A generalized approach to fast interpretation of objects and their features has so far eluded researchers. In manufacturing, this interpretation can be approached from the vision point of view or from the CAD data perspective. Presently, CAD systems are widely used in several aspects of manufacturing production. It is therefore more efficient to use CAD data for object reasoning in manufacturing, especially when systems will eventually be data driven. Components can be modelled on a CAD system using various modelling techniques and the representation of their geometric information is still CAD system dependent. However, the advent of the Initial Graphics Exchange Specification (IGES) now makes it possible to represent CAD data in a neutral and standard manner.

This paper describes a scheme for recognizing and representing features for CAD data extracted using the IGES interface. The concepts developed are based on graph-based feature representation, where features are represented by a set of faces as well as their topological adjacency.

Strategies for classifying features and methods of decomposing a complicated feature into several simpler features for recognition purposes are discussed.

This paper presents a conceptual and computational framework to support experts in the design and manufacturing of high quality products. The framework is based on the development of specific knowledge artifacts characterized by tools for the management of functional, procedural, and experiential knowledge. As a case study, the GUITAR HERO project is presented. The project aims at building a knowledge-based system to support experts of a handicraft enterprise involved in the design and manufacturing of electric guitars characterized by an aluminum body. The domain of the project is extremely innovative, because electric guitars are typically manufactured with different kinds of wood rather than metals or other materials. To this aim, an ontological representation of the electric guitar has been implemented exploiting NavEditOW, a computational framework for the codification, navigation, and querying of ontologies over the Internet, based on the OWL language.

Achieving the dimensional integrity for a complex structural assembly is a demanding task due to the manufacturing variations of parts and the tolerance relationship between them. Although assigning tight tolerances to all parts would solve the problem, an economical solution is taking advantage of small motions that joints allow, such that critical dimensions are adjusted during assembly processes. This paper presents a systematic method that decomposes product geometry at an early stage of design, selects joint types, and generates subassembly partitioning to achieve the adjustment of the critical dimensions during assembly processes. A genetic algorithm generates candidate assemblies based on a joint library specific for an application domain. Each candidate assembly is evaluated by an internal optimization routine that computes the subassembly partitioning for optimal in-process adjustability, by finding a series of minimum cuts on weighted graphs. A case study on a three-dimensional automotive space frame with the accompanying joint library is presented.

The surface roughness of the machined parts is one of the most important factors that have considerable influence on the quality and functional properties of products. The objective of this study is development of a surface roughness prediction model for machining Inconel 718 in high-pressure jet assisted turning using the fuzzy expert system, where the fuzzy system is optimized using two bioinspired algorithms: genetic algorithm and particle swarm optimization. The effect of various influential machining parameters, such as diameter of the nozzle, pressure of the jet, cutting speed, feed rate, and distance between the impact point of the jet and cutting edge were taken into consideration in this study. The predicted surface roughness values obtained from developed fuzzy expert systems were compared with the experimental data, and the results indicate that proposed systems can be effectively used to estimate the surface roughness in high-pressure jet assisted turning.

In designing a state space of possible designs is implied by the representation used and the computational processes that operate on that representation. GAs are a means of effectively searching that state space which is defined by the length of the genotype's bit string. Of particular interest in design computing are processes that enlarge that state space to change the set of possible designs. This paper presents one such process based on the generalization of the genetic crossover operation. A crossover operation of genetic algorithms is reinterpreted as a random sampling of interpolating phenotypes, produced by a particular case of phenotypic interpolation. Its generalization is constructed by using a more general version of interpolation and/or by adding extrapolation to interpolation. This generalized crossover has a potential to move the current population outside of the original state space. An adaptive strategy for state space enlargement, which is based on this generalization, is designed. This strategy can be used for computational support of creative designing. An example is given.

Prior research has identified set-based design as a method that accounts for the high level of uncertainty that is associated with the design of innovative products or systems. Rather than precisely specifying a system architecture in the early design stages, set-based design builds on designing a system and its architecture in an evolutionary way. The literature on set-based design has studied how a system's design evolves by moving from a number of optional design ideas to the final system through gradually eliminating unfeasible design ideas and continually developing design ideas for which engineers increasingly establish feasibility. However, little is known about how firms set up the design process and the organization to successfully create new products with set-based design. Our research contributes to closing this gap. First, we study how firms determine the number (i.e., portfolio) of design ideas to pursue, an important step of the early design process. Second, we study how firms organize for set-based design by assigning teams to develop design ideas and eventually design a system's architecture. Our research uses an exploratory case study approach, investigating five cases in three different firms. First, we find that the early design process is characterized by the absence of formal idea evaluation and selection. Instead, firms start to pursue all initially created design ideas, evaluating and selecting them in an evolutionary manner as the design project progresses. Second, we identify two organizational approaches associated with set-based design: assign one team to pursue all ideas or assign one team per design idea.

It is now becoming increasingly common for products to be designed via an interdisciplinary approach, particularly when an engineering enterprise adopts the concurrent engineering approach. Essentially, this implies that several heterogeneous sources of knowledge are simultaneously involved during the design phase of the product. The benefits often cited as a result of such an approach are increased quality and innovation, decreased time-to-market, and lower manufacturing costs. However, the approach also accentuates the problem of how to handle and manage conflicts, which frequently arise due to several factors as discussed in this paper. This paper also describes a system called Schemebuilder, which is an integrated design workbench aimed at supporting the conceptual and embodiment phases of interdisciplinary systems design, and its mechanisms for handling and resolving conflicts.

This paper presents a framework for teaching design engineering in a global context using innovative technologies to enable distributed teams to work together effectively across international and cultural boundaries. The Digital Libraries for Global Distributed Innovative Design, Education, and Teamwork (DIDET) Framework represents the findings of a 5-year project conducted by the University of Strathclyde, Stanford University, and Olin College that enhanced student learning opportunities by enabling them to partake in global, team-based design engineering projects, directly experiencing different cultural contexts and accessing a variety of digital information sources via a range of innovative technology. The use of innovative technology enabled the formalization of design knowledge within international student teams as did the methods that were developed for students to store, share, and reuse information. Coaching methods were used by teaching staff to support distributed teams and evaluation work on relevant classes was carried out regularly to allow ongoing improvement of learning and teaching and show improvements in student learning. Major findings of the 5-year project include the requirement to overcome technological, pedagogical, and cultural issues for successful eLearning implementations. The DIDET Framework encapsulates all the conclusions relating to design engineering in a global context. Each of the principles for effective distributed design learning is shown along with relevant findings and suggested metrics. The findings detailed in the paper were reached through a series of interventions in design engineering education at the collaborating institutions. Evaluation was carried out on an ongoing basis and fed back into project development, both on the pedagogical and the technological approaches.

This paper evaluates an evolution strategy to tune conventional proportional plus integral plus derivative (PID) and gain scheduling PID control algorithms. The approach deals with the utilization of an evolution strategy with learning acceleration by derandomized mutative step-size control using accumulated information. This technique is useful to obtain the following characteristics: (1) freedom of choice of a performance index, (2) increase of the convergence speed of evolution strategies to get a local minimum to determine controller design parameters, and (3) flexibility and robustness in the automatic design of controllers. Performance analysis and experimental results are carried out using a laboratory scale nonlinear process fan and plate. The practical prototype contains features such as nonminimum phase, dead time, resonant, and turbulent disturbance behavior that motivate the utilization of intelligent control techniques.

This article describes an investigation into the feasibility of using contextual reasoning to monitor and supervise the collaborative work of several knowledge workers working together on a project. Managing large and complex projects is a difficult task that requires situational awareness by the project manager to be able to be proactive when possible and to react correctly in the presence of events. In complex projects, effective oversight of the project personnel and the progress of the project are essential in ensuring that project objectives are met. This is especially true of projects that require contributions from various experts, whose interaction may be limited to a Web-based collaborative tool. Such oversight is typically the job of a project manager who is tasked with avoiding cost overruns, shipment delays, and ensuring product effectiveness. We utilize context-based reasoning and contextual graphs as the tools of choice for implementing an agent that emulates the function of a competent project manager. We use rocket design and manufacture as the domain to evaluate our technique. We use a public domain rocket design software package developed by the National Aeronautics and Space Administration as a guide to the domain. The article describes the investigation, its results, and the related works in a collaborative design project.

Shape grammars have been developed to codify a specific type of artifact – Queen Anne houses, Buffalo bungalows – or the style of a particular designer – Andrea Palladio, Frank Lloyd Wright, or Álvaro Siza Vieira. However, these specific grammars fail to encode recurrent design moves or features that are above the particularities of a specific design style or the idiosyncrasies of a specific designer and, therefore, are common to a larger category of designs and maybe reutilized and incorporated in the definition of new, specific design languages. To overcome these limitations, the notion of generic grammars for defining design domains is introduced. Its application to the urban design domain is illustrated by showing a generic grammar implementation resulting in a City Information Modeling platform composed of a parametric design interface connected to a geographic database.

When the idea of software reuse appeared in 1968, new horizons for software design were open. But some major problems appeared and most of the expectations were not met. One of the problems encountered is the selection of the right software component. This is related not only to the similarity between the desired functionality and the function delivered by the retrieved software component, but also to the effort needed to modify the chosen component to accommodate the desired functionality. Most of the research done in the case-based reasoning area has been in developing accurate and efficient retrieval algorithms. We think that case-based reasoning retrieval concepts and ideas can be successfully applied to software reuse. In this article we propose a metric to assess similarity between software cases supported on functional and behavioral knowledge. One important aspect of this metric is that reusability is taken into account to estimate the amount of effort needed to reuse retrieved software cases. We also present experimental work that shows that similarity at the functional level is the most important aspect of the similarity metric proposed.

In the construction industry, projects are becoming increasingly large and complex, necessitating multiple subcontractors. Traditional centralized coordination techniques used by general contractors become insufficient as subcontractors perform most work and provide their own resources. When subcontractors cannot provide enough resources, they hinder their own performance, that of other subcontractors, and ultimately the entire project. Thus, projects need a new distributed coordination approach wherein all of the concerned subcontractors can respond to changes and reschedule a project dynamically. This paper presents a new distributed coordination framework for project schedule changes (DCPSC) that is based on an agent-based negotiation approach wherein software agents evaluate the impact of changes, simulate decisions, and give advice on behalf of the human subcontractors. A case example demonstrates the significance of the DCPSC. It compares two centralized coordination methodologies used in current practice to the DCPSC framework. We demonstrate that our DCPSC framework always finds a solution that is better than or equal to any of two centralized coordination methodologies.

In this paper we present an application of AI search techniques to a class of problems that arise in transportation systems analysis. Rather than adapting the time-space network formulation typically used in Operations Research, we propose a discrete dynamic network to represent a scheduled service network. In a discrete dynamic network, there are finite, discrete, predetermined possibilities for moving from one vertex to another. Visiting a vertex has a cost (possibly zero), which may depend both on how the vertex was reached and how it will be left.

We describe the DYNET search algorithm for finding optimal paths in discrete dynamic networks. DYNET has been implemented in a working system (TRAINS) which searches the entire Dutch railway services network. An optimal path in a discrete dynamic network makes us arrive at our destination as early as possible (given our planned earliest departure time), and given this earliest arrival time (eat), will allow us to leave as late as possible, thereby guaranteeing a shortest path relative to the eat. DYNET first conducts a forward search to find the earliest possible arrival time, then a backward search which uses results of the forward search, to find the latest departure to arrive at that eat. Various AI techniques (symmetries, abstraction spaces, distance estimates, etc.) improve the performance of DYNET.

This paper presents in detail a parametric shape grammar for the generation of ancient Greek and Roman library plans. Ancient Libraries showcase a significant variability of scale, monumentality, and design with the use of different architectural components, and researchers cannot identify them as easily as other building types. The grammar is in 2D and captures all the variability of libraries from the simpler forms of the Hellenistic period to the more monumental of the Roman period, creating a vast range of designs. The paper presents the grammar-generated plans of the known libraries based on the evidence in the archaeological record. A frequency analysis of the occurrence of the rules in the derivations ranks the different characteristics of libraries and the architectural forms with which they occur in the corpus, to determine the probability of specific rules and to interpret them as mandatory or optional. The contribution of this work is that the shape grammar summarizes the design principles of ancient libraries visually and helps establish the building type of the ancient library. The frequency analysis assists tremendously in the reconstruction of fragmentarily preserved ancient libraries by providing a system in the reconstruction of the missing parts, when ambiguity is involved.

This paper introduces the special issue “Advances in Implemented Shape Grammars: Solutions and Applications” and frames the topic of computer implementations of shape grammars, both with a theoretical and an applied focus. This special issue focuses on the current state of the art regarding computer implementations of shape grammars and brings a discussion about how those systems can evolve in the coming years so that they can be used in real life design scenarios. This paper presents a brief state of the art of shape grammars implementation and an overview of the papers included in the current special issue categorized under technical design, interpreters and interface design, and uses cases. The paper ends with a comprehensive outlook into the future of shape grammars implementations.

How do humans judge the creativeness of an artwork or other artifact? This article suggests that such judgments are based on the pleasures of an aesthetic experience, which can be modeled as a mathematical product of psychological arousal and appraisal. The arousal stems from surprise, and is computed as a marginal entropy using information theory. The appraisal assigns meaning, by which the surprise is resolved, and is computed as a posterior probability using Bayesian theory. This model is tested by obtaining human ratings of surprise, meaning, and creativeness for artifacts in a domain of advertising design. The empirical results show that humans do judge creativeness as a product of surprise and meaning, consistent with the computational model of arousal and appraisal. Implications of the model are discussed with respect to advancing artificial intelligence in the arts as well as improving the computational evaluation of creativity in engineering and design.

Internal analogies are created if the knowledge of source domain is obtained only from the cognition of designers. In this paper, an understanding of the use of internal analogies in conceptual design is developed by studying: the types of internal analogies; the roles of internal analogies; the influence of design problems on the creation of internal analogies; the role of experience of designers on the use of internal analogies; the levels of abstraction at which internal analogies are searched in target domain, identified in source domain, and realized in the target domain; and the effect of internal analogies from the natural and artificial domains on the solution space created using these analogies. To facilitate this understanding, empirical studies of design sessions from earlier research, each involving a designer solving a design problem by identifying requirements and developing conceptual solutions, without using any support, are used. The following are the important findings: designers use analogies from the natural and artificial domains; analogies are used for generating requirements and solutions; the nature of the design problem influences the use of analogies; the role of experience of designers on the use of analogies is not clearly ascertained; analogical transfer is observed only at few levels of abstraction while many levels remain unexplored; and analogies from the natural domain seem to have more positive influence than the artificial domain on the number of ideas and variety of idea space.