In recent years, the engineering industry has become significantly competitive. Among the many criteria identified at enterprises as competitive advantages, the quality of the products manufactured holds a significant place. In addition to the main methods of improving product quality, the article discusses technologies that have only recently gained recognition – these are informational or digital technologies widely used in the management of enterprises in the real sector of the economy. Such technologies include distributed database technologies (Blockchain), big data (Big Data), digital twins (Digital Twin), the Internet of Things (Internet of Things), artificial intelligence (Artificial Intelligence), and several others. The authors believe that the potential of the latter for managing the quality of service in engineering enterprises is not sufficiently studied and implemented in practice. This work analyzes the possibilities of wider implementation of artificial intelligence-based technologies in the service management system to reduce costs in servicing high-tech equipment and to enhance the competitiveness of manufacturers.

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AI-Driven After-Sales Service Management for Complex Machine-Building Products

  • Boris A. Shvaiko,
  • Yury G. Gertsik

摘要

In recent years, the engineering industry has become significantly competitive. Among the many criteria identified at enterprises as competitive advantages, the quality of the products manufactured holds a significant place. In addition to the main methods of improving product quality, the article discusses technologies that have only recently gained recognition – these are informational or digital technologies widely used in the management of enterprises in the real sector of the economy. Such technologies include distributed database technologies (Blockchain), big data (Big Data), digital twins (Digital Twin), the Internet of Things (Internet of Things), artificial intelligence (Artificial Intelligence), and several others. The authors believe that the potential of the latter for managing the quality of service in engineering enterprises is not sufficiently studied and implemented in practice. This work analyzes the possibilities of wider implementation of artificial intelligence-based technologies in the service management system to reduce costs in servicing high-tech equipment and to enhance the competitiveness of manufacturers.