A review on data-driven process monitoring methods: Characterization and mining of industrial data
Safe and stable operation plays an important role in the chemical industry. Fault detection
and diagnosis (FDD) make it possible to identify abnormal process deviations early and …
and diagnosis (FDD) make it possible to identify abnormal process deviations early and …
A review of machine learning kernel methods in statistical process monitoring
The complexity of modern problems turns increasingly larger in industrial environments, so
the classical process monitoring techniques have to adapt to deal with those problems. This …
the classical process monitoring techniques have to adapt to deal with those problems. This …
Sistema de gestión ISO 9001-2015: técnicas y herramientas de ingeniería de calidad para su implementación
FLC Medina, APL Díaz… - Ingeniería Investigación y …, 2017 - dialnet.unirioja.es
El presente artículo muestra una evolución de la calidad en función de la normatividad
existente en busca de mejora de procesos, además, como las normas ISO 9000 impactan …
existente en busca de mejora de procesos, además, como las normas ISO 9000 impactan …
Process monitoring using variational autoencoder for high-dimensional nonlinear processes
In many industries, statistical process monitoring techniques play a key role in improving
processes through variation reduction and defect prevention. Modern large-scale industrial …
processes through variation reduction and defect prevention. Modern large-scale industrial …
An approach to monitoring quality in manufacturing using supervised machine learning on product state data
Increasing market demand towards higher product and process quality and efficiency forces
companies to think of new and innovative ways to optimize their production. In the area of …
companies to think of new and innovative ways to optimize their production. In the area of …
Hybrid approach to document anomaly detection: an application to facilitate RPA in title insurance
Anomaly detection (AD) is an important aspect of various domains and title insurance (TI) is
no exception. Robotic process automation (RPA) is taking over manual tasks in TI business …
no exception. Robotic process automation (RPA) is taking over manual tasks in TI business …
A Big Data Analytics-driven Lean Six Sigma framework for enhanced green performance: a case study of chemical company
The advent of new technologies alongside the generation of the vast amount of data in the
manufacturing processes makes Green Lean Six Sigma (GLSS) approaches very …
manufacturing processes makes Green Lean Six Sigma (GLSS) approaches very …
Automatic anomaly detection on in-production manufacturing machines using statistical learning methods
Anomaly detection is becoming increasingly important to enhance reliability and resiliency
in the Industry 4.0 framework. In this work, we investigate different methods for anomaly …
in the Industry 4.0 framework. In this work, we investigate different methods for anomaly …
A weighted support vector machine method for control chart pattern recognition
P Xanthopoulos, T Razzaghi - Computers & Industrial Engineering, 2014 - Elsevier
Manual inspection and evaluation of quality control data is a tedious task that requires the
undistracted attention of specialized personnel. On the other hand, automated monitoring of …
undistracted attention of specialized personnel. On the other hand, automated monitoring of …
Statistical learning methods applied to process monitoring: An overview and perspective
The increasing availability of high-volume, high-velocity data sets, often containing variables
of different data types, brings an increasing need for monitoring tools that are designed to …
of different data types, brings an increasing need for monitoring tools that are designed to …