The Role of Seven Basic Tools in the Era of Industry 4.0 and AI

Abstract

This study examines the evolving role and relevance of the Seven Basic Tools of Quality in the context of Industry 4.0 and Artificial Intelligence through a systematic literature review. The research investigates how these traditional quality management tools adapt and integrate with emerging technologies while assessing their continued relevance in modern manufacturing environment. Through a comprehensive analysis of academic literature, this study reveals significant transformations in the implementation of Seven Basic Tools. The findings demonstrate that these tools remain fundamentally relevant but require substantial adaptation to meet contemporary challenges. Integration with Industry 4.0 technologies has enhanced their capabilities, with studies showing that implementation of IoT in real time control chart has improve accuracy rate up to 100% and calculation speed of 4.731 seconds compared to manual system. Implementation of machine learning to enhance production quality control also showed good accuracy from 75% to 100% under various lighting condition in textile manufacturing. The research also identifies key challenges in implementation, particularly regarding data complexity and workforce competency requirements. This study contributes to the understanding of how traditional quality management tools can be effectively modernized and suggests frameworks for their integration with advanced digital technologies.