Structural topology design optimization using Genetic Algorithms with a bit-array representation

In this paper, a bit-array representation method for structural topology optimization using the Genetic Algorithm (GA) is implemented. The importance of structural connectivity in a design is further emphasized by considering the total number of connected objects of each individual explicitly in an equality constraint function. To evaluate the constrained objective function, Deb’s constraint handling approach is further developed to ensure that feasible individuals are always better than infeasible ones in the population to improve the efficiency of the GA. A violation penalty method is proposed to drive the GA search towards the topologies with higher structural performance, less unusable material and fewer separate objects in the design domain. An identical initialization method is also proposed to improve the GA performance in dealing with problems with long narrow design domains. Numerical results of structural topology optimization problems of minimum weight and minimum compliance designs show the success of this bit-array representation method and suggest that the GA performance can be significantly improved by handling the design connectivity properly.     

A framework to integrate design knowledge reuse and requirements management in engineering design

This paper presents a framework to integrate requirements management and design knowledge reuse. The research approach begins with a literature review in design reuse and requirements management to identify appropriate methods within each domain. A framework is proposed based on the identified requirements. The framework is then demonstrated using a case study example: vacuum pump design. Requirements are presented as a component of the integrated design knowledge framework. The proposed framework enables the application of requirements management as a dynamic process, including capture, analysis and recording of requirements. It takes account of the evolving requirements and the dynamic nature of the interaction between requirements and product structure through the various stages of product development.     

Platform-based product design and development: A knowledge-intensive support approach

This paper presents a knowledge-intensive support paradigm for platform-based product family design and development. The fundamental issues underlying the product family design and development, including product platform and product family modeling, product family generation and evolution, and product family evaluation for customization, are discussed. A module-based integrated design scheme is proposed with knowledge support for product family architecture modeling, product platform establishment, product family generation, and product variant assessment. A systematic methodology and the relevant technologies are investigated and developed for knowledge supported product family design process. The developed information and knowledge-modeling framework and prototype system can be used for platform product design knowledge capture, representation and management and offer on-line support for designers in the design process. The issues and requirements related to developing a knowledge-intensive support system for modular platform-based product family design are also addressed.     

Feature-based design and material blending for free-form heterogeneous object modeling

In this paper, a new feature-based method is proposed to represent and design heterogeneous objects. Material governing features are defined to control material composition inside the objects. Interrelations between the material governing features and material attributes are established in the design process and retained in the object model. Free-form B-spline functions are used to represent complex shapes of geometry and material features. A new material feature blending method is used to determine continuous material variation. To obtain the best material features, an optimization problem is constructed based on the object's functional requirements. Variant models are easily generated by changing the geometric and material features using the constraints between them. Implementation and examples are also presented in this paper.     

Automated functional design of engineering systems

This paper presents a prototype intelligent system, the knowledge-based functional design automation system (KBFDA) for automating the functional design process of engineering products/systems. An integrated knowledge representation scheme combines rule-based and object-oriented representation methods to represent functions and function related design characteristics in an intelligent design environment. A knowledge-based functional reasoning strategy uses this representation to automatically generate physical behaviors from desired functions or behaviors. The required behaviors are then combined in different configurations to develop a set of potential concept variants that meet the functional requirements and functional constraints given in a design specification. Finally, the variants are ranked according to the degree to which they meet non-functional constraints. The variant with the lowest rank (score) is selected as the best solution. A case study design of a terminal insertion unit is presented to demonstrate the practicality of the proposed approach.     

Version management needs for structural engineering design

As design objects are created during the design process, it is not sufficient to represent only a single current state of each object. Instead, it will usually be necessary to represent a number of past and current states, existing parallel to each other at various design stages. This requirement has led to the development of various schemes to help manage and control multiple occurrences of a design object.In this paper versions of structural engineering design objects are defined and a scheme for organizing these versions is proposed. A design for a version manager in an object-based design system is then presented. The manager has limited capabilities but can be used as a step toward defining a more complete version management and control system.     

Information management for integrated design environments

This paper identifies requirements for an engineering design information management system. Future CAD systems must support a wide range of activities — such as definition, manipulation and analyses of complex product information models. These models represent not only conventional data associated with current CAD applications, but also design information characterizing the correlations between the requirements, functions, behaviors and physical form of the product. Such functionality is important for both the individual designer and the design organization, as the need to manage information as a corporate asset is becoming a critical component of business strategy. This paper explores these needs using two design studies. The first study illustrates some major concepts relative to non-routine design activities, while the second study focuses on the routine design activities relative to organization interactions. These studies were used to elicit high level requirements which serve as the basis for the development of prototype software systems. These prototypes are briefly introduced here.     

A feature-based approach towards an integrated product model including conceptual design information

Due to the highly complex and informal data that has to be managed in the conceptual design this early design phase still lacks of suitable computer support. Furthermore, existing approaches towards a computer aided conceptual design are insufficiently integrated with the downstream applications of the product development process. The paper therefore introduces an approach towards a feature-based integrated product model that incorporates a feature-based representation scheme for capturing product semantics handled in the conceptual design phase and links early design with part and assembly modelling.     

Extended object model for product configuration design

This paper presents an extended object model for case-based reasoning (CBR) in product configuration design. In the extended object model, a few methods of knowledge expression are adopted, such as constraints, rules, objects, etc. On the basis of extended object model, case representation model for CBR is applied to product configuration design system. The product configuration knowledge can be represented by the extended object. The model can support all the processes of CBR in product configuration design, such as case representation, indexing, retrieving, and case revising. The presented model is an extension of the traditional object-oriented model by including the relationship class used to express the relation between the cases, constraints class used in the product configuration knowledge representation, index class used in case retrieving, and solution class used in case revising. Therefore, the product configuration knowledge used in the product configuration design can be represented by using this model. In the end, a metering pump product configuration design system is developed on the basis of the proposed product configuration model to support customized products.     

An Object-Logic model for the representation and processing of design standards

There are two distinct categories of knowledge in a design standard: (1) knowledge of the organization of design objects and (2) knowledge of the methods used in reasoning about the design objects. The object-oriented paradigm lends itself naturally to representing the organizational aspect of the design standard. The logic programming paradigm, on the other hand, is well suited to implementing the reasoning mechanisms for design and conformance checking. The object-oriented and logic programming paradigms are combined to provide a unified Object-Logic model for the representation of design codes and the processing of design standards. By storing the design provisions in a knowledge base, the model is capable of performing conformance checking and component design. To evaluate the feasibility and practicality of this model, a prototype system, HyperLRFD++, has been implemented for parts of the American Institute of Steel Construction (AISC) Load and Resistance Factor Design (LRFD) specification and tested on sample problems.     

Assessing the impact of geometric design intent annotations on parametric model alteration activities

The effective representation and communication of design intent plays a crucial role in CAD model alteration activities. In history-based parametric modeling systems, design intent information is usually expressed implicitly within the model. However, there is evidence that suggests that an explicit representation can increase productivity and quality and facilitate the transferring of design knowledge throughout the different stages of the product lifecycle. In this paper, we assess the effectiveness of 3D annotations as mechanisms for explicit design intent representation and examine their impact in model alteration processes that require a direct interaction with the model's geometry. We present the results of a series of studies aimed at measuring user performance and model quality in two scenarios. First, we hypothesized that annotations are valuable tools to provide design information when inadequate modeling assumptions can be made by designers. Second, we evaluated annotations as tools to communicate design decisions when multiple options are available. In both cases, results show statistically significant benefits of annotated models, suggesting the use of this technique as a valuable approach to improve design intent communication.     

A proposed ontology to support the hardware design of building inspection robot systems

Due to the growing number of architecturally complex buildings built in recent decades, mobile building inspection robot systems are required to operate in increasingly complex environments. This leads to higher requirements for their hardware design. The existing literature on the design of building inspection robots has implicitly mentioned the impact of building environments and building defects on defining robot hardware design requirements. However, the explicit representation of what information is required to define a specific hardware requirement is stimissing. To fill this gap, this paper presents an ontology that provides an overview of the building and inspection domain objects that affect the determination of robot hardware design requirements (RoboDesign). It also explores the relationship between specific robot hardware requirements and features of complex buildings and their defects. The RoboDesign ontology integrates two main domain ontology models including a Robot System Model and a Building and Defect Model. A content evaluation and an automated consistency checking are conducted for the internal evaluation of the ontology. Additionally, the proposed ontology is implemented in two wall-climbing inspection robot design cases to check if the investigation of the robot’s application environment is comprehensive. The validation results also demonstrate that the use of the proposed ontological model allows to efficiently retrieve information required to determine a particular hardware requirement.     

An integrated decision-making method for product design scheme evaluation based on cloud model and EEG data

Selecting the optimal design scheme is a vital task in the product design area. It not only improves the performance of the product, but also leads to the greatest satisfaction of customers. However, existing methods express qualitative evaluation information roughly, and none of them has taken the implicit psychological states of customers into consideration. Therefore, an integrated decision-making method for product design scheme evaluation is proposed. This method applies the cloud model to facilitate the evaluation process of experts and uses the EEG data to reveal the psychological states of customers. Benefit from the probability theory and fuzzy set theory, the cloud model deals with the fuzziness and randomness simultaneously. It can decrease the cognitive discrepancy of experts and allow the information distortion to be neutralized to a great extent. Since the experts are not the final users of products, the evaluation results from experts cannot truly reflect the psychological states of customers when they use the product. An experiment is designed to collect the EEG data which can reveal the implicit psychological states of customers. The recorded data are segmented based on the operation process and tagged with the self-reported psychological states. Subsequently, the wavelet packet decomposition is applied and the sample entropy of each EEG frequency band is extracted as the feature. Taking advantage of the random forest classifier, the psychological states of customers can be classified with the average accuracy of 90.76%. This study can lead to a practical system for automatic assessment of psychological states in future applications. The evaluation process of elevator design schemes is conducted as a case study to illustrate the feasibility of the proposed method.     

Causal design knowledge: Alternative representation method for product development knowledge management

This paper presents a mathematical comparison of procedural knowledge and causal knowledge, and discusses the potential roles and feasibility of causal knowledge across product development knowledge management. Since reuse of knowledge is so important in product development, various knowledge management approaches have been introduced. Most of the product design knowledge is represented by procedural knowledge, which unfortunately requires cumbersome processes to define, and is typically inadequate for representing the kind of knowledge generated during the product development process. A causal knowledge representation, however, can help us to overcome this limitation and is an alternative formalism for representing product design knowledge. In this paper we compare the procedural and causal knowledge representations. We present the mathematical definitions of two knowledge paradigms, then mathematically describe the relationship between the two. Both knowledge paradigms are then compared based on the perspective of knowledge expression, decision alternative representation, reasoning capability, and knowledge cultivation. This paper concludes that causal knowledge representation is superior to procedural knowledge representation based on the four perspectives. Finally, the knowledge systems are modeled using Systems Modeling Language (SysML), and we present a case study that demonstrates the causal knowledge features using a realistic example from industry.