Shih Wen Hsiao

A semantic and shape grammar based approach for product design

Abstract A semantic recognition and rule-oriented approach for developing a product design is proposed. The development of an office chair is used to describe the design procedures. A number of referential products are used to quantify partial correlation coefficients, which represent individual contributions of constituent components to the impression of a whole product with respect to an image, by using the ‘quantification theory type I’ and ‘semantic differential method’. The results are then built as an image database. A computer program is constructed by integrating the techniques of constructing B-splines, shape grammars and fuzzy operations to provide a CAD environment in which 3D basic models of a product can be constructed by starting with inputting an image word(s) and the corresponding membership functions for describing the image of the required product. After a basic product model has been constructed, new product forms can further be generated by regulating the shapes of the component(s) using shape rule(s).

Concurrent design method for developing a new product

Abstract A concurrent customer-oriented design method for developing a new product is addressed in this article. The design of a secure music-toy for children aged under seven is taken as a case study to specify the implementation procedures of this method. The qualitative design parameters and design criteria are first deployed with the quality function deployment and failure mode and effect analysis technologies and then quantified with the analytic hierarchy process technology to get the best design targets with which the detail design is completed. The design for assembly technology is also used to analyze the assembly performance and the costs of design alternatives. In this manner, a product that more nearly fits the consumer needs and is of higher competitiveness can be designed and the total quality is managed after the design process has been completed. Relevance to industry Developing a high quality and low cost product is an important policy of an enterprise in todays highly competitive marketplace. To reach this objective, a systematically transparent method by integrating several techniques is proposed in this study. With this systematic methodology, a high quality and low cost product that more fits the consumer needs is to be designed and consequently the competitiveness of the product is improved.

Applying the semantic transformation method to product form design

Abstract A semantic transformation method for product form design is proposed. In this model, an image database for the relationships between the product shapes and image words is built using the membership functions of a fuzzy set, and a multidimensional perceptual space for the relationships between the abstract image words and the embodiment shape regulating rules is also constructed using the multidimensional scaling (MDS) method. A computer program is constructed by integrating the technique of constructing B-splines, the image database and fuzzy query operations to provide a CAD environment in which 3D basic models of a product can be constructed by starting with inputting an image word(s) for describing the image of the required product. After a basic product model has been constructed, new product forms can further be generated by regulating the shape of the basic model using the suggested embodiment shape regulation rule which is obtained by inputting a required image to analyze the direction cosines of the embodiment shape regulation rules with respect to the required image in the multidimensional semantic recognition space. Though automotive form design is taken as an example in this study, this method can also be used to develop other products.

A structural component-based approach for designing product family

This study presents a novel approach for establishing an intelligent support system in order to design a product family through managing variety. Two approaches are applied successively. First, the Quality Function Deployment (QFD) approach identifies the exterior drivers of design variation. Second, the Interpretive Structural Model (ISM) technique is applied to visualize the hierarchy of component interactions within a product. This approach represents the design priority and related design constraints within a product using a structural graph, helping designers to create variant design solutions in a product family for different market requests. The methodology proposed here is illustrated via the example of the design of a family of automatic drip coffee makers.

A morphing method for shape generation and image prediction in product design

Abstract A shape morphing and image prediction method for product design is proposed in this article, in which a feature-based method is first used to construct 3-D CAD models of a product, then new shapes are generated with a shape morphing method and the images of the morphed shapes are analyzed using modified gray theory with Fourier residual correction. With the aid of this model, the designer can quickly obtain a product form and its corresponding image to help him/her to design the required product. Though LCD monitor design is applied, this method can also be used to develop other products.

An image evaluation approach for parameter-based product form and color design

The parameter-based technique provides an efficient and valid means of constructing 3-D geometric models in many CAD software systems. However, its use is generally restricted to the design of mechanical components with regular configurations, and it is not ideally suited to product form and color design. This paper proposes a rapid conceptual design approach, which creates color-rendered forms and combines parameter-based features with fuzzy neural network theorems and gray theory to predict their image evaluation. Two evaluation models (Evaluation Model I and Evaluation Model II) are developed and applied in a case study of an electronic door lock design. Model I uses a fuzzy neural network to predict the overall image, while Model II uses a gray clustering operation for the color image evaluation and two fuzzy neural networks for the form image evaluation and the overall image evaluation. The results show that the image prediction capability of Model II is superior to that of Model I (RMSE: 0.062 versus 0.105). Furthermore, the overall image evaluation is dominated by the door locks color rather than by its form (RMSE: 0.071 versus 0.162). The dominance of color in determining the image evaluation may be due to the specified image words, form evolution restrictions, or the membership grade ranges of the test color samples and the test form samples, etc. Having established the superiority of Model II, it is applied to develop a consultative design interface integrated with a professional CAD system in order to demonstrate the effectiveness of the proposed product design and image evaluation approach. The design system presented in this study enables a designer to predict the likely image tendencies of a designed product without the need to create and test a prototype model. Hence, he or she can make any design parameter modifications necessary to ensure that the finished product meets its specified image goals.

FUZZY LOGIC BASED DECISION MODEL FOR PRODUCT DESIGN

Abstract A fuzzy decision-making method for selecting an optimum design from various design alternatives is proposed. The development of a juicer is taken as an example in this study. The evaluation objectives are arrangd in a hierarchial structure with several levels. The relative contribution (weighting function) of each objective to the overall value of the solution and the rating or degree of approximation of a solution with respect to a given objective are quantified with the membership functions of a fuzzy set. A computer program built with a weighted generalized mean method is used to calculate the fuzzy probability level by level from the lowest-level objectives. After the fuzzy expected values of the top-level objectives are calculated, they are then used to make a decision quantitatively on selecting the optimal design alternative. This method can also be used to solve other design problems.

Fuzzy Set Theory Based Decision Model for Determining Market Position and Developing Strategy for Hospital Service Quality

Many crucial aspects of service management are multifaceted. However, the traditional approach to measuring complex dimensions such as service quality clearly is inadequate. Essentially, this study integrated the five dimensions of SERVQUAL and adopted a fuzzy set theory based research design. The five dimensions of SERVQUAL were tested for five hospitals using Fuzzy set theory to clarify the positioning of service quality in the healthcare market and suggest service strategy implementation priorities of service strategies. This result enables managers to collate the service strategy of the benchmarking hospital and competitors in the local market, and also permits hospital decision-makers to consider the weight of the five dimensions while modifying the service strategy. Such an approach can also clarify the fundamental strengths and weaknesses of service quality.

A reverse engineering based approach for product form design

Abstract A reverse engineering based approach for product form design is addressed in this article. In this method, the designer makes 3D product models based on his/her ideas with polyurethane or polystyrene foam first. The data points on the surface of the product are then measured using a non-contact 3D scan device, and the point clouds for 30 cross-sections of these products are obtained based on the measured information. New shapes are further generated with two different product models using four shape blending/morphing techniques. In this manner, the designer can generate creative product that fits user’s demand in a shorter time.

Forecasting and Evaluating the Tourist Hotel Industry Performance in Taiwan Based on Grey Theory

Although Grey theory is extensively adopted to construct the forecasting models for evaluating organisational performance, it is rarely used in the hotel industry. This study draws on the GM(1,1) model to accurately predict the coming years output value and on Grey relational analysis to select the best-performing hotels in Taiwan. Measures of hotel performance — including profit before tax, ROI before tax, revenue per employee, REVPAR, revenue per square meter, and occupancy rate — were collected from the Tourism Bureau in Taiwan. These data contain the performance of 56 international tourist hotels in 2002 and industry data from 1992 to 2005. Results in this study indicate that four-point GM(1,1) is the best model for predicting output value in the future. In addition, this investigation reveals the various competitive advantages and strategies in these top hotels, such as their appropriate site, higher price, and higher occupancy rate.