Applied IT & Engineering
Information and engineering sciences | Online ISSN 3068-0115
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Volume 2 Number 1 2024
RESEARCH ARTICLE (Open Access)
Integrating IoT, Artificial Intelligence, and Lean Six Sigma in SME Manufacturing: A DMAIC-Based Framework for Waste Reduction and Operational Excellence
Md Fazle Alahi Bhuiyan1*
Applied IT & Engineering 2 (1) 1-8 https://doi.org/10.25163/engineering.2110774
Submitted: 01 January 2024 Revised: 06 February 2024 Accepted: 13 February 2024 Published: 15 February 2024
Abstract
Background: Manufacturing facilities — particularly small and medium-sized enterprises — have long operated under pressure to produce more, waste less, and remain competitive in markets that do not pause to accommodate organizational inertia. Traditional shop floor management systems, built for earlier eras of production, increasingly struggle to meet these demands. The fourth industrial revolution has placed three powerful tools within reach: the Internet of Things (IoT), artificial intelligence (AI), and Lean manufacturing practices. Each has demonstrated value independently. What remains less settled, and arguably more important, is whether they can be made to work together in a structured, scalable way that does not assume large-enterprise resources.
Methods: This study examined a semi-automated skid steer loader manufacturing facility comprising five production departments, 25 workstations, and 52 personnel. A mixed-methods design was employed, combining direct shop floor observation, production records analysis, and supervisory discussions with a systematic review of published Industry 4.0 implementation literature. The DMAIC (Define, Measure, Analyze, Improve, Control) framework structured both the diagnostic and intervention phases of the study.
Results: Baseline analysis revealed substantial inefficiencies across all five departments — aggregate cycle time of 6,800 minutes, combined idle time of 470 minutes, and downtime ranging from 105 to 330 minutes per department. Five anomaly categories were identified: machinery, manpower, layout, quality, and operational constraints. A technology-matched intervention framework, integrating IoT sensor deployment, AI-driven predictive analytics, and Lean tools including 5S, Six Sigma, and Kaizen, was developed and mapped onto the DMAIC cycle.
Conclusion: Strategic integration of IoT, AI, and Lean practices within a DMAIC framework offers a credible, organizationally grounded path toward operational excellence in SME manufacturing. Phased implementation, beginning with Lean discipline before layering digital technologies, is recommended as the most feasible and durable approach.
Keywords: Internet of Things (IoT); Lean Six Sigma; DMAIC framework; Industry 4.0; small and medium enterprises (SMEs)
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