Banca de QUALIFICAÇÃO: LILLIAN OGECHI UDECHUKWU

Uma banca de QUALIFICAÇÃO de MESTRADO foi cadastrada pelo programa.
DISCENTE : LILLIAN OGECHI UDECHUKWU
Data: 24/09/2026
HORA: 09:00
LOCAL: UFABC on line
TÍTULO:

Integrating Digital Twin and Artificial Intelligence Technologies for Improved Efficiency, Competitiveness, and Adaptability in Smart Manufacturing

PÁGINAS: 100
RESUMO:

Artificial Intelligence (AI) and Digital Twin (DT) technologies are becoming increasingly
important in smart manufacturing because they can support activities such as real-time
monitoring, prediction, simulation, process optimization, and decision-making. However, adopting these technologies does not automatically guarantee improved business performance.
Their effectiveness may also depend on how they are integrated into existing manufacturing
processes and whether the organization has the appropriate technological and organizational
conditions to support their use. Therefore, this study aims to investigate how the integration of
AI and DT contributes to business performance in smart manufacturing. Specifically, the study
will examine how these technologies are currently applied, their contribution to efficiency,
competitiveness, and adaptability, and the organizational and technological factors that enable or
hinder their effective integration. Based on these findings, the study will also develop practical
recommendations for improving AI-DT integration in smart manufacturing. The research will adopt a qualitative approach using an embedded single-case study of a
Brazilian company operating in industrial automation and digital transformation. Data will be
collected mainly through semi-structured interviews with professionals who have relevant
knowledge and experience of the company's AI and DT initiatives, supported by documentary
evidence and observation where appropriate. The interview questions and analytical categories
will be developed from the theoretical framework and previous empirical studies to maintain
alignment between the research objectives, data collection, and analysis. The collected data will
be analyzed using a systematic coding process that combines literature-based categories with the
possibility of identifying new themes emerging from participants' experiences. The study is
expected to provide a clearer understanding of how AI-DT integration works in a real
organizational setting and to offer practical insights that may support manufacturing
organizations seeking to obtain greater business value from these technologies.

 

MEMBROS DA BANCA:
Presidente - Interno ao Programa - 2328074 - FRANCIANE FREITAS SILVEIRA
Membro Titular - Examinador(a) Interno ao Programa - 1544379 - ANDERSON ORZARI RIBEIRO
Membro Titular - Examinador(a) Externo ao Programa - 2073298 - ERIK GUSTAVO DEL CONTE
Membro Suplente - Examinador(a) Interno ao Programa - 1914234 - ALEXANDRE ACACIO DE ANDRADE
Membro Suplente - Examinador(a) Externo ao Programa - 2327844 - SILVIA NOVAES ZILBER TURRI