In the modern business world, Artificial Intelligence (AI) is revolutionizing the way operations are managed and increasing business productivity and efficiency. AI-powered systems are proof that technology is transforming the way companies operate. Deep learning, an interconnected network of artificial intelligence “nodes”, has enabled the development of new approaches to managing operations. A widely used textbook by Russell and Norvig states that AI is the intelligence of machines and software, a branch of computer science designed to create this intelligence.
AI technology has gained increasing attention in many industries, as it facilitates cost-effective solutions for the supply chain and provides greater visibility to decision makers at a high level. Several case studies can help researchers to understand the phenomenon studied and also to develop new approaches to managing operations. The contact between the company and its customers is crucial for corporate operations. Therefore, more advanced IT systems are required to address the multi-level and highly variable problems of industrial operations in digitalization. AI is an emerging field in computer science due to the latest advances in deep neural networks, convolutional neural networks, mathematical optimization techniques used in operations research, programming with restrictions, and various numerical methods. The main objectives of using AI in operations management are improving the life cycle of assets by ensuring the correct procedures for spare parts, moving from a calendar-based system to condition-based maintenance, and reducing operating expenses and life cycle costs.
AI uses a large amount of data to identify patterns in people's search behaviors and provide them with more relevant information about their circumstances. Hossein Rahnama, founder and CEO of the AI concierge company Flybits and a visiting professor at the Massachusetts Institute of Technology, worked with TD Bank to integrate AI into regular banking operations. The growing amount of data is collected from sensor sources, commercial transactions and operations. The technical reasons for using AI in operations management are that the development of machine learning and most intelligent technologies begin in SCM. The AI research community has been related to DSS and other approaches in the area of operations management, such as planning and programming, since the 1960s. To simultaneously improve its inspection work and the quality of its products, the Japanese company NEC has developed a warehouse product inspection system using image recognition technology in logistics operations. In conclusion, AI is transforming the way companies operate by revolutionizing operations management and increasing business productivity and efficiency.
The main objectives of using AI in operations management are improving asset life cycles, moving from calendar-based systems to condition-based maintenance, and reducing operating expenses and life cycle costs.
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