DMAIC applied to the production control of manufactured replacement parts: a case study in an agricultural machinery factory
DOI:
https://doi.org/10.47456/bjpe.v10i5.46993Keywords:
DMAIC, Lean Manufacturing, Control, Material FlowAbstract
The globalized and competitive world requires companies to maintain increasingly strict levels of quality and process control. The challenge of ensuring a high standard of serviceability for the customer demands that tasks be performed in a way that avoids wasting material and human resources, adding value to the final service or product. Within this context, this work aims to identify the root causes responsible for delays in the shipment of replacement parts from an agricultural machinery company to its distribution center, proposing implementations to improve the manufacturing process of these parts through the DMAIC methodology, guided by the principles of lean manufacturing.
Downloads
References
Clemente, M. & Domingues, L. (2022). Analysis of Project Management Tools to support Knowledge Management. In: CENTERIS - International Conference on Enterprise Information Systems / ProjMAN - International Conference on Project MANagement / HCist – International Conference on Health and Social Care Information Systems and Technologies.
Karunathilake, E. M. B. M., et al (2023). The Path to Smart Farming: Innovations and Opportunities in Precision Agriculture. Agriculture. DOI: https://doi.org/10.3390/agriculture13081593
Mittal, A., et al (2023). The performance improvement analysis using Six Sigma DMAIC methodology: A case study on Indian manufacturing company. Cell. DOI: https://doi.org/10.1016/j.heliyon.2023.e14625
Theodore, A. (2006). Introduction to Engineering Statistics and Six SIGMA. Statistical Quality Control and Design of Experiments and Systems. Londres: Springer.
Carroll, C. (2013). Six Sigma for Powerful Improvement. A Green Belt DMAIC Training Sysytem with Software Tools and 25-Lesson Course. Florida: CRC Press DOI: https://doi.org/10.1201/b14806
Díaz-Reza, J. R., García Alcara, J. L., & Morales García, A. S. (2022). Best Practices in Lean Manufacturing: A relational Analysis. Suiça: Springer. DOI: https://doi.org/10.1007/978-3-030-97752-8
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Daniel Alejandro Mantilla Gómez, Fernando de Araújo, Aline Gonçalves do Santos, Lázaro Antônio da Fonseca Júnior (Autor)
This work is licensed under a Creative Commons Attribution 4.0 International License.
All works published in the Brazilian Journal of Production Engineering (BJPE) are licensed under Creative Commons Attribution 4.0 International (CC BY 4.0).
This means that:
Anyone can copy, distribute, display, adapt, remix, and even commercially use the content published in the journal;
Provided that due credit is given to the authors and to BJPE as the original source;
No additional permission is required for reuse, as long as the license terms are respected.
This policy complies with the principles of open access, promoting the broad dissemination of scientific knowledge.
2.png)
