Marmolejo-Saucedo, José Antonio
Main Affiliation
Preferred name
Marmolejo-Saucedo, José Antonio
Official Name
Marmolejo-Saucedo, José Antonio
ORCID
0000-0002-8539-9828
Researcher ID
IYJ-1596-2023
Scopus Author ID
57204678532
4 results
Now showing 1 - 4 of 4
- Some of the metrics are blocked by yourconsent settings
Item type:Publication, Integrating Digital Twins into Smart Warehousing: A Practice-Based View Framework for Identifying and Prioritizing Critical Success Factors(MDPI AG, 2026-03-26); 12 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Problems of Sensors with a View to Digital Twins: A Review of the LiteratureThis work presents a theoretical approach to sensors as components of digital twins. It seeks to know the different types of sensors used in factories and their problems with a view to being one of the information input mechanisms of digital twins. The most commonly used sensors were identified as distance, humidity, position, pressure, proximity, sound, temperature, speed, magnetic, and light sensors. Thus, this chapter briefly describes the main characteristics of these sensors and highlights the problems that different authors have reported, with a view to being considered when integrating them into the digital twin. The problems identified in the literature by types of sensors are classified to identify their recurrence. Kendall’s coefficient of agreement was applied to look for similar problems between different types of sensors. The results showed little agreement, with technical results being the most frequent, followed by physical and environmental results. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.2 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Cloud-based architecture of digital twins applied to the optimal design of large-scale supply chains(Universidad Nacional de San Martin, 2026); ; The design of large-scale supply networks is an NP-hard MILP problem that requires dynamic representation and efficient optimization in industrial contexts. This study proposed, implemented, and validated a four-layer cloud-based architecture that integrates Microsoft Azure Digital Twins (ADT), a multi-echelon MILP model, a hybrid PSO, and a Python-based integration engine with bidirectional synchronization. The main algorithmic contribution consisted of using the linear relaxation of the MILP as the PSO fitness function, providing a formal lower bound for the original problem. A total of 74 experimental runs were conducted using a capacity repair operator, achieving a zero-infeasibility rate. The evaluated instances, across S, M, and XL scales and five complexity levels, showed an inverse relationship between the integrality gap and the quality of the PSO solution. Likewise, instances with low combinatorial complexity achieved over 90% consistency in opening decisions, preserving the decision state of the digital twin. The proposed framework integrates cloud-based architecture, MILP optimization, and hybrid PSO for supply chains with experimental validation. © The authors © Revista Científica de Sistemas e Informática.