Combining Expert Systems Technology and User’S Requirements: Design Issues for Expert System Development for Corrosion Engineering

Expert system has the least focus on requirement engineering. In facts, requirement engineering is important to get all the requirements needed for an expert system. If the requirements do not meet the clients' needs, the expert system is considered fail although it works perfectly. Currently, there are a lot of studies proposing and describing the development of expert systems. However, they are focusing in a specific and narrow domain of problems. Also, the major concern of most researchers is the design issues of the expert system. Therefore, we emphasize on the very first step of success expert system development - requirement engineering. Hence, we are focusing in the requirement engineering techniques in order to present the most practical way to facilitate requirement engineering processes. In this paper, we analyze expert system attributes, requirement engineering processes in expert system developments and the possible techniques that can be applied to expert system developments. Next, we propose the most appropriate techniques for the expert system developments based on the analysis. From this paper, a set of techniques for expert system development will be provided.

The application of an expert system (expert system) which is very useful for the wider community is certainly very much needed by society today. Apart from that, this development also supports various human activities. Expert systems are also able to make recommendations for a series of user actions. The aim of this research is to determine the development of expert systems in management information systems. The research method used in this research is a descriptive research method with theoretical studies, namely a method that discusses several possibilities for solving actual problems by collecting data, compiling or classifying them, analyzing and interpreting them with existing theories and comparing them from literature sources. The research results show the development of expert systems in management information systems, namely knowledge bases, inference engines, and user interfaces. It can be concluded that expert systems help work and technological progress more quickly and the decision-making process is based on existing information and facts. Expert systems have also been used in various fields, from medical, legal, to financial. In developing an expert system, it is necessary to increase the level of knowledge related to the latest technology and information. So you can utilize modern technology to complete work more effectively and efficiently.

In this study, a part of a complete Expert System (ES) for powder technology is presented. It deals with the powder selection according to predetermined recommended or required material properties and specific powder characteristics. This leads to the determination of the most common powder production (i.e., processing) method, which satisfies the specified powder requirements for a specific application. For this purpose a detailed functional prototype expert system is developed using a rule-based knowledge representation model. The expert system is designed to acquire knowledge from the user then give recommendations. The inference engine, EXSYS-CORVID, is used as the development tool. The forward and backward chain technique is utilized, thus the reverse process is also be possible. Therefore, the system will determine or assign some primary powder characteristics and production method to satisfy or achieve the required product and vice versa. The developed expert system is flexible, easy to be implemented, modified and extended. The system displayed excellent performance and typical illustrative examples are shown. The proposed system is believed to assess in increasing productivity in the field of powder technology and increases the profitability and competitiveness of the process in a modern ever increasing industries.

This paper considers the possible enhancement of the capabilities of an expert system tool. Most of the commercial tools currently available are not particularly suitable for developing expert systems that involve routine design calculations. To overcome this drawback for engineering applications, numerical computations may be carried out by conventional computer programs which can be linked to an expert system tool through its external program interface. This type of expert systems is called a "hybrid" or "coupled" expert system. Practicing engineers will, sooner or later, face the need to use hybrid expert systems. This paper presents a case study which shows how the capabilities of a commercial expert system tool can be enhanced by integrating it with a conventional computer program. The hybrid expert system developed by the authors for illustration purpose can be used for the analysis of plane steel trusses and the evaluation of member design forces. It utilizes an in-house program called “Manager” to integrate two commercial software packages: an expert system tool called KES and a structural analysis package named PFRAME. The capabilities of the hybrid system appear to exceed those of the individual software packages. Key words: knowledge based expert systems, expert system building tools, hybrid expert systems, structural analysis, structural design.

Expert system is made to transfer the expert knowledge into the system, so it hopefully can give solution to problem.“Expert system for diagnosis of infection TBC lung disease” is an alternative for the various expert system that can be used to overcome the problem. The aim of designing expert system is for diagnosis of infection TBC lung disease, should that users can diagnose towards this illnes based on symptoms put into this system. Development of expert system uses knowledge base stored in database using Paradox, rule based with forward chaining method.The result of consultation with the system indicate that this system can determine disease and suggestion based on symptoms inputed by user. Keyword : Expert System, Forward Chaining, Knowledge Base

This article discusses the selection of the domain for a knowledge-based expert system for a corporate application. The selection of the domain is a critical task in an expert system development. At the start of a project looking into the development of an expert system, the knowledge engineering project team must investigate one or several possible expert system domains. They must decide whether the selected application(s) are best suited to solution by present expert system technology, or if there might be a better way (or, possibly, no way) to attack the problems. If there are several possibilities, the team must also rank the potential applications and select the best available. To evaluate the potential of possible application domains, it has proved very useful to have a set of desired attributes for good expert domain. This article presents such a set of attributes. The attribute set was developed as part of a major expert system development project at GTE Laboratories. It was used recurrently (and modified and expanded continually) throughout an extensive application domain evaluation and selection process.

Kidney disease is a prevalent health issue affecting millions of people globally. Early and accurate diagnosis of kidney diseases can help in the timely and effective management of the condition. Expert systems, such as those using the Certainty Factor (CF) method, can provide doctors with valuable assistance in diagnosing kidney diseases more efficiently and accurately. This study aims to develop a kidney disease diagnosis expert system using the CF method. The developed system consists of data collection, data storage, and data processing components, with the CF method used to calculate diagnostic confidence levels and decision-making based on predetermined rules. The knowledge acquisition process was carried out by interviewing three nephrologists to obtain rules for diagnosing kidney diseases. The expert system's evaluation is conducted by comparing the system's diagnostic accuracy with a specialist doctors. The results show that the developed expert system has an accuracy rate of 85.7% in diagnosing kidney diseases. The system also has a user-friendly interface, which allows doctors to input symptoms and obtain a diagnosis quickly and accurately. The developed system has several advantages over traditional diagnosis methods. It can diagnose multiple kidney diseases simultaneously and provide a differential diagnosis, allowing doctors to choose the most appropriate treatment plan for their patients. The system also has the potential to reduce diagnostic errors and improve patient outcomes.

The most important development in expert systems is the introduction and proliferation of frameworks, or shells, that allow rapid prototyping, easy expansion, and continued maintenance. Several shells are now in commercial use and have been used to build expert systems of recognized value. The state of the art and several new lines of development will be discussed. Some of the developments involve fundamental research in AI on knowledge representation and inference; others involve making the shell environments themselves more intelligent.

The development of a rule-based expert system (referred to as SCAR) for assisting electricians in diagnosing electrical faults in a shuttle car is discussed. Insight 2+, a microcomputer-based expert-system development tool by Level Five Research, Inc. was used in creating the system. The program requires the user to specify the initial symptoms of the failed machine; then the most probable cause of failure is traced through the knowledge base, with the software requesting additional information, such as voltage or resistance measurements, as needed. A causal-reasoning approach, which was used to develop the production rules, is described. The organization, implementation, and limitations of the knowledge base are also presented, along with a brief discussion of the ongoing development of a new system, SCAR.2. >

An efficient solids control procedure or mechanism is one of the keys to drilling optimization. This can be achieved by employing proper solids control equipment while drilling is in progress. This paper presents an expert system that is developed for the selection of proper solids control equipment. An expert system is an interactive computer based tool that simulates the thought process of human experts to solve complex problems in a specific domain. The key stages in the development include: problem definition and analysis, knowledge acquisition (involving consultation with experts), knowledge-base development, interface development, and finally input and output data presentation. The expert system developed has four important modules. The first module is based on an extensive survey of the literature available on the subject to date. Upon input from its user, it suggests the best possible combination of solids control equipment that is compatible with the drilling parameters. The second module helps the user in carrying out density control calculations pertaining to solid control. The third module is in a text mode, and describes the solids control equipment commonly installed on the rigs, along with the criterion involved in their application. The fourth module allows the user to note down his experience pertaining to any particular situation he may have come across. This can be of help to him, or to any other user who may be faced with a similar situation later. This paper presents the methodology and various examples under these four modules to demonstrate field related applications. The salient features on this expert system are its " userfriendliness" and ability to constantly self-improve itself constantly by maintaining a " dynamic memory." A listing of the program is included in this paper to allow readers to validate the technique and gain benefit of the paper. At the rig site, this system will allow the user to familiarize himself with the solids control equipment. This will help in obtaining the best possible equipment arrangement for effective solids control and various density control calculations. Introduction Selection of the right kind of drilling fluid is essential for economic drilling of wells. During drilling, drilled solids or cuttings generated at the bit, mix and interact with the initially formulated drilling fluid, and bring about changes in its density, rheology, and other properties of the fluid. These factors, in turn, are determined by such interacting variances as lithology, fluid properties, penetration rate and the wellbore geometry. Several studies(1-8) mention the disadvantages related to poor solids removal while the drilling is in progress. These include higher density, higher viscosity, higher filtration rate, and higher filter cake thickness. Practically, this means lower rates of penetration, reduction in bit-bearing life, higher torque and drag and more chances of stuck pipe. Definitely, this is uneconomical for drilling operations. A large number of variables are often involved in deciding the type of solids control equipment that has to be employed for a particular kind of drilling situation.

This paper describes experiments designed to test the feasibility of linking discrete-event simulation models with expert systems. Two microcomputer systems are used: one contains the simulation model, while the other contains the expert system. The paper shows that by linking a simulation model with an expert system, it is possible to use the combination for simulation parameter learning, expert system development and expert system control of a simulation model.

It is well recognized that the evaluation of the knowledge-based system is very important and difficult in the development of expert systems in the domains such as aviation and navigation. To alleviate some of the difficulties, and to reduce the development cost, the authors proposed an evaluating procedure based on simulation. The proposed procedure was designed to validate the functionality and capability of an expert system that was developed to provide decision-making support in ship navigation. In this paper, the developed expert system for collision avoidance is first outlined, and the procedure to evaluate the developed expert system by using a simulation-based approach is presented in details. It is also concluded that the simulation-based procedure is feasible and effective for evaluating expert systems in a number of different domains.

Expert systems are computer programmes that can reproduce the behaviour of human experts in specific problem domains. In many places, development of expert systems is the major focus of fifth generation software projects. Accordingly, enormous amounts of resources are being spent on work in this field. Expert systems have enjoyed considerable success in many scientific and technological applications but their application in the field of management. is relatively recent. In this article, Rekha Jain presents an overview of expert systems and addresses several issues that will be of interest to managers who are likely to consider using expert systems in their organizations.

3 - Expert systems and other areas of artificial intelligence

The traditional approaches used for the development of expert systems are mainly based on the interaction between the knowledge engineer and the domain expert. However, the role of user in the development process has been undermined. The human factors involved in the user/expert-system interaction are fundamental to the development of expert system and must be taken into account. This paper adopts the soft systems concept to represent the expert system development as a soft system which allows us to consider all relevant facets of the environment. Based on the soft systems concept, a new methodology for establishing the expert system development system (ESDS) is introduced. >