Data Driven Fault Detection For Industrial Processes

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Data-Driven Fault Detection for Industrial Processes

Author : Zhiwen Chen
Publisher : Springer
ISBN 13 : 3658167564
Total Pages : 124 pages
Book Rating : 4.6/5 (581 download)

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Book Synopsis Data-Driven Fault Detection for Industrial Processes by : Zhiwen Chen

Download or read book Data-Driven Fault Detection for Industrial Processes written by Zhiwen Chen and published by Springer. This book was released on 2017-01-02 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: Zhiwen Chen aims to develop advanced fault detection (FD) methods for the monitoring of industrial processes. With the ever increasing demands on reliability and safety in industrial processes, fault detection has become an important issue. Although the model-based fault detection theory has been well studied in the past decades, its applications are limited to large-scale industrial processes because it is difficult to build accurate models. Furthermore, motivated by the limitations of existing data-driven FD methods, novel canonical correlation analysis (CCA) and projection-based methods are proposed from the perspectives of process input and output data, less engineering effort and wide application scope. For performance evaluation of FD methods, a new index is also developed.

Data-Driven Fault Detection and Reasoning for Industrial Monitoring

Author : Jing Wang
Publisher : Springer Nature
ISBN 13 : 9811680442
Total Pages : 277 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Data-Driven Fault Detection and Reasoning for Industrial Monitoring by : Jing Wang

Download or read book Data-Driven Fault Detection and Reasoning for Industrial Monitoring written by Jing Wang and published by Springer Nature. This book was released on 2022-01-03 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book assesses the potential of data-driven methods in industrial process monitoring engineering. The process modeling, fault detection, classification, isolation, and reasoning are studied in detail. These methods can be used to improve the safety and reliability of industrial processes. Fault diagnosis, including fault detection and reasoning, has attracted engineers and scientists from various fields such as control, machinery, mathematics, and automation engineering. Combining the diagnosis algorithms and application cases, this book establishes a basic framework for this topic and implements various statistical analysis methods for process monitoring. This book is intended for senior undergraduate and graduate students who are interested in fault diagnosis technology, researchers investigating automation and industrial security, professional practitioners and engineers working on engineering modeling and data processing applications. This is an open access book.

Data-Driven and Model-Based Methods for Fault Detection and Diagnosis

Author : Majdi Mansouri
Publisher : Elsevier
ISBN 13 : 0128191651
Total Pages : 322 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Data-Driven and Model-Based Methods for Fault Detection and Diagnosis by : Majdi Mansouri

Download or read book Data-Driven and Model-Based Methods for Fault Detection and Diagnosis written by Majdi Mansouri and published by Elsevier. This book was released on 2020-02-05 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data-Driven and Model-Based Methods for Fault Detection and Diagnosis covers techniques that improve the quality of fault detection and enhance monitoring through chemical and environmental processes. The book provides both the theoretical framework and technical solutions. It starts with a review of relevant literature, proceeds with a detailed description of developed methodologies, and then discusses the results of developed methodologies, and ends with major conclusions reached from the analysis of simulation and experimental studies. The book is an indispensable resource for researchers in academia and industry and practitioners working in chemical and environmental engineering to do their work safely. Outlines latent variable based hypothesis testing fault detection techniques to enhance monitoring processes represented by linear or nonlinear input-space models (such as PCA) or input-output models (such as PLS) Explains multiscale latent variable based hypothesis testing fault detection techniques using multiscale representation to help deal with uncertainty in the data and minimize its effect on fault detection Includes interval PCA (IPCA) and interval PLS (IPLS) fault detection methods to enhance the quality of fault detection Provides model-based detection techniques for the improvement of monitoring processes using state estimation-based fault detection approaches Demonstrates the effectiveness of the proposed strategies by conducting simulation and experimental studies on synthetic data

Data-driven Methods for Fault Detection and Diagnosis in Chemical Processes

Author : Evan L. Russell
Publisher : Springer Science & Business Media
ISBN 13 : 1447104099
Total Pages : 193 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Data-driven Methods for Fault Detection and Diagnosis in Chemical Processes by : Evan L. Russell

Download or read book Data-driven Methods for Fault Detection and Diagnosis in Chemical Processes written by Evan L. Russell and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: Early and accurate fault detection and diagnosis for modern chemical plants can minimise downtime, increase the safety of plant operations, and reduce manufacturing costs. The process-monitoring techniques that have been most effective in practice are based on models constructed almost entirely from process data. The goal of the book is to present the theoretical background and practical techniques for data-driven process monitoring. Process-monitoring techniques presented include: Principal component analysis; Fisher discriminant analysis; Partial least squares; Canonical variate analysis. The text demonstrates the application of all of the data-driven process monitoring techniques to the Tennessee Eastman plant simulator - demonstrating the strengths and weaknesses of each approach in detail. This aids the reader in selecting the right method for his process application. Plant simulator and homework problems in which students apply the process-monitoring techniques to a nontrivial simulated process, and can compare their performance with that obtained in the case studies in the text are included. A number of additional homework problems encourage the reader to implement and obtain a deeper understanding of the techniques. The reader will obtain a background in data-driven techniques for fault detection and diagnosis, including the ability to implement the techniques and to know how to select the right technique for a particular application.

Fault Detection and Diagnosis in Industrial Systems

Author : L.H. Chiang
Publisher : Springer Science & Business Media
ISBN 13 : 1447103475
Total Pages : 281 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Fault Detection and Diagnosis in Industrial Systems by : L.H. Chiang

Download or read book Fault Detection and Diagnosis in Industrial Systems written by L.H. Chiang and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: Early and accurate fault detection and diagnosis for modern chemical plants can minimize downtime, increase the safety of plant operations, and reduce manufacturing costs. This book presents the theoretical background and practical techniques for data-driven process monitoring. It demonstrates the application of all the data-driven process monitoring techniques to the Tennessee Eastman plant simulator, and looks at the strengths and weaknesses of each approach in detail. A plant simulator and problems allow readers to apply process monitoring techniques.

Data-Driven Fault Detection and Reasoning for Industrial Monitoring

Author : Jing Wang
Publisher : Springer
ISBN 13 : 9789811680434
Total Pages : 264 pages
Book Rating : 4.6/5 (84 download)

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Book Synopsis Data-Driven Fault Detection and Reasoning for Industrial Monitoring by : Jing Wang

Download or read book Data-Driven Fault Detection and Reasoning for Industrial Monitoring written by Jing Wang and published by Springer. This book was released on 2022-01-04 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book assesses the potential of data-driven methods in industrial process monitoring engineering. The process modeling, fault detection, classification, isolation, and reasoning are studied in detail. These methods can be used to improve the safety and reliability of industrial processes. Fault diagnosis, including fault detection and reasoning, has attracted engineers and scientists from various fields such as control, machinery, mathematics, and automation engineering. Combining the diagnosis algorithms and application cases, this book establishes a basic framework for this topic and implements various statistical analysis methods for process monitoring. This book is intended for senior undergraduate and graduate students who are interested in fault diagnosis technology, researchers investigating automation and industrial security, professional practitioners and engineers working on engineering modeling and data processing applications. This is an open access book.

Data-driven Design of Fault Diagnosis and Fault-tolerant Control Systems

Author : Steven X. Ding
Publisher : Springer Science & Business Media
ISBN 13 : 1447164105
Total Pages : 306 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Data-driven Design of Fault Diagnosis and Fault-tolerant Control Systems by : Steven X. Ding

Download or read book Data-driven Design of Fault Diagnosis and Fault-tolerant Control Systems written by Steven X. Ding and published by Springer Science & Business Media. This book was released on 2014-04-12 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data-driven Design of Fault Diagnosis and Fault-tolerant Control Systems presents basic statistical process monitoring, fault diagnosis, and control methods and introduces advanced data-driven schemes for the design of fault diagnosis and fault-tolerant control systems catering to the needs of dynamic industrial processes. With ever increasing demands for reliability, availability and safety in technical processes and assets, process monitoring and fault-tolerance have become important issues surrounding the design of automatic control systems. This text shows the reader how, thanks to the rapid development of information technology, key techniques of data-driven and statistical process monitoring and control can now become widely used in industrial practice to address these issues. To allow for self-contained study and facilitate implementation in real applications, important mathematical and control theoretical knowledge and tools are included in this book. Major schemes are presented in algorithm form and demonstrated on industrial case systems. Data-driven Design of Fault Diagnosis and Fault-tolerant Control Systems will be of interest to process and control engineers, engineering students and researchers with a control engineering background.

Model-Based Fault Diagnosis Techniques

Author : Steven X. Ding
Publisher : Springer Science & Business Media
ISBN 13 : 1447147995
Total Pages : 533 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Model-Based Fault Diagnosis Techniques by : Steven X. Ding

Download or read book Model-Based Fault Diagnosis Techniques written by Steven X. Ding and published by Springer Science & Business Media. This book was released on 2012-12-20 with total page 533 pages. Available in PDF, EPUB and Kindle. Book excerpt: Guaranteeing a high system performance over a wide operating range is an important issue surrounding the design of automatic control systems with successively increasing complexity. As a key technology in the search for a solution, advanced fault detection and identification (FDI) is receiving considerable attention. This book introduces basic model-based FDI schemes, advanced analysis and design algorithms, and mathematical and control-theoretic tools. This second edition of Model-Based Fault Diagnosis Techniques contains: • new material on fault isolation and identification and alarm management; • extended and revised treatment of systematic threshold determination for systems with both deterministic unknown inputs and stochastic noises; • addition of the continuously-stirred tank heater as a representative process-industrial benchmark; and • enhanced discussion of residual evaluation which now deals with stochastic processes. Model-based Fault Diagnosis Techniques will interest academic researchers working in fault identification and diagnosis and as a text it is suitable for graduate students in a formal university-based course or as a self-study aid for practising engineers working with automatic control or mechatronic systems from backgrounds as diverse as chemical process and power engineering.

Data-Driven Design of Fault Diagnosis Systems

Author : Adel Haghani Abandan Sari
Publisher : Springer Science & Business
ISBN 13 : 3658058072
Total Pages : 149 pages
Book Rating : 4.6/5 (58 download)

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Book Synopsis Data-Driven Design of Fault Diagnosis Systems by : Adel Haghani Abandan Sari

Download or read book Data-Driven Design of Fault Diagnosis Systems written by Adel Haghani Abandan Sari and published by Springer Science & Business. This book was released on 2014-04-22 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: In many industrial applications early detection and diagnosis of abnormal behavior of the plant is of great importance. During the last decades, the complexity of process plants has been drastically increased, which imposes great challenges in development of model-based monitoring approaches and it sometimes becomes unrealistic for modern large-scale processes. The main objective of Adel Haghani Abandan Sari is to study efficient fault diagnosis techniques for complex industrial systems using process historical data and considering the nonlinear behavior of the process. To this end, different methods are presented to solve the fault diagnosis problem based on the overall behavior of the process and its dynamics. Moreover, a novel technique is proposed for fault isolation and determination of the root-cause of the faults in the system, based on the fault impacts on the process measurements.

Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods

Author : Chris Aldrich
Publisher : Springer Science & Business Media
ISBN 13 : 1447151852
Total Pages : 388 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods by : Chris Aldrich

Download or read book Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods written by Chris Aldrich and published by Springer Science & Business Media. This book was released on 2013-06-15 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique text/reference describes in detail the latest advances in unsupervised process monitoring and fault diagnosis with machine learning methods. Abundant case studies throughout the text demonstrate the efficacy of each method in real-world settings. The broad coverage examines such cutting-edge topics as the use of information theory to enhance unsupervised learning in tree-based methods, the extension of kernel methods to multiple kernel learning for feature extraction from data, and the incremental training of multilayer perceptrons to construct deep architectures for enhanced data projections. Topics and features: discusses machine learning frameworks based on artificial neural networks, statistical learning theory and kernel-based methods, and tree-based methods; examines the application of machine learning to steady state and dynamic operations, with a focus on unsupervised learning; describes the use of spectral methods in process fault diagnosis.

Advanced methods for fault diagnosis and fault-tolerant control

Author : Steven X. Ding
Publisher : Springer Nature
ISBN 13 : 3662620049
Total Pages : 664 pages
Book Rating : 4.6/5 (626 download)

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Book Synopsis Advanced methods for fault diagnosis and fault-tolerant control by : Steven X. Ding

Download or read book Advanced methods for fault diagnosis and fault-tolerant control written by Steven X. Ding and published by Springer Nature. This book was released on 2020-11-24 with total page 664 pages. Available in PDF, EPUB and Kindle. Book excerpt: The major objective of this book is to introduce advanced design and (online) optimization methods for fault diagnosis and fault-tolerant control from different aspects. Under the aspect of system types, fault diagnosis and fault-tolerant issues are dealt with for linear time-invariant and time-varying systems as well as for nonlinear and distributed (including networked) systems. From the methodological point of view, both model-based and data-driven schemes are investigated.To allow for a self-contained study and enable an easy implementation in real applications, the necessary knowledge as well as tools in mathematics and control theory are included in this book. The main results with the fault diagnosis and fault-tolerant schemes are presented in form of algorithms and demonstrated by means of benchmark case studies. The intended audience of this book are process and control engineers, engineering students and researchers with control engineering background.

Machine Learning-Based Fault Diagnosis for Industrial Engineering Systems

Author : Rui Yang
Publisher : CRC Press
ISBN 13 : 1000594939
Total Pages : 87 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Machine Learning-Based Fault Diagnosis for Industrial Engineering Systems by : Rui Yang

Download or read book Machine Learning-Based Fault Diagnosis for Industrial Engineering Systems written by Rui Yang and published by CRC Press. This book was released on 2022-06-16 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides advanced techniques for precision compensation and fault diagnosis of precision motion systems and rotating machinery. Techniques and applications through experiments and case studies for intelligent precision compensation and fault diagnosis are offered along with the introduction of machine learning and deep learning methods. Machine Learning-Based Fault Diagnosis for Industrial Engineering Systems discusses how to formulate and solve precision compensation and fault diagnosis problems. The book includes experimental results on hardware equipment used as practical examples throughout the book. Machine learning and deep learning methods used in intelligent precision compensation and intelligent fault diagnosis are introduced. Applications to deal with relevant problems concerning CNC machining and rotating machinery in industrial engineering systems are provided in detail along with applications used in precision motion systems. Methods, applications, and concepts offered in this book can help all professional engineers and students across many areas of engineering and operations management that are involved in any part of Industry 4.0 transformation.

Monitoring Multimode Continuous Processes

Author : Marcos Quiñones-Grueiro
Publisher : Springer Nature
ISBN 13 : 3030547388
Total Pages : 153 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Monitoring Multimode Continuous Processes by : Marcos Quiñones-Grueiro

Download or read book Monitoring Multimode Continuous Processes written by Marcos Quiñones-Grueiro and published by Springer Nature. This book was released on 2020-08-04 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines recent methods for data-driven fault diagnosis of multimode continuous processes. It formalizes, generalizes, and systematically presents the main concepts, and approaches required to design fault diagnosis methods for multimode continuous processes. The book provides both theoretical and practical tools to help readers address the fault diagnosis problem by drawing data-driven methods from at least three different areas: statistics, unsupervised, and supervised learning.

Three Approaches to Data Analysis

Author : Igor Chikalov
Publisher : Springer Science & Business Media
ISBN 13 : 3642286674
Total Pages : 209 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Three Approaches to Data Analysis by : Igor Chikalov

Download or read book Three Approaches to Data Analysis written by Igor Chikalov and published by Springer Science & Business Media. This book was released on 2012-07-28 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, the following three approaches to data analysis are presented: - Test Theory, founded by Sergei V. Yablonskii (1924-1998); the first publications appeared in 1955 and 1958, - Rough Sets, founded by Zdzisław I. Pawlak (1926-2006); the first publications appeared in 1981 and 1982, - Logical Analysis of Data, founded by Peter L. Hammer (1936-2006); the first publications appeared in 1986 and 1988. These three approaches have much in common, but researchers active in one of these areas often have a limited knowledge about the results and methods developed in the other two. On the other hand, each of the approaches shows some originality and we believe that the exchange of knowledge can stimulate further development of each of them. This can lead to new theoretical results and real-life applications and, in particular, new results based on combination of these three data analysis approaches can be expected. - Logical Analysis of Data, founded by Peter L. Hammer (1936-2006); the first publications appeared in 1986 and 1988. These three approaches have much in common, but researchers active in one of these areas often have a limited knowledge about the results and methods developed in the other two. On the other hand, each of the approaches shows some originality and we believe that the exchange of knowledge can stimulate further development of each of them. This can lead to new theoretical results and real-life applications and, in particular, new results based on combination of these three data analysis approaches can be expected. These three approaches have much in common, but researchers active in one of these areas often have a limited knowledge about the results and methods developed in the other two. On the other hand, each of the approaches shows some originality and we believe that the exchange of knowledge can stimulate further development of each of them. This can lead to new theoretical results and real-life applications and, in particular, new results based on combination of these three data analysis approaches can be expected.

Fault-Diagnosis Systems

Author : Rolf Isermann
Publisher : Springer Science & Business Media
ISBN 13 : 3540303685
Total Pages : 478 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Fault-Diagnosis Systems by : Rolf Isermann

Download or read book Fault-Diagnosis Systems written by Rolf Isermann and published by Springer Science & Business Media. This book was released on 2006-01-16 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: With increasing demands for efficiency and product quality plus progress in the integration of automatic control systems in high-cost mechatronic and safety-critical processes, the field of supervision (or monitoring), fault detection and fault diagnosis plays an important role. The book gives an introduction into advanced methods of fault detection and diagnosis (FDD). After definitions of important terms, it considers the reliability, availability, safety and systems integrity of technical processes. Then fault-detection methods for single signals without models such as limit and trend checking and with harmonic and stochastic models, such as Fourier analysis, correlation and wavelets are treated. This is followed by fault detection with process models using the relationships between signals such as parameter estimation, parity equations, observers and principal component analysis. The treated fault-diagnosis methods include classification methods from Bayes classification to neural networks with decision trees and inference methods from approximate reasoning with fuzzy logic to hybrid fuzzy-neuro systems. Several practical examples for fault detection and diagnosis of DC motor drives, a centrifugal pump, automotive suspension and tire demonstrate applications.

Diagnosis and Fault-tolerant Control 1

Author : Vicenc Puig
Publisher : John Wiley & Sons
ISBN 13 : 1119882311
Total Pages : 290 pages
Book Rating : 4.1/5 (198 download)

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Book Synopsis Diagnosis and Fault-tolerant Control 1 by : Vicenc Puig

Download or read book Diagnosis and Fault-tolerant Control 1 written by Vicenc Puig and published by John Wiley & Sons. This book was released on 2021-12-01 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent advances in fault diagnosis strategies for complex dynamic systems. Its impetus derives from the need for an overview of the challenges of the fault diagnosis technique, especially for those demanding systems that require reliability, availability, maintainability and safety to ensure efficient operations. Moreover, the need for a high degree of tolerance with respect to possible faults represents a further key point, primarily for complex systems, as modeling and control are inherently challenging, and maintenance is both expensive and safety-critical. Diagnosis and Fault-tolerant Control 1 also presents and compares different diagnosis schemes using established case studies that are widely used in related literature. The main features of this book regard the analysis, design and implementation of proper solutions for the problems of fault diagnosis in safety critical systems. The design of the considered solutions involves robust data-driven, model-based approaches.

Fault Detection, Diagnosis and Prognosis

Author : Fausto Pedro García Márquez
Publisher : BoD – Books on Demand
ISBN 13 : 1789842131
Total Pages : 177 pages
Book Rating : 4.7/5 (898 download)

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Book Synopsis Fault Detection, Diagnosis and Prognosis by : Fausto Pedro García Márquez

Download or read book Fault Detection, Diagnosis and Prognosis written by Fausto Pedro García Márquez and published by BoD – Books on Demand. This book was released on 2020-02-05 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the main concepts, state of the art, advances, and case studies of fault detection, diagnosis, and prognosis. This topic is a critical variable in industry to reach and maintain competitiveness. Therefore, proper management of the corrective, predictive, and preventive politics in any industry is required. This book complements other subdisciplines such as economics, finance, marketing, decision and risk analysis, engineering, etc. The book presents real case studies in multiple disciplines. It considers the main topics using prognostic and subdiscipline techniques. It is essential to link these topics with the areas of finance, scheduling, resources, downtime, etc. to increase productivity, profitability, maintainability, reliability, safety, and availability, and reduce costs and downtime. Advances in mathematics, modeling, computational techniques, dynamic analysis, etc. are employed analytically. Computational techniques, dynamic analysis, probabilistic methods, and mathematical optimization techniques are expertly blended to support the analysis of prognostic problems with defined constraints and requirements. The book is intended for graduate students and professionals in industrial engineering, business administration, industrial organization, operations management, applied microeconomics, and the decisions sciences, either studying maintenance or needing to solve large, specific, and complex maintenance management problems as part of their jobs. The work will also be of interest to researches from academia.