Optimization of user experience in interaction design through a Taguchi‐based hybrid approach

User experience (UX), which encompasses all aspects of a user’s interaction with an interactive product, has been recognized as central to interaction design. This paper proposes a Taguchi‐based hybrid approach to realize the optimal UX design. In this approach, design analysis is first used to identify design patterns and UX characteristics. According to the results, a Taguchi experiment is conducted and the signal‐to‐noise ratios are computed. Subsequently, the preference weights for the UX characteristics are obtained by using analytical hierarchy process‐based group decision making. A multiperformance characteristic index is then defined based on the gray relational grade (GRG) obtained through gray relational analysis. On the basis of the GRG, the optimal design can be obtained. A mobile health application design was used to demonstrate the proposed approach. The results show that this approach can effectively enhance UX quality and be used as a universal design approach for optimizing UX.     

Application of fuzzy-based Taguchi method to the optimization of extrusion of magnesium alloy bicycle carriers

By using fuzzy-base Taguchi method, this study investigates the optimal process parameters that maximize multiple performance characteristics index (MPCI) for hot extrusion of AZ31 and AZ61 magnesium alloy bicycle carriers. The larger-the-better quality characteristics of flattening strength and T-slot fracture strength as well as the smaller-the-better quality characteristic of extrusion load is considered in the MPCI. Through MPCI inference model, a manufacture method with less extrusion load and better mechanical properties under hot extrusion can be obtained. The signal-to-noise (S/N) ratios of the three quality characteristics??flattening strength, T-slot fracture strength and extrusion load??are calculated for the products based on experimental results. And the S/N ratio serves as the input variable to fuzzy control unit, and MPCI is a single output variable. The obtained MPCI is used to analyze optimal process parameters. This study finds combination of process parameters that optimizes MPCI, and conducts confirmatory experiments to prove the accuracy of optimal combination of process parameters thus selected. Finally, mechanical properties of AZ31, AZ61 magnesium alloy and A6061 aluminum alloy bicycle carriers are tested to identify differences among these three materials.     

Product attributes and user experience design: how to convey product information through user-centered service

The user experience (UX) is a critical issue in both the product design and service sector. Ensuring that customers can easily understand a product or service and thus ensuring higher satisfaction with the customer–product (service) interaction process is essential for survival among competitive industries. However, few studies have attempted to integrate all relevant factors into a comprehensive model of UX. The present study addresses this need by proposing a conceptual UX interaction model that incorporates the characteristics of usability and user interaction level based on quality of experience. A method to apply the model and the steps to implement the data collection and analysis are also proposed. The UX interaction model requires a systematic approach to: (1) decompose the product or service characteristics during a UX interaction process; (2) determine typology of UX items of each characteristic; and (3) select appropriate and feasible strategies to improve these UX items. A quantitative survey for mobile phone users was developed to investigate differences among types of UX and product characteristics. This study provides valuable empirical evidence on the UX interaction model for particular industries where superior quality service experiences are to be achieved.     

Optimization of bead geometry of submerged arc weld using fuzzy based desirability function approach

The present study highlights application of Taguchi’s robust design coupled with fuzzy based desirability function approach for optimizing multiple bead geometry parameters of submerged arc weldment. Fuzzy inference system has been adapted to avoid uncertainly, imprecision and vagueness in experimentation as well as in data analysis by traditional Taguchi based optimization approach. Detailed methodology and unique features of the proposed method has been highlighted through a case study. The said approach can efficiently be used in off-line quality control of any production process as well as automation of the process.     

The use of the Taguchi method with grey relational analysis to optimize the thin-film sputtering process with multiple quality characteristic in color filter manufacturing

The paper proposes an approach to improve the yield of Chrome (Cr) thin-film sputtering process of the black matrix (BM) in color filter manufacturing and to find the robust parameters of the process with multiple quality characteristics by using the Taguchi method combined with the grey relational analysis. The research considers the correlation between quality characteristics and applies the principal component analysis to eliminate the multiple co-linearity. The weights of the quality characteristics are determined by employing the entropy measurement method. Two quality characteristics and four control factors with three levels were selected. Based on the Taguchi quality design concept, a L9 orthogonal array table was chosen for the experiments. The confirmation experiment verifies the proposed grey-based Taguchi method has the ability to find out the optimal process parameters with multiple quality characteristics. Besides, manufacturing with the attained optimal process parameters can reduce the opportunities of repair and rework of Cr thin-film and raise the yield.     

基于灰色层次分析法的老年人APP 用户体验评价研究

为了提高老年人APP 的用户体验水平,提出一种基于灰色层次分析法(AHP)的老 年人APP 用户体验评价模型。首先,构建用户体验的评价体系;接着,通过AHP 计算评价指 标的权重;最后,采用灰色关联分析法(GRA)将用户体验的评价指标整合为灰色关联度,从而 根据灰色关联度选择最优方案。以移动医疗APP 作为案例,结果表明基于灰色AHP 的APP 用 户体验评价模型可以有效地评价老年人APP 的用户体验水平,为设计决策提供依据。     

A psychometric user experience model based on fuzzy measure approaches

User experience (UX) is considered a key quality of interactive products in today’s competitive mass markets and is of growing interest in both academia and industry. UX concerns the encounters a user has while interacting with products, systems, and services. It is ubiquitous, omnipresent, and dynamic in nature, referring to the non-quantifiable, subjective, affective-based, and context-dependent processes. UX is difficult for researchers to objectively and uniformly measure as it involves complex human perceptual interpretations of experiential responses with a certain degree of uncertainty, imprecision, and vagueness. Based on the user experience questionnaire (UEQ), this paper presents a psychometric UX model using fuzzy measure approaches, the purpose of which is to develop a metric for quantitative assessment of certain product UXs through a user experience index (UXI). This model enables researchers to understand users’ perceptions of the interactions that constitute qualities of using a specific product. An empirical study concerning the episodic UX measures of using a set of touch mice was conducted to verify the applicability and effectiveness of the proposed UX model. The theoretical and practical implications of the UX model are also discussed.     

Determining optimal levels of engineering characteristics in quality function deployment under multi-segment market

Customers often have various requirements and preferences on a product. A product market can be partitioned into several market segments, each of which contains a number of customers with homogeneous preferences. In this paper, a methodology which mainly involves a market survey, fuzzy clustering, quality function deployment (QFD) and fuzzy optimization, is proposed to achieve the optimal target settings of engineering characteristics (ECs) of a new product under a multi-segment market. An integrated optimization model for partitioned market segments based on QFD technology is established to maximize the overall customer satisfaction (OCS) for the market considering the weights of importance of different segments. The weights of importance of market segments and development costs in the model are expressed as triangular fuzzy numbers in order to describe the imprecision caused by human subjective judgement. The solving approach for the fuzzy optimization model is provided. Finally, a case study is provided for illustrating the proposed methodology.     

Using sketches and storyboards to assess impact of age difference in user experience

We compared two versions of a touch-screen digital thermostat using a framework encompassing several user experience (UX) characteristics, and here describe how the implementation of certain design factors (specialists, praises, tooltips and increased interactivity) was done on mixed-fidelity prototypes of the user interface. We illustrate how the experimental comparison, involving 20 university students and 20 older adults, revealed important differences in UX, including perceived ease of use, behavioral intentions, enjoyment, quality, satisfaction, trust and usability, measured mainly through established questionnaires.Analysis revealed that using that kind of artifacts is a very cost effective way to elicit interesting and useful results; many UX variables are significantly affected by design factors and by age differences, as expected; effects of design factors go well beyond usability and therefore could not be caught by running an investigation focused only on usability.Age difference matters: older adults do not respond to addition of specialists, praises and tooltips as younger users do. We argue that potential benefits of these design choices are outweigh by the increase in complexity of the user interface.From a methodological viewpoint we suggest using a particular array of UX characteristics and metrics when testing mixed-fidelity prototypes. Not all the metrics that we adopted were equally useful, and in particular perceived usability, subjective mental effort, and emotions did not help us highlighting differences.     

Fuzzy cognitive map based quality function deployment approach for dishwasher machine selection

The traditional quality function deployment (QFD) approach deals with the weights of customer requirements (CRs), relationships among CRs and design requirements (DRs), correlation among DRs by using crisp values. This paper uses fuzzy numbers to improve the drawbacks of the traditional QFD method because fuzzy numbers enable to make consistent decisions in uncertain environment to decision makers. The existing papers handle a simple multiplication operation to calculate the correlation among CRs and the correlation among DRs. This study proposes fuzzy cognitive map (FCM) approach to calculate these correlations so that FCM is a successful method to handle the interactions among criteria. This paper contributes to the literature by integrating QFD approach and fuzzy cognitive map approach. The weights of DRs are defined in the result of the proposed QFD approach. These weights are used to evaluate the dishwasher machine alternatives in intuitionistic fuzzy VIKOR method. Intuitionistic fuzzy number (IFS) ensures to handle more information than type-1 fuzzy number to describe the fuzziness and the uncertainty of the real life world. Finally, the proposed approach has been implemented to a dishwasher machine selection in order to test its validity.     

Solving the multi-response problem in Taguchi method by benevolent formulation in DEA

The Taguchi method is an efficient approach for optimizing a single quality response. In practice, however, most products/processes have more than one quality response of main interest. Recently, the multi-response problem in the Taguchi method has gained a considerable research attention. This research, therefore, proposes an efficient approach for solving the multi-response problem in the Taguchi method utilizing benevolent formulation in data envelopment analysis (DEA). Each experiment in Taguchi’s orthogonal array (OA) is treated as a decision making unit (DMU) with multiple responses set inputs and/or outputs. Each DMU is evaluated by benevolent formulation. The ordinal value of the DUM’s efficiency is then used to decide the optimal factor levels for multi-response problem. Three frequently-investigated case studies are adopted to illustrate the proposed approach. The computational results showed that the proposed approach provides the largest total anticipated improvement among principal component analysis (PCA), DEA based ranking approach (DEAR) and other techniques in literature. In conclusion, the proposed approach may provide a great assistant to practitioners for solving the multi-response problem in manufacturing applications on the Taguchi method.     

Multi-objective multi-population biased random-key genetic algorithm for the 3-D container loading problem

The container loading problem (CLP) has important industrial and commercial application for global logistics and supply chain. Many algorithms have been proposed for solving the 2D/3D container loading problem, yet most of them consider single objective optimization. In practice, container loading involves optimizing a number of objectives. This study aims to develop a multi-objective multi-population biased random-key genetic algorithm for the three-dimensional single container loading problem. In particular, the proposed genetic algorithm applied multi-population strategy and fuzzy logic controller (FLC) to improve efficiency and effectiveness. Indeed, the proposed approach maximizes the container space utilization and the value of total loaded boxes by employing Pareto approach and adaptive weights approach. Numerical experiments are designed to compare the results between the proposed approach and existing approaches in hard and weak heterogeneous cases to estimate the validity of this approach. The results have shown practical viability of this approach. This study concludes with discussions of contributions and future research directions.     

Improving the lighting performance of a 3535 packaged hi-power LED using genetic programming,quality loss functions and particle swarm optimization

The lighting performance of a 3535 packaged hi-power LED (light-emitting diode) is mainly influenced by its geometric design and the refractive properties of its materials. In the past, engineers often determined the settings of the geometric parameters and selected the refractive properties of the materials through a trial-and-error process based on the principles of optics and their own experience. This procedure was costly and time-consuming, and its use did not ensure that the settings of the design parameters were optimal. Therefore, this study proposed a hybrid approach based on genetic programming (GP), Taguchi quality loss functions, and particle swarm optimization (PSO) to solve the multi-response parameter design problems. The feasibility and effectiveness of the proposed approach was demonstrated by a case study on improving the lighting performance of an LED. The confirmation results showed that all of the key quality characteristics of an LED fulfill the required specifications, and the comparison found that the proposed hybrid approach outperforms the traditional Taguchi method in solving this multi-response parameter design problem. The proposed hybrid approach can be extended to solve parameter design problems with multiple responses in various application fields.     

Combining VIKOR with GRA techniques to evaluate service quality of airports under fuzzy environment

The aim of this paper was to present an effective approach for evaluating service quality of Northeast-Asian international airports by conducting customer surveys. In general, evaluation of service quality is a complex multicriteria decision-making (MCDM) problem; therefore, a complex decision process is often involved in which multiple requirements and fuzzy conditions have to be taken into consideration simultaneously. By combining concepts of VIKOR and grey relational analysis (GRA), a new fuzzy MCDM method was proposed to deal with the evaluation of service quality problems in the international airports. This model was solved by an effective algorithm, which incorporated the decision-maker’s attitude and/or preference for customers’ assessments on weights and performance ratings of each criterion. An empirical study for evaluating service quality of seven major Northeast-Asian international airports was put forth to illustrate an application of the proposed model. The study results showed that this approach is an effective means for tackling MCDM problems involving subjective assessments of qualitative attributes in a fuzzy environment.     

An integrated neuro-genetic approach incorporating the Taguchi method for product design

Product design is a multidisciplinary activity that requires the integration of concurrent engineering approaches into a design process that secures competitive advantages in product quality. In concurrent engineering, the Taguchi method has demonstrated an efficient design approach for product quality improvement. However, the Taguchi method intuitively uses parameters and levels in measuring the optimum combination of design parameter values, which might not guarantee that the final solution is the most optimal. This work proposes an integrated procedure that involves neural network training and genetic algorithm simulation within the Taguchi quality design process to aid in searching for the optimum solution with more precise design parameter values for improving the product development. The concept of fractals in computer graphics is also considered in the generation of product form alternatives to demonstrate its application in product design. The stages in the general approach of the proposed procedures include: (1) use of the Taguchi experimental design procedure, (2) analysis of the neural network and genetic algorithm process, and (3) generation of design alternatives. An electric fan design is used as an example to describe the development and explore the applicability of the proposed procedures. The results indicate that the proposed procedures could enhance the efficiency of product design efforts by approximately 7.8%. It is also expected that the proposed design procedure will provide designers with a more effective approach to product development.     

属性权重完全未知的犹豫模糊双边匹配决策

针对基于犹豫模糊属性（HFV）信息且权重完全未知的双边匹配（TSM）问题,提出一种多属性匹配决策方法。首先,根据双方主体给出的犹豫模糊多属性评价值,通过最大化各属性之间的离差和从而确定属性权重;然后,由犹豫模糊有序加权平均算子集结多属性及权重信息获得双方的匹配度;进而建立一种基于匹配度的多目标优化模型,并使用极大极小法转化为单目标优化模型求解得到匹配方案;最后,进行实例分析和对比,所提方法得到目标函数值分别为1.689和1.575,且匹配解唯一。实验结果表明,所提方法可避免因主观确定目标函数权重而产生不唯一匹配解。     

Application of SVR,Taguchi loss function,and the artificial bee colony algorithm to resolve multiresponse parameter design problems: a case study on optimizing the design of a TIR lens

Multiresponse parameter design problems have become increasingly important and have received considerable attention from both researchers and practitioners since there are usually several quality characteristics that must be optimized simultaneously in most modern products/processes. This study applies support vector regression (SVR), Taguchi loss function, and the artificial bee colony (ABC) algorithm to develop a six-staged procedure that resolves these common and complicated parameter design problems. SVR is used to model the mathematical relationship between input control factors and output responses, and the ABC algorithm is used to find the optimal control factor settings by searching the well-constructed SVR models in which the Taguchi loss function is applied to evaluate the overall performance of a product/process. The feasibility and effectiveness of the proposed approach are demonstrated via a case study in which the design of a total internal reflection (TIR) lens is optimized while fabricating an MR16 light-emitting diode lamp. Experimental results indicate that the proposed solution procedure can provide highly robust design parameter settings for TIR lenses that can be directly applied in real manufacturing processes. Comparisons with the Taguchi method reveal that the Taguchi method is an undesirable and inappropriate method for resolving multiple-response parameter design problems, while the ABC algorithm can search the solution spaces in continuous domains modeled via SVR instead of in the limited discrete experiment levels, thus finding a more robust design than that obtained by the traditional analysis of variance. Consequently, the proposed integrated approach in this study can be considered feasible and effective and can be popularized as a useful tool for resolving general multiresponse parameter design problems in the real world.     

一种基于组合赋权法的Web服务选择策略*

针对Web服务选择中服务请求偏好权重表达的模糊性及服务质量(QoS)属性值间存在的相互制约关系等问题,提出一种基于组合赋权法的Web服务选择策略。首先利用模糊层次分析法(FAHP)和主成分分析法(PCA)分别计算主观QoS权重和客观QoS权重;然后综合主、客观QoS权重利用组合赋权法(CWA)计算服务请求的综合QoS权重;最后提出一种综合评价函数,以保障所选择的服务在满足服务请求偏好的基础上,能更准确地反映候选Web服务总体QoS水平。实例分析表明该方法是有效的。     

Simultaneous Constrained Model Predictive Control and Identification of DARX Processes

In this work, we formulate a new approach to simultaneous constrained model predictive control and identification (MPCI). The proposed approach relies on the development of a persistent excitation (PE) criterion for processes described by DARX models. That PE criterion is used as an additional constraint in the standard on-line optimization of MPC. The resulting on-line optimization problem of MPCI is handled by successively solving a series of semi-definite programming problems. Advantages of MPCI in comparison to other closed-loop identification methods are (a) Constraints on process inputs and outputs are handled explicitly, (b) Deterioration of output regulation is kept to a minimum, while closed-loop identification is performed. The applicability of the method is illustrated by a number of simulation studies. Theoretical and computational issues for further investigation are suggested.     

Defining user experience goals to guide the design of industrial systems

The key prerequisite for experience-driven design is to define what experience to design for. User experience (UX) goals concretise the intended experience. Based on our own case studies from industrial environments and a literature study, we propose five different approaches to acquiring insight and inspiration for UX goal setting: Brand, Theory, Empathy, Technology, and Vision. Each approach brings in a different viewpoint, thus supporting the multidisciplinary character of UX. The Brand approach ensures that the UX goals are in line with the company's brand promise. The Theory approach utilises the available scientific knowledge of human behaviour. The Empathy approach focuses on knowing the actual users and stepping into their shoes. The Technology approach considers the new technologies that are being introduced and their positive or negative influence on UX. Finally, the Vision approach focuses on renewal, introducing new kinds of UXs. In the design of industrial systems, several stakeholders are involved and they should share common design goals. Using the different UX goal-setting approaches together brings in the viewpoints of different stakeholders, thus committing them to UX goal setting and emphasising UX as a strategic design decision.