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Industry industrial networks, systems, complexes and computers

Industry industrial networks, systems, complexes and computers

Critical infrastructures, such as electricity generation plants, transportation systems, oil refineries, chemical factories and manufacturing facilities are large, distributed complexes. Plant operators must continuously monitor and control many different sections of the plant to ensure its proper operation. During the last decades this remote command and control has been made feasible due to the development of networking technology and the advent of Industrial Control Systems ICS. ICS are command and control networks and systems designed to support industrial processes.

Dear readers! Our articles talk about typical ways to resolve Industry industrial networks, systems, complexes and computers, but each case is unique.

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Master programs: Informatics and Computer Engineering

Beyond these everyday experiences, there have been critical computer system bugs and defects that have resulted in the loss of human life such as the people who died on-board the Boeing Max 8 flights in Indonesia and Ethiopia during —, the people who perished on Iran Air Flight when it was mistakenly shot down as an enemy combatant by the USS Vincennes in , the 28 US soldiers who were killed in by Iraqi Scud missiles that penetrated through an errant Patriot missile defense system, and the 6 patients overdosed by the Therac radiation machine during — Thanks to the general purpose nature of boolean logic and binary arithmetic represented in silicon integrated circuits that can be composed to calculate, store and communicate, computer systems have become woven into the fabric of Life; they help manage human activities and assets in a remarkable array of fields including commerce, education, entertainment, government, healthcare, infrastructure, military, science, and transportation.

However as computers expand their reach and human reliance upon them grows, our modern economy and society bears substantial costs and serious risks for these computer systems defects and IT project problems. The strategic areas of this failure model are familiar for those already in IT: Technology , Organization , and Process. The Process area is comprised of Scope , Flow , and Communications. The Organization realm consists of Culture , Governance , and Resources.

Some of these parts affect others within their area and also connect across the broader area boundaries. We will explore each element of the model, illustrate them with representative stories, and describe solutions to prevent and recover from computer system and IT project failure. The primary audience of this book is the current and next generation of computer systems professionals, and my hope is that the text helps them avoid the problems that have been encountered in the past and renews their ethical and moral imperative to deliver better, safer, more secure systems in the future because our lives depend on it.

The secondary audience of this work is the general reader who may be interested in computer systems and how they impact their lives and the world around them. The analysis of the computer systems failure model naturally starts with Technology itself. Complexity is one of the critical technology elements in the model that fundamentally differentiates computer systems and projects from other human artifacts.

While the layperson has an intuitive sense of what complexity means, scientists in biology, computer science, economics, and physics are still wrestling to refine and precisely employ this subtle concept, so I want to introduce some important definitions at the outset. Simple comes from the Latin root simplex, and it means easy to know and understand. Simple objects are atomic or readily reducible to just a few elementary parts; simple relationships connote direct, linear, sequential connections between objects.

Between the simple and complex, there lies the complicated which refers to parts, units, and systems that are not simple, but remain knowable, linear, exhaustively describable, relatively bounded, and somewhat predictable, understandable and manageable through best practices, checklists, design and implementation heuristics, maintenance intervals, reference manuals, visual diagrams, detailed plans, and institutionalized human expertise perhaps assisted by computers themselves.

For a progressive computing analogy using these terms, consider that my keyboard and mouse are simple, my personal computer is complicated, while Internet security is complex.

A major thesis of this text is that the complexity of computer hardware and software systems has exceeded our current understanding of how these systems work and fail, and furthermore, these systems are approaching the complexity of biological systems based on their cardinality and their networked hierarchy due to the widespread connectivity of the Internet and World Wide Web.

The physicist Seth Lloyd proposed three criteria to measure the complexity of an object or process: what is its degree of organization, how difficult is it to describe, and how difficult is it to create, and he enumerated more than forty different metrics.

For the purposes of our computer systems failure model, we shall focus on metrics of cardinality and networked hierarchy because they align with complexity, are measurable, and can be associated with computer systems failures. Let us first examine system complexity based on cardinality , or size. The original computer hardware metric is transistor count on an integrated circuit IC.

Since Intel introduced the microprocessor in , transistor counts have exponentially risen from about 2, in the Intel model to eight billion in the core Intel Xeon Phi model released in , a remarkable increase of 4 million times as the gate length concomitantly dropped from 10, nm in the model to just 14 nm in the Xeon Phi. Due to the higher transistor density and smaller gate length, computer scientists and engineers are reaching the physical limits of silicon atoms around 0.

The sister metric for software size is Lines of Code LOC , whereby each line represents roughly a computer instruction analogous to a deoxyribonucleic acid DNA base pair.

For a broader perspective, I have shared below a tabular excerpt of the Lines of Code data set sourced from Visual Capitalist. LOC also does not take into account programming language abstraction meaning a low-level line of x86, MIPS, or SPARC assembly language code is fundamentally different and more limited in the logical work it can accomplish as compared to a higher-level line of C, Java, or Python.

Next, we shall extend the concept of system cardinality from its external dimensions to its internal state space. In , Claude Shannon proposed encoding and transmitting information on communication channels based on digital relays and flip-flop circuits using binary digits and arithmetic ; for messages with N possible states, Shannon showed that channels using binary encodings could represent these messages using log2N bits.

In , Maurice Howard Halstead articulated a comprehensive set of software metrics in an effort to make software engineering more like a science and less an art. For given a program P with n1 distinct operators, n2 distinct operands, N1 total operators, and N2 total operands, Halstead proposed several measures.

The common intuition behind these algorithmic component metrics is that most computations should be short, simple, and sequential enough to reliably understand, document, code, test, and troubleshoot. Computer programmers still use the ideas of Chaitin, Kolmogrov, and Solomonoff to commonly evaluate the performance tradeoffs of different algorithms.

Furthermore, a sound white box testing strategy can be derived from the McCabe CC metric such that each function or method has an equivalent number of test cases preferably automated to its cyclomatic complexity size. While some studies have shown a positive correlation between the CC metric and the number of code defects, the research has not been conclusive.

This has not stopped international safety standards such as ISO and IEC however, from mandating that software have low cyclomatic complexity. Again, we draw inspiration from biology and briefly reflect on its strata that consists of DNA, proteins, organelles, cells, tissues, organs, organisms, and ecosystems; individuals, families, and communities of organisms also compete and collaborate with each other for resources within ecosystems.

So both biological and computational ecosystems are multilayer structures comprised of interacting components that have dynamic relationships pulsing within their layers and reverberating across them. Given this diversity in the computer network hierarchy, one might well ask what are reasonable metrics to measure it. Some have proposed trivial metrics such as the size, height or volume of the graph. Others have suggested variations on connectivity , which is the maximum number of edges that can be removed before a graph is split into two non-connected subgraphs.

An interesting approach refining connectivity called the global reaching centrality GRC computes the difference between the maximum and average value of the generalized reach centralities over the network whereby a local reaching centrality of a node I in graph G is the proportion of all nodes in the graph that can be reached from I via outgoing edges.

Although measuring network complexity remains an active area of research, efforts to quantify the concepts of node degree and dependence are confirming the fundamental hypothesis of network and complex systems researchers across multiple disciplines that relationship transitivity matters more than often credited in the traditional Newtonian-Cartesian ethic rooted in linear cause-and-effect, decomposability, reductionism, foreseeability of harm, time reversibility, and an obsession with finding broken parts and blaming people that still dominates mainstream intellectual theory and practice in accident investigations, the law, and systems engineering.

Some component and system requirements such as correctness, cost, compliance, performance, reliability, and usability do range between simple and complicated, and they can be managed in a relatively straightforward approach. We shall investigate technologies and processes to improve system Quality for these requirements in another chapter.

However, other important system properties we care about such as reliability, safety, and security are emergent, macroscopic, and transcendentally transitive ; they require a thoroughly different language and mental model than the Newtonian-Cartesian ethic and ultimately more systematic solutions that go up-and-out instead of just down-and-in.

For example, the Arpanet collapse on October 27, occurred due to several contributing factors: a hardware defect dropped bits in memory, the software had error detecting codes for transmission but not storage, a separate software flaw that garbage collected messages but was poisoned by the simultaneous existence of identical messages, and finally the sheer growth of the network size itself due to its initial success later contributed to its impact upon failure.

The common threads of these stories about computer systems failure and others we will explore in the text are multiple causes, technology and human aspects, and an intrinsic complexity reflecting the modern, globalized, technocratic, bureaucratic society that we live in.

Like entropy in thermodynamics, technological complexity has grown as computer systems are used to solve more problems of larger Scope and as they become more interconnected through intentional system integration as well as unforeseen dependencies of distributed systems.

Peter Deutsch, a senior distinguished engineer at Sun Microsystems, articulated several fallacies of distributed systems programming common to computer professionals: 1 The network is reliable, 2 Latency is zero, 3 Bandwidth is infinite, 4 The network is secure, 5 Topology does not change, 6 There is one administrator, and 7 The network is homogeneous.

In practice, none of these fallacies are ever true, and yet too often as we shall see throughout the text, they rear their head like the hydra of Greek mythology. Lets step back further from the purely technological aspects of computer system complexity and consider how it is affected by the human dimensions reflected through economics, politics, psychology, and sociology.

These computer hardware and software systems are designed, constructed, deployed, maintained, and then used by different people in different places over different periods of time, regulated by different legal jurisdictions, and under the pressure of important environmental influences e. Sociologists, psychologists, and human factors researchers have been especially interested in these ingredients in the later half of the 20th century and how they affect the recipes of system success and failure.

Melvin Conway presciently stated in that organizations which design systems are constrained to produce designs which are copies of the communication structures of these organizations.

Charles Perrow coined the phrase normal accidents in to describe a system failure that was not simply the cause-and-effect result of an imperfect part, process, or person than can be remedied in an isolated, linear, reductionist manner, but a system failure unfolding from the coupled interfaces, hidden connections, and non-linear feedback loops between components situated in a complex system with high risk, catastrophic potential. We must also note that software manufacturers are generally exempt from lemon laws in North America, Europe, and Asia that are common place for physical device makers; users especially of computer software have a license filled with a litany of abstruse disclaimers to use, but not to own the system.

Furthermore, in the hyper-competitive, relatively unregulated societies of the USA and Asia, there is a remarkably dominant paradigm that emphasizes economic growth, materialism, and market forces, treats the natural environment as a resource and not as something to be intrinsically valued, favors risk-and-reward relativity over absolute safety, and socializes catastrophic risks such as environmental disasters and financial crises as externalities that private corporations and individuals can absolve themselves responsibility for and delegate to the general public and taxpayer.

For want of a nail, the shoe was lost. For want of a shoe, the horse was lost. For want of a horse, the rider was lost. For want of a rider, the battle was lost. For want of a battle, the kingdom was lost. All for the loss of a horseshoe nail. Rural English saying collected by English poet, George Herbert Managing system complexity is less about fixing the broken gears of a machine and more about introducing plasticity, resilience and robustness throughout the lattice of relationships of an amphibious high rise structure balanced upon pontoons.

Taleb defines antifragility as a convex response to a stressor or source of harm, leading to a positive sensitivity to increase in volatility or variability, stress, dispersion of outcomes, or uncertainty. From a Technology dimension, the primary antifragile principles, practices, and parts are abstraction, decoupling, de-centralization, dependence mapping, end-to-end testing, error-handling, fault-tolerance, formal verification, hazard analysis e. Chaos Monkey ,self-healing e.

Kubernetes, OpenShift, AWS Elastic Beanstalk , separation of privileges, virtualization, and paradoxically, simplicity when appropriate. From the Process facet, project and product activities must flow in an Agile manner not waterfall and thus be open to change. Smaller scopes should be embraced earlier to allow teams time for trial-and-error and proofs-of-concept to reduce risk.

Test-driven engineering and peer review should be adopted during design and construction to improve quality. Scrums, sprint retrospectives, and milestone post-mortems should be regularly scheduled and meeting minutes published to enable learning throughout the system life cycle. Finally, from the Organizational aspect, good governance means assigning clear system and project accountability, combines risk and reward metrics to evaluate initiatives across the portfolio, elicits executive support, and engages stakeholders.

From a resource standpoint, organizations must manage talent, schedules, and budgets carefully with an eye on the aforementioned governance metrics. Finally, organizations need to foster a healthier, more heterogeneous culture that makes space for humility, paranoia, pessimism, and vigilance to balance the complacency, optimism, overconfidence, and technophilia that underpins the hegemonic mental model for many in engineering, business, government, and society.

Complexity is at the heart of this Gordian knot that has been tied as mankind has reached beyond his grasp, however it can be managed and gently unfolded if we are open-minded to a comprehensive set of strategies and tactics. Enjoy the article? Follow me on Medium and Twitter for more updates. References :. Sign in. Get started. Bishr Tabbaa Follow. Write the first response.

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Control in Technical Systems

Developing a distributed robotic complex with remote Internet access and "Industry Developing control systems for technological robots and robotic industrial complexes in remote access modes K Developing a distributed robotic complex with remote Internet access and "Industry The task is to develop a robotics and robotic complexes control system in the remote access mode using the Internet with visualization of the technological process.

John Impagliazzo , Eduard Proydakov. Springer , 6 sept. The 32 revised papers were carefully selected from numerous submissions; many of them were translated from Russian.

This volume provides a comprehensive state of the art overview of a series of advanced trends and concepts that have recently been proposed in the area of green information technologies engineering as well as of design and development methodologies for models and complex systems architectures and their intelligent components. The book presents a systematic exposition of research on principles, models, components and complex systems and a description of industry- and society-oriented aspects of the green IT engineering. The chapters provide an easy to follow, comprehensive introduction to the topics that are addressed, including the most relevant references, so that anyone interested in them can start the study by being able to easily find an introduction to the topic through these references. At the same time, all of them correspond to different aspects of the work in progress being carried out by various research groups throughout the world and, therefore, provide information on the state of the art of some of these topics, challenges and perspectives. Springer , 21 sept.

Complex System Failure: The Whole is More than the Sum of its Parts

Computing is any activity that uses computers to manage, process, and communicate information. It includes development of both hardware and software. Computing is a critical, integral component of modern industrial technology. Major computing disciplines include computer engineering , software engineering , computer science , information systems , and information technology. In a general way, we can define computing to mean any goal-oriented activity requiring, benefiting from, or creating computers. Thus, computing includes designing and building hardware and software systems for a wide range of purposes; processing, structuring, and managing various kinds of information; doing scientific studies using computers; making computer systems behave intelligently; creating and using communications and entertainment media; finding and gathering information relevant to any particular purpose, and so on. The list is virtually endless, and the possibilities are vast. ACM also defines five sub-disciplines of the computing field: [2].

Core Technologies Powering the IIoT Machine

The confluence of IT and OT opens a multitude of avenues for capital-intensive industrial sectors. IoT is effectively enabling devices — usually with some type of sensor or measurement aspect — to be linked so that the information is available for other systems for consideration, and even calculation of control aspects. In a DCS, signals from sensors throughout the plant — used to measure temperature, flow, speed, levels, etc. In this way, real-time information from the world was brought into the control mechanism for — you guessed it — consideration and even calculation of control aspects.

Beyond these everyday experiences, there have been critical computer system bugs and defects that have resulted in the loss of human life such as the people who died on-board the Boeing Max 8 flights in Indonesia and Ethiopia during —, the people who perished on Iran Air Flight when it was mistakenly shot down as an enemy combatant by the USS Vincennes in , the 28 US soldiers who were killed in by Iraqi Scud missiles that penetrated through an errant Patriot missile defense system, and the 6 patients overdosed by the Therac radiation machine during — Thanks to the general purpose nature of boolean logic and binary arithmetic represented in silicon integrated circuits that can be composed to calculate, store and communicate, computer systems have become woven into the fabric of Life; they help manage human activities and assets in a remarkable array of fields including commerce, education, entertainment, government, healthcare, infrastructure, military, science, and transportation.

Developing a distributed robotic complex with remote Internet access and "Industry Contact Info. Terms and Conditions. Useful links.

Complex System Failure: The Whole is More than the Sum of its Parts

Today the development of technologies made it possible to introduce industry automation systems into almost all manufacturing fields. Industry automation of production processes enhances labor efficiency and allows cutting net cost and improving product quality. Moreover, it extends the equipment service life, saves consumables and raw materials, and improves production safety as a whole. Open Technologies offers the following services in the frames of construction of industry automation systems:.

Big Data for industries, simulation of systems, data services for quality assessment, predictive maintenance, anomaly detection. The research Institute for Complex Systems defines its scope in this emerging field for which informatics, intelligent data analysis, massively distributed computing, mathematical modeling and systems engineering are the main supports. By promoting the transfer of knowledge and technology from the academic field to the local and regional economy, the Institute intends to develop interdisciplinary approaches and build national and international cooperation. Current research activities and achievements are in environmental applications, smart buildings, energy management, pathology detection, intelligent wireless networks, smart mobility or event detection in video surveillance. The institute specializes in areas such as massive information processing, cloud computing, machine learning, business intelligence and signal processing.

Scope of Technical Committees

BotSlayer is an application that helps track and detect potential manipulation of information spreading on Twitter. It can be used by journalists, researchers, civil society organizations, corporations, and political candidates to discover in real-time new coordinated disinformation campaigns. Read about how you can join the effort to spot the manipulation of social media. Send your students to this great event! Over the course of five years, 20 researchers from IU and Northeastern University, mostly graduate students, will spend a semester in one of the partner institutions in Europe, and 20 researchers from those institutions will do the same in the U.

A pyramid of industrial automation systems A comparison of current networks in industry. +2 complexes using industrial PLCs as well as its. impact on [14] Industrial computer and communication product guid,ALLEN BRADLEY.

Encyclopedia of Sustainable Technologies provides an authoritative assessment of the sustainable technologies that are currently available or in development. Sustainable technology includes the scientific understanding, development and application of a wide range of technologies and processes and their environmental implications. Systems and lifecycle analyses of energy systems, environmental management, agriculture, manufacturing and digital technologies provide a comprehensive method for understanding the full sustainability of processes. In addition, the development of clean processes through green chemistry and engineering techniques are also described. Both approaches are long established and widely recognized, playing a key role in the organizing principles of this valuable work.

Kyrgyz Technical University

Each TC coincides with a technical area within the CC. The scope of each technical area is described below. Developing control design methods for all systems that are subject to model uncertainty and compensating for uncertainty by using adaptation and machine learning techniques. The TC members' expertise include the design of adaptive controllers, adaptive state observers, adaptive parameter estimators, adaptive predictors, adaptive filters, etc.

Competitive Challenge Facing U. United States. Committee on Commerce, Science, and Transportation.

Informatics and computer engineering is the field of science and technology that encompasses the ways and means, and methods of human activity, aimed at creating and using of computers, computer systems and networks, automated information processing and control systems, software and automated design systems. The objective of the master program is to train highly qualified specialists in the field of software development, research and development of design technology for hard- and software systems and specialized hardware of information control systems, distributed and embedded systems of various purpose, and the making of relevant toolkits.

Она услышала шелест одежды, и вдруг сигналы прекратились. Сьюзан замерла. Мгновение спустя, как в одном из самых страшных детских кошмаров, перед ней возникло чье-то лицо. Зеленоватое, оно было похоже на призрак.

Семистраничная доктрина сжато излагала программу его работы: защищать системы связи американского правительства и перехватывать сообщения зарубежных государств. На крыше главного служебного здания АНБ вырос лес из более чем пятисот антенн, среди которых были две большие антенны, закрытые обтекателями, похожими на громадные мячи для гольфа. Само здание также было гигантских размеров - его площадь составляла более двух миллионов квадратных футов, вдвое больше площади штаб-квартиры ЦРУ.

Внутри было протянуто восемь миллионов футов телефонного кабеля, общая площадь постоянно закрытых окон составляла восемьдесят тысяч квадратных футов.

Сьюзан рассказала Дэвиду про КОМИ НТ, подразделение глобальной разведки, в распоряжении которого находилось немыслимое количество постов прослушивания, спутников-шпионов и подслушивающих устройств по всему земному шару. Ежедневно тысячи сообщений и разговоров перехватывались и посылались экспертам АНБ для дешифровки.

Нуматака решил, что ему необходима дополнительная информация. Выскочив из кабинета, он повернул налево по главному коридору здания Нуматек. Сотрудники почтительно кланялись, когда он проходил мимо. Нуматака хорошо понимал, что эти поклоны вовсе не свидетельствует об их любви к нему, они - всего лишь знак вежливости, которую японские служащие проявляют по отношению даже к самым ненавистным начальникам.

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