Innovative Lean Manufacturing Approaches Using Waste Reduction Tools in Large-Scale Production Lines

Abstract

This study evaluates the effectiveness of Digital Lean implementation in manufacturing environments, leveraging Industrial Internet of Things (IIoT) sensors to integrate lean manufacturing principles with Industry 4.0 technologies. Adopting a mixed-methods research design, it combines quantitative performance data from IIoT sensors with qualitative insights from stakeholder interviews to assess impacts on waste reduction, process efficiency, and operational performance. The theoretical framework explores the harmonious integration of lean tools (e.g., 5S, kaizen, value stream mapping) with digital innovations like AI algorithms and predictive analytics, without conflicting with traditional practices. Empirical findings from a case study demonstrate that AI-driven IIoT systems enhance sorting accuracy (up to 98%), reduce inefficiencies by 30-45%, and support lean outcomes such as zero-defect production. Limitations include technical challenges like sensor drift and contextual barriers in small-scale settings, while research gaps highlight the need for broader scalability and cost-benefit analyses. The conclusion emphasizes that Digital Lean, as a synergy of lean and Industry 4.0, drives sustainable manufacturing excellence, with recommendations for future pilot studies and policy alignments. Overall, the study contributes to advancing lean methodologies in the digital era, validating IIoT-enabled practices through rigorous evaluation.