Expert systems allow users to leverage the knowledge of experts without requiring their presence. These systems, though limited to fields where questions can be precisely stated, are useful in any field where experts are rare, expensive, or inaccessible. They can both automate a lengthy decision process and deal with large quantities of data that might overwhelm a human.

In artificial intelligence, an expert system is a computer system that emulates the decision-making ability of a human expert. Expert systems are designed to solve complex problems by reasoning about knowledge, represented primarily as if–then rules rather than through conventional procedural code. The first expert systems were created in the 1970s and then proliferated in the 1980s. Expert systems were among the first truly successful forms of AI software.

An expert system is divided into two sub-systems: the inference engine and the knowledge base. The knowledge base represents facts and rules. The inference engine applies the rules to the known facts to deduce new facts. Inference engines can also include explanation and debugging capabilities.

https://en.wikipedia.org/wiki/Expert_system

http://www.encyclopedia.com/topic/Expert_systems.aspx

http://aitopics.org/sites/default/files/classic/Machine_Intelligence_10/MI10-Ch14-Buchanan.pdf

Use of expert system is now days  more of a tradition than convention , ever since the dawn of computerization /automation in work , avoiding the human intelligence. You call it either  expert  system or decision support , they all are contributing so handsomely , but cross verification with ground truth , called validation of model is utmost important in any discipline of science .

Expert systems allow users to leverage the knowledge of experts without requiring their presence. These systems, though limited to fields where questions can be precisely stated, are useful in any field where experts are rare, expensive, or inaccessible. They can both automate a lengthy decision process and deal with large quantities of data that might overwhelm a human.

In artificial intelligence, an expert system is a computer system that emulates the decision-making ability of a human expert. Expert systems are designed to solve complex problems by reasoning about knowledge, represented primarily as if–then rules rather than through conventional procedural code. The first expert systems were created in the 1970s and then proliferated in the 1980s. Expert systems were among the first truly successful forms of AI software.

An expert system is divided into two sub-systems: the inference engine and the knowledge base. The knowledge base represents facts and rules. The inference engine applies the rules to the known facts to deduce new facts. Inference engines can also include explanation and debugging capabilities.

https://en.wikipedia.org/wiki/Expert_system

http://www.encyclopedia.com/topic/Expert_systems.aspx

http://aitopics.org/sites/default/files/classic/Machine_Intelligence_10/MI10-Ch14-Buchanan.pdf

Nowadays, it is very difficult to do research without use of the expert system. Artificial Intelligence is one of the new tool to solve very complex engineering planning problems which is nothing but the application of expert system through a computer. Random number generator is key for artificial intelligence particularly for heuristic optimization.

I retired from university in 1999 but continued a contract work until 2008, finally retiring from the frontier of research. During my research years, I did not use any expert system because the topics I treated was not so complex as to need difficult decision-making.

Yes. I feel now a days, it is essential.

The expert system gathers information by presenting the user with a series of questions. That information is integrated with its stored rules (knowledge) to generate more specific questions. In some cases (e.g., medical diagnosis), the expert system can suggest actions for the user to take (e.g., a culture or blood test) to gather more information. Eventually, the expert system delivers a decision or conclusion, often accompanied by an explanation of how it was reached.

For more information, please consult the following link

http://www.encyclopedia.com/topic/Expert_systems.aspx

Yes, I do dear @Shafagat. I use an expert systems in the area of automation& process control.

"Auctoritas" psychiatric expert system shell.

Kovács M1, Juranovics J.

 Abstract

We present a short description of a complex psychiatric computer expert system, including functions that help the physicians and the hospital staff in the administrative, diagnostic, therapeutic, statistical, and scientific work. There are separate data-storing, health insurance-supporting, or simple advisory programs, but we can not avail a system--in our country--that provides us with all these functions together. Hence the aim of our program is to produce a universal computer system that makes the patients' long distance follow-up possible. Our diagnostic expert system shell, which is appropriate for using the symptoms and criteria scheme of the internationally accepted diagnostic systems such as DSM and ICD, helps to archive homogeneous, up-to-date psychiatric nosology; this is essential for the correct diagnostic, statistical, and scientific work. Let us introduce our expert system. It consists of four parts: administration, diagnostic decision support system, activities concerning treatment, and statistics. The part called "Administration" contains all data about actual and emitted in-patients and out-patients, including their particulars and data necessary for health insurance (duration of treatment, diagnosis); here we find and edit medical documents. The most important part of the "Auctoritas" system is the "Diagnostic decision support system." In practice, expert systems use decision trees with yes-no logic, fuzzy logic, and pattern matching on the basis of the method of deduction; and backward chaining or forward chaining on the basis of the direction of deduction. Our system uses the methods of fuzzy logic and backward chaining. In other medical disciplines, good results are achieved by applying the pattern matching method; to make validity and verification researches, however, these systems are inappropriate. The diagnoses relying on the up-to-date psychiatric diagnostic systems--DSM-IV and ICD-X--are based on classical logic and can be correctly validated and verified. Hence we have chosen the fuzzy logic, which is the up-to-date extension of classical logic and influences the validity and verification researches, for the construction of our system. The diagnostic part is a shell that can be filled up optionally with knowledge bases of the DSM-IV, ICD-X, or other diagnostic systems and has the following structure. The diagnostic course is biphased as we can differ symptoms and criteria (duration of the illness, aethyological factors). We managed to extend the traditional applications using yes-no logic with three factors that make the system more sensitive and flexible. These are the scaling, sorting by importance of symptoms, and reliability-validity results. The "scaling" means that the physician scales the input symptoms by severity; this influences the statistical probability of the possible diagnoses. "Sorting by importance" is gauging certain symptoms by importance in a syndrome. Finally the third point, "reliability-validity results," means taking account of the latest validity values of a certain disorder of the used diagnostic system--according to the latest validity researches--and the diagnostical reliability of our expert system. The "Activity concerning treatment" is a practical part of our program that contents the examination and therapy scheduling and monitoring results. Under the point of "Statistics," we can prepare all data of the patients in various ways. In summary, the "Auctoritas" computer system is a global database managing the newly-developed advisory system; it is appropriate for managing a complete hospital network system for the continuing individual long-distance observation of patients. It collects all the necessary information of one patient in one file. The long-term benefit is that it can compile and process large amounts of information about the patients and help physicians come to scientific conclusions for research and publications.

http://www.ncbi.nlm.nih.gov/pubmed/8591608

Dear Colleagues,

Good Day,

......  "Capabilities of Expert Systems: General View

The most important applied area of AI is the field of expert systems. An expert system (ES) is a knowledge-based system that employs knowledge about its application domain and uses an inferencing (reason) procedure to solve problems that would otherwise require human competence or expertise. The power of expert systems stems primarily from the specific knowledge about a narrow domain stored in the expert system's knowledge base.

It is important to stress to students that expert systems are assistants to decision makers and not substitutes for them. Expert systems do not have human capabilities. They use a knowledge base of a particular domain and bring that knowledge to bear on the facts of the particular situation at hand. The knowledge base of an ES also contains heuristic knowledge - rules of thumb used by human experts who work in the domain."...

Please, see the link...

http://www.umsl.edu/~joshik/msis480/chapt11.htm

Dear Colleagues,

Good Day,

"Expert Systems in Control Engineering: A Review of the Perspective

Abstract

With the increasing complexities of modern day plants and systems as well as the explosion of the control engineering packages and techniques, the use of expert systems is gaining popularity. A number of expert systems has been built and applied to solve control engineering problems. This paper attempts to present a perspective view of this new area. A number of important issues such as numerical stability of control algorithms, different knowledge engineering tools and techniques and their application to different control engineering expert systems has been addressed in this paper. The salient features of a number of representative systems have also been discussed."...

http://www.tandfonline.com/doi/abs/10.1080/02564602.1991.11438734

Hi, yes I have used some techniques of expert systems in my research work. This is done by emulating human experiance in evaluating defined engineering problems. The most diffecult task in developing expert systems is how to capture and represent human knowledge and the implement the same way of human thinking.

Expert systems is one of Artificial intelligence techniques.

Dear Ms Mahmudova,

As funny as this may sound, in my work so far nope.

 "artificial" I would get a bit frenzied when used.

Is it  commercially viable , yes starting with interactive games... 

In research - software work on commands you build it. In a way it processes  a whole lot of commands provided it can make sensible operations . i guess this again needs someone to visualize all possible scenarios, brings us back to the "expert".

Nonetheless, fault tolerance and safety certainly needs such systems (Nuclear plants , automation industry and Hacking /for network  security)   

Dear Dr. Shafagat Mahmudova,

Expert system has no sense in modern research tools. It was coined and was quite popular and was useful in early 90's.   

I never used expert system in my research, perhaps due to my experimental work

Application of expert systems for solving real life engineering problems is the present days demand. Since, researchers are focusing on very complex problems which are very very difficult to solve using the well established mathematical tools. So we really need something which can be able to tackle such problems easily. And, I think expert system are fulfilling these requirements. That is why, we often used to apply expert systems to solve real life engineering problems.

Regards,

Mahamad Nabab Alam

yes, i think this, but the Possibilities in our countries cant not do this

I agree with you sir Abdul aziz Jaafar.

I am not aware of such system in my field of interest. Before submission of paper  I am mostly guided by logic, prior experience and intuition. It worked well so far.

Nowdays , most of the statistical packages a re nothing but expert systems only , revolutionarised the whole concept of statistical computing. Within no time , your data is analysed and ready for interpretation of your results. But , the other side of such expert systems is the gradual depletion of that intelligent art of  manual computing , thereby , developing your own intelligence ?

Expert Systems are computer programs that are derived from a branch of computer science research called Artificial Intelligence (AI). AI's scientific goal is to understand intelligence by building computer programs that exhibit intelligent behavior. It is concerned with the concepts and methods of symbolic inference, or reasoning, by a computer, and how the knowledge used to make those inferences will be represented inside the machine.

Of course, the term intelligence covers many cognitive skills, including the ability to solve problems, learn, and understand language; AI addresses all of those. But most progress to date in AI has been made in the area of problem solving -- concepts and methods for building programs that reason about problems rather than calculate a solution.

http://www.slideshare.net/norelianamdsharif/topic-8-expert-system

Dear Colleagues,

Good Day,

Here are really excellent papers for you, hope you find them useful,,,,

... Yes ..

Dear Shafagat, sure that modern  tools from automation and computer aided systems should become the custom tools of ones  desks. Expert systems derived from artificial intelligence methods  could help decision making in engineering process for example, same as in other fields of science. Personally i have developed in the mid of the 90's of the late century an expert system for quality assurance assessment of welded structures used in industrial petrochemical plans

Dear @Fairouz Bettayeb,

Thank you very much for opinion.

Regards, Shafagat

Dear @Subhash C. Kundu,

Thank you very much for answer and links.

Regards,Shafagat

Dear @Ghassan A AlKindi,

Thank you very much for comment.

Regards,Shafagat

I share your point of view, dear @ Ali A R Aldallal,

Regards, Shafagat

Expert systems in civil engineering

Knowledge-based expert systems are computer programs, based on artificial intelligence (Ai) techniques, designed to reach the level of performance of a human expert in some specialized problem solving domain.

Expert systems have a great potential for practical use in ill-structured problem solving domains where explicit algorithms do not exist or where traditional computer programs provide only restricted problem solving capabilities

As the civil engineering and construction processes and the construction site increase in complexity, expert systems will increasingly augment or replace conventional algorithmic programs in which all decisions have to be anticipated and pre programmed. Expert systems are applicable to a wide range of tasks, and many problems in the civil engineering domain, such as structural design, structural

modeling, structural diagnosis, site investigation, estimating, scheduling and contingency management, are potential expert system applications. The development of construction robots provides many new applications for expert systems including tasks such as sensor interpretation, equipment diagnosis, operational planning and operational monitoring. Finally, design for robotic construction will be a new domain, and one particularly suited for expert system application.

Applications of expert systems in civil engineering

Expert systems are associated with some basic characteristics of civil engineering problems, such as incompleteness and inaccuracy of data, multidisciplinary approaches and the need of complementary qualitative analysis. Examples of expert systems in many civil engineering branches such as structural, geotechnical and environmental engineering are discussed in the attached books and conference proceedings.

Adeli, H. (Ed.). (2003). Expert systems in construction and structural engineering. CRC Press.

Expert Systems in Civil Engineering: Proceedings of a Symposium Sponsored by the Technical Council on Computer Practices of the American Society of Civil Engineers in Conjunction with the ASCE Convention in Seattle, Washington, April 8-9, 1986

Allen, R. H. (1992). Expert systems for civil engineers: Knowledge representation. ASCE.

rockiasamy, M. (1992). Expert Systems: Applications for Structural, Transportation, and Environmental Engineering. CRC press.

https://books.google.com/books?id=ousmAAAAMAAJ

https://books.google.com/books?id=W4lRAAAAMAAJ

https://books.google.com/books?isbn=0203401107

https://books.google.com/books?isbn=0849342171

I utterly agree with Dr. Behrouz Ahmadi-Nedushan, because his responds are complete and comprehensive.

Dear Behrouz Ahmadi-Nedushan,

Thank you very much for att. file. Your opinion is appreciated.

Regards, Shafagat

The use expert systems in medicine:

The medical information technology for emulation

of human reasoning process and human expert problem

solving is knowledge-based system. In literature

survey, MYCIN [1] is an expert system for diagnose

or remedy bacterial infections, PUFF [2] is developed

to diagnose lung disease, ANGY helps physicians to

diagnose the narrowing of coronary vessels by identifying

and isolating coronary vessels in angiograms,

BABY aids clinicians by monitoring patients in a

newborn intensive care unit (NICU), MECS-AI helps

physicians to make diagnoses and to suggest treatments.

Other example In oncology we use expert system in cancer chemotherapy; The use of AI (artificial intelligence) techniques, with its logical-deductive mechanisms, that reproduce

the human reasoning without the restriction of human capabilities in memory and association,

is particularly suitable for those medical problems, in which you must regard a great number of

prognoses and their effects and interactions. 

Ref

1. Durkin, John. Expert System : Design and Development.

New York : Macmillan Publishing Company,

Inc., 1994.

[2] Giarratano, Joseph. ; and Riley, Gary. Expert Systems

: Principles and Programming(Fouth Edition).

Canada : Thomson, 2005.

http://www.ijabme.org/images/stories/ijabme/2009/j092009.pdf

Dear @ Gamal Abdul Hamid ,

Thanks for providing this informative link and your opinion.

Regards, Shafagat

Dear Colleagues,

Good Day,

"EXPERT SYSTEMS FOR CALCULUS TEACHING" 

This is the title of an excellent paper, you may try and read it, hoping it is useful to you.

Please, see the link for detail.....

http://www.mtm.ufsc.br/geiaam/EXPERT_SYSTEMS_FOR_CALCULUS_TEACHING.html

Dear @Hazim Hashim Tahir,

Thank you very much for your opinion.

Regards, Shafagat

KBES in engineering design

The emergence of Knowledge Based Expert Systems (KBES) provides a means for the engineer to use the computer as an aid in the solution of ill-structured problems. KBES are interactive computer programs that incorporate the knowledge and judgment of experts in appropriate domains. These systems promise to introduce changes at least as far-reaching as the entire computer revolution to date. The number of papers published on the applications of KBES to engineering problems in the last decade reflects the interest being shown in the engineering community.

The development of a KBES presently involves the cooperative effort between one or more experts who possess the domain-dependent knowledge and a knowledge engineer (KE). The KE elicits the knowledge and uses either an expert system building tool or a general-purpose language to represent and manipulate it. The representation of knowledge in a KBES is dependent on the selection of the tool or language to be used. The KE must make a choice among several available tools before embarking into a major developmental task; the ease of building an expert system depends in part on

the choice of the tool.KBES are interactive computer programs which attempt to simulate the expert's thought processes, providing advice for a wide range of problems as described above. 

KBES typically consists of three major components:

Source:

Maher, M. L., Sriram, D., & Fenves, S. J. (1984). Tools and techniques for knowledge based expert systems for engineering design. Advances in Engineering Software (1978), 6(4), 178-188.