A formal method for subjective design evaluation with multiple attributes

A procedure for evaluation of multiple attributes in the preliminary design stage is necessary to the development of a more formal theory and methodology of design. In this paper we prescribe, demonstrate, and compare two such techniques: fuzzy set analysis and multiattribute utility analysis. We analyze the problem of preliminary material selection for an automotive bumper beam to illustrate the application of both analytical procedures. Preliminary assessment of incommensurate performance measures of weight, cost, shape restriction, stiffness, and corrosion are made for steel and polymer composite alternatives. Fuzzy analysis readily accommodates design evaluation based on semantic assessment of relative attribute levels, although it can also employ information which is entirely numerical. In contrast, utility analysis requires considerable numerical quantification. For the example studied, the ordinal ranking of alternatives was the same for both methods. Recommendations include using fuzzy analysis in the earliest stages of preliminary design evaluation or in situations limited to semantic input from design decision makers. Utility analysis may be used in later stages of preliminary design, where numerical quantification of attribute levels is possible and when decision makers are able to assess the individual attribute utility functions in the standard way. The results of utility analysis can be used to quantify acceptable design tradeoffs between attribute levels and can be used in later stages of the iterative design process.

: The purpose of this report is to provide general information concerning software design methodologies to technical management personnel. In particular, the report is aimed at managers who are in the planning stages of a software development and are facing the decisions of whether to use a formal design methodology and which methodology to use. To accomplish this objective a definition of design methodology is presented, explained and illustrated. Major design philosophies are discussed and the kinds of applications which they address are described. Following this introductory information, various management perspectives on software design methodologies are presented. In general, these perspectives pertain to the current state of software design methodology development and support tools, as well as relevant application experiences. (author)

A formal methodology is presented which may be used to evaluate design alternatives in the iterative design/redesign process. Deterministic multiattribute utility analysis is used to compare the overall utility or value of alternative designs as a function of the levels of several performance characteristics of a manufactured system. The evaluation function reflects the designers subjective preferences. Sensitivity analysis provides quantitative information as to how a design should be modified in order to increase its utility to the design decision maker. Improvements in one or more areas or performance and tradeoffs between attributes which would increase desirability of a design most may be quantified. A case study of materials selection and design in the automotive industry is presented. The methodology was applied to 6 automotive companies in the United States and Europe, and results are used to illustrate the steps followed in application.

This chapter presents a formal optimization methodology for the seismic design of multiple tuned-mass-dampers (MTMDs) for the multi-modal control of 3D irregular buildings. The total weight of all TMDs is minimized while both inter-story drifts and total accelerations are constrained to allowable values so as to lead to a performance-based-design. The results reveal that, with the right design, MTMDs can mitigate both structural and nonstructural earthquake damage. Hence, they can potentially present a multi-hazard strategy to mitigate both winds and earthquakes.

Provision of free, downloadable industry-standard reconfigurable hardware EDA tools is a growing and welcome trend. Low cost, ever-more-complex FPGA-based embedded system development platforms with host interface control are becoming more readily available. This paper describes a series of structured VHDL workshop modules which use the Xilinx ISE Webpack/ModelsimXE electronic design automation (EDA) tools and Digilent Spartan-3 hardware development system. The described course implements an extendable embedded system, which performs a selection of image and audio processing applications, controlled by a host graphical user interface (GUI). A formal structured design, documentation and test methodology is incorporated throughout the course. Enhancements to EDA tool VHDL and diagram creation wizard support are proposed to aid VHDL capture automation and design visualisation. Improved student understanding and achievement level in VHDL programming, digital embedded system design techniques and FPGA implementation has resulted

This paper presents the current state of microfluidic design from a practitioner's perspective. The capture of microfluidic design practice was facilitated through a combination of industry survey and expert interviews, allowing the authors to draw out models for microfluidic design. Exploration of the current practice of microfluidic design showed that formal design methodologies were not in use. This research has also found that sub-section interactions have been addressed in an inadequate fashion by current design practices. The work presented in this paper outlines the scope for further research in the development of a formal design methodology for microfluidics.

We present an interactive, computationally assisted, methodology for capturing and incorporating designer preferences into a numerical search for design concepts. An initial pool of manually created designs is parameterized and used in a computational search that recombines features to form new designs in a semi-automated way. Designs are evaluated quantitatively by performance calculations and evaluated qualitatively by human designers. Designer preference is captured when visual representations of designs are presented to the designer for subjective evaluation. The methodology searches for optimally performing designs, guided by quantitative performance models and designer preferences. The methodology couples the speed of computational searches with the ability of human designers to subjectively evaluate unmodeled objectives. The new methodology is demonstrated with a vehicle architecture example, which generates a set of designs that progressively improves in performance and more fully meets designer preference. The proposed method brings the ability to generate numerous, optimally performing solutions across a wide solution space, in an efficient and human-centered way, and does so in the early stages of design.

Wheel hubs have undergone new form changes as an essential part of New Energy Vehicles (NEV). At the same time, consumers' emotional preferences for the wheel hub design of NEV differ from those of traditional vehicles. However, designers' original knowledge and experience cannot be fully applied, which has limitations. Generative algorithms have been widely used in product design. Therefore, this paper proposes a form design method that combines Kansei Engineering (KE) and Generative Adversarial Networks (GAN) to investigate consumers' emotional preferences for wheel hub form design of NEV and provide designers and manufacturers with design insights. First, a wheel hub dataset is established by collecting and processing images from the website to train GAN and generate various design alternatives. Second, the experts deconstruct the wheel hub form into main features and screen several representative samples. Third, a Kansei questionnaire is distributed to investigate users' emotional preferences and satisfaction with the NEV wheel hub form. Next, the questionnaire data is analyzed and visualized to obtain the relationship between emotional preferences and design features to form a design guide. Finally, Design solutions are selected from the generated wheel hub alternatives according to the design guidelines to realize design automation. This study proposes a systematic method for NEV wheel hub form design, which provides theoretical and practical support for designers to meet user needs more efficiently.

Welding is an absolutely essential component of industries such as the automotive industry, the construction industry and even the aviation industry. Although it is a widespread technology it is still characterized by lots of uncertainties. This still requires well experienced and highly skilled workforce to design and perform safe welding processes. The early knowledge of distortion and residual stresses is almost an issue which is influenced mainly by the welding parameters and the fixture design. But more and more engineers want to know as well final properties of the assembled components. With the beginning of the computer age in the 1970s and 1980s last century, the numerical prediction of manufacturing processes using FEM was gradually getting better and has established itself in the industry since the 1990s as a standard tool. Unlike in metal casting and forming industry, however, the everyday use of FEM-simulation tools for welding processes eked out a shadowy existence for a long time. This paper will give a short classification of welding simulation types and a structured overview on the technical questions. Selected case studies and the benefits achieved through simulations with the software Simufact.welding are discussed. Finally an outlook on future developments will be given. Key words: Simufact welding, FEM, Welding simulation, Automotive industry, Virtual design

OVIDE: A Software Package for Verifying and Validating Petri Nets

Early diagnosis is especially important, because cataracts develop slowly and many patients are not aware of their gradual loss of sight until very late in the disease when vision is irreversibly affected. Therefore, improving methods for cataract screening is an important field of research. This research involves the combination of engineering and medical methods in order to create physical solutions which eliminate suffering caused by cataract-related blindness. These methods must address cost effectiveness and reliability issues [4]. One way to address these issues is to use inexpensive computer technology to design and develop automated cataract classification systems for diagnosis support. Computer-based systems come with their own set of challenges, which result from the immense flexibility of modern processing machines [5]. One of these shortcomings is state space explosion and nondeterminism of large-scale systems. To overcome, or at least manage, these challenges, this type of medical support system must be designed with a formal and model-driven design methodology [6,7].

A formal definition and design methodology for discrete‐time higher‐order sliding mode (DHOSM) based on finite difference method is proposed. A generalised reaching law is proposed to achieve r ‐order sliding mode in discrete time, and its behaviour and stability are analysed. The proposed reaching law is used to design a higher‐order sliding mode control for an uncertain LTI system. The concept is experimentally validated on a real‐time rectilinear plant and is compared with the existing algorithms on the basis of sensitivity function and ‐continuity. The results and comparison show that the proposed sliding algorithm has superior disturbance rejection capability as well as better continuity. This work is the first attempt to formally define and design DHOSM as opposed to discretisation of continuous time higher‐order sliding mode.

Design methods support the derivation of alternative design solutions, and based on product requirements, it provides a platform for the evaluation and selection of appropriate solutions. Because of the driving needs of design and manufacturing industries and also the quest to remain competitive, several design methodologies aimed at addressing aspects of industrial requirements have emerged. This study identifies current best practice design methodologies and their performance when compared with current trends in design and manufacturing. Based on the review, the strengths and weaknesses of current methods are highlighted and used as the platform to support the recommendation for an integrated design and manufacturing methodology. The integrated design and manufacturing methodology rest on the strengths of product design, cost engineering, enterprise and process simulation modelling techniques. This method can help in the (re)design and (re)engineering of products and processes for better cost indications; help determine appropriate manufacturing paradigms; perform virtual experiments to understand implication of production volume changes on designs and flexibility needs in production systems.

Design is an uncertain human activity involving decisions with uncertain outcomes. Sources of uncertainty in product design include uncertainty in modeling methods, market preferences, and performance levels of subsystem technologies, among many others. The performance of a technology evolves over time, typically exhibiting improving performance. As the performance of a technology in the future is uncertain, quantifying the evolution of these technologies poses a challenge in making long-term design decisions. Here, we focus on how to make decisions using formal models of technology evolution. The scenario of a wind turbine energy company deciding which technology to invest in demonstrates a new technology evolution modeling technique and decision making method. The design of wind turbine arrays is a complex problem involving decisions such as location and turbine model selection. Wind turbines, like many other technologies, are currently evolving as the research and development efforts push the performance limits. In this research, the development of technology performance is modeled as an S-curve; slowly at first, quickly during heavy research and development effort, and slowly again as the performance approaches its limits. The S-curve model typically represents the evolution of just one performance attribute, but designers generally deal with problems involving multiple important attributes. Pareto frontiers representing the set of optimal solutions that the decision maker can select from at any point in time allow for modeling the evolution of technologies with multiple attributes. As the performance of a technology develops, the Pareto frontier shifts to a new location. The assumed S-curve form of technology development allows the designer to apply the uncertainty of technology development directly to the S-curve evolution model rather than applying the uncertainty to the future performance, giving a more focused application of uncertainty in the problem. The multi-attribute technology evolution modeling technique applied in decision-making gives designers greater insight when making long-term decisions involving technologies that evolve.

Knowledge based-system for alternative design, cost estimating and scheduling