Six sigma en la era digital: Integración con inteligencia artificial y Big data para la mejora de procesos

Jesús Dolores Trejo Muñoz; Jorge Adolfo Pinto Santos; Eduardo Rafael Poblano Ojinaga; Manuel Arnoldo Rodríguez Medina; Perla Ivette Gómez Zepeda

doi:10.61273/neyart.v3i4.114

Authors

Jesús Dolores Trejo Muñoz National Technological Institute of Mexico
Jorge Adolfo Pinto Santos National Technological Institute of Mexico
Eduardo Rafael Poblano Ojinaga National Technological Institute of Mexico
Manuel Arnoldo Rodríguez Medina National Technological Institute of Mexico
Perla Ivette Gómez Zepeda National Technological Institute of Mexico

DOI:

https://doi.org/10.61273/neyart.v3i4.114

Keywords:

Six Sigma, DMAIC, Artificial Intelligence, Big Data, Predictive Quality Control, Industry 4.0, Machine Learning, Smart Manufacturing

Abstract

This article investigates the integration of the Six Sigma methodology with Artificial Intelligence (AI) and Big Data to optimize processes in the digital era. Developed in the 1980s, Six Sigma has become a systematic approach to reducing variability and improving quality in industrial and service processes. However, with the rise of tools such as AI and Big Data, a new frontier for process optimization has emerged.

The study analyzes how the combination of these technologies enables a reduction in analysis time, a decrease in manufacturing defects, and an optimization of operational productivity, along with a more sustainable approach to processes. Case studies in industries such as soap manufacturing, semiconductors, and textiles are highlighted, demonstrating significant results from AI and Big Data applications, such as reducing defects from 4.5% to 0.8% and optimizing resource consumption.

Despite the benefits, challenges such as high costs and a lack of training in AI and Big Data are identified. The article concludes that integrating these technologies with Six Sigma represents a significant evolution in process improvement, fostering innovation and competitiveness in the Industry 4.0 era. Investing in training and scalable tools is recommended to maximize the benefits of this integration.

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Author Biographies

Jesús Dolores Trejo Muñoz , National Technological Institute of Mexico

Jesús Dolores Trejo Muñoz is a mechatronics engineer and a master's student in industrial engineering specialising in Six Sigma, currently in the process of obtaining his degree. He works as a lecturer at the Technological Institute of Ciudad Juárez, where he teaches classes related to digital manufacturing and continuous improvement. He has experience in operations coordination, X-ray equipment maintenance, and projects in Industry 4.0 and CNC. He is currently responsible for ionising radiation facilities, ensuring compliance with radiological safety regulations.

Jorge Adolfo Pinto Santos , National Technological Institute of Mexico

Jorge Adolfo Pinto Santos is a research professor in the Postgraduate Studies and Research Division at the Ciudad Juárez Institute of Technology (ITCJ), with 15 years of teaching experience in higher education institutions. He holds a Master's degree in Industrial Engineering from the Laguna Institute of Technology and a PhD in Technology from the Autonomous University of Ciudad Juárez (2021). His research focuses on Quality Engineering, Six Sigma, and Multivariate Statistics. In addition, his professional experience includes Quality Assurance, Production Control, Storage Systems, and Purchasing. He is currently Head of the Division of Postgraduate Studies and Research at ITCJ and an evaluator of key competencies at the Standardisation and Certification Council.

Eduardo Rafael Poblano Ojinaga , National Technological Institute of Mexico

Eduardo Rafael Poblano Ojinaga is an Industrial Engineer who graduated from the National Technological Institute of Mexico, La Laguna Technological Institute. He obtained a Master of Science in Industrial Engineering (1995) and a Master's Degree in Administrative Engineering (2000) from the Technological Institute of Ciudad Juárez. He received his Doctorate in Technology from the Autonomous University of Ciudad Juárez (2019). His line of research is related to Strategic Planning, Quality Engineering, and SEM. He has professional experience as a Manufacturing, Quality, and Engineering Manager, as well as a consultant in Quality Engineering, Six Sigma, and Teamwork.

Manuel Arnoldo Rodríguez Medina , National Technological Institute of Mexico

Manuel Arnoldo Rodríguez Medina is a chemical engineer with a master's degree and doctorate in industrial engineering from the Technological Institute of Ciudad Juárez. With more than 45 years of experience in teaching and research, he is a pillar of the training of engineers and science teachers at TecNM-ITCJ. His areas of expertise include statistics, quality control, experimental design, reliability, Bayesian statistics, and operations research. He has published more than 35 articles in national and international journals, which has earned him a place in the National System of Researchers (SNI) Level 1.

Perla Ivette Gómez Zepeda , National Technological Institute of Mexico

Perla Ivette Gómez Zepeda holds a PhD in Administration from the Faculty of Accounting and Administration at the Autonomous University of Chihuahua. She has 16 years of teaching experience and is a candidate member of the National System of Researchers (SNII), as well as holding Level II status in the State System of Researchers (SEI) of the State of Chihuahua. Her lines of research include the Internet, Gender Studies, SMEs, Logistics, and Industrial Engineering.

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