Object-Oriented Knowledge-Based System for Distribution Transformer Design

The first stage in any machine design process involves a substantial heuristic exercise to select the machine best suited to a set of specifications. The second stage obtains the dimensions of a selected machine and a design that satisfies specifications. The final stage usually involves optimization and the finite-element method. We present an object-oriented knowledge-based system for distribution transformer design with the first two stages fully automated. We describe the rationale for the system, the architectural design procedure, and the approach taken in constructing the system for practical applications.      

A knowledge-based decision support system for locating a manufacturing facility

This paper examines the design and implementation of a knowledge-based decision support system (KBDSS) in the facility location domain. The KBDSS for locating a manufacturing facility is intended to support facilities planners in improving the quality of strategic decision-making in facility location. A survey of past location studies was conducted to identify the major considerations of location analysts and to develop a hierarchy of factors for locating a manufacturing facility in the USA. Location evaluation is accomplished via a location model that is formulated as a linear additive multiattribute utility model. The microcomputer-based DSS developed integrates an object-oriented expert system with other modeling tools, such as a database management system and a C-based interactive graphical user interface. The system incorporates subjective, judgemental evaluations from management with objective, factual location data to recommend the best location for a new manufacturing facility. The system also makes transparent the justification for its recommendations by providing appropriate textual and graphical explanation facilities.     

A framework for integrating databases with knowledge bases for structural engineering

The focus of this paper is on the problem of how can we easily combine the advantages of database and knowledge-based systems. Solving this problem has the potential to radically extend the usefulness of existing database systems. Conversely, the solution would also make large-scale knowledge-based systems less costly to construct. In order to solve this problem, we present a framework for exploring the various alternatives in the integration of the two kinds of systems. We also use this framework to motivate our proposed solution: knowledge-embedded database systems. Our proposal entails the use of simple but powerful extensions of a database system to increase its ability to represent and manipulate knowledge. We describe Kbase, an environment for developing knowledge-embedded database systems. We further illustrate our proposed solution with IPDOS, a Kbase application for the preliminary design of offshore structures.     

DESIGN OF A KNOWLEDGE-BASED ON-LINE SIMULATION SYSTEM TO CONTROL A MANUFACTURING SHOP FLOOR

In this paper, the design principles of a new knowledge-based on-line simulation (KBOLS) architecture for the purpose of integrating the supervisory decision making process with a shop floor control system is discussed. The requirements for implementing the KBOLS architecture in a computer integrated manufacturing environment are presented. The special features of the KBOLS architecture include a knowledge-based controller capable of interacting with the shop floor and a manufacturing simulator, a shared blackboard data structure for knowledge bases, and a learning module. The KBOLS architecture is implemented in a flexible manufacturing system for analyzing interruptions due to machine breakdowns and rush orders.     

Features-based castability evaluation

A features-driven knowledge-based approach to the quantitative assessment of castings for ease of manufacture is presented. Geometric features such as undercuts, holes, sharp corners and hot spots are recognized from a solid model of the casting and analysed by a number of dimensionless criteria functions. The criteria have been developed through a detailed study of design heuristics used by practising engineers and are written as functions of geometric attributes of component and tool features. This is useful for identifying problem features in a casting at an early stage and for objective comparison of two or more design solutions for manufacturability. The proposed approach lends itself to computer implementation for automating the design of castings in a concurrent engineering environment.     

A prototype knowledge-based system for material selection of ceramic matrix composites of automotive engine components

A prototype knowledge based system (KBS) for material selection of ceramic matrix composites (CMC) for engine components such as piston, connecting rod and piston ring is proposed in this paper. The main aim of this research work is to select the most suitable material for the automotive engine components. The selection criteria are based upon the pre-defined constraint value. The constraint values are mechanical, physical properties and manufacturing techniques. The constraint values are the safety values for the product design. The constraint values are selected from the product design specification. The product design specification values are selected from the past design calculation and some values are calculated by the help of past design data. The knowledge-based system consists of several modules such as knowledge acquisition module, inference module and user interface module. The domains of the knowledge-based system are defined as objects and linked together by hierarchical graph. The system is capable of selecting the most suitable materials and ranks the materials with respect to their properties. The design engineers can choose the required materials related to the materials property.     

Knowledge-based recursive least squares techniques for heterogeneous clutter suppression

The design of knowledge-based adaptive algorithms has been dealt with for the cancellation of heterogeneous clutter. To this end, the application of the recursive least squares (RLS) technique has been revisited for the rejection of unwanted clutter, and modified RLS filtering procedures have been devised accounting for the spatial variation of the clutter power as well as of the disturbance covariance persymmetry property. Then the authors introduce the concept of knowledge-based RLS and explain how the a priori knowledge about the radar operating environment can be adopted for improving the system performance. Finally, the authors assess the benefits resulting from the use of knowledge-based processing both on simulated and on measured clutter data collected by the McMaster IPIX radar in November 1993     

Concurrent engineering: decomposition and scheduling of design activities

Design of complex products or large scale systems involves hundreds of resources (designers, analysts, computers, software systems, and procedures) and thousands of design activities. In this paper, a methodology is presented for decomposition of the design task into activities and modules. The methodology is based or clustering of design activities into groups that allow effective organization oi resources required in the design process. A knowledge-based approach is used for managing design activities. The system performs analysis aiming at exploring concurrency and reducing the design project makespan.     

Development of a knowledge-based system for dynamic scheduling

In this paper we develop an interactive, real time, knowledge-based approach for dynamic scheduling. Blackboard concept has been utilized to organize and maintain the dynamic data base. The major knowledge representation schemes used in the system include frame structures, relational tables, and production rules. The system design is highly modular in nature thereby providing the ease for further development and enhancement. Based on this system, a design philosophy of an AI/OR integrated approach is also presented.     

An expert system for the design and analysis of composite structures

A prototype expert system is described for concurrent design and analysis of composite structures. This system integrates symbolic, numerical and knowledge-based tools in an object-oriented programming environment for design synthesis, evaluation and modification. The system determines structural behavior utilizing a combination of analytical and numerical tools. Design modifications and structural optimization are performed using heuristic and experientially derived knowledge bases. The different domain-specific programs and commercial packages utilized by the system are integrated using a generic interfacing mechanism. The utility of the system is demonstrated by means of a design case study for a typical aircraft or rotorcraft structural component.     

On implementation of computational algorithms for optimal design 1: Preliminary investigation

In this two part paper, the problem of implementation of computational algorithms for design optimization into a computer software is discussed. A recently developed algorithm that generates and incorporates approximate second order information about the problem is selected for detailed analyses and discussions. It is shown that numerical behaviour of the algorithm is influenced by variation of the key parameters and procedures. The concept of numerical experiments is introduced, and certain variations of the algorithm and parameters are selected and their influence on its performance is studied. It is shown that the numerical rate of convergence can be substantially improved with proper procedures and values of the parameters. The first part of the paper describes some preliminary analyses and investigations. The second part describes further numerical analyses and detailed procedures for evaluation of performance of various variations of an algorithm or different computer codes. The basic conclusion from the study is that robust and efficient implementation of algorithms requires expert knowledge and considerable numerical experimentation. A wide range of small scale and large scale problems of varying difficulty must be solved to evaluate performance of an algorithm. The study suggests development of knowledge-based systems for practical design optimization.     

In-house development of scheduling decision support systems: case study for scheduling semiconductor device test operations

Most manufacturing processes can benefit from an automated scheduling system. However, the design of a fast, computerised scheduling system that achieves high-quality results and requires minimal resources is a difficult undertaking. Efficient scheduling of a semiconductor device test facility requires an information system that provides good schedules quickly. Semiconductor device testing is the last stage of the long semiconductor manufacturing process, and therefore is subjected to customer service pressures. The cost of an off-the-shelf computerised scheduling system may be prohibitive for many companies. In addition, many companies are taken aback by other characteristics of off-the-shelf scheduling systems, such as code confidentiality, maintenance costs, and failure rates. We draw upon the literature and our field case to discuss some of the trade-offs between in-house development and off-the-shelf acquisition of software. We describe the in-house design and implementation of a scheduling decision support system for one device test facility. Using the design and implementation process of this system as a case study, we discuss how one facility uses in-house design of systems in a strategic way, as a competitive capability.     

Integrated modular fixture design,pricing and inventory control expert system

The aim of this paper is to trace the evolution of modular fixturing systems (MFS) and its impacts on high-precision machining industries. The strength of current computer-aided tools for modular fixture design is reviewed together with their weaknesses. Recent trends in the integration of knowledge-based and 3D solid CAD techniques for modular fixture design, pricing and inventory control are described. The functionality, design and knowledge representation techniques of a 3D Modular Fixture Design EXpert, MOFDEX system forms the core of this paper.     

A hybrid case-based reasoning CAD system for injection mould design

Injection mould design generally lies on the critical path of a new product development. The design efficiency will have significant impact on the overall lead time of a new product. This paper presents a prototype injection mould-design system using a hybrid case-based reasoning (HCBR) approach. Case-based reasoning (CBR) is a solving paradigm that uses previous episodes on solving problems similar to the problem at hand (the new problem) as the basis for solving the new problem. In this hybrid system, CBR is incorporated with generalized design knowledge, and provides a flexible and comprehensive model of design. The knowledge base of the system would be accessed by mould designers through interactive programs so that their own intelligence and experience could also be incorporated with the total mould design. The approach provides a workable model of mould design system with CBR and knowledge-based expert system intelligent support, which could suggest good and proven design solutions to new design problems quickly, avoiding the time necessary to create those designs from scratch, for the plastic products manufacturing industry.     

Determining steelmaking aim chemistry utilizing an iterative and knowledge-based approach

Development of knowledge-based systems for material design is a complex task, due to the interelationship of many factors in the steelmaking process. In addition, design specifications vary frequently and materials design knowledge is held in a largely intuitive undefined format. This paper discusses the first stage of a material design system which deals with the determination of the steelmaking aim chemistry. If an attempt is made to design aim chemistry based on the mathematical approach of utilizing the empirical models between various design parameters it would result in an unrealistic design because relationships between various design parameters are not always linear. Therefore applying the knowledge-based approach along with the mathematical approach to deal with this complex task is inevitable. The approach put forward in this paper is a hybrid one, where the knowledge base is applied at every stage of the design process to utilize expert as well as heuristic knowledge of metallurgists to obtain designs which are realistic and which take account of the various limitations and constraints encountered in steelmaking. The material design is also characterized by extensive utilization of the grade history database which contains performance data for various steel grades and thickness combinations. The inputs to the system are through interactive dialogue sessions and the basic inputs consist of the material standards, size, quantity, tonnage, end use and customers' special requirements. These basic inputs along with the numerous rules in the knowledge bases as well as mathematical modelling enable the effective design of steelmaking aim chemistry.     

Use of expert systems in the design of thermal equipment and processes

A study has been carried out on the use of knowledge-based computer-aided design methodology for the design of thermal systems. An expert system is developed using a Prolog-based front end, where the design rules, material databases, computational procedures, and the relevant expert knowledge are implemented. A combination of quantitative and heuristic inputs are employed in the design process. The basic approach employs an iterative redesign strategy, starting with an initial design obtained from the available knowledge base, and the design parameters are iteratively varied until the specified design rules and constraints are satisfied. The general approach can be employed for a variety of thermal systems. The application to a practical system is demonstrated by the design of an electrical furnace used in the thermal processing of materials. The results from the numerical simulation and design of this system are presented to indicate the basic features and the versatility of the expert system.     

A cooperative approach to the structure elucidation problem

The development of a knowledge-based system for chemical structure elucidation is discussed. An object-centred knowledge representation language has been created that handles values, procedures and rules. This language has been used to construct infrared and mass spectroscopy knowledge sources. These form part of a blackboard problem-solving system that attempts to construct structural hypotheses based on the spectroscopic data supplied by the user and is directed by a flexible scheduling mechanism utilising explicit control knowledge. The design of a complete structure elucidation problem solver is proposed on the basis of the results of this feasibility study.     

基于模型设计方法的混合磁悬浮平台的控制设计及实现

基于模型的设计方法,利用Matlab/Simulink对磁悬浮系统进行浮点数字PID控制仿真,并结合定点控制器DSP2812,实现系统控制的快速构建,达到系统模型及控制设计、系统仿真和硬件实现的无缝集成,从而加速控制系统的快速开发.首先,在Matlab/Simulink环境中建立系统控制模型,并利用其自带的定点工具箱对数字控制器进行定点化处理,建立可以移植的带有数字平均滤波的Simulink代码模型.再通过RTDX功能进行算法的调试与验证,并进行代码模型的优化.最终自动生成可靠的C代码到控制器来实现对混合磁悬浮平台的控制,实现在模型仿真和系统实施的集成和统一.并由实物进行了验证．     

Impact of the NSF State/Industry/University Cooperative Research Center on low-cost,high-speed polymer composites processing on the research and educational programs at Michigan State University

The objectives of the National Science Foundation (NSF) State of Michigan/Industry/University Cooperative Research Center on low-cost, high-speed polymer composites processing at Michigan State University (MSU) are design, development and deployment of technology and knowledge-based systems that will reduce costs of polymer composites processing by (a) insuring faster processes, (b) reducing component costs, and (c) reducing implementation times of new composite designs. Significant accomplishments have been made in research, education and technology transfer in the areas of novel processing, liquid molding, thermoplastic processing, intelligent design and process modeling, and interphases and joining. The Center's primary educational activities were supported by the National Institute of Standards and Technology-Advanced Technology Program (NIST-ATP) with General Motors and General Electric, and the Technology Reinvestment Project (TRP) with the University of Delaware and the US Department of Defense.The Center's role in the four-year NIST-ATP was to disseminate injection-molded thermoplastics design methodologies to automotive, appliance, computer and other key US industries. The program enabled the Center to develop course material, a CD-ROM design manual, and workshop materials on state of the art thermoplastics design knowledge. To date, hundreds of individuals have participated in the workshops, and the material developed in this program is being integrated into undergraduate, graduate and continuing education offerings. The TRP program brought together the NSF Center at MSU and the composite materials center at the University of Delaware (UD) in a collaborative composite materials education and training effort for the Department of Defense and the durable goods industry. Educational developments included incorporation of knowledge derived from the TRP program into 49 new or existing engineering courses (23 at MSU and 26 at UD); six experiments for a new teaching laboratory; four workshops; four videotaped instructional modules (two each for liquid molding RTM technology and the injection molding technology); interactive WEB-based simulations and tutorials; and development of knowledge-based software.     

Hybrid neuro-fuzzy approach to the generation of measuring points for knowledge-based inspection planning

A knowledge-based inspection planning system is presented that can generate effective and consistent inspection plans automatically. The knowledge-based inspection planning system integrates part geometry information, tolerance information and heuristic knowledge of experienced inspection planners to determine the numbers and positions of measurement points. The system receives the tolerance information from users and stores it in the common database with 3D CAD geometry. A set of fuzzy rules and membership functions is automatically extracted from historic learning data using a hybrid neuro-fuzzy method. After the fuzzy rules are generated by the hybrid neuro-fuzzy model, a genetic algorithm is applied to optimize the weight parameters to find the best values for the constants. The proposed knowledge-based inspection planning system provides the stable and consistent inspection plan by removing the subjectivity of a human planner.