A new edition of the Lean Six Sigma Green Belt Diploma program , offered by the Operations Department of the Faculty of Engineering, has concluded. Under the direction of Carlos Ruiz Huidobro , the professionals explored the application of the DMAIC methodology for problem-solving. This methodology aims to resolve problems effectively and improve business, institutional, and organizational performance.

During the last class, the students presented their final projects to obtain their Lean Six Sigma Green Belt certification: real-world case studies from various companies. What did the projects involve? They analyzed real-world cases and developed improvement proposals using the DMAIC methodology. Having obtained their certification, the students will continue their training for Lean Six Sigma Black Belt in the second semester.

We'd like to share some of the projects where the DMAIC methodology was applied to solve complex problems in various types of operations, such as product manufacturing, logistics, agriculture, oil and gas, maintenance, medicine, education, and other services. This involved applying a systematic and disciplined process using Lean and Six Sigma tools. During the projects, they identified and validated the importance of each root cause—sometimes simple, sometimes complex and hidden—with data, improving the actual performance of their operations. For example:

• 📍 Last mile delivery loading efficiency: The project improved the efficiency of truck loading with agricultural fertilizers, thereby reducing last-mile logistics costs. Initial truck loading capacity was at 69%, but efficiency reached 80% by the project's end.
• 📍Optimization of the paint thickness of the finished product In order to meet specifications, minimizing excess paint, root causes were identified through practical tests with statistical data validation. The process was improved from 20% to over 70% with the improvement actions already implemented.
• 📍Oil well start-up times: The project aims to reduce losses due to delays in restarting production wells after repairs using pulling equipment. Previously, only 34% of wells began production within the first eight hours of repair. The project's impact was significant: 70% of wells resumed production within eight hours.
• 📍Reduced dispersion and improved speed of Laboratory Results reporting to patients and doctors, eliminating the great heterogeneity in reporting times and validation of results for critical patients.
• 📍Customer dispatch and delivery performance: The problem identified at the company was the lack of measurement of delivery times for orders to customers of an agricultural supply center. Therefore, the company sought to measure delivery times and customer satisfaction levels. Based on the data analysis, a truck matrix was created, categorized by time, distance, and capacity. The results obtained from the project allowed for the identification of a root cause, enabling safe and timely deliveries.
• 📍Reduce product stamping time In order to meet 100% of orders on time, the process involved identifying Lean waste (MUDA), standardizing processes, implementing visual management, and controlling variables validated with planning and production data. This improved processing time by more than 50%, directly impacting productivity, which increased by 25%.
• 📍Improving the quality of auto parts production By identifying the root causes that impacted the process variables, eliminating failure and rework costs at the end of the line, controlling the process variables and implementing Error Proofing (Poka-Yoke) in critical processes.

We congratulate all the students for their work; they have reached very interesting conclusions that allowed them to establish different action plans to generate improvements in each of their companies. 

If you are interested in learning more about the operations area of ​​the Faculty of Engineering, we invite you to visit our website: https://www.austral.edu.ar/ingenieria/ingenieria-posgrados/encontra-tu-programa/operaciones-industria-40/.