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Author: Richard J. Fickelscherer
Publisher: John Wiley & Sons
ISBN: 1118481968
Category : Technology & Engineering
Languages : en
Pages : 218
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Book Description
Tested and proven strategy to develop optimal automated process fault analyzers Process fault analyzers monitor process operations in order to identify the underlying causes of operational problems. Several diagnostic strategies exist for automating process fault analysis; however, automated fault analysis is still not widely used within the processing industries due to problems of cost and performance as well as the difficulty of modeling process behavior at needed levels of detail. In response, this book presents the method of minimal evidence (MOME), a model-based diagnostic strategy that facilitates the development and implementation of optimal automated process fault analyzers. MOME was created at the University of Delaware by the researchers who developed the FALCON system, a real-time, online process fault analyzer. The authors demonstrate how MOME is used to diagnose single and multiple fault situations, determine the strategic placement of process sensors, and distribute fault analyzers within large processing systems. Optimal Automated Process Fault Analysis begins by exploring the need to automate process fault analysis. Next, the book examines: Logic of model-based reasoning as used in MOME MOME logic for performing single and multiple fault diagnoses Fuzzy logic algorithms for automating MOME Distributing process fault analyzers throughout large processing systems Virtual SPC analysis and its use in FALCONEERTM IV Process state transition logic and its use in FALCONEERTM IV The book concludes with a summary of the lessons learned by employing FALCONEERTM IV in actual process applications, including the benefits of "intelligent supervision" of process operations. With this book as their guide, readers have a powerful new tool for ensuring the safety and reliability of any chemical processing system.
Author: Richard J. Fickelscherer
Publisher: John Wiley & Sons
ISBN: 1118481968
Category : Technology & Engineering
Languages : en
Pages : 218
Get Book Here
Book Description
Tested and proven strategy to develop optimal automated process fault analyzers Process fault analyzers monitor process operations in order to identify the underlying causes of operational problems. Several diagnostic strategies exist for automating process fault analysis; however, automated fault analysis is still not widely used within the processing industries due to problems of cost and performance as well as the difficulty of modeling process behavior at needed levels of detail. In response, this book presents the method of minimal evidence (MOME), a model-based diagnostic strategy that facilitates the development and implementation of optimal automated process fault analyzers. MOME was created at the University of Delaware by the researchers who developed the FALCON system, a real-time, online process fault analyzer. The authors demonstrate how MOME is used to diagnose single and multiple fault situations, determine the strategic placement of process sensors, and distribute fault analyzers within large processing systems. Optimal Automated Process Fault Analysis begins by exploring the need to automate process fault analysis. Next, the book examines: Logic of model-based reasoning as used in MOME MOME logic for performing single and multiple fault diagnoses Fuzzy logic algorithms for automating MOME Distributing process fault analyzers throughout large processing systems Virtual SPC analysis and its use in FALCONEERTM IV Process state transition logic and its use in FALCONEERTM IV The book concludes with a summary of the lessons learned by employing FALCONEERTM IV in actual process applications, including the benefits of "intelligent supervision" of process operations. With this book as their guide, readers have a powerful new tool for ensuring the safety and reliability of any chemical processing system.
Author: Richard J. Fickelscherer
Publisher: John Wiley & Sons
ISBN: 9781118372319
Category : Technology & Engineering
Languages : en
Pages : 0
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Book Description
Automated fault analysis is not widely used within chemical processing industries due to problems of cost and performance as well as the difficulty of modeling process behavior at needed levels of detail. In response, this book presents the method of minimal evidence (MOME), a model-based diagnostic strategy that facilitates the development and implementation of optimal automated process fault analyzers. With this book as their guide, readers have a powerful new tool for ensuring the safety and reliability of any chemical processing system.
Author: Richard J. Fickelscherer
Publisher: John Wiley & Sons
ISBN: 1119825911
Category : Science
Languages : en
Pages : 436
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Book Description
Artificial Intelligence in Process Fault Diagnosis A comprehensive guide to the future of process fault diagnosis Automation has revolutionized every aspect of industrial production, from the accumulation of raw materials to quality control inspections. Even process analysis itself has become subject to automated efficiencies, in the form of process fault analyzers, i.e., computer programs capable of analyzing process plant operations to identify faults, improve safety, and enhance productivity. Prohibitive cost and challenges of application have prevented widespread industry adoption of this technology, but recent advances in artificial intelligence promise to place these programs at the center of manufacturing process analysis. Artificial Intelligence in Process Fault Diagnosis brings together insights from data science and machine learning to deliver an effective introduction to these advances and their potential applications. Balancing theory and practice, it walks readers through the process of choosing an ideal diagnostic methodology and the creation of intelligent computer programs. The result promises to place readers at the forefront of this revolution in manufacturing. Artificial Intelligence in Process Fault Diagnosis readers will also find: Coverage of various AI-based diagnostic methodologies elaborated by leading experts Guidance for creating programs that can prevent catastrophic operating disasters, reduce downtime after emergency process shutdowns, and more Comprehensive overview of optimized best practices Artificial Intelligence in Process Fault Diagnosis is ideal for process control engineers, operating engineers working with processing industrial plants, and plant managers and operators throughout the various process industries.
Author: Jakub Breier
Publisher: Springer
ISBN: 3030113337
Category : Technology & Engineering
Languages : en
Pages : 342
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Book Description
This book presents a collection of automated methods that are useful for different aspects of fault analysis in cryptography. The first part focuses on automated analysis of symmetric cipher design specifications, software implementations, and hardware circuits. The second part provides automated deployment of countermeasures. The third part provides automated evaluation of countermeasures against fault attacks. Finally, the fourth part focuses on automating fault attack experiments. The presented methods enable software developers, circuit designers, and cryptographers to test and harden their products.
Author: Heinz D. Unbehauen
Publisher: EOLSS Publications
ISBN: 1848261551
Category :
Languages : en
Pages : 524
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Book Description
This Encyclopedia of Control Systems, Robotics, and Automation is a component of the global Encyclopedia of Life Support Systems EOLSS, which is an integrated compendium of twenty one Encyclopedias. This 22-volume set contains 240 chapters, each of size 5000-30000 words, with perspectives, applications and extensive illustrations. It is the only publication of its kind carrying state-of-the-art knowledge in the fields of Control Systems, Robotics, and Automation and is aimed, by virtue of the several applications, at the following five major target audiences: University and College Students, Educators, Professional Practitioners, Research Personnel and Policy Analysts, Managers, and Decision Makers and NGOs.
Author: Jianjun Shi
Publisher: CRC Press
ISBN: 1420003909
Category : Business & Economics
Languages : en
Pages : 492
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Book Description
Variability arises in multistage manufacturing processes (MMPs) from a variety of sources. Variation reduction demands data fusion from product/process design, manufacturing process data, and quality measurement. Statistical process control (SPC), with a focus on quality data alone, only tells half of the story and is a passive method, taking corre
Author: Maciej Szafarczyk
Publisher: Springer Science & Business Media
ISBN: 1447134583
Category : Technology & Engineering
Languages : en
Pages : 291
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Book Description
Automation is a predominant objective in the development of modern and advanced manufacturing production. Automatic Supervision in Manufacturing (ASM) addresses unavoidable disturbances occurring during production. Its application results in the unmanned functioning of manufacturing systems through comprehensive and reliable supervision. Automatic Supervision in Manufacturing is a collection of contributions written by specialists in the field from Europe and the USA. It deals with the concept of automatic supervision, the classification of supervisory systems and their functions. This publication will be of great interest to researchers and engineers in the areas of production and manufacturing.
Author: Sarat Kumar Sahoo
Publisher: Frontiers Media SA
ISBN: 2832541674
Category : Technology & Engineering
Languages : en
Pages : 196
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Book Description
The advancement of sustainable energy is becoming an important concern for many countries. The traditional electrical grid supports only one-way interaction of power being delivered to the consumers. The emergence of improved sensors, actuators, and automation technologies has consequently improved the control, monitoring and communication techniques within the energy sector, including the Smart Grid system. With the support of the aforementioned modern technologies, the information flows in two-ways between the consumer and supplier. This data communication helps the supplier in overcoming challenges like integration of renewable technologies, management of energy demand, load automation and control. Renewable energy (RE) is intermittent in nature and therefore difficult to predict. The accurate RE forecasting is very essential to improve the power system operations. The forecasting models are based on complex function combinations that include seasonality, fluctuation, and dynamic nonlinearity. The advanced intelligent computing algorithms for forecasting should consider the proper parameter determinations for achieving optimization. For this we need, new generation research areas like Machine learning (ML), and Artificial Intelligence (AI) to enable the efficient integration of distributed and renewable generation at large scale and at all voltage levels. The modern research in the above areas will improve the efficiency, reliability and sustainability in the Smart grid.
Author: J. Ranta
Publisher: Elsevier
ISBN: 148329904X
Category : Computers
Languages : en
Pages : 457
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Book Description
This volume provides a state-of-the-art review of the development and future use of man-machine systems in all aspects of business and industry. The papers cover such topics as human-computer interaction, system design, and the impact of automation in general, and also by the use of case studies describe a wide range of applications in such areas as office automation, transportation, power plants, machinery and manufacturing processes and defence systems. Contains 73 papers.
Author: Mohieddine Jelali
Publisher: Springer Science & Business Media
ISBN: 1447145461
Category : Technology & Engineering
Languages : en
Pages : 489
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Book Description
Control Performance Management in Industrial Automation provides a coherent and self-contained treatment of a group of methods and applications of burgeoning importance to the detection and solution of problems with control loops that are vital in maintaining product quality, operational safety, and efficiency of material and energy consumption in the process industries. The monograph deals with all aspects of control performance management (CPM), from controller assessment (minimum-variance-control-based and advanced methods), to detection and diagnosis of control loop problems (process non-linearities, oscillations, actuator faults), to the improvement of control performance (maintenance, re-design of loop components, automatic controller re-tuning). It provides a contribution towards the development and application of completely self-contained and automatic methodologies in the field. Moreover, within this work, many CPM tools have been developed that goes far beyond available CPM packages. Control Performance Management in Industrial Automation: · presents a comprehensive review of control performance assessment methods; · develops methods and procedures for the detection and diagnosis of the root-causes of poor performance in complex control loops; · covers important issues that arise when applying these assessment and diagnosis methods; · recommends new approaches and techniques for the optimization of control loop performance based on the results of the control performance stage; and · offers illustrative examples and industrial case studies drawn from – chemicals, building, mining, pulp and paper, mineral and metal processing industries. This book will be of interest to academic and industrial staff working on control systems design, maintenance or optimisation in all process industries.
