The Role of Quantum Machine Learning in the Transition from Industry 4.0 to Industry 5.0

Abstract

The current review's goal is to examine the strategic significance of Quantum Machine Learning (QML) as a technology tool or strategic enabler of Industry 5.0, the approaching industrial revolution. To summarize and categorize the most common forms, antecedents, and outcomes of sustainable innovation, the primary objective of this study is to systematically identify and critically evaluate the literature on sustainable innovation in Industry 5.0 since January 2020. A thorough search and review of 5984 scholarly articles were identified during the systematic review, and 36 publications were chosen by a cyclic filtration for a careful review in the fields of Industry 5.0 and QML to analyze the articles' contents. The findings demonstrate that QML provides a revolutionary improvement in decision-making platforms, system security, and data analytics in Industry 4.0. By taking into consideration a methodical and critical assessment of the research manuscripts, the proposed survey offers readers an impactful insight into the functions of quantum machine learning as an enabler to Industry 5.0 processes. QML is emphasized as a key driver for secure, intelligent, and sustainable industrial ecosystems through QML-assisted designs across various verticals, such as smart healthcare, manufacturing, digital twins, and Cobots, as this review methodically examines the enabling technologies shaping the Industry 5.0 vision. It also highlights how QML can improve decision-making, ensure post-quantum security, optimize resources, and speed up the realization of human-centric, energy-efficient, and resilient Industry 5.0 systems as quantum computing advances.