Advancing Manufacturing Through Artificial Intelligence: Current Landscape, Perspectives, Best Practices, Challenges, and Future Direction

Abstract

The industrial sector is currently undergoing a transformative era of intelligent automation driven by Artificial Intelligence (AI) capabilities. This synergy greatly enhances efficiency and seamlessly enables data-driven decision-making processes. These advantages enable more efficient resource allocation and enhance production planning precision. This paper aims to provide state-of-the-art and ongoing developments in the AI landscape within the manufacturing industry. In addition, the review explores the key areas where AI is being applied in manufacturing, such as predictive maintenance, quality control, process optimization, supply chain management, robotics and automation, and intelligent decision support systems. The review also encompasses an exploration of the challenges encountered by the manufacturing sector, alongside an investigation into the potential of AI to mitigate these challenges. Furthermore, this work thoroughly reviews recent AI advancements, including explainable AI, human-robot collaboration, edge computing, and the Internet of Things (IoT) integration. The review concludes by providing recommendations, highlighting best practices, and providing insights into potential collaborative opportunities.

Keywords

• Smart manufacturing
• Industry 4.0
• artificial intelligence
• automation
• machine learning
• quality control