Previsão do lead time de processos usando mineração de dados
Carregando...
Data
2021-03-09
Autores
Título da Revista
ISSN da Revista
Título de Volume
Editor
Universidade Federal de Goiás
Resumo
The era of Industry 4.0 leads to constant adaptations of production processes and
generates a significant amount of information. In this way, information management
becomes a crucial factor to guarantee the competitive strategy in the industries. One
of the information to be managed is textit lead time, time between the customer
requesting an order and it being available. Usually, it can be estimated using expensive
measurements or traditional methods that do not normally reflect the actual behavior of
the data or do not support the significant amount of information generated in Industry
4.0. In addition, there are gaps in the literature on textit lead time forecasting, such as
the use of smart methods to predict textit lead time across the supply chain. In this
context, the objective of this research is to use data mining using machine learning
algorithms to predict the textit lead time in real processes. The proposed methodology
made use of the textit Knowledge Discovery in Databases (KDD) cycle structured in the
selection, pre-processing, transformation, data mining and knowledge discovery phases.
The learning algorithms for textit Linear Regression (LR), textit Random Forest (RF),
textit Support Vector Machine (SVM), textit K-Nearest Neighbors (KNN) were tested and
textit Multilayers Perceptron (MLP). To validate the experiments, three databases from
the Electronic Information System (SEI), a supply chain from a pharmaceutical logistics
sector and from the industrial automation sector for the ceramic sector, were used. The
results showed that data mining is an effective tool for analyzing data generated in
the fourth industrial revolution for forecasting textit Lead time and decision making on
production planning and control.
Descrição
Palavras-chave
Mineração de dados, Inteligência artificial, Aprendizado de máquina, Lead time, Data mining, Artificial intelligence, Knowledge discovery in databases, Machine learning
Citação
OLIVEIRA, M. B. Previsão do lead time de processos usando mineração de dados. 2021. 85 f. Dissertação (Mestrado em Engenharia de Produção) - Universidade Federal de Goiás, Catalão, 2021.