Definition of System Engieering by John A. Thomas

http://www.youtube.com/v/1QRFk9f7rrU&amp

Challenges of acquiring a PhD

PhD students have to take responsibility managing their own learning and getting a PhD. They are also responsible for determining what is required as well as for carrying it out, and must always keep in touch in regular meetings with the supervisor. The student is the main person responsible for his/her PhD research. Doing a PhD clearly indicates that this is a student’s own research and work. The actual research to be reported used the case study method. Three Malaysian PhD students from three major disciplines of study, arts, science and social science, were interviewed in depth several times within a year. However only one case study which focusing on Science discipline will be presented in this article in order to achieve a better understanding of the story. All three case studies would make the present article too long. The objective of this research is to provide better guidelines for effective roles of a PhD Science student especially the foreign student. As a result, the research had developed the best effective roles in order for students to success in their study.

Geminoid F Robot

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Reading the article about the female Geminoid  F Robot makes me think about their value in the system, especially in an Enterprise where the behavior of the humans are not well understood, but the behavior of the Geminoid could be.

 

The coverage of this news shows that we are not too far from having gynoid and androids living with us. This would be an interesting stir to our social medium and it would be interesting to see how this is going to change the direction of humans.

 

As exciting as this news is, I still can’t stop thinking about the scifi movies where the robots eventually group up against humans and become detrimental to humans. Again, this is another problem System Engineers need to look out for, especially in a System of System, where the whole is greater than the sum of its comprising systems.

 

 

http://www.fastcompany.com/1607031/android-robots-human-robotics-gynoid-augmented-reality-augmented-humans-science

Modeling from a System Engineering viewpoint

Following is a summary from readings of a book that I consider important.

·         A model is any incomplete representation of reality, an abstraction

·         Models could be mathematical(quantitative), physical, mental, or a qualitative. Nonetheless, the essence is the question/s that the model can reliably answer for us.

·         Sample of modeling languages developed as part of the IDEF family

o   IDEF0-Focus is a functional or process model of a system

o   IDEF1- Focus is an informational model of the information needed to support the functions of a system

o   IDEF1X- Focus is a semantic data model using relational theory and an entity-relationship modeling technique

o   IDEF2- Focus is a dynamic model of the system

o   IDEF3- focus  is both process and object state transition model of a system

·         3 types of questions:

o   Descriptive: most commonly used in science and engineering. A descriptive model attempts to predict answers to questions which the truth may or may not be obtained in the future. Descriptive models are measured by the power or richness, understandability to both wide and narrow audiences, and precision with which they can be used to define the relative entity.

o   Normative: can not be tested but are judged on their understandability and appeal across deciplines they can be used. Either it’s logical, or it should be refuted logically.

o   Definitive: how should a concept be defined.

·         Most effective process for developing and using a model is to begin by defining the questions the model should be able to answer.

·         Models should be developed, tested, and refined.

·         System validity addresses whether we have built the right system.

·         IDEF0 Page Hierarchy

o   A-0: Context or system function diagram ( contains A0)

o   A0 : Level 0 diagram with first tier functions specified

Verification vs. Validateion

Verfication: Did I build the right system?

Validation: Did I design the system right?

A good Architecture?

A good system architecture exhibits conceptual integrity; that is, it comes equipped with a set of design rules that aid in reducing complexity and that can be used as guidance in detailed design and in system verification. The rules may be represented as a pattern, such as pipes and filters. In the best case there are verifiable rules, such as “any virtual device of the same type may replace any other virtual device of the same type in the event of device failure,” or “all processes contending for the same resource must have the same scheduling priority.”

A contemporary architect might say that the object or system under construction must have the following characteristics.

·         It has the functionality required by the customer.

·         It is safely buildable on the required schedule.

·         It performs adequately.

·         It is reliable.

·         It is usable and safe to use.

·         It is secure.

·         It is affordable.

·         It conforms to legal standards.

·         It will outlast its predecessors and its competitors.

 

Architecture: General abstract from this world

A building is very different from a symphony, but both have architectures. Further, all architects talk about beauty in their work and its results. A building architect might say that a building should provide an environment suitable for working or living, and that it should be beautiful to behold; a musician that the music should be playable, with a discernible theme, and that it should be beautiful to the ear; a software architect that the system should be friendly and responsive to the user, maintainable, free of critical errors, easy to install, reliable, that it should communicate in standard ways with other systems, and that it, too, should be beautiful.

 

An architecture can help assure that the system satisfies the concerns of its stakeholders, and it can help deal with the complexity of conceiving, planning, building, and maintaining the system.

 

In our discussion we will use “architecture” as a noun to denote a set of artifacts, including documentation such as blueprints and building specifications that describe the object to be built, wherein the object is viewed as a set of structures.

NSF Proposals

Here are a couple of interesting pointers for submitting an NSF proposal. This is not a comprehensive and complete list, but it does touch upon some of the important features that a proposal should contain.

1- The proposal should not be an abstract, but a self-contained description of the activity if the proposal was funded.

2- broader impacts should be described, which show the implications of advancing this research

3- Details should be understandable to people who are not in the field, but technical enough to convey the importance of the research.

CSER Conference- March 17-19

The Conference on Systems Engineering Research (CSER) is to be held at Stevens from March 17th – 19th, 2010.

 For more information, visit:

http://sse.stevens.edu/research/sponsored-conferences/cser/

 You can read the Conference brochure at: (pdf format)

http://sse.stevens.edu/fileadmin/sse/research/sponsored_conferences/CSER_2010_CFP_FINAL_.pdf

Governance vs. Management

In Governance, the weak line of control would spread horizontal, where in Management, it would be going top down.

DSM: A tool for complexity management

Research on matrix based complexity management has come a long way. Originating from a process focus with the first published formulation of a Design Structure Matrix (DSM) by Don Steward in 1981 , a whole community has developed around this research. The DSM is able to model and analyze dependencies of one single type within one single domain. For a product, e.g. the domain “components” can be regarded.

The figure shows a simple process consisting of six tasks that are shown as a flow chart on the right hand side and a DSM representing that process on the left hand side. There are numerous algorithms to analyze the overall structure of the relationships within a DSM, e.g. tearing, banding and partitioning, or the analysis for different structural properties (see DSM tutorial).

Figures: Actually the figures makes all this make sense. The website does an excellent job at making this confusing and mind-boggling as much as possible. Who in the world explains DSM in two paragraphs? lol.... he he... But that's right, because I can do it... pshhh...

Some Basics of Systems Engineering

 These are my notes from reading some books, and I find these as important concepts that should always have attention focused on them.

1- Never forget that the system being addressed by one group of engineers is the subsystem of another group and the supersystem of yet a third group. ( elevating the idea of Enterprise Systems)

2- System Engineers must identify the stakeholders needs throughout the system's lifecylce and define objects in the triad of cost, schedule, and performance ---- cheaper, faster, and better.

3- Design during the engineering of a system is the preliminary activity that has the purpose of satisfying the stakeholders requirements, and begins in the mind of the system engineer, and has to be transformed into models employing visual formats in a highly skilled manner for success to be achieved.

4- One of the legends of Systems Engineering to me could be Joe Shea, his involvement in large scale projects, definition of Systems Engineering, dedication shown by working three shifts, SE fashion icon by wearing red socks, and finally nervous breakdown for overworking himself ( duuhh!!!), but we salute him for his hard work.

5- Requirement vs Specification: Specification is a collection of requirements that completely define the constraints and performance requirements for a specific physical entity that is part of the system.

6- Design Decomposition of Architectures and Specs:
  Operational Req
  Sys Op Arch (Segment specs)
  Segment Operational Arch (element spec)
  Element Operational Architecture ( Component Specs)
  Component Operational Architecture ( CI specs)

7- Originating Requirements are found in Operational needs, or operational requirements Document, (ORD), and the restatement and derivation of the system requirements becomes System Requirement Document (SRD).

Complex Systems

A quick run through by Wikipedia:

 

A complex system is a system composed of interconnected parts that as a whole exhibit one or more properties (behavior among the possible properties) not obvious from the properties of the individual parts.^{[citation needed]} This characteristic of every system is called emergence and is true of any system, not just complex ones^{[citation needed]}.

A system’s complexity may be of one of two forms: disorganized complexity and organized complexity.^[1] In essence, disorganized complexity is a matter of a very large number of parts, and organized complexity is a matter of the subject system (quite possibly with only a limited number of parts) exhibiting emergent properties.

Examples of complex systems include ant colonies, human economies and social structures, climate, nervous systems, cells and living things, including human beings, as well as modern energy or telecommunication infrastructures. Indeed, many systems of interest to humans are complex systems.

Complex systems are studied by many areas of natural science, mathematics, and social science. Fields that specialize in the interdisciplinary study of complex systems includesystems theory, complexity theory, systems ecology, and cybernetics.

 

Complex Systems in Searching

Well, Stephen Wolfram might have done something that needs further insight and attention. What google has done for the search arena is spectacular, but what Wolfram Alpha is doing is perhaps more praise worthy. Part of the fascination lies in the NKS which Stephen developed. I personally like this notion, and find his thinking and thought pattern as a necessity or a gift for people in the field of system. I mean the reason that we aren’t able to properly solve or tackle a problem is because we’ve exhausted all channels that could be used under the traditional method, but with NKS, well, you are talking about a whole new paradigm.

 

When asked about Wolfram Alpha and Googles difference, Stephen gave the best answer:

"You would probably not use Wolfram Alpha to shop for a new car, find blog posts about a topic, or to choose a resort for your honeymoon. It is not a system that will understand the nuances of what you consider to be the perfect romantic getaway, for example--there is still no substitute for manual human-guided search for that. Where it appears to excel is when you want facts about something, or when you need to compute a factual answer to some set of questions about factual data."

 

Stephen Wolfram

Stephen Wolfram is a distinguished scientist, inventor, author, and business leader. He is the creator of Mathematica, the author of A New Kind of Science, the creator ofWolfram|Alpha, and the founder and CEO of Wolfram Research. His career has been characterized by a sequence of original and significant achievements.

Born in London in 1959, Wolfram was educated at Eton, Oxford, and Caltech. He published his first scientific paper at the age of 15, and had received his PhD in theoretical physics from Caltech by the age of 20. Wolfram's early scientific work was mainly in high-energy physics, quantum field theory, and cosmology, and included several now-classic results. Having started to use computers in 1973, Wolfram rapidly became a leader in the emerging field of scientific computing, and in 1979 he began the construction of SMP—the first modern computer algebra system—which he released commercially in 1981.

In recognition of his early work in physics and computing, Wolfram became in 1981 the youngest recipient of a MacArthur Prize Fellowship. Late in 1981 Wolfram then set out on an ambitious new direction in science aimed at understanding the origins of complexity in nature. Wolfram's first key idea was to use computer experiments to study the behavior of simple computer programs known as cellular automata. And starting in 1982 this allowed him to make a series of startling discoveries about the origins of complexity. The papers Wolfram published quickly had a major impact, and laid the groundwork for the emerging field that Wolfram called "complex systems research."

Through the mid-1980s, Wolfram continued his work on complexity, discovering a number of fundamental connections between computation and nature, and inventing such concepts as computational irreducibility. Wolfram's work led to a wide range of applications—and provided the main scientific foundations for such initiatives as complexity theory and artificial life. Wolfram himself used his ideas to develop a new randomness generation system and a new approach to computational fluid dynamics—both of which are now in widespread use.

Following his scientific work on complex systems research, in 1986 Wolfram founded the first research center and the first journal in the field, Complex Systems. Then, after a highly successful career in academia—first at Caltech, then at the Institute for Advanced Study in Princeton, and finally as Professor of Physics, Mathematics, and Computer Science at the University of Illinois—Wolfram launched Wolfram Research, Inc.

Wolfram began the development of Mathematica in late 1986. The first version of Mathematica was released on June 23, 1988, and was immediately hailed as a major advance in computing. In the years that followed, the popularity of Mathematica grew rapidly, and Wolfram Research became established as a world leader in the software industry, widely recognized for excellence in both technology and business.

Following the release of Mathematica Version 2 in 1991, Wolfram began to divide his time between Mathematica development and scientific research. Building on his work from the mid-1980s, and now with Mathematica as a tool, Wolfram made a rapid succession of major new discoveries. By the mid-1990s his discoveries led him to develop a fundamentally new conceptual framework, which he then spent the remainder of the 1990s applying not only to new kinds of questions, but also to many existing foundational problems in physics, biology, computer science, mathematics, and several other fields.

After more than ten years of highly concentrated work, Wolfram finally described his achievements in his 1200-page book A New Kind of Science. Released on May 14, 2002, the book was widely acclaimed and immediately became a bestseller. Its publication has been seen as initiating a paradigm shift of historic importance in science, with new implications emerging at an increasing rate every year.

Wolfram has been president and CEO of Wolfram Research since its founding in 1987. In addition to his business leadership, Wolfram is deeply involved in the development of the company's technology, and continues to be personally responsible for overseeing all aspects of the functional design of the coreMathematica system.

Wolfram has a lifelong commitment to research and education. In addition to providing software for a generation of scientists and students, Wolfram's company maintains some of the web's most visited sites for technical information. Wolfram is also increasingly active in defining new directions for education, especially in the science he has created.

Building on Mathematica, A New Kind of Science, and the success of Wolfram Research, Wolfram in May 2009 launched Wolfram|Alpha—an ambitious, long-term project to make as much of the world's knowledge as possible computable, and accessible to everyone.

Systems in Obama's World

A couple of months ago, I attended a lecture, where the guest lecture, Jon Wade, was talking about the importance of System Engineering in solving tomorrows problems. It made total sense, a lot of the challenges that America is facing in this new decade and century are systematic challenges.

For example, when the Christmas day suspect terrorist was able to board the plane, Obama said: “ System Failed in a major way”(SILOBreaker). He did not mention a particular agency or entity for the failure, like the CIA or HLS agency, but he mentioned a system level failure. That is because times have changed and true essence of synergy is shaping more as a reality than a myth. As Aristotle once said it, the whole is the sum of its parts, and that is a challenge that we are still facing and where Systems Engineer would have a big impact.

The same goes for the solution to the Health care reform or starting the green technology revolution for the future. As the complexitiy of problems increase, there needs to be a new set of tools and methods to approach these problems, and that is what Systems Engineers need to think about.