Applied IT & Engineering

Information and engineering sciences | Online ISSN 3068-0115
31
Citations
44.8k
Views
27
Articles
Submit
  1. You are here:
  2. Home
  3. Journals
  4. Engineering
Your new experience awaits. Try the new design now and help us make it even better
Switch to the new experience
Applied IT & Engineering

Volume 2 Number 1 2024

Article Contents

Figures and Tables
RESEARCH ARTICLE   (Open Access)
Contents Vol 2 (1)

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*

+ Author Affiliations

Applied IT & Engineering 2 (1) 1-8 https://doi.org/10.25163/engineering.2110774

Submitted: 01 January 2024 Revised: 06 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)

References

Anosike, A., Alafropatis, K., Garza-Reyes, J. A., Kumar, A., Luthra, S., & Rocha-Lona, L. (2021). Lean manufacturing and internet of things – A synergetic or antagonist relationship? Computers in Industry, 129, 103464. https://doi.org/10.1016/j.compind.2021.103464

Chiarini, A., Belvedere, V., & Grando, A. (2020). Industry 4.0 strategies and technological developments. An exploratory research from Italian manufacturing companies. Production Planning & Control, 31(16), 1385–1398. https://doi.org/10.1080/09537287.2019.1710304

Chiarini, A., & Kumar, M. (2021). Lean Six Sigma and Industry 4.0 integration for Operational Excellence: evidence from Italian manufacturing companies. Production Planning & Control, 32(13), 1084–1101. https://doi.org/10.1080/09537287.2020.1784485

Ciano, M. P., Dallasega, P., Orzes, G., & Rossi, T. (2021). One-to-one relationships between Industry 4.0 technologies and Lean Production techniques: a multiple case study. International Journal of Production Research, 59(5), 1386–1410. https://doi.org/10.1080/00207543.2020.1821119

Florescu, A., & Barabas, S. (2022). Development Trends of Production Systems through the Integration of Lean Management and Industry 4.0. Applied Sciences, 12(10), 4885. https://doi.org/10.3390/app12104885

Frank, A. G., Dalenogare, L. S., & Ayala, N. F. (2019). Industry 4.0 technologies: Implementation patterns in manufacturing companies. International Journal of Production Economics, 210, 15–26. https://doi.org/10.1016/j.ijpe.2019.01.004

Glover, W. J., Farris, J. A., & Van Aken, E. M. (2015). The relationship between continuous improvement and rapid improvement sustainability. International Journal of Production Research, 53(13), 4068–4086. https://doi.org/10.1080/00207543.2014.991841

Hohmeier, K. C., Renfro, C., Loomis, B., Alexander, C. E., Patel, U., Cheramie, M., Cernasev, A., Hagemann, T., Chiu, C.-Y., Chisholm-Burns, M. A., & Gatwood, J. D. (2022). The Lean Six Sigma Define, Measure, Analyze, Implement, Control (LSS DMAIC) Framework: An Innovative Strategy for Quality Improvement of Pharmacist Vaccine Recommendations in Community Pharmacy. Pharmacy, 10(3), 49. https://doi.org/10.3390/pharmacy10030049

Hughes, L., Dwivedi, Y. K., Rana, N. P., Williams, M. D., & Raghavan, V. (2022). Perspectives on the future of manufacturing within the Industry 4.0 era. Production Planning & Control, 33(2–3), 138–158. https://doi.org/10.1080/09537287.2020.1810762

Ivanov, D., & Dolgui, A. (2021). A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0. Production Planning & Control, 32(9), 775–788. https://doi.org/10.1080/09537287.2020.1768450

Li, L.-R. (2019). Lean Smart Manufacturing in Taiwan—Focusing on the Bicycle Industry. Journal of Open Innovation: Technology, Market, and Complexity, 5(4), 79. https://doi.org/10.3390/joitmc5040079

Liao, M.-H., & Wang, C.-T. (2021). Using Enterprise Architecture to Integrate Lean Manufacturing, Digitalization, and Sustainability: A Lean Enterprise Case Study in the Chemical Industry. Sustainability, 13(9), 4851. https://doi.org/10.3390/su13094851

Lin, Y., Wang, Y., & Kung, L. (2015). Influences of cross-functional collaboration and knowledge creation on technology commercialization: Evidence from high-tech industries. Industrial Marketing Management, 49, 128–138. https://doi.org/10.1016/j.indmarman.2015.04.002

Malek, Y. N., Kharbouch, A., Khoukhi, H. El, Bakhouya, M., Florio, V. De, Ouadghiri, D. El, Latre, S., & Blondia, C. (2017). On the use of IoT and Big Data Technologies for Real-time Monitoring and Data Processing. Procedia Computer Science, 113, 429–434. https://doi.org/10.1016/j.procs.2017.08.281

Mendes, D., Gaspar, P. D., Charrua-Santos, F., & Navas, H. (2023). Synergies between Lean and Industry 4.0 for Enhanced Maintenance Management in Sustainable Operations: A Model Proposal. Processes, 11(9), 2691. https://doi.org/10.3390/pr11092691

Moeuf, A., Pellerin, R., Lamouri, S., Tamayo-Giraldo, S., & Barbaray, R. (2018). The industrial management of SMEs in the era of Industry 4.0. International Journal of Production Research, 56(3), 1118–1136. https://doi.org/10.1080/00207543.2017.1372647

MR Haque, & MNM Khan. (2023). Strategic Integration of Big Data Analytics to Enhance Risk Management, Sustainable Supply Chains, and Business Competitiveness in the United States. Business & Social Sciences, 1(1), 1–7. https://doi.org/10.25163/business.1110498

P Choudhury, & M Sharfuddin. (2023). Management Information Systems in Contemporary Business: Prospects, Strategic Advantages, and Future Challenges. Business & Social Sciences, 1(1), 1–7. https://doi.org/10.25163/business.1110509

P Choudhury, & N Imtiaz. (2020). Overcoming Data Excess to Improve Decision-Making and Information Systems Plans for Organizational Performance. Journal of Primeasia, 1(3), 1–7. https://doi.org/10.25163/primeasia.1110403

Radanliev, P., De Roure, D., Page, K., Nurse, J. R. C., Mantilla Montalvo, R., Santos, O., Maddox, L., & Burnap, P. (2020). Cyber risk at the edge: current and future trends on cyber risk analytics and artificial intelligence in the industrial internet of things and industry 4.0 supply chains. Cybersecurity, 3(1), 13. https://doi.org/10.1186/s42400-020-00052-8

Rahardjo, B., Wang, F.-K., Yeh, R.-H., & Chen, Y.-P. (2023). Lean Manufacturing in Industry 4.0: A Smart and Sustainable Manufacturing System. Machines, 11(1), 72. https://doi.org/10.3390/machines11010072

Rodriguez Delgadillo, R., Medini, K., & Wuest, T. (2022). A DMAIC Framework to Improve Quality and Sustainability in Additive Manufacturing—A Case Study. Sustainability, 14(1), 581. https://doi.org/10.3390/su14010581

Shahin, M., Chen, F. F., Bouzary, H., & Krishnaiyer, K. (2020). Integration of Lean practices and Industry 4.0 technologies: smart manufacturing for next-generation enterprises. The International Journal of Advanced Manufacturing Technology, 107(5–6), 2927–2936. https://doi.org/10.1007/s00170-020-05124-0

Shrouf, F., & Miragliotta, G. (2015). Energy management based on Internet of Things: practices and framework for adoption in production management. Journal of Cleaner Production, 100, 235–246. https://doi.org/10.1016/j.jclepro.2015.03.055

Trakadas, P., Simoens, P., Gkonis, P., Sarakis, L., Angelopoulos, A., Ramallo-González, A. P., Skarmeta, A., Trochoutsos, C., Calvο, D., Pariente, T., Chintamani, K., Fernandez, I., Irigaray, A. A., Parreira, J. X., Petrali, P., Leligou, N., & Karkazis, P. (2020). An Artificial Intelligence-Based Collaboration Approach in Industrial IoT Manufacturing: Key Concepts, Architectural Extensions and Potential Applications. Sensors, 20(19), 5480. https://doi.org/10.3390/s20195480

Tripathi, V., Chattopadhyaya, S., Mukhopadhyay, A. K., Sharma, S., Li, C., Singh, S., Hussan, W. U., Salah, B., Saleem, W., & Mohamed, A. (2022). A Sustainable Productive Method for Enhancing Operational Excellence in Shop Floor Management for Industry 4.0 Using Hybrid Integration of Lean and Smart Manufacturing: An Ingenious Case Study. Sustainability, 14(12), 7452. https://doi.org/10.3390/su14127452

Vlachos, I. P., Pascazzi, R. M., Zobolas, G., Repoussis, P., & Giannakis, M. (2023). Lean manufacturing systems in the area of Industry 4.0: a lean automation plan of AGVs/IoT integration. Production Planning & Control, 34(4), 345–358. https://doi.org/10.1080/09537287.2021.1917720

Wan, J., A. A. H. Al-awlaqi, M., Li, M., O’Grady, M., Gu, X., Wang, J., & Cao, N. (2018). Wearable IoT enabled real-time health monitoring system. EURASIP Journal on Wireless Communications and Networking, 2018(1), 298. https://doi.org/10.1186/s13638-018-1308-x

Wang, W., Yang, H., Zhang, Y., & Xu, J. (2018). IoT-enabled real-time energy efficiency optimisation method for energy-intensive manufacturing enterprises. International Journal of Computer Integrated Manufacturing, 31(4–5), 362–379. https://doi.org/10.1080/0951192X.2017.1337929

Wang, X., Yew, A. W. W., Ong, S. K., & Nee, A. Y. C. (2020). Enhancing smart shop floor management with ubiquitous augmented reality. International Journal of Production Research, 58(8), 2352–2367. https://doi.org/10.1080/00207543.2019.1629667


Article metrics
View details
0
Downloads
0
Citations
25
Views

View Dimensions


View Plumx


View Altmetric



0
Save
0
Citation
25
View
0
Share

Stay connected