While there are many project management tools and software packages available, these are not widely used in the design curriculum at colleges and universities. This may reflect some of the differences between conventional projects and design activities. In particular, the open-ended nature of design activities and the need to clarify the client's intention may lead to the conclusion that conventional project management tools are only useful for the most routine activities in the design process. It is suggested that there is a market for a new set of tools for teaching the management of design. These tools should incorporate the most useful of the current management tools and integrate them with some of the requirements of effective design, including support for clarification of objectives, functional analysis, and generation and evaluation of alternatives.

Methodologies have been developed and implemented in LISP and OPS-S languages which address type synthesis of mechanisms. Graph theory and separation of structure from function concepts have been integrated into an expert system called DOMES (Design Of Mechanism by an Expert System) to effectively implement the following three activities: 1. enumeration of all non-isomorphic labelled graphs; 2. identification of those graphs which satisfy structural constraints; 3. sketching of mechanisms corresponding to a given graph.

Developed theories and algorithms are applied to a robot gripper design and a variable-stroke piston engine design. The results from these two applications indicate that the automated techniques effectively identify all previously obtained solutions via manual techniques. Additional solutions are also identified and several errors of the manual process are detected. The developed methodologies and software appear to perform a complete and unbiased search of all possible candidate designs and are not prone to the errors of the manual process. Other important features of DOMES are: 1. it can learn and reason, by analogy, about a new design problem based on its experience of the problems previously solved by the system: 2. it has the capability to incrementally expand its knowledge base of rejection criteria by converting into LISP code information obtained through a query-based interactive session with a human designer; 3. it can select the set of rejection criteria relevant to a design problem from its knowledge base of rejection criteria. These procedures could become a powerful tool for design engineers, especially at the conceptual stage of design.

Current supportive bio-inspired design methods focus on handcrafting the inspiration engineers use to speed up bio-inspired design. However promising, such methods are not scalable as the time investment is shifted to an up-front investment. Furthermore, most proposed methods require the engineer to adopt a new design process. The current study presents FISh, a scalable search method based on the standard engineering design process. By leveraging machine translation between a representative corpus of biological and engineering texts, the engineer can start the search using engineering terminology, which, behind the scenes, is automatically converted to a biological query. This conversion is done using language models trained on patents and biological publications for the engineering and biology domains. Both models are aligned using the most used English words. The biological query is used to retrieve biological documents that describe the most relevant functionality for the engineering query. The presented method allows searching for bio-inspiration using a free-text query. Furthermore, updating the underlying datasets, models and organism aspects is automated, allowing the system to stay up to date without requiring interactive effort. Finally, the search functionality is validated by comparing the search results for the functionality of existing bio-inspired designs with their inspiring organisms.

Although graphic representations have proven to be of value in computer-aided support and have received much attention in both research and practice (Goldschmidt, 1991; Goel, 1995; Achten, 1997; Do, 2002), linguistic representations presently do not significantly contribute to improve the information handling related to the computer support of a design product. During its life cycle, engineers and designers make many representations of a product. The information and knowledge used to create the product are usually represented visually in sketches, models, (technical) drawings, and images. Linguistic information is complementary to graphic information and essential to create the corporate memory of products. Linguistic information (i.e., the use of words, abbreviations, vocal comments, annotations, notes, and reports) creates meaningful information for designers and engineers as well as for computers (Segers, 2004; Juchmes et al., 2005). Captions, plain text, and keyword indexing are now common to support the communication between design actors (Lawson & Loke, 1997; Wong & Kvan, 1999; Heylighen, 2001; Boujut, 2003). Nevertheless, it is currently scarcely used to its full potential in design, maintenance, and manufacturing.

The article is an extended version of the verbal summary presented at the concluding lunch of the workshop on “Computing Futures in Engineering Design.” In the paper, the first person is used to differentiate my observations or reactions from the summaries of the speakers' presentations. The common themes that emerge during the workshop are: the need to set the discipline-specific context before computational tools are used; the incompatibilities between point tools that hinder their use; the paramount importance of teamwork; and the need to understand and treat design as a social process.

Using the theory of fuzzy sets, this paper develops a fuzzy logic reasoning system as an augmentation to a rule-based expert system to deal with fuzzy information. First, fuzzy set theorems and fuzzy logic principles are briefly reviewed and organized to form a basis for the proposed fuzzy logic system. These theorems and principles are then extended for reasoning based on knowledge base with fuzzy production rules. When an expert system is augmented with the fuzzy logic system, the inference capability of the expert system is greatly expanded; and the establishment of a rule-based knowledge base becomes much easier and more economical. Interpretations of the system’s power and possible future research directions conclude the paper.

An efficient locally minimum-time trajectory planning algorithm for coordinately operating multiple robots is introduced. The task of the robots is to carry a common rigid object from an initial position to a final position along a given path in three-dimensional workspace in minimum time. The number of robots in the system is arbitrary. In the proposed algorithm, the desired motion of the common object carried by the robots is used as the key to planning of the trajectories of all the non-redundant robots involved. The search method is used in the trajectory planning. The planned robot trajectories satisfy the joint velocity, acceleration and torque constraints as well as the path constraints. The other constraints such as collision-free constraints, can be easily incorporated into the trajectory planning in future research.

In constraint-based design, components are modeled by variables describing their properties and subject to physical or mechanical constraints. However, some other constraints are difficult to represent, like comfort or user satisfaction. Partially defined constraints can be used to model the incomplete knowledge of a concept or a relation. Instead of only computing with the known part of the constraint, we propose to complete its definition by using machine-learning techniques. Because constraints are actively used during solving for pruning domains, building a classifier for instances is not enough: we need a solver able to reduce variable domains. Our technique is composed of two steps: first we learn a classifier for the constraint's projections and then we transform the classifier into a propagator. We show that our technique not only has good learning performances but also yields a very efficient solver for the learned constraint.

This study presents an application to optimize the use of an L-cut guillotine machine. The application has two distinct parts to it; first, a number of rectangular shapes are placed on as few metal sheets as possible by using genetic algorithms. Second, the sequence for cutting these pieces has to be generated. The guillotine's numeric control then uses this sequence to make the cuts.

The formal approach to shapes and their algebras, as it appears in shape grammar theory, has been reviewed. It starts with geometric elements and their partial algebras, continues to shapes, their algebras, and boundaries, as well as algebras that calculate with shapes and their boundaries. There is a number of new concepts introduced along the way. These include diagonal decompositions and their algebras which simplify calculations with shapes, b-paired diagonal decompositions which extend calculations with shapes and their boundaries from diagonal shapes only to all shapes, and m-order boundaries which extend the concept of shape boundaries and allow for calculations with multiple representations of shapes. It also shows that algebras of shapes are infinite direct sums of diagonal algebras.

It is desirable for complex engineered systems to be resilient to various sources of uncertainty throughout their life cycle. Such systems are high in cost and complexity, and often incorporate highly sophisticated materials, components, design, and other technologies. There are many uncertainties such systems will face throughout their life cycles due to changes in internal and external conditions, or states of interest, to the designer, such as technology readiness, market conditions, or system health. These states of interest affect the success of the system design with respect to the main objectives and application of the system, and are generally uncertain over the life cycle of the system. To address such uncertainties, we propose a resilient design approach for engineering systems. We utilize a Kalman filter approach to model the uncertain future states of interest. Then, based upon the modeled states, the optimal change in the design of the system is achieved to respond to the new states. This resilient method is applicable in systems when the ability to change is embedded in the system design. A design framework is proposed encompassing a set of definitions, metrics, and methodologies. A case study of a communication satellite system is presented to illustrate the features of the approach.

The specific semantics of CAD objects are analysed concerning their nature their dynamicity and their consistency during the design process. The nature of CAD objects is concerned with their structure and relationships. The dynamicity is concerned with the evolving nature of the objects, i.e. their behavior. The consistency is concerned with their completeness and relationships with integrity constraints.

A new methodology for semantic constraints management and control is defined. It relies extensively on database and expert system technologies for the implementation of new concepts, e.g. logical prototypes of objects and object equivalence class.

It provides a sound and unified basis for modelling the dynamic nature of complex objects, concerning both the management of their structure and the certification of the update operations, i.e. the control of their correctness.

The functionalities of CADB, a prototype expert database system that supports these features, are detailed. CADB is currently implemented in Prolog on VAX™ 11/785 and APOLLO™ workstations.

Considering manufacturing expertise during the early stages of design can be of great benefit. Such information can greatly improve not only the quality of a design, but it can also ensure the generation of an easily manufactured design. This, in turn, can lower the final cost of the designed product. By evaluating how easily an evolving conceptual design can be made, potential hazards can be avoided before any detailed design efforts commence. The conceptual manufacturing planning requisite to such an evaluation is the focus of this paper. A domain-independent strategy for conceptual manufacturing planning is presented. A task-structure analysis of this strategy shows its domain independence. A specific implementation of this strategy for polymer composites manufacturing planning (Socharis) is discussed. The high-level implementation details of Socharis are presented as instantiations of the conceptual manufacturing planning strategy. Finally, the validity of the planning strategy and the utility of Socharis are assessed.

The logic of typed feature structures is a sorted description logic that has enjoyed widespread usage in grammar design for the last 20 years. Woodbury and Burrow have faithfully preserved its strengths in adapting it to design space navigation research, although the weaknesses it has exhibited in the context of natural language grammar design are likely to surface here as well.

The fuzziness of the traditional multiaxial fatigue prediction model is discussed and the fuzzy theory is applied into fatigue reliability analysis. The fuzzy linear regression analysis method is used to determine the fuzzy coefficients in the multiaxial stress–life equation under a small sample condition, and the corresponding multiaxial fatigue probabilistic stress–life curve is calculated with different confidence levels.

This paper presents a knowledge-based problem solving environment for numerical simulation of problems described by partial differential equations (PDEs). The system aims to facilitate the simulation requirements of different user groups that include engineers, mathematicians and numerical analysts. To attain this objective, a flexible multi-perspective modelling environment is proposed which incorporates three natural modelling platforms, namely; a physical model, a mathematical model and a numerical model. The modelling environment is integrated with a sophisticated numerical solver. We believe that combination of an open modelling system with a basic numerical simulator provides a powerful problem solving environment capable of meeting the needs of these different user groups. The overall system architecture is based on automatic transformation using mathematical and numerical knowledge bases between the three identified models. The knowledge bases are organized in a frame based manner to reflect the hierarchical nature of the knowledge in PDEs and numerical algorithms. The object oriented paradigm is used to bind local rule bases to each frame and for implementing a global inference mechanism which works over the hierarchical knowledge structures. Evaluation of the modelling environment has indicated that engineers can tackle PDE based engineering problems without the necessity for detailed knowledge of mathematics or numerical techniques and mathematicians can examine the mathematical properties of PDEs without the requirement of numerical expertise.

During the design of complex systems, a design process may be subjected to stochastic disruptions, interruptions, and changes, which can be described broadly as “design impulses.” These impulses can have a significant impact on the transient response and converged equilibrium for the design system. We distinguish this research by focusing on the interactions between local and architectural impulses in the form of designer mistakes and dissolution, division, and combination impulses, respectively, for a distributed design case study. We provide statistical support for the “parallel character hypothesis,” which asserts that parallel arrangements generally best mitigate dissolution and division impulses. We find that local impulses tend to slow convergence, but systems also subjected to dissolution or division impulses still favor parallel arrangements. We statistically uphold the conclusion that the strategy to mitigate combination impulses is unaffected by the presence of local impulses.

In this work, an artificial neural network model is established to understand the relationship among the tensile properties of as-printed Ti6Al4V parts, annealing parameters, and the tensile properties of annealed Ti6Al4V parts. The database was established by collecting published reports on the annealing treatment of selective laser melting (SLM) Ti6Al4V, from 2006 to 2020. Using the established model, it is possible to prescribe annealing parameters and predict properties after annealing for SLM Ti-6Al-4V parts with high confidence. The model shows high accuracy in the prediction of yield strength (YS) and ultimate tensile strength (UTS). It is found that the YS and UTS are sensitive to the annealing parameters, including temperature and holding time. The YS and UTS are also sensitive to initial YS and UTS of as-printed parts. The model suggests that an annealing process of the holding time of fewer than 4 h and the holding temperature lower than 850°C is desirable for as-printed Ti6Al4V parts to reach the YS required by the ASTM standard. By studying the collected data of microstructure and tensile properties of annealed Ti6Al4V, a new Hall-Petch relationship is proposed to correlate grain size and YS for annealed SLM Ti6Al4V parts in this work. The prediction of strain to failure shows lower accuracy compared with the predictions of YS and UTS due to the large scattering of the experimental data collected from the published reports.

Spreadsheets are difficult to use in applications, where only incomplete or inexact data (e.g., intervals) are available-a typical situation in various design and planning tasks. It can be argued that this is due to two fundamental shortcomings of the computational paradigm underlying spreadsheets. First, the distinction between input and output cells has to be fixed before computations. Second, cells may have only exact values. As a result, spread-sheets support the user only with primitive iterative problem solving schemes based on trial-and-error methods. A constraint-based computational paradigm for next generation interval spreadsheets is presented. The scheme makes it possible to exploit incomplete/inexact data (intervals), and it can support problem solving in a top-down fashion. Current spreadsheets constitute a special case of the more general interval constraint spreadsheets proposed.