sustainability. It covers various applications of AI, including automation, robotics, predictive maintenance, and quality control, illustrating how these technologies can streamline processes and reduce waste. Zárate addresses the challenges of adopting AI, such as resistance to change and the need for skilled personnel, while also highlighting the significant opportunities for companies that embrace these technologies. He provides actionable insights and best practices for integrating AI into existing workflows, emphasizing the importance of robust data infrastructure. Ultimately, the book encourages industry leaders to adopt AI strategically to overcome traditional barriers and drive innovation, making it an essential resource for anyone looking to remain competitive in the evolving metalworking landscape.

New techniques from computational intelligence have attracted the interest of manufacturing researchers in academia, government and industry. These techniques include artificial neural networks, tabu search and evolutionary computing. While these computational techniques inspired by nature have shown promise in many manufacturing applications such as robotics, machine vision, process control, process planning and scheduling, there is little in the literature on their practical use. Moving these techniques from simulated data sets, toy problems or laboratory settings to real industrial applications is a large and uncertain step. This paper focuses on the technology transfer issues and solutions when using computational intelligence for off-line control of manufacturing processes and scheduling of production environments.

2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), 2018

In order to embrace new generation artificial intelligence to upgrade manufacturing industry, we propose the concept of new generation artificial intelligence-driven intelligent manufacturing (NGAIIM), which is a new manufacturing paradigm integrating human/machine/environment/information into product lifecycle activities. First, we introduce new generation artificial intelligence. Second, we present NGAIIM connotation, NGAIIM architecture and its technology system. Then, we examine a NGAIIM use case-CASICloud. Finally, we provide suggestions for directing the NGAIIM development.

International Journal of Recent advances in Mechanical Engineering, 2014

This paper shows a framework of the different techniques for the design of the planning and governing components, implementation, Evolution and execution of an intelligent manufacturing system. Architecture of a modern manufacturing industry is presented, which makes possible to create specific manufactrons system for the specific tasks, depending on the self-operated analysis of its essential characteristics. The manufactronic industry concept helps in the integration of intelligence and to increase flexibility at the maximum level of the manufacturing system as well as at the minimum level of the particular machine. This concept is implemented & demonstrated in the automobile and aeronautical industries, but can be simply applied to nearly all manufacturing industries. Implementation of manufactronic techniques in the industries helps to forecast and to fulfill the rapidly varying customer requirements, to produce high quality products in sufficient quantities with reduction in costs. The Modern Intelligence Technologies are also presented in this paper.