An IKBS implementation

This paper details the practical approaches and solutions taken in the implementation of an INTERLISP programmed knowledge based program. Although some of the solutions used are particular to the specific problem domain of this program, the general pragmatic methods are of wider interest. The program excerpts are given in Pseudo-LISP code.     

An approach to multicriterion optimization problems for engineering design

Optimization problems in mechanical engineering design are often modelled as nonlinear programming problems. A multicriterion optimization approach to this problem is developed in this work. The problem formulation is given, and the min-max principle for this problem is discussed. Next, an algorithm is provided for comparing solutions using this principle.The solution which is defined by the min-max principle of optimality may be called the best compromise considering all the criteria simultaneously and on equal terms of importance. This principle is fully formalized mathematically and used to obtain the optimal solution automatically. The algorithm for comparing solutions gives us, from any set of solutions, the one which is optimal in the min-max sense.Seeking the optimal solution in the min-max sense can be carried out in many different ways. Some methods based upon the Monte Carlo method and trade-off studies are proposed.The approach as discussed here is applied to the design of machine tool gearboxes. The problem is formulated as finding the basic constructional parameters (modules, numbers of teeth etc.) of a gearbox which minimizes simultaneously four objective functions: volume of elements, peripheral velocity between gears, width of gearbox and distance between axes of input and output shafts. A detailed example considering a lathe gearbox optimization problem is also presented. This example indicates that for some mechanical engineering optimization problems, using this approach, we can automatically obtain a solution which is optimal and acceptable to the designer.     

A novel engineering tool for creative design of fluid systems

Computational fluid dynamics is not often used early in the conceptual design stage of product development due to the lengthy computation times involved with solving complex computational fluid dynamics models. At this early stage, design options are being explored and significant changes are common, and therefore updated solutions must be found quickly to make these models effective. Because of this, computational fluid dynamics models are often reduced to analysis tools used later in the process and are used for refinement rather than for creative engineering design. This paper presents a novel method to create computational fluid dynamics models that can be used earlier in the engineering design process. The key aspects of analysis models used in the initial, creative phase of design are the ability to make changes and re-analyze the altered model quickly. Typically, computational fluid dynamics analysts choose to re-analyze the entire altered model to maintain the same level of accuracy. This can take a significant amount of time because the entire domain must be recalculated. Much of this time is devoted to fine-tuning the model, i.e., improving the accuracy of details of the domain that are sometimes non-essential to the bulk characteristics of the flowfield. However, in the early stage of the design process, decisions are often made based on the large-scale behavior of the fluid flow; fine details are often inconsequential. We have taken advantage of this premise to decrease the turnaround time required to re-analyze a computational fluid dynamics model using the Adaptive Modeling by Evolving Blocks Algorithm. The Adaptive Modeling by Evolving Blocks Algorithm is a genetic programming-based optimization program that segregates a flowfield and places minimal cost solvers in regions with simple flow dynamics while placing full-scale computational fluid dynamics solvers in the more complex regions to preserve accuracy. The program evolves the combined segregation scheme and solver placement until a reliably accurate, faster multi-solver model is found. Substantial reductions in solution times have been found in some cases. The results show an improvement in the speed of the multi-solver when compared with a single-model solution with no significant loss of accuracy.     

An aided tool for enterprise network design

1 IntroductionThe key technologies of AT-based expert system are shown as follows: the networkrequirement template, information quantification and distribution model, computer networkdesign model, network design knowledge representation and the construction of knowledgedatabase, network planning inferring mechanism, EN (Enterprise Network) performanceevaluation model, network simulation, and so on.Existing network design tools (NDT) may be divided into two basic types. One canaid to plot f…     

An object design framework for structural engineering

Object-oriented principles have introduced several useful concepts for developing complex software systems. As a result, several methodologies have been suggested for the overall design of software systems based on these concepts. Methodologies and frameworks for designing objects that are to be part of the software systems are currently lacking. This paper proposes anobject design framework andmethodology, which utilizes the object-oriented concepts, for planning, organizing and designing structural engineering design objects. Design objects in an integrated structural engineering system are complex and often related to each other in various different ways. The paper also identifies several important relationships among structural engineering design objects. These relationships serve as communication channels through wich design objects send messages to and receive responses from each other. Several examples, drawn from reinforced concrete structures, will be presented to demonstrate the object design methodology and to illustrate how the framework is effective in reducing the complexity of design objects in an integrated structural engineering system.     

Automatic differentiation as a tool in engineering design

Automatic Differentiation (AD) is a tool that systematically implements the chain rule of differentiation to obtain the derivatives of functions calculated by computer programs. In this paper, it is assessed as a tool for engineering design. The paper discusses the forward and reverse modes of AD, their computing requirements, as well as approaches to implementing AD. It continues with the application of two different tools to two medium-size structural analysis problems to generate sensitivity information typically necessary in an optimization or design situation. The paper concludes with the observation that AD is to be preferred to finite differencing in most cases, as long as sufficient computer storage is available; in some instances, AD may be the alternative to consider in lieu of analytical sensitivity analysis.     

TracED: A tool for capturing and tracing engineering design processes

The design of products or production processes in many engineering disciplines such as chemical, or software engineering, involves many creative and sometimes unstructured activities, with an opportunistic control flow. During these design processes, several models are generated, which have different levels of abstraction of the object being designed. Given the difficulties in dealing with this complexity using an improvised way, there is an urgent need for tools that support the capture and tracing of this process. In this proposal, TracED, a computational environment to support the capture and tracing of engineering design process is presented. It allows defining a particular engineering design domain and supporting the capture of how products under development are transformed along an engineering design process. Particularly, in this work, we consider software architectures design domain. As in any complex process, the support of computational tools is required for enabling its capture.     

A genetic tool for optimal design sequencing in complex engineering systems

Methods in multidisciplinary design optimization rely on computer tools to manage the large amounts of information involved. One such tool is DeMAID (DEsign Manager's Aide for Intelligent Decomposition), which incorporates planning and scheduling functions to analyse the effect of the information coupling between design tasks in complex systems on the efficiency of the design process. Scheduling involves the formation of circuits of interdependent design tasks, and the minimization of feedbacks within these circuits. Recently there has been interest in the incorporation of other considerations in the sequencing of tasks within circuits. This study presents the program Gendes (GENetic DEsign Sequencer), a sequencing tool based on a genetic algorithm. The program currently has the capability to minimize feedbacks as well as crossovers (intersections in the flow of design information which obscure straightforward evaluation), and allows the potential for other considerations in the sequencing function.This paper presents the development of this tool and the methods used. The results of computational studies to determine the most effective settings of the genetic algorithm for the task sequencing problem are presented, including population size, objective function weighting for the tradeoff between feedbacks and crossovers, mutation rate, and choice of selection operator and fitness function form. The incorporation of Gendes into the DeMAID scheduling function is explored, and the method is applied to two test systems to show its feasibility.     

An integrated component design approach to the development of a design information system for customer-oriented product design

In product design, the designer must draw upon many different types of information including both product-user requirements and design developments in related fields. As each designer has his/her own subjective opinion, an appropriate link between the user requirements and design features must be carefully developed to generate the most suitable design recommendation.The objective of this research is to develop a component design approach for the generation and evaluation of feasible design alternatives to help designers make the most effective design decisions. The development of the approach is based on the concept of component design and interaction links between user requirements and design output parameter values so that the design alternatives can be generated. A confidence interval for order statistics is then used to determine if enough unique feasible design alternatives have been generated. The research is presented in conjunction with a ballpoint pen design to demonstrate the feasibility and advantages of this approach.The results should provide designers with a useful method for the development of a design information system that will efficiently generate and evaluate a set of feasible design alternatives in product design process.     

An approach for reverse engineering of design patterns

For the maintenance of software systems, developers have to completely understand the existing system. The usage of design patterns leads to benefits for new and young developers by enabling them to reuse the knowledge of their experienced colleagues. Design patterns can support a faster and better understanding of software systems. There are different approaches for supporting pattern recognition in existing systems by tools. They are evaluated by the Information Retrieval criteria precision and recall. An automated search based on structures has a highly positive influence on the manual validation of the results by developers. This validation of graphical structures is the most intuitive technique. In this paper a new approach for automated pattern search based on minimal key structures is presented. It is able to detect all patterns described by the GOF [15]. This approach is based on positive and negative search criteria for structures and is prototypically implemented using Rational Rose and Together.     

An Intelligent Tool to Support Requirements Analysis and Conceptual Design of Database Design

As an application of artificial intelligence and expert system technology to database design,this paper presents an intelligent design tool NITDT,which comprises a requirements specification language NITSL,a knowledge representation language NITKL,and an inference engine with uncertainty reasoning capability.NITDT now covers the requirements analysis and conceptual design of database design.However,it is possible to be integrated with another database design tool,NITDBA,developed also at NIT to become an integrated design tool supporting the whole process of database design.     

An interactive fuzzy multi-objective optimization method for engineering design

The coupling of performance functions due to common design variables and uncertainties in an engineering design process will result in difficulties in optimization design problems, such as poor collaboration among design objectives and poor resolution of design conflicts. To handle these problems, a fuzzy interactive multi-objective optimization model is developed based on Pareto solutions, where the metric function and some additional constraints are added to ensure the collaboration among design objectives. The trade-off matrix at the Pareto solutions was developed, and the method for selecting weighting coefficients of optimization objectives is also provided. The proposed method can generate a Pareto optimal set with the maximum satisfaction degree and the minimum distance from ideal solution. The favorable optimal solution can be then selected from the Pareto optimal set by analyzing the trade-off matrix and collaborative sensitivity. Two examples are presented to illustrate the proposed method.     

An active set rqp algorithm for engineering design optimization

Optimum design of complex engineering systems needs a globally and superlinearly convergent (robust and efficient) algorithm using active set strategy. Such an algorithm based on extensions of Pshenichny's linearization method is derived in the paper. In the original method, a linearized subproblem with a quadratic step-size constraint is used to compute a direction of design change. No second-order information is computed or approximated for use in the direction finding problem. Therefore, the rate of convergence is only linear. In the paper, we propose to incorporate a variable metric W which is a positive-definite approximation to the Hessian of the Lagrange function. This gives local superlinear rate of convergence to the algorithm. Some other computational improvements are discussed and incorporated. The proposed improvements appear to be quite simple. They are, however, quite significant for applications to engineering design problems. This is explained and several small-scale problems are solved using a program based on the modified algorithm. Results are compared to Pshenichny's original algorithm. The modified algorithm is considerably more efficient compared to the previous algorithm. It also appears to be quite robust, though more extensive testing is needed on a wider range of problems.     

An efficient multiobjective differential evolution algorithm for engineering design

Solving engineering design and resources optimization via multiobjective evolutionary algorithms (MOEAs) has attracted much attention in the last few years. In this paper, an efficient multiobjective differential evolution algorithm is presented for engineering design. Our proposed approach adopts the orthogonal design method with quantization technique to generate the initial archive and evolutionary population. An archive (or secondary population) is employed to keep the nondominated solutions found and it is updated by a new relaxed form of Pareto dominance, called Pareto-adaptive ϵ-dominance (paϵ-dominance), at each generation. In addition, in order to guarantee to be the best performance produced, we propose a new hybrid selection mechanism to allow the archive solutions to take part in the generating process. To handle the constraints, a new constraint-handling method is employed, which does not need any parameters to be tuned for constraint handling. The proposed approach is tested on seven benchmark constrained problems to illustrate the capabilities of the algorithm in handling mathematically complex problems. Furthermore, four well-studied engineering design optimization problems are solved to illustrate the efficiency and applicability of the algorithm for multiobjective design optimization. Compared with Nondominated Sorting Genetic Algorithm II, one of the best MOEAs available at present, the results demonstrate that our approach is found to be statistically competitive. Moreover, the proposed approach is very efficient and is capable of yielding a wide spread of solutions with good coverage and convergence to true Pareto-optimal fronts.     

Case-based reasoning techniques to support reusability in a requirement engineering and system design tool

CASA (computer aided systems architecting) is a methodology and tool to support the design of complex technical systems. It combines approaches from systems and requirement engineering and AI. System design in CASA is requirement-driven, and works by a hierarchical stepwise top-down refinement of designs and a hierarchical decision-making process. One important task in CASA deals with the reusability of existing design artifacts and is supported by case-based reasoning techniques. Based on given structural specifications and formal requirements, a search procedure finds the best inexact match in a design base and computes an estimated degree of fulfillment for requirements. The approach employs efficient graph-matching and indexing schemes for case retrieval and structural similarities, and has adapted usual similarity measures to compute degree of fulfillment of requirements. It has been shown by different sample projects that the developed methods can be of great practical assistance to a designer.     

An improvement on the automatic tool for relational database design

This paper corrects some misconceptions regarding an automatic tool for relational database design. A modified algorithm (SYNTHESIZER+) from the synthesis algorithm SYNTHESIZER is presented. For a given set of FDs, it can produce a third normal form (3NF) relational database schema with a minimum number of relations.     

Systems for unified life-cycle mechanical engineering design: Shared-Tool architectures versus distributed tool architectures

A unified life-cycle engineering design (ULCED) system embodying conceptual design, detailed design, redesign, design for manufacturing, and design maintainability forms the basis of a new computer-based design discipline for improving the overall quality of manufactured goods. The objective of such a system is to review, evaluate, and analyze the entire life cycle of a product and to incorporate, in an integrated fashion, life-cycle knowledge within the design process. Individual CAD/CAM/CAE software, developed under various programming environments and operating systems, and on various types of computer hardware, have met with only limited success in achieving total computational integration. At the initial stages of development of such a system exploration of both technologically and economically feasible architectures is of critical importance.Two ULCED system architectures, broadly classified as shared-tool and distributed-tool, are described and compared on the basis of current computer hardware, available commercial software and data bases, and existing computer programming environments. Important evaluation issues to be considered include implementation costs and complexity and the feasibility of system creation.