INDUSTRIAL ENGINEERING APPROACHES TO QUALITY CONTROL IN HYBRID MANUFACTURING A REVIEW OF IMPLEMENTATION STRATEGIES

Abstract

Hybrid manufacturing, which integrates additive and subtractive processes within unified workflows, has emerged as a transformative paradigm in advanced production systems, yet it continues to face persistent challenges in achieving stable and predictable quality outcomes. This review critically examines how industrial engineering approaches are being applied to overcome these challenges, focusing on the implementation strategies that enable robust quality control in hybrid manufacturing environments. Drawing on an extensive analysis of 128 peer-reviewed articles collectively amassing over 12,000 citations, this study synthesizes evidence across five major thematic areas: statistical process control and design of experiments for process stabilization, multi-sensor in-situ monitoring and real-time feedback for defect prevention, digital twin–guided planning for predictive control, data-driven analytics and process mining for continuous improvement, and organizational enablers such as cross-functional teams, structured training, and layered audits for sustained performance. The findings reveal that when these industrial engineering methods are integrated into cohesive, closed-loop architectures, they deliver measurable improvements in process capability indices, reduce scrap and rework rates, enhance first-pass yield, and shorten time-to-stability after new product introduction. In contrast to earlier assumptions that hybrid manufacturing was too variable for conventional quality tools, the evidence demonstrates that structured industrial engineering frameworks now serve as the backbone of quality assurance in this domain. However, the review also identifies ongoing challenges, including data interoperability barriers, cross-domain calibration gaps, and the need for graded human-in-the-loop oversight to mitigate edge-case failures. Overall, this study highlights a decisive shift in hybrid manufacturing quality control from reactive, post-process inspection toward proactive, data-driven, and organizationally embedded systems, positioning industrial engineering not merely as a supplementary toolkit but as the central framework for scaling hybrid manufacturing into a reliable, cost-effective, and globally competitive production strategy.