Next generation process planning systems should be capable of dealing with industrial demands of versatility, flexibility, and agility for product manufacturing. Development of process planning system is heavily dependent on feature recognition, but presently there is no satisfactory feature recognition system relying on a single method. In this paper, we describe a hybrid feature recognition method for machining features that combines three feature recognition technologies: graph-based, convex volume decomposition, and maximal volume decomposition. Based on an evaluation of the strengths and weaknesses of these methods, we integrate them in a sequential workflow, such that each method recognizes features according to its strengths, and successively simplifies the part model for the following methods. We identify two anomalous cases arising from the application of maximal volume decomposition, and discuss their cure by introducing limiting halfspaces. All recognized features are combined into a unified hierarchical feature representation, which captures feature interaction information, including geometry-based machining precedence relations.

Increasing intelligence in new products has necessitated a closer look at the application of design theory and methodology in the specific context of intelligent systems. In this paper, after reviewing the several prevalent notions of intelligent systems, some of the parameters and the measure of intelligence are discussed. The earlier work on evaluation of information content of automation systems is extended in the context of intelligent systems. The paper discusses a generic definition of intelligence more suitable for measurement in the realm of axiomatic design theory. It investigates the different issues pertaining to computation of information and its interpretation as a measure of intelligence considering an example of the basic maneuvers of an autonomous robot. The paper discusses the observations and elucidates the usefulness of information as a metric for measurement of intelligence.

Training novice users how to operate an Atomic Force Microscope (AFM) is expensive due to the cost of equipment and the time required to train users in a hands-on learning environment. Training large groups of users simultaneously presents a problem because usually only one AFM is available for use. To alleviate this problem, a virtual training simulator for AFM training has been developed. The training simulator is a Windows-based software program designed to allow users to simulate basic AFM operation on a PC. Instructors can use this tool to demonstrate the exact same instruction that a user would receive in an AFM lab within the confines of a classroom or computer lab. The graphical user interface (GUI) of the simulator replicates the interface of one of the most popular commercial AFM models to aid learning transfer from the simulator to the actual AFM. The goal of this paper is to provide a brief overview of the work that has been completed towards creating this virtual training simulator. The virtual AFM simulator modeling, design, and implementation are described.

An integrated end-to-end lifecycle engineering process management system is deemed critical to boost the manageability, efficiency and responsiveness of an engineering enterprise. The challenge lies in the realization of such a system that is flexible and scalable. To overcome the challenge, a configurable module based system technology is developed to simplify the realization of a complex process management system and to offer the system a high level of flexibility and scalability. The technology is based on the belief that a complex process management system can be built by a set of static and process-based function modules. Each of the function modules consists of a set of categorized elements to meet the desired functional requirements. These categorized elements can be extracted into a unified process model upon which a configurable modular can be developed. The modular can be configured into a desired function module with specific functional requirements. The assignment of the function modules to the specific roles at the lifecycle processes forms a system. The technology has been successfully applied in a company specializing in make-to-order operations.

As new representations are introduced to model various aspects of engineering design or to support computer aided design automation systems, these representations should be evaluated with respect to their intrinsic and extrinsic properties. One such property that is explored in this paper is “representational expressiveness”. This paper provides a systematic approach to exploring the expressiveness of new design representations by providing an evaluation of the design exemplar with respect to expressiveness. This expressiveness is decomposed into: coverage of vocabulary, flexibility of definition of vocabulary, type of vocabulary, mappability to existing representations, and support of basic design tasks. The design exemplar is examined with respect to these aspects of expressiveness, systematically laying a foundation for the intrinsic justification for basing future design automation systems on the principles of the design exemplar. This paper is not intended to be a comprehensive review of all aspects of the design exemplar. Rather, this paper is written to compel the design automation community to begin to develop a more systematic and reasoned approach in evaluating the automation systems and representations that are introduced in our research.

This paper introduces an approach to OWL-based hybrid product knowledge model for collaborative engineering environment. The participants in collaborative engineering want to share and reason product knowledge through internet without any heterogeneity and ambiguity. In this paper, the hybrid product knowledge model is proposed using first-order logic(FOL), relational database(RDB) and web ontology language(OWL) according to a formal ontology. Our knowledge model can be used to develop an integrated knowledge-base which reduces heterogeneity and ambiguity. Firstly, the collaborative engineering domain is analyzed and then the product knowledge is organized into four levels such as product context model, product specific model, product design model and product manufacturing model. Secondly, the four levels are represented by FOL in layered fashion. The concepts and the instances of a formal ontology are used for recursive representation of the four levels. The instances of the concepts of an upper level like product context model are considered as the concepts of an adjacent lower level like product specific model, and this mechanism is applied to the other levels. Thirdly, these logic representations are integrated with the schema and the instances of a relational database. Finally, OWL-based product knowledge model is developed, in which OWL representation of the four levels are defined through the integration of the logic representation and OWL primitives. Thus, a hybrid product knowledge model is constructed, in which the four product knowledge models have their major representation such as FOL, RDB, or OWL according to the characteristics of each model. This approach enables engineer to share product knowledge through internet reducing ambiguity, and utilize it as basis for additional reasoning.

Reuse of design knowledge is an important goal in engineering design, and has received much attention. A substantial set of algorithms, methodology, and developed systems exist which support various aspects of this goal. However, the majority of these systems are built around a particular user interface, often some form of Web-based repository portal. The work described here presents search and other core functionality as web services rather than a monolithic repository system. These services may then be employed by a variety of applications, integrating them into interfaces familiar to the designer, extending functionality, streamlining their use, and enabling them to be employed throughout the design process. This paper demonstrates this approach by wrapping previously developed repository search algorithms as web services, and then using these within a plug-in for an existing commercial CAD environment. Based on issues encountered in developing this demonstration, this paper also discusses the challenges and potential approaches toward a more general, widespread application of web services in engineering design.

A virtual training environment for a 3-axis CNC milling machine is presented. The key elements of the environment are: (a) textured 3D photo-realistic virtual models of the machines and lab; (b) machine simulator for the machines’ controls and moving parts; (c) semi-empirical model of the machining operation; (d) hierarchical knowledge-base for process training; (e) unstructured knowledge-base for lecture delivery; (f) natural-language human-like intelligent virtual tutors. Applications of the AVML include: training students to operate manufacturing machines in a safe environment, allowing students and researchers to view and interact with highly accurate physical simulation of manufacturing machines, and optimization of the manufacturing process plan by testing various plans on the virtual machine before actual machining. The virtual training environment will significantly reduce the cost and increase the accessibility and safety of advanced manufacturing training.

The compressed CO 2 was supplied from the CO 2 cylinder to the steel vessel containing yeast-water mixture until the pressure inside the steel vessel reached a desired pressure level. The steel vessel was kept at the prescribed pressure level during the treatment period. After the treatment, the pressure inside the vessel was released to the atmospheric pressure within the evacuation time by controlling the relief control valve. The sterilization effect was evaluated by vial counting the treated sample taken from the steel vessel. Several experiments have been performed varying each factor such as the total treatment time, the evacuation time and the applied pressure. As a result, it was verified that these factors are strongly related to the sterilization effect. In addition, it was observed that increase of the treatment time could enhance the concentration rate of CO 2 in the mixture. Furthermore, it was concluded that fast depressurizing rapidly expanded CO2 penetrated into each yeast cell. Also, the experimental results showed that when treatment time is longer, the pressure becomes higher, and the evacuation time is shorter, thus, a better sterilizing effect was obtained. Contrary to the results above, both the treatment time and the evacuation time rarely affected sterilization effect under supercritical condition. By adopting Supercritical condition, a desirable result could be achieved with shorter treatment and longer evacuation time. Thus, as long as supercritical condition is adopted for test, either fast evacuation time or long treatment time is not essential any more.

The goal of the present work is three fold. Firstly to create the forward continuum model of a multi-species diffusing system under simultaneous presence of chemical reactivity and temperature as the general case of all hydrogen storage systems. Secondly, cast the problem of hydrogen storage in a pragmatic product-design context where the appropriate design parameters of the system are determined via appropriate optimization methods that utilize extensive experimental data encoding the behavior of the system. Thirdly, demonstrate this methodology on characterizing certain systemic parameters. Thus, the context of the work presented is defined by a data-driven characterization of coupled heat and mass diffusion models of hydrogen storage systems from a multiphysics perspective at the macro length scale. In particular, a single wall nanotube (SWNT) based composite is modeled by coupled partial differential equations representing spatio-temporal evolution of distributions of temperature and hydrogen concentration. Analytical solutions of these equations are adopted for an inverse analysis that defines a non-linear optimization problem for determining the parameters of the model by objective function minimization. Experimentally acquired and model produced data are used to construct the system’s objective function. Simulations to demonstrate the applicability of the methodology and a discussion of its potential extension to multi-scale and manufacturing process optimization are also presented.

Designing and developing highly engineered products requires direct (and more dynamic) associations between customers’ specifications and product characteristics (or its behaviors). In order to meet the specified customer performance, cost, and integrity goals, a multitude of specialized analyses, heuristics, shortcuts, look-up tables, equations, algorithms, finite elements, and material substitution at multiple levels (system, subsystems, components and parts) are ought to be performed. The product geometries of such engineered product are often complex and many parts are designed interactively from scratch using a 3D commercial computer-aided design (CAD) — lately often referred as Product Life-cycle Management (PLM) system. Today, this very “PLM-based” engineered product-design process is often “static”, very “feature or geometry-dependent,” “knowledge-intensive,” and therefore, engineers often takes considerable time (months) to complete this manual process. Today, more and more companies want to quickly reengineer a product from a multitude of family solutions (corresponding to various design trade-off studies). They are interested in some dynamic form of a decision-based system that could automatically filter through a multitude of historical product solutions and quickly reconfigure one that meets the customer requirements with the least cost, weight, and time investment. Such decision-based product automation is not an easy task by any means. Product definitions without knowing specific geometry are hard to conceive, capture generically, and reuse widely (via any generative tool). A typical product development process —by its nature— is highly dynamic, nonlinear, discrete, feature-dependent, and part-dependent. The solution is not easy, since problem formulation is time-bound, has numerous discrete inputs, topologies, and several mathematical discontinuities. This paper discusses the system architecture of the Knowledge-driven Automation (KDA) program — established at Parker in 2002. It addresses many of the above product development issues and problems. In particular, authors describe a Knowledge-based System Engineering Process for Obtaining Engineering Design Solutions in a Commercial PLM Setting. The architecture and solutions use a number of innovative knowledge-based engineering (KBE) concepts and procedures. Through strategic use of generative modeling, spreadsheet tables, part and assembly templates, system engineering concepts, and our proprietary “smart part concepts,” authors were able to engineer-to-configure a family of hydraulic actuators automatically from their customer specifications using a set of PLM (CATIA V5 and its underlying knowledgeware) tools.

The emergence of computer and network technology has provided opportunities for researchers to construct and build systems to support dynamic, real-time, and collaborative engineering design in a concurrent manner. This paper provides an understanding of the product design in a distributed environment where designers are in different geographic locations and are required to be involved in the design process to ensure successful product design. A design process model that captures the major interactions among stakeholders is presented, based on the observation of cooperation and collaboration. The stakeholders’ interactions are divided into activity and system level to distinguish the interactions in group design activities and design perspective evolution. An initial computer implementation of the design model is presented. The design system consists of a set of tools associated with design and a management system to facilitate distributed designers to support various design activities, especially conceptual design. Our research emphasis of design collaboration in this paper is: (i) Model a Cooperative-collaborative design process; (ii) Support synchronized design activities; and (iii) Structure the complex relations of various design perspectives from engineering disciplines.

Selecting the “right” solid modeling software is a complex, multi-criteria decision-making problem. Some of these criteria relate to ease of learning, educational materials built into the software, learning curve issues, performance of the software for different solid modeling functions, operations and utilities, and cost. Beyond selecting the right software, the decision-maker should also be concerned about (1) conceptual learning of the solid modeling topics while “the right software” is being used, and (2) transfer of conceptual learning between solid modelers. This is because a sound conceptual learning using one software might increase the probability of learning another in less time. Accordingly, this paper investigates the impact of icon recognition as an aid to transfer conceptual learning between solid modelers. The investigation includes a review of the literature on icon design and usage as it relates to solid modeling, in addition to an experiment in which the icon recognition correctness for over 20 operation icons were compared across two modelers. The results shed light into the impact of icon designs on the transfer of learning between solid modelers using the correct recognition counts as the transfer measure.

In new models of CNC machines, NURBS interpolation function can process tool paths represented in NURBS form (called NURBS tool paths) so that cutters can conduct NURBS motions, which can machine sculptured surfaces with high surface accuracy and finish. However, most CAM systems could not convert the tool paths with discrete cutter locations into NURBS tool paths, and the conventional data fitting methods can not calculate a NURBS curve to represent the given cutter locations in high precision. In this work, a new high precision fitting approach is proposed for generating NURBS tool paths. The main contribution of this work is to propose NURBS tool paths and fit the tool paths through the cutter locations more precisely with fewer control points. Since NURBS tool paths can make accurate and smooth sculpture surfaces, this approach can promote the usage of NURBS tool paths in manufacturing industry.

This paper addresses some issues that many mechanical engineering departments are facing or soon will be facing in response to the rapid development in the area of MCAD as the industry is making transition from 2-D to 3-D and embracing the concept of Product Lifecycle Management (PLM). Something we took for granted before now becomes an issue. For example, as the 3-D based CAD package becomes more and more powerful and much easier to use than its 2-D counterpart, do we still need to teach engineering graphics using 2-D CAD packages or should we use the 3-D CAD package for the same purpose? The next question then would be which package is better and easier for the students to use to learn the basics of geometric construction and orthographic projection theory. This paper tries to discuss these issues and provide some input on the importance of the issues. As the parametric 3-dimensional MCAD package becomes more affordable and evolves into a mature lifecycle product management package, more curriculum changes would have to follow to meet the demands of the industry.

Today, organizations have to deal with the integration of applications across company borders, and must support collaboration of business processes between organizations in networked environments that are seamless, flexible and interoperable. This characteristic of horizontality, where one application embraces more than one domain of activity, is frequently found and raises the need for integration and cooperation between multiple standard application protocols and business objects. However, a standard for data representation cannot cove the whole range of activities one application needs to handle. This paper contributes by proposing a framework that supports interoperability in distributed heterogeneous networked environments, assisting in the integration of reference models described following dissimilar methodologies. This framework assists in the automatic mapping between ISO10303 STEP, UML and XML models. The proposed work results from research developed and validated in the scope of the IMS SMART-fm project ( www.smart-fm.funstep.org , www.ims.org ), involving partners from USA, Europe, Canada and Australia, using emerging approaches for modeling and technology.

The present paper is motivated by the need to develop technological infrastructure for informed and reliable decision support in various crisis and disaster management situations. It describes our prototype data-driven fire hazard simulator capable of predicting fire propagation dynamics that allows the user to take decisions based on reliable micro-future predictions of fire propagation based on potential personnel actions. Several heterogeneous technologies are integrated to achieve this goal. The GRID is utilized for running legacy codes enabling fire-propagation prediction. Sensor networks are used to enable simulation steering and correction. Base-stations enable data and communications coordination. Handheld or other wearable devices are terminal and initial points of interaction of the first responders with the rest of the system. Agent middleware is utilized to coordinate all heterogeneous software present. A demonstration of the first incarnation of this infrastructure is implemented over Bluetooth and WiFi enabled communications between the handheld devices and the base-stations involved.

To meet the needs of efficient turbine blade designs, CFD predictions of a complex 3D flow field in turbine blade passages have been incorporated in the design process during the last decade. Owing to the numerous advantages possessed by a 3-D CFD technology many industries already use a 3D blading technique in the design process of turbomachines. In addition, blade lean and sweep have been implemented to increase the blade row efficiency. Experimental studies have shown some advantages of these features. However, most of the experimental results were combined with other features together as well; thus making it difficult to determine the effects of individual superior features. The development of CFD techniques has made it possible to do three-dimensional turbulent flow analyses in a very short time. In this study, numerical studies are presented to demonstrate the sweep effects on a transonic compressor airfoil. The purpose of this study is to investigate the sweep effects without changing other compressor blade features; i.e. keeping the blade outflow angles and section shapes to be the same at design sections for all cases. Through this study the sweep effect in a transonic compressor rotor blade was tested. The results showed that the sweeps redistribute the flow reducing the secondary flow loss, depending on the baseline. It was shown that the forward sweep reduces the tip loading in terms of the static pressure coefficient.

This paper establishes a new class of analytical solutions for nonlinear boundary value problems defined by systems of ordinary differential equations. This class uses Bezier functions derived from Bezier curves. Three engineering examples, (1) a fully developed laminar flow in a pipe with constant surface temperature; (2) a three dimensional flow over a rotating disk; (3) a three dimensional rotating flow over a stationary disk, are solved and the analytical solution is provided. These solutions are graphically indistinguishable from the exact or numerical solutions used for comparison. The solutions are obtained through standard design optimization techniques. The approach is simple. The set up is direct. No state space formulation is necessary for handling the set of differential equations. The procedure is independent of the type or the discipline the problem belongs to. The procedure is adaptive through the selection of the order of the Bezier functions.

Modern engineering design requires the exploration of complex nonlinear design spaces that relate large numbers of design variables and performance criteria. Effective exploration and decision making requires the availability of efficient representations of high dimensional design spaces. Techniques from the field of metamodeling, which builds models of models, are often used to represent complex design relationships. We have developed an alternative, spline-based metamodeling technique that is amenable to adaptive representation of high dimensional spaces and facilitates optimization-based exploration of such spaces. This paper describes our technique for fitting Non-Uniform Rational B-splines (NURBs) to points in a design space generated from simulations or experiments. The algorithm is illustrated with examples from metamodeling and nonlinear optimization literature. The results indicate that our method achieves an average global correlation of more than 99% and an average maximum local RMS error of less than 3% of full scale.