Pedro Juan Rivera Torres

• Doctor of Philosophy
• MSCA Fellow at University of Salamanca

Modeling manufacturing processes assists the design of new systems, allowing predictions of future behav- iors, identifying improvement areas and evaluating changes to existing systems. Probabilistic Boolean networks (PBN) have been used to study biological systems, since they combine uncertainty and rule-based representation. A novel approach is p...

The development of systems capable of diagnosing new and multiple faults in industrial systems is an active research topic. In this paper a model-based diagnostic system capable of diagnosing new and multiple faults using fuzzy logic as a fundamental tool is proposed. Also, the wavelet transform is used for isolating noise present in measurements....

Theoretical modeling of manufacturing systems assists the design of new systems for predictions of future behavior, identifies improvement areas, and evaluates changes to existing systems. This doctoral dissertation contributes in the field of manufacturing systems and process modeling, using Probabilistic Boolean Networks (PBN). As a first contri...

Recent developments in intelligent manufacturing have validated the use of probabilistic Boolean networks (PBN) to model failures in manufacturing processes and as part of a methodology for Design Failure Mode and Effects Analysis (DFMEA). This paper expands the application of PBNs in manufacturing processes by proposing the use of interventions in...

Probabilistic Boolean Networks can capture the dynamics of complex biological systems as well as other non-biological systems, such as manufacturing systems and smart grids. In this proof-of-concept manuscript, we propose a Probabilistic Boolean Network architecture with a learning process that significantly improves the prediction of the occurrenc...

In recent decades, the field of statistical linguistics has made significant strides, which have been fueled by the availability of data. Leveraging Twitter data, this paper explores the English and Spanish languages, investigating their rank diversity across different scales: temporal intervals (ranging from 3 to 96 h), spatial radii (spanning 3 k...

A self-organizing complex-network modeling method, probabilistic Boolean networks, is presented as a model-based diagnostic system for detecting and isolating different types of faults, failures, and modes of operation in which a network of intelligent power routers is deployed over a standard power test case: the Western System Coordinating Counci...

With the accelerated penetration of cloud computing and Internet-of-Things (IoTs) in contexts such as smart factories, digital manufacturing has been introduced to improve the effectiveness of manufacturing by taking advantage of massive amount of digital information. One of the digital manufacturing pathways is collecting data from IoT services an...

Proper maintenance is at the heart of any manufacturing operation. Predictive maintenance strategies can reduce or eliminate unscheduled downtime due to failures caused by reactive or run-to-failure maintenance strategies, increase production capacity, reduce costs, and extend equipment lifetime. However, many small to medium enterprises (SME) are...

In the field of Smart Grids, the necessity arises to continuously improve efficient and resistant, high-quality electrical power, concurrently handling all possible faults and failures. Reaching such goal requires high reliability in their components, appropriate maintenance, and a calculated occurrence of failures. Accurate operation of the system...

Statistical linguistics has advanced considerably in recent decades as data has become available. This has allowed researchers to study how statistical properties of languages change over time. In this work, we use data from Twitter to explore English and Spanish considering the rank diversity at di↵erent scales: temporal (from 3 to 96 hour interva...

The area of smart power grids needs to constantly improve its efficiency and resilience, to provide high quality electrical power in a resilient grid, while managing faults and avoiding failures. Achieving this requires high component reliability, adequate maintenance, and a studied failure occurrence. Correct system operation involves those activi...

Introducción: Para lograr elevados niveles de producción con calidad y con una utilización eficiente de la materia prima, las industrias deben tener instalados sistemas de diagnóstico de fallos procesando la información obtenida por los sistemas de adquisición de datos y control. El funcionamiento de estos sistemas se ve afectado por el ruido, la p...

The accurate description of a complex process should take into account not only the interacting elements involved but also the scale of the description. Therefore, there can not be a single measure for describing the associated complexity of a process nor a single metric applicable in all scenarios. This article introduces a framework based on mult...

Probabilistic Boolean Networks (PBN) are a tool in Complex-Adaptive Systems theory used primarily for bioinformatics. They possess complexity, adaptability, self-organization, and emergence. Learning occurs in the fundamental sense of adaptation to changes; the system adapts in order to survive. This work presents an alternative means to smart-grid...

The area of Smart Power Grids needs to constantly improve its efficiency and resilience, to pro-vide high quality electrical power, in a resistant grid, managing faults and avoiding failures. Achieving this requires high component reliability, adequate maintenance, and a studied failure occurrence. Correct system operation involves those activities...

Developing systems and methodologies capable of monitoring the condition and diagnosing multiple faults in industrial/manufacturing systems are topics of active and continuous research. In this paper, a fault diagnosis system inspired on the Probabilistic Boolean Networks (PBN) with Intervention model is suggested as a tool for diagnosing faults of...

Probabilistic Boolean Networks (PBN) are a tool in Complex-Adaptive Systems theory used primarily for bioinformatics. They possess complexity, adaptability, self-organization, emergence, and self-similarity. They are sensitive to initial conditions, and react to environmental perturbations. Learning occurs in the fundamental sense of adaptation to...

Developing systems and methodologies capable of monitoring the condition and diagnosing multiple faults in industrial/manufacturing systems are topics of active and continuous research. In this paper, a fault diagnosis system inspired on the Probabilistic Boolean Networks (PBN) with Intervention model is suggested as a tool for diagnosing faults of...

The area of smart power systems needs continuous improvement of its efficiency and reliability, to produce power with optimal quality in a resilient, fault-tolerant grid. Components must be highly reliable, properly maintained, and the occurrence of faults and failures has to be studied. Guaranteeing correct system operation to performance specific...

The area of Smart Power Systems has a continuous need for improvement of its efficiency and reliability, in order to produce power with optimal quality in a re-silient, fault-tolerant grid. To achieve such a goal, system components must be highly reliable, properly maintained, and the occurrence of faults and failures has to be studied. Guaranteein...

Developing methodologies for fault diagnosis in industrial/manufacturing systems is an active area of research. In this paper, a fault diagnosis scheme based on the Probabilistic Boolean Networks (PBN) model is proposed for a group of machines in a manufacturing process. The proposal takes into ac- count the failure modes which affect the function...

Developing systems and methodologies capable of monitoring the condition and diagnosis of multiple faults in industrial systems is a topic of active and continuous research. This paper presents a fault diagnosis system based on Probabilistic Boolean Networks as a fundamental tool is proposed for diagnosing faults of a group of machines in a manufac...

In this paper, a hybrid algorithm using fuzzy clustering techniques is proposed for developing a robust fault diagnosis platform in industrial systems. The proposed algorithm is applied in a fault diagnosis scheme with online detection of novel faults and automatic learning. The hybrid algorithm,algorithm initially identifies the outliers based on...

Theoretical modeling of manufacturing processes assists the design of new systems for predictions of future behavior, identifies improvement areas, and evaluates changes to existing systems. A novel approach is proposed to model industrial machines using probabilistic Boolean networks (PBNs) to study the relationship between machine components, the...