Carlos Perez-Galvan's scientific contributions

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Publications (2)

Figure 1: Batch processes have a combination of different data types....
Figure 2: Overlay of a batch drying process, 36, 37 with the...
Figure 3: Overlay of the drying temperature profile (a) and phases (c,...
Figure 5: Contrary to landmarks or fingerprints, Functional PCA can...
+12 Figure 6: FPCA results for the temperature profiles in the dryer. The...
Industrial Data Science for Batch Manufacturing Processes
Preprint
Full-text available
  • Sep 2022
Batch processes show several sources of variability, from raw materials' properties to initial and evolving conditions that change during the different events in the manufacturing process. In this chapter, we will illustrate with an industrial example how to use machine learning to reduce this apparent excess of data while maintaining the relevant...
Fig. 6 Simplified hierarchical view of automation infrastructures in...
Fig. 7 Industrial data science workflow based on the IBM crossindustry...
Fig. 8 Classification of industrial data applications where offline...
Fig. 9 Common modeling steps using an industrial data set with hundreds...
+7 Fig. 15 This figure shows a simplified schematic representation of...
Industrial data science – a review of machine learning applications for chemical and process industries
Article
Full-text available
  • Jan 2022
In the literature, machine learning (ML) and artificial intelligence (AI) applications tend to start with examples that are irrelevant to process engineers (e.g. classification of images between cats and dogs, house pricing, types of flowers, etc.). However, process engineering principles are also based on pseudo-empirical correlations and heuristi...

Citations

... AI involves several methodological domains, such as reasoning, knowledge representation, solution search, and the basic paradigm of machine learning (ML) among them. In the last few years, especially since the introduction of AlphaGo, ML has been greatly developed in the field of industrial chemistry and chemical engineering, thus greatly helping the development of pharmaceuticals and fine chemicals, thus reducing time and cost [3][4][5]. So far, much of the literature has summarized the application of machine learning algorithms in the chemical industry ( Figure 2) [6]. ...
Reference: A Review on Artificial Intelligence Enabled Design, Synthesis, and Process Optimization of Chemical Products for Industry 4.0