•  
  •  
 

Keywords

Intelligent Systems, Industrial Management, Cyber-Physical Systems, Internet of Things, Machine Learning, Automation Challenges, Decision Support Systems

Document Type

Article

Abstract

The modern industrial management is quite dependent on intelligent systems that promote intensifying automation and general efficiency in different industries. With the introduction of advanced technologies in form of AI, machine learning, CPS and IoT these systems move the industrial functionality to a great extent. By combining, such technologies have the ability to quickly interpret data, detect the need for maintenance early in the line and make informed decisions, which produce highly optimized manufacturing processes. Automation has automated the process, reducing costs considerably, producing more, and maintaining high standards. Development of industry 4.0 has been a major tool in coordinating the merge of smart technologies to satisfy the efficiency in conversation between machines, software, and man. The adoption of intelligent systems has helped in increasing operational flexibility, reducing the downtime, and increased commitment to sustainability. Similar benefits have materialized in areas such as manufacturing, pharmaceuticals and logistics within which intelligent systems integration results in reduced cycle times and better inventory control and safer operations. However, the increased application of these technologies is limited by such issues as lack of compatibility of legacy systems, organizational factors, and lack of competent personnel. As predictable, it is critical to get over these hurdles to actualize the potential of intelligent systems and promote sustainable industrial efficiency. With the advancement of technology, role of intelligent systems to play in the development of industrial management policies, moving the industry towards sustainability and supporting global market success will increase.

Download

Share

COinS