Conceptual Design Problem Research Articles

A cross-disciplinary technology transfer for search-based evolutionary computing: from engineering design to software engineering design

Although object-oriented conceptual software design is difficult to learn and perform, computational tool support for the conceptual software designer is limited. In conceptual engineering design, however, computational tools exploiting interactive evolutionary computation (EC) have shown significant utility. This article investigates the cross-disciplinary technology transfer of search-based EC from engineering design to software engineering design in an attempt to provide support for the conceptual software designer. Firstly, genetic operators inspired by genetic algorithms (GAs) and evolutionary programming are evaluated for their effectiveness against a conceptual software design representation using structural cohesion as an objective fitness function. Building on this evaluation, a multi-objective GA inspired by a non-dominated Pareto sorting approach is investigated for an industrial-scale conceptual design problem. Results obtained reveal a mass of interesting and useful conceptual software design solution variants of equivalent optimality—a typical characteristic of successful multi-objective evolutionary search techniques employed in conceptual engineering design. The mass of software design solution variants produced suggests that transferring search-based technology across disciplines has significant potential to provide computationally intelligent tool support for the conceptual software designer.

Extended Collaboration Pursuing Method for Solver Larger Multidisciplinary Design Optimization Problems

The collaboration pursuing method is a sampling-based multidisciplinary design optimization method, which does not rely on sensitivity analysis. It was found that the collaboration pursuing method is constrained by the effectiveness of sampling in a design space when solving larger multidisciplinary design optimization problems. Three new modules, that is, discrete sampling, new initialization process, and active design variable control, are developed in this work to extend the collaboration pursuing method's capability in dealing with larger multidisciplinary design optimization problems. Using the collaboration pursuing method with the new modules, called extended collaboration pursuing method, a conceptual aircraft design problem involving structures, aerodynamics, and propulsion is successfully solved. The extended collaboration pursuing method is a promising new multidisciplinary design optimization method to solve larger multidisciplinary design optimization problems with better accuracy and comparable efficiency, when compared with other multidisciplinary design optimization methods.

Axiomatic Based Decomposition for Conceptual Product Design

This paper describes a structured methodology for decomposing the conceptual design problem in order to facilitate the design process and result in improved conceptual designs that better satisfy the original customer requirements. The axiomatic decomposition for conceptual design method combines Alexander's network partitioning formulation of the design problem with Suh's Independence Axiom. The axiomatic decomposition method uses a cross‐domain approach in a House of Quality context to estimate the interactions among the functional requirements that are derived from a qualitative assessment of customer requirements. These interactions are used in several objective functions that serve as criteria for decomposing the design network. A new network partitioning algorithm is effective in creating partitions that maximize the within‐partition interactions and minimize the between‐partition interactions with appropriate weightings. The viability, usability, and value of the axiomatic decomposition method were examined through analytic comparisons and qualitative assessments of its application. The new method was examined using students in engineering design capstone courses and it was found to be useable and did produce better product designs that met the customer requirements. The student‐based assessment revealed that the process would be more effective with individuals having design experience. In a subsequent assessment with practicing industrial designers, it was found that the new method did facilitate the development of better designs. An important observation was the need for limits on partition size (maximum of four functional requirements.) Another issue identified for future research was the need for a means to identify the appropriate starting partition for initiating the design.

A study on the grammatical construction of function structures

Function structures are used during conceptual engineering design to transform the customer requirements into specific functional tasks. Although they are usually constructed from a well-understood black-box description of an artifact, there is no clear approach or formal set of rules that guide the creation of function structures. To remedy the unclear formation of such structures and to provide the potential for automated reasoning of such structures, a graph grammar is developed and implemented. The grammar can be used by a designer to explore various solutions to a conceptual design problem. Furthermore, the grammar aids in disseminating engineering functional information and in teaching the function structure concept to untrained engineers. Thirty products are examined as a basis for developing the grammar rules, and the rules are implemented in an interactive user environment. Experiments with student engineers and with the automated creation of function structures validate the effectiveness of the grammar rules.

Formal Verification of the NASA Runway Safety Monitor

The Runway Safety Monitor (RSM) designed by Lockheed Martin is part of NASA's effort to reduce aviation accidents. We developed a Petri net model of the RSM protocol and used the model checking functions of our tool SMART to investigate behaviors that can be classified as missed alarm scenarios in RSM. To apply discrete-state techniques and mitigate the impact of the resulting state-space explosion phenomenon, our model uses a highly discretized view of the system obtained by partitioning the monitored runway zone into a grid of smaller volumes and by considering scenarios involving only two aircraft. The model also assumes that there are no communication failures, such as bad input from radar or lack of incoming data, thus it relies on a consistent view of reality by all participants. In spite of these simplifications, we were able to expose potential problems in the RSM conceptual design. Our findings were forwarded to the design engineers, who undertook corrective action. The results stress the high level of efficiency attained by the new model checking algorithms implemented in our tool SMART, and demonstrate their applicability to real-world systems. Attempts to verify RSM with NuSMV and SPIN have failed due to excessive memory consumption.

Peer tutoring in conceptual design

A peer tutoring scheme has been introduced into the Department of Engineering at the University of Liverpool to help 2nd year undergraduate students tackle conceptual design problems. Conceptual design is an iterative process consisting of a series of generative and evaluative stages, which gradually converge on a preferred conceptual solution. Students are generally less comfortable with the task of generating, evaluating and presenting ideas and this leaves them less able to tackle a conceptual design project without the help and intervention of available teachers or experts. Formally, the students were taught through lectures, coursework and critique sessions. Peer tutors were trained to facilitate group sessions whereby the students were able to discuss ideas, evaluate new concepts, generate solutions and learn to communicate more effectively within a non-threatening environment. The students developed problem-solving skills, became more confident and took more responsibility for their own learning. The peer tutoring process also had a positive effect on the tutors, who felt they had become more responsible and employable, improved their communication and leadership skills and deepened their own understanding of design, as a result of the peer tutoring experience.

A genetics-based approach for the principle conceptual design of mechanical products

This paper presents a genetics-based approach for solving conceptual design problems in dealing with functional relation changes. A functional representation model based on verb-attributes is proposed to supply computers with sufficient functional information needed in principle conceptual design. Using bio-genetics as a blueprint, a concept of product gene is proposed, which is employed to index principle solutions (PSs), and therefore bridges the gap between relation change-based functions (RCFs) and their corresponding PSs. A knowledge base is built by extracting product genes from existing PSs by means of reverse transcription and translation. An illustrative design example has been provided to show the capability and effectiveness of the developed, genetics-based principle conceptual design platform (GPCDP).

Rediscovering the analysis of interconnected decision areas

The method known as the analysis of interconnected decision areas (AIDA) has been in use for nearly 40 years, but has made little headway into engineering design. This paper describes an implementation of AIDA that is useful to engineering designers wishing to combine the solution principles of various subfunctions within a product in new ways. Traditionally, the method is used to understand how one decision affects the options available to other decisions in a large-scale project. The method is to be used interactively with designers participating in a brainstorming session so that ideas are added to AIDA and immediately combined with other compatible ideas. The existing implementation has been tested in a classroom setting in which upper level undergraduates have successfully used the AIDA method along with numerous of design methods to solve conceptual design problems.

Guest Editorial

Guest Editorial

The establishment and reasoning of knowledge base system for mechanism kinematic schemes

As one of the key problems of computer-aided conceptual design (CACD) for mechanism kinematic schemes, the effective establishment and management of knowledge base systems of kinematic behaviours and mechanisms is still troubled by information redundancy and unreasonable structure at present. Retrieval efficiency and solving intelligence of knowledge base reasoning systems on the basis of the knowledge classification method mentioned above have many unsatisfactory factors. So in this paper, firstly, data standardization technology and combined classification methods have been applied to carry out the classification of kinematic behaviours and mechanisms in the mapping field between the kinematic behaviour level and the mechanism level of conceptual design. Also, the principle of computer coding and storing have been built to give a fast and broad selection of mechanisms that meets the requirements of basic motion characters. Then on the basis of what was mentioned above, the heuristic matching propagation principle (HMPP) of kinematic behaviours and its truth table serve as a guide to perform mechanism type selections. The knowledge base automatic reasoning system of mechanism kinematic schemes based on HMPP is developed. By means of depth first search strategy, the motion requirements are matched against objects in the knowledge base along the orientation of function unit-mechanism ID→function unit ID→kinematic behaviour ID(output/input)→motion type coding/ continuity coding/linearity coding/directionality coding at four different levels of abstraction. Top-down design process in this paper conforms to the law of innovative thinking for designers. If a direct match in a higher level was not discovered, then the design course will be transformed into the match at a low level automatically. According to the truth table of HMPP, once non-zero elements in kinematic behaviour ID (“1” or “2”) appear in the matching process, they will propagate until the solving process is over, and become one of the coding of the feasible solutions. The heuristic nature of HMPP presents a top-down solving method to decompose the complex requirements into several simpler ones. Different from traditional solving methods, the method presented in our research work has two advantages. Firstly it is easier to be operated and realized with a computer. Secondly, it is a creative process by nature. Finally, an application is given to indicate its practicability and effectiveness.

I-Promise—intelligent protective material selection

Abstract The paper describes I-Promise, an expert system for configuration design of complex protective materials. Configuration problem of I-Promise is a part of conceptual design of complex protective materials; hence, the context of conceptual design and configuration problems is briefly described before the detailed description of I-Promise, its problem domain, its design, and its application. Due to the complexity and sequential nature of its task, I-Promise is designed as a series of three specialized expert systems. I-Promise is a real-world system, built on top of the information system of an enterprise that produces and delivers complex protective materials.

Computerized rules-based regeneration method for conceptual design of mechanisms

This paper presents a rules-based computerized symbolic carrier regeneration method for mechanical system conceptual design. In this method, design requirements of mechanical systems are expressed by regeneration rules which are composed mainly of symbols and logical codes; non-isomorphic graphs are chosen to be graphic carriers for symbolic carrier regeneration process; in each regeneration step, similarity identification needs to be done on symbolic carrier elements-links, so as to prevent redundant schemes. General design requirements can be expressed by simple Boolean calculation (AND, OR), relation calculation (adjacent, overlapping, topological relationship) and functional elements (concepts). Based on computer and object oriented encapsulation technology, the method can solve general conceptual design problems of mechanical systems. Designers need not know much about specialized knowledge and can fulfill design process of mechanical products.

A Rational Compromise in the System Problem of Disclosure of Conceptual Uncertainty

A general approach and methods are proposed for matched system solution of the following sequence of interconnected problems: the construction of a set of objective functions from empirical data under conceptually uncertain conditions, the determination of a Pareto set under the condition of a rational mutual matching of the set of values and the domain of objective functions, and a multicriterion choice of a rational solution on a Pareto set under the condition of a compromise between inconsistent objectives. As a result, new possibilities are opened up for finding rational compromises in multicriterion problems of conceptual design, situation prediction, and innovation planning.

Conceptual design and flight simulation of space stations

This paper focuses on the conceptual design and flight simulation of space stations. Its goal is to discern the factors which influence the configurational design of a space station system. This is done in order to define an adequate methodology with an adapted set of computer tools for early conceptual design of space stations. First we review the history of space station design in order to show what factors drove conceptual space station designs in the past. After that, a methodological design approach for space stations is introduced with special emphasis on design rules applicable to the development of the configuration of a space station. Finally, the design example of a minimum space station with growth potential demonstrates the way in which methods and tools established in this study can be applied to a conceptual design problem.

Pareto‐Optimal Conceptual Design of the Structural Layout of Buildings Using a Multicriteria Genetic Algorithm

This article presents a computational procedure for multicriteria optimal conceptual design of the structural layout of buildings subject to given specifications and requirements. Two objective criteria are considered for evaluating alternative designs. The first objective concerns minimizing the building project cost through minimization of a function defining the combined costs of the building structural system and the land for the building site. The second objective concerns optimizing the flexibility of floor space usage, which is a qualitative criterion that is given a quantitative form through minimization of an exponential function that relates tributary load area to the spacing of columns. A multicriteria genetic algorithm (MGA) is applied to solve the biobjective conceptual building layout design problem using Pareto optimization theory . The MGA process is shown to be similar to that of the simple genetic algorithm, except that the fitness evaluation of candidate designs is based on a distance metric related to the Pareto‐optimal set. A variable‐mutation technique is introduced to maintain genetic diversity and to accelerate the stochastic search for the global optimum. An example conceptual building layout design is presented using the MGA, and the applicability and efficiency of the developed computational conceptual design procedure are discussed.

Application of a cascade BAM neural expert system to conceptual design for facility layout

The major contribution of this novel application is the pilot development and feasibility study for a bank of cascade BAM (Bidirectional Associative Memories) neural networks. This improved BAM structure functions as an expert system for conceptual facility layout or for preliminary construction layout design. This application, rather than being a better analytical algorithm or a better production expert system, builds a neural expert system with the capability of incrementally learning layout design examples for a given set of constraints. The cascade BAM incremental learning methodology, which distinguishes this system from the more frequently used Backpropagation Network (BPN) learning system, creates effective multibidirectional generalization behavior from qualitative, goal-driven layout design experience. The initial tests of learnability are presented by its applicability to conceptual layout design problems, and their solutions are assessed and compared with the learning ability of a standard BAM. Issues deserving further investigation are addressed as well.

Multidisciplinary Conceptual Design Optimization of Space Transportation Systems

This paper presents a recent history of progress both in disciplinary modeling and in optimization methods and frameworks for space transportation systems conceptual design and analysis. The disciplinary models and process typically used for space transportation analyses are identified, including physicsbased and empirical models. The diverse characteristics of these disciplinary models require equally diverse integration and optimization approaches to enable implementation of automated, multidisciplinary design systems. Two general approaches are described for integrating these disciplinary models into computational frameworks for automated vehicle synthesis and optimization. Several optimization approaches are discussed including parameter, gradient-based, stochastic, and collaborative methods. Representative examples are given of multidisciplinary applications of optimization methods to the launch vehicle conceptual design problem. A primary goal for the future is to enable a space transportation design-to-cost capability.

Hydraulic Circuit Synthesis based on Functional Structure. 1st Report. Adaptive Synthesis Method from Design Cases.

An adaptive synthesis method for hydraulic circuits is proposed using a case-based reasoning technique based on their functional structure. Since synthesis of hydraulic circuits is a typical problem of conceptual design and is expertise-oriented and combinatorial, it is difficult to declaratively represent useful design knowledge. In our design method, past design cases are stored in the case base, and then a circuit is generated by arranging suitable past cases which are retrieved from the case base in accordance with the required functional structure. In order to measure such functional structure, design specifications are represented by labels. Design cases are adaptively manipulated into a target design using three synthesis strategies, decomposition, series combination and parallel combination, based on surplus or deficit of labels. This synthesis method is applied to some design problems in order to show its effectiveness and validity. Moreover, it is integrated with a logical simulation method based on symbol manipulation, which will be presented in the second report, in order to verify arranged circuits.

Agent-based approach to a design support system for the synthesis of continuous chemical processes

A successful, computer-aided design support system can help a process designer focus on making effective design decisions, not merely tedious routine calculations. Such a system is essential to enhance quality of design in terms of economics, environmental benignity, reliability, robustness, and operability. Such a statement is even more accepted when applied to conceptual design problems, where gross design specifications are given while a combinatorial number of design alternatives exists. This paper presents an agent-based approach as a systematic and efficient way to design a computer-aided support system for the synthesis of continuous, single-product chemical processes. An agent-based approach allows us to handle design knowledge as an object and thus greatly improve the modularity and reusability of that knowledge. Such modularity leads to increased ease in the relaxation of design decisions and the generation of design alternatives, both of which functions are critically important in dealing with the complexity and uncertainty of conceptual design problems. Such reusability leads to the increased productivity in the development of a design support system.

Machine Learning of Design Rules: Methodology and Case Study

This paper describes a methodology for applying machine learning to problems of conceptual design, and presents a case study of learning design rules for wind bracings in tall buildings. Design rules are generated by induction from examples of minimum weight designs. This study investigates the applicability of machine learning methods that are capable of constructive induction, that is of automatically searching for and generating problem‐relevant attributes beyond those originally provided. The decision rules generated by machine learning programs specify design configurations that are recommended, typical, infeasible, or those that are to be avoided. The learned rules captured some of the essential expert's understanding of the design characteristics involved in selecting wind bracings for tall buildings. These results are promising and demonstrate a potential practical usefulness of the proposed methodology for automated generating of design rules.