Expert System For Management Research Articles

Deckle Optimization and Winder Roll Management in Paper Manufacturing

This work proposes an expert management system of winding as linked with paper machine production planning and coordination. The integrated management system operates at three levels which receives the information of deckle buckets sent by paper machIne production planning. The main goal of deckle optimization at the highest level is to minimize the paper waste in arranging the reels in a bucket and provide the deckle information to a lower level. The winder optimization at the lower level receives the deckle information. The general goal of winding optimization is to maximize the roll quality and to provide the winding rate equal to the paper machine production. Corresponding to the generated optimum results, the winder optimization block generates the supervisory set point values such as: for web tension, and the target diameter of finished roll, to provide a high quality roll with the desired final diameter.

Expert systems in agriculture and resource management

This paper gives a description of some representative examples of expert systems applied to problems in agriculture and biological resource management. The discussion of agricultural expert systems focuses on several decision support systems for crop management, describing the systems themselves and the implementation efforts surrounding them. The examples of the application of expert systems to biological resource management focus on the integration of expert systems with geographic information systems. A description of some of the more recent developments in agricultural expert systems, still in the prototype stage, is then given, followed by a summary discussion of possible environmental implications of the use of expert systems in agriculture and resource management.

Expert Systems in Production and Operations Management: Results of a Survey

I surveyed 74 knowledge engineers from private organizations to examine empirically the state of expert systems in these organizations. I asked the knowledge engineers to rate issues related to successful implementation, the extent of use in several areas, the original motivations for implementation, the perceived and quantified benefits of implementation, the interactions with end users, and the knowledge acquisition techniques they used to aid development. I report the results and describe some specific expert systems that the respondents' organizations have developed and are currently using.

Exercise countermeasure protocol management expert system

Exercise will be used primarily to countermeasure against deconditioning on extended space flight. In this paper we describe the development and evaluation of an expert system for exercise countermeasure protocol management. Currently, the system includes two major subsystems: baseline prescription and prescription adjustment. The baseline prescription subsystem is designed to provide initial exercise prescriptions while prescription adjustment subsystem is designed to modify the initial prescription based on the exercised progress. The system runs under three different environments: PC, SUN workstation, and Symbolic machine. The inference engine, baseline prescription module, prescription adjustment module are developed under the Symbolic environment by using the ART (Automated Reasoning Tool) software. The Sun environment handles database management features and interfaces with PC environment to obtain physical and physiological data from exercise units on-board during the flight. Eight subjects' data have been used to evaluate the system performance by comparing the prescription of nine experienced exercise physiologists and the one prescribed by the expert system. The results of the validation test indicated that the performance of the expert system was acceptable.

Development and implementation of a knowledge acquisition methodology for crop management expert systems

This paper presents methodology developed for knowledge acquisition for crop management expert systems. The proposed methodology is described through an extended waterfall model for knowledge acquisition. The way in which the methodology was implemented is presented, and the experience gained is discussed. Although the methodology has evolved through the development of an expert system for cucumber seedling production, it can be used for other crops. A field prototype of this expert system was implemented and is currently being tested in a real environment.

The implementation of expert systems

A descriptive mail survey of managers of work groups using expert system (ES) technology was performed to gain insight into the management of the ES implementation process. This article presents survey results representing 45 different ES projects that have been successfully implemented in organizations. Each of the managers was asked to evaluate the importance of 13 factors to ES implementation success and to report on the organizational climate and practices related to ES implementation. The survey results are generally consistent with earlier implementation research and indicate that successful ES implementation requires management attention to a combination of organizational factors, implementation activities, and technical factors. Implementation practices that were associated with the successful ES implementations were commitment to the ES project, user participation, and management support.

Integrated Information Management Expert System For Structural Engineering of Buildings

Abstract: This paper describes the development of an integrated Information Management expert system (IMXpert) which enables structural engineers or architects to produce results of high quality within a short time in works related to the structural engineering of buildings. IMXpert gives various data or functions according to the user's request.The study can be divided into problem analysis and system design. For the systematic representation of building structure and the structural design process, an object‐oriented design method has been used for the problem analysis. Various types of structural components and operations closely related to them have been extracted and defined as independent objects. The complete building structure and structural design process can be represented by combining these objects and operations. A centralized database has been designed for the consistent and integrated management of object instances.

Expert systems in management and administration - are they really different from Decision Support Systems?

Historically, the fields of Decision Support Systems and Expert Systems grew up from different backgrounds; Management Information Systems and Artificial Intelligence, respectively. As a result, many people still regard them as unrelated fields, although Operational Researchers are working in both of them. Expert Systems in particular have found it difficult to escape from an image of being isolated; not just from Decision Support Systems, but from all other types of computer system. Succesful applications appeared to be confined to very well-defined tasks; either small systems for tasks of an operational nature, or large systems requiring expensive specialised computer support. The spread of Expert Systems into management and administrative applications from the scientific/technical domains of the early systems has been very slow. The view put forward in this paper is that for Expert Systems to be applied to problems in management or administration, the traditional ‘closed-world’ picture of an Expert System is usually inadequate. The real manifestation of the Expert System's role (and indeed that of the human expert) involves much more negotiation and interaction than in scientific/technical domains. The consequences for the resulting system are that it looks much more like the traditional picture of a Decision Support System than a classic standalone Expert System. The argument will be illustrated by reference to examples of ‘Expert System’ developments, including systems for production control, crime pattern analysis, telephone marketing, and the drawing up of contracts.

A knowledge-based decision support system for project management

A KBS is proposed in this paper to enable the incorporation of expertise into project management. This represents an alternative to traditional algorithmic approaches, and the structure and development of a prototype expert system for project management are described. The KBS enables the user to selectively modify and constrain single activities or the entire network by specified amounts, reconfigure the network, and recompute resource usage in each case. It therefore represents a potentially useful decision support tool for performing exploratory and sensitivity analyses in managing large projects and a training tool for less-experienced planners.

Oestrus detection in cattle: recent developments

A review is presented of recent studies on improvement of oestrus detection aids and development of methods for determining the proper insemination time, without the need to detect the behavioural manifestation of oestrus. Emphasis is placed on: (1) automated and telemeterable mass that could be incorporated in computerized expert management systems; (2) increasing the efficiency and accuracy of detection by simultaneous or consecutive use of more than one method.

An Expert System for Integrated Production Management in Muskmelon

A management expert system that enables producers to fully assess the integrated resource requirements, management risks, and profit potential for growing muskmelon was developed. The expert system environment Guru was used as the development software.

A review of “Expert Systems in Factory Management—Knowledge Based CIM”. By W. MEYER (Ellis Horwood Books, 1990) (price not given).

A review of “<i>Expert Systems in Factory Management—Knowledge Based CIM</i>”. By W. MEYER (Ellis Horwood Books, 1990) (price not given).

An expert system for analytical data management

An expert system for analytical data management

Decision Support System for Crop Planning during Droughts

Demand for water is increasing continually, whereas available supplies are more or less constant. Under these circumstances there is an urgent need to introduce efficient techniques in water resources management for optimal utilization of available water. Water management under drought conditions assumes great importance in a tropical region such as India, where one‐third of the cropped area is affected by frequent droughts. This paper deals with the development and application of an expert system for drought management. A linear programming model was used to generate optimal cropping patterns from past drought experiences as also from synthetic drought occurrences. These policies together with the knowledge of the experts were incorporated in an expert system. Using this, one can identify the degree of drought in the current situation and its similarity to the identified drought events and be able to get the corresponding management strategy.

Expert system for refinery off-site facility management

In refinery off-site plants, the equipment configuration is often changed or the plant facilities expanded to meet market demand. To manage such changes, we have developed an expert system for refinery off-site facility management. The expert system has a database containing information about all off-site plant facilities and pipeline networks; the database may be displayed graphically in the form of plant instrumentation diagrams, and maintenance of this graphic database is easy. The system also provides support for plant operation: it finds all available paths through the pipeline network— for moving oil from a tank to a berth, for example-and automatically generates all necessary sequence and batch control information for the associated distributed control system to move the oil through any of the chosen paths. In normal operation, this system is maintenance-free. The expert system allows process changes to be handled by normal maintenance personnel, rather than requiring computer specialists.

The strategic use of expert systems for risk management in the insurance industry

The applications focus and development history of two large expert systems for underwriting life insurance cases are used to consider the linkage between business strategy and project focus for major information systems development. It is shown that the project selection and evolution processes of these two companies have resulted in two distinctly different expert system applications, the product of their respective business positioning. The article also presents a detailed description of how expert systems can be used to enhance the productivity and effectiveness of risk management in the life insurance business.

SYNthesis LIBrary, an expert system for chemical-reaction knowledge-base management

SYNLIB (SYNthesis LIBrary) is an expert system which allows laboratory scientists to rapidly and interactively search databases of chemical reaction information. SYNLIB is fully supported on personal computer and RISC workstation platforms and requires minimal computer expertise on the part of the chemist. By encouraging hands-on access to information, SYNLIB allows complex chemical synthesis concepts to be presented directly to the practicing laboratory scientist. SYNLIB searching enables the user to query chemical reaction knowledge bases for matches to combinations of structural and non-structural chemical questions. We discuss the design considerations for expert systems specifically for chemists and present an analysis of the chemical-reaction information available from the published literature. A search for the formation chemistry of functionalized α,β-unsaturated ketones is used to illustrate the search strategies available.

The DIME System: A Preliminary Report

AbstractInvestment management is a complex, yet promising, domain for the application of intelligent automation. In this paper we discuss the Diversified Investment Management Expert (DIME) system which is under development. DIME is designed to operate in a dynamic environment and hence one of its salient features is its knowledge acquisition via learning. The system starts out with some rules built into it, and machine‐learning techniques are used to acquire further knowledge with time. In this paper we focus on how similarity‐based learning (SBL) is used to acquire new rules and explanation‐based learning (EBL) to refine the built‐in rules and the newly acquired ones.

A Blackboard Approach for Resolving Conflicting Irrigation and Insecticide Scheduling Recommendations

A blackboard was used to link an irrigation expert system with an insect pest management expert system to determine the most economical rescheduling alternative for conflicting irrigation and insecticide scheduling recommendations. The blackboard was demonstrated for several combinations of insect and water stress levels. The blackboard was also used to study the effect of rainfall probability on rescheduling conflicting irrigation and insecticide applications. The rescheduling decision was found to be sensitive to water stress, insect damage, and rainfall probability.

Automatic knowledge learning in an expert system for space management and planning

A procedure of self-learning and knowledge reducing is described. It concerns the step of knowledge acquisition for an expert system for space management and planning. Section 1 gives a general presentation of the expert system. It underlines the main characteristics of the tool. Section 2 describes the problem of knowledge acquisition and internal representation: it underlines that experts often give different expressions for the same ‘reality’, so that it becomes necessary to define ‘knowledge conflict resolution’. Section 3 explains the logical bases of self-learning and knowledge reducing: we propose: an index of consistency which ‘evaluates’ if two proposed rules are ‘near’ and can be reduced into a unique one, or not; an index of leadership which defines, while knowledge reducing, what is the ‘predominant’ rule; a ‘compromise law’ which makes the system able to operate this reducing. Section 4 briefly presents the developed procedure (Appendix 1 presents the corresponding algorithm).