Aluno: Luis Antonio Villa Suarez
Resumo
This study explores how Lean Six Sigma (LSS), a data-driven process improvement
methodology, can be effectively redesigned through the integration of digital
technologies in the context of supply chain management. The research adopts a
qualitative, literature-based approach using secondary data extracted from peer-reviewed
case studies and technical documentation. By analyzing these published examples, the
study identifies how digital tools such as IoT, cloud computing, AI, and data analytics
can be integrated into the DMAIC framework to drive operational excellence. The
findings reveal that digital enhancements to LSS amplify its impact on process efficiency,
quality, and adaptability. The study concludes with strategic recommendations and
introduces a DMAIC 4.0 model as a roadmap for digital transformation in supply chain
environments.
To address this, the research focuses on how Lean Six Sigma can help redesign supply
chain processes to make them more effective. Using the DMAIC approach (Define,
Measure, Analyze, Improve, Control), The study examines published case examples from
industries like manufacturing, retail, and logistics. It shows how organizations have
applied Lean Six Sigma tools to reduce waste, improve delivery times, and better manage
inventory.
This study adopts a qualitative, secondary-research design grounded in a structured
literature review. The search strategy was carried out mainly in Google Scholar,
complemented by Scopus, Web of Science, Emerald, Taylor & Francis to ensure coverage
of peer-reviewed publications. Keywords such as “Lean Six Sigma,” “Industry 4.0,”
“Supply Chain,” “Operational Excellence,” and “Digital Transformation” were
combined using Boolean operators. The search was restricted starting mainly from 2010
period (with some exceptions), reflecting the rise of Industry 4.0 technologies in supply
chain management. To ensure academic quality, only English-language, peer-reviewed
articles, books, and conference proceedings that explicitly addressed Lean Six Sigma in
digital, or supply chain contexts were included. After screening and applying
inclusion/exclusion criteria, a final sample of a specific number of studies was
thematically analysed.
Trabalho final de Mestrado