A customer-involved design concept evaluation based on multi-criteria decision-making fusing with preference and design values

Customer-involved design concept evaluation (CDCE) is a key issue for developing new product welcomed by customers, but seldom studies have considered the integrated utilization of objective design values (DVs) and customers’ subjective preference values (PVs). Our previous study has attempted to fuse with DVs and PVs in CDCE, while this is only limit to few situations under benefit-like and cost-like evaluation criteria. For better CDCE, this study further fuses with DVs and PVs in more complex situations, and puts forward an improved version of rough distance to redefined ideal solution (RD-RIS II) in multi-criteria decision-making (MCDM) scope to select the optimal concept. Different from old RD-RIS in previous study, RD-RIS II not only supports the ideal solution definition (ISD) processes for both quantitative and qualitative evaluation criteria, and but more importantly, it utilizes more useful information (value, feature, number and impact) from DVs and PVs to redefine the new positive ideal solution (PIS) and negative ideal solution (NIS). Through the rough distance calculation, the alternative which is close to PIS and far away from NIS is selected as the best one. Besides, the feasibility of RD-RIS II is validated via the application in real design evaluation example, and three empirical comparisons confirm that RD-RIS II makes more comprehensive decision than other MCDM-based evaluation methods, especially when the choices of customers and designers are conflicting, therefore it could provide more reasonable evaluation result which has better credibility and stability than others.     

Design concept evaluation considering information reliability,uncertainty, and subjectivity: An integrated rough-Z-number-enhanced MCGDM methodology

Design concept evaluation plays a vital role in new product development due to its critical impact on successive design activities as well as the novelty and competence of the final product. Lots of decision-making techniques have been developed for the design concept evaluation under various contexts. However, existing methods mainly focus on the evaluation under precise environments or fuzzy set scenarios. Whereas in reality, most risk assessments are derived from experts’ subjective judgments. The reliability of the evaluation is rarely taken into consideration. To bridge this gap, this study proposes a rough-Z-number-enhanced MCGDM (multi-criteria group decision-making) to resolve the design concept evaluation considering information reliability, uncertainty, and subjectivity. A rough-Z-number is introduced to incorporate into the MCGDM framework to represent the individual evaluation and aggregate group risk assessments. A rough-Z-number-based AHP (analytic hierarchy process) is presented to determine the criteria weights. A rough-Z-number-based MABAC (multi-attributive border approximation area comparison) is proposed to rank the design concepts. Experiments and comparative analyses demonstrate the advantage of the rough-Z-number extended MCGDM in complex and uncertain decision-making environments. With the rough-Z-number-based enhancement, the information reliability, uncertainty, and subjectivity in design concept evaluation are well characterized.     

An integrated decision-making method for product design scheme evaluation based on cloud model and EEG data

Selecting the optimal design scheme is a vital task in the product design area. It not only improves the performance of the product, but also leads to the greatest satisfaction of customers. However, existing methods express qualitative evaluation information roughly, and none of them has taken the implicit psychological states of customers into consideration. Therefore, an integrated decision-making method for product design scheme evaluation is proposed. This method applies the cloud model to facilitate the evaluation process of experts and uses the EEG data to reveal the psychological states of customers. Benefit from the probability theory and fuzzy set theory, the cloud model deals with the fuzziness and randomness simultaneously. It can decrease the cognitive discrepancy of experts and allow the information distortion to be neutralized to a great extent. Since the experts are not the final users of products, the evaluation results from experts cannot truly reflect the psychological states of customers when they use the product. An experiment is designed to collect the EEG data which can reveal the implicit psychological states of customers. The recorded data are segmented based on the operation process and tagged with the self-reported psychological states. Subsequently, the wavelet packet decomposition is applied and the sample entropy of each EEG frequency band is extracted as the feature. Taking advantage of the random forest classifier, the psychological states of customers can be classified with the average accuracy of 90.76%. This study can lead to a practical system for automatic assessment of psychological states in future applications. The evaluation process of elevator design schemes is conducted as a case study to illustrate the feasibility of the proposed method.     

基于模糊贝叶斯决策的核心概念抽取方法

为了提高特定领域核心概念抽取的效率,提出一种基于模糊贝叶斯决策的核心概念抽取方法。在特定领域内随机抽取大量文本并进行分词获取候选概念;然后采用TF-IDF算法计算候选概念的各项特征值,采用概念隶属度归一化处理候选概念特征值;最终通过贝叶斯决策计算候选概念为核心概念的概率。在财经领域相关数据集上进行文本核心概念抽取的实验结果表明,所提方法的F1值相比TextRank、LDA主题模型、word2vec词聚类模型、RNN、LSTM等的F1值有所提高。综合实验结果表明,基于模糊贝叶斯决策的核心概念抽取方法在核心概念抽取方面表现较好。     

An integrated AHP and VIKOR for design concept evaluation based on rough number

Design concept evaluation at the early stage of product design has been widely recognized as one of the most critical phases in new product development as it determines the direction of the downstream design activities. However, the information at this stage is mainly subjective and imprecise which only depends on experts’ judgments. How to handle the vagueness and subjectivity in design concept evaluation becomes a critical issue. This paper presents a systematic evaluation method by integrating rough number based analytic hierarchy process (AHP) and rough number based compromise ranking method (also known as VIKOR) to evaluate design concepts under subjective environment. In this study, rough number is introduced to aggregate individual judgments and preferences and deal with the vagueness in decision-making. A novel AHP based on rough number is presented to determine the weight of each evaluation criterion. Then an improved rough number based VIKOR is proposed to evaluate the design concept alternatives. Sensitivity analysis is conducted to measure the impact of the decision makers’ risk to the final evaluation results. Finally, a practical example is put forward to validate the performance of the proposed method. The result shows that the proposed decision-making method can effectively enhance the objectivity in design concept evaluation under subjective environment.     

基于证据距离的改进DS/AHP 多属性群决策方法

证据推理/层次分析(DS/AHP)方法采用了AHP法的层次结构模型和证据理论的分析过程,为不确定多属性决策问题的解决提供了新思路,但其在构造知识矩阵中用0代表残缺信息是不合理的.鉴于此,对DS/AHP方法进行了改进,并将改进后的方法拓展到群决策中,研究了专家群体权向量的确定方法.具体地,引入证据距离的概念,通过计算专家证据的综合距离来对专家赋权,体现了群决策中的多数人规则.     

Integrated rough VIKOR for customer-involved design concept evaluation combining with customers’ preferences and designers’ perceptions

Customer-involved design concept evaluation (DCE) allows customers to take part in evaluating the design alternatives to get more popular design concept. Traditional customer-involved DCE methods still focus on the collection of customer responses and only consider cost and benefit characteristics of design criteria in multi-criteria decision-making (MCDM) based evaluation process. Few studies have customized the decision-making algorithms specifically aimed at customers’ preferences. This paper further explores the customers’ influences in the early stages of the product design development, and proposes a new rough number based MCDM model (i.e., VIKOR) incorporating customers’ preferences for design specifications along with designers’ perceptions for the characteristics of design criteria (cost and benefit) to perform concept evaluation under subjective environment, and this proposed method is named as integrated rough VIKOR (IR-VIKOR). The objective of this study is to identify the best design concept which maximizes the satisfactions of expectations from most customers as well as conforms to the characteristics of design criteria. Firstly, Shannon entropy is used to obtain the weightings and relative importance ratings of design criteria from the customers’ preferences. Secondly, the customers’ preferences for design attribute values, the importance ratings of design criteria and the characteristics of design criteria are combined together to define the ideal solutions to calculate the rough evaluation index of each design alternative in IR-VIKOR, and finally the ranking result is provided by IR-VIKOR to determine the best design concept. A practical design example is introduced to illustrate the evaluation process of this proposed method, and the empirical comparisons are further carried out to validate its superiority for DCE. Through the sensitivity analysis experiments including i) inside IR-VIKOR, and ii) between IR-VIKOR and other classical MCDM methods, the proposed method is proved to be a reliable and feasible customer-involved DCE approach.     

Product concept evaluation and selection using data mining and domain ontology in a crowdsourcing environment

For product design and development, crowdsourcing shows huge potential for fostering creativity and has been regarded as one important approach to acquiring innovative concepts. Nevertheless, prior to the approach could be effectively implemented, the following challenges concerning crowdsourcing should be properly addressed: (1) burdensome concept review process to deal with a large amount of crowd-sourced design concepts; (2) insufficient consideration in integrating design knowledge and principles into existing data processing methods/algorithms for crowdsourcing; and (3) lack of a quantitative decision support process to identify better concepts. To tackle these problems, a product concept evaluation and selection approach, which comprises three modules, is proposed. These modules are respectively: (1) a data mining module to extract meaningful information from online crowd-sourced concepts; (2) a concept re-construction module to organize word tokens into a unified frame using domain ontology and extended design knowledge; and (3) a decision support module to select better concepts in a simplified manner. A pilot study on future PC (personal computer) design was conducted to demonstrate the proposed approach. The results show that the proposed approach is promising and may help to improve the concept review and evaluation efficiency; facilitate data processing using design knowledge; and enhance the reliability of concept selection decisions.     

An improved iterative stochastic multi-objective acceptability analysis method for robust alternative selection in new product development

Alternative selection in new product development (NPD) is a multi-criteria decision-making (MCDM) problem. It usually starts with incomplete, imprecise or even partially missing information. Currently, most existing methods in dealing with this problem cannot work well if required information is incomplete or missing. It is acknowledged that stochastic multi-objective acceptability analysis (SMAA) can be applied to address MCDM problem with incomplete preference information and uncertain criteria measurements. In SMAA, alternatives are evaluated based on SMAA measurements (acceptability index, central weight vector and confidence factor). The discriminability of SMAA for the optimum alternative heavily depends on differences of SMAA measurements among different alternatives. Usually, a large number of alternatives and high level of uncertainty are involved in alternative selection in NPD. In this situation, the differences among SMAA measurements are not obvious, and therefore SMAA cannot deal with such problem very well. To this end, this paper proposes an improved SMAA method called Iterative-SMAA (I-SMAA) for alternative selection in NPD. In the I-SMAA, an iterative multi-step decision-making process is suggested to improve differences of SMAA measurements among different alternatives, and thus assist decision makers (DMs) to positively discern from the most preferred alternative. To enhance the decision-making efficiency, sensitive criteria are acquired in each iteration by ranking sensitivity analysis. DMs are guided to provide partial preference information and give more accurate criteria measurements for sensitive criteria rather than all criteria. Eventually, to verify the proposed method, a numerical example of the existing literature is solved with the method, and the results are compared. And then, a practical example of a preparation equipment for coal samples is further employed to verify the practicability of the proposed I-SMAA.     

基于结构熵权 TOPSIS 法的产品设计方案评估研究

为了提高企业在产品设计方案评估阶段进行合理决策的效率,提出了一种基于结 构熵权双基点法(TOPSIS)的产品设计方案评估方法。在评估流程中,首先确定产品设计方案评 价指标,专家对各评价指标进行重要度排序,在得到了“典型排序”后经过结构熵计算和“认识盲 度”计算,得出各评价指标的权重,以替代双基点法中专家主观设定的权重系数;其次,构建设 计方案各指标加权标准决策的矩阵,进而求得各指标的理想解,基于以上可得到各设计方案距 离理想解的相对贴近度,经对比后确定设计方案的排序情况,从而得到各方案的优劣。最后, 将该评估流程应用于录音笔设计方案评估的决策中,验证了该方法的可行性与有效性。     

A hybrid evaluation method for human error probability by using extended DEMATEL with Z-numbers: A case of cargo loading operation

Human error probability (HEP) evaluation and prediction is one of the most significant tasks to enhance human reliability in marine industry. Among various kinds of HEP evaluation techniques, the Human Error Assessment and Reduction Technique (HEART) technique is regarded as an effective and empirical tool that has been widely adopted in various fields. However, current HEART techniques are insufficient to address HEP evaluation problem in which the self-assurance of expert's judgment and inter-dependencies between Error-producing conditions (EPCs) are considered. Therefore, the purpose of this paper is to develop a hybrid HEART framework (H-HEART-F) to address this problem by integrating Z-numbers and the decision-making trial and evaluation laboratory (DEMATEL) method. First, the Z-numbers are introduced to model the uncertainty and self-assurance of evaluation information from various experts. Then, the Z-number power weighted average (Z-PWA) operator is proposed to aggregate the individual evaluation information into a group direct influenced matrix. Next, an extended DEMATEL method based on possibility degree measure is constructed to determine the proportion of effect of each EPC by considering the self-assurance of expert's judgment and inter-dependencies between EPCs. Finally, the HEP estimation for the cargo loading operation in oil or chemical tanker ship is presented to demonstrate the availability and feasibility of the H-HEART-F. After that, the sensitivity analysis and comparison study are conducted to further illustrate the reasonableness and effectiveness of the proposed method.     

应用Vague优化决策方法对小麦新品种综合评估

提出新的从单值数据向Vague数据的转化公式,提出新的Vague集U和V之间的相似度量公式。综合现有的方法,得到Vague优化决策方法。应用Vague优化决策方法对小麦新品种进行评估,结果是令人满意的。     

Affective judgment in creative design: A method of fitness evaluation to the problem/solution spaces

A method of fitness evaluation to the problem/solution spaces is proposed based on the affective judgment in creative design. Six experienced designers and one-hundred-one users participated in a set of exploratory experiments on affective judgement of automobile design. From the experimental data, we identify the differences in designer's affective appeal in a design and user's affective response to the design. From data analysis, we confirm the general validity of that the ‘creative’ aspect of design can be described by introducing the notions of ‘default’ and ‘surprise’ problem/solution spaces. The affective judgments based on the expectations of designers and users are shown to be an effective alternative to quantitative metrics in design evaluation and concept selection. The presented findings suggested that the success and creativity are not the same, the goal of design practice is to find solutions that are both creative and successful.     

基于多层次灰色综合评价法的工业设计方案优选决策模型及其应用

为辅助企业在产品设计方案评估阶段进行合理地决策,减少设计的盲目性和主观性,基于多层次灰色综合评价法构建了工业产品设计方案优选决策模型.在评价流程中,首先依据层次分析法(AHP)与熵权法通过定性、定量分析,合理地进行评价指标权重系数的确定.其次,采用灰色关联度分析法对各设计方案进行灰色加权关联度的计算,确定其排序,并依据...     

Product concept generation and selection using sorting technique and fuzzy c-means algorithm

Product conceptualization is regarded as a key activity in new product development (NPD). In this stage, product concept generation and selection plays a crucial role. This paper presents a product concept generation and selection (PCGS) approach, which was proposed to assist product designers in generating and selecting design alternatives during the product conceptualization stage. In the PCGS, general sorting was adapted for initial requirements acquisition and platform definition; while a fuzzy c-means (FCM) algorithm was integrated with a design alternatives generation strategy for clustering design options and selecting preferred product concepts. The PCGS deliberates and embeds a psychology-originated method, i.e., sorting technique, to widen domain coverage and improve the effectiveness in initial platform formation. Furthermore, it successfully improves the FCM algorithm in such a way that more accurate clustering results can be obtained. A case study on a wood golf club design was used for illustrating the proposed approach. The results were promising and revealed the potential of the PCGS method.     

A method of constructing an inspiration library driven by user-perceived preference evaluation data for biologically inspired design

Biologically inspired design (BID) is one of the common methods for product design. To solve the problem of inaccurate acquisition of inspirational creatures due to the lack of user perception preference analysis, a data-driven intelligent service model for BID considering user perception needs is proposed based on Kansei engineering. Firstly, by extracting the perceptual features of creatures from the semantic source elements of products through mapping and encodes them, we proposed a data acquisition method based on intuitionistic fuzzy sets considering different customer preference distributions, bridging the gap caused by the asymmetry between designers and users. Secondly, the functional relationship between biometric features and user-perceived attributes is identified and predicted, and a predictive model of biodata considering user preferences is obtained by multiple linear regression analysis. Finally, based on the data clustering and reorganization theory to understand the organization and dynamics of the database, the construction of a BID library was completed, and the design resources in the library were used as analyzed knowledge for designers to plan design activities. Taking the bionic design of a UAV product as an example, a prototype of a computer-aided design service system was developed based on the theory proposed in the article, and the analyzed knowledge was used to improve the efficiency and science of the design, effectively verifying the usefulness of this study for design. To a certain extent, this study addresses the problem of cognitive limitations of designers and cognitive differences between designers and users, promotes the application of bioinspiration in product design, and improves the marketability of design solutions.     

An ideation method for generating new product ideas using TRIZ,concept mapping,and fuzzy linguistic evaluation techniques

The quality of initial ideas is considered a critical determinant for successful new product development (NPD). This study presents an ideation method for generating new product ideas. The aims of the proposed method are (1) to clarify and identify potential problems involved in the knowledge domain of the product design through the Su-field enhanced concept mapping diagram; (2) to abstract inventive problems and generate novel product ideas by means of the theory of inventive problem solving (TRIZ) methodology; and, (3) to develop an effective decision aiding method for evaluating alternative ideas and determining promising product ideas using fuzzy linguistic evaluation techniques. The applicability of the ideation method is demonstrated through a case study of an air purifier design. The theoretical and practical implications of the ideation method are also discussed.     

基于复合幂函数修正G1法的商户综合评价

针对多指标综合评价问题中主客观权重相悖时客观权重淹没主观权重的问题,以G1法和客观赋权法为基础,提出了复合幂函数修正G1法的组合赋权模型。首先,建立指标体系并通过G1法确定各指标主观排序和主观初始向量;然后,利用客观赋权法计算各指标客观向量;其次,在不改变主观排序的情况下利用复合幂函数算出主客观结合的综合权重;最后,利用各指标标准化后的值和综合权重计算综合评价值。采用大众点评网的商户数据进行综合评价实验：该模型的均方根误差（RMSE）为3.891,均低于G1-熵权法的8.818和标准差修正G1法的4.752,且覆盖率优于两种对比方法;分别修改主观初始向量和主观排序进行对比实验,修改主观排序的均方根误差为5.430,高于修改主观初始向量的1.17。实验结果表明,该模型得到的评价值与大众点评网官方的评分的一致性较高,且该模型弱化了主观初值对评分结果的影响,体现了主观排序的基础作用。     

Conceptual design evaluation considering the ambiguity semantic variables fusion with conflict beliefs: An integrated Dempster-Shafer evidence theory and intuitionistic fuzzy -VIKOR

Quantifying the uncertain linguistic evaluation from decision-makers (DMs) is one of the most challenging parts in the conceptual design decision. Although fuzzy decision models have been widely used to capture potential uncertainty by assigning a fuzzy term with the certain belief, the ambiguity subjective evaluation of semantic variables with conflict beliefs derived from DMs have not been well addressed. To solve this drawback, a concept decision model based on Dempster-Shafer (DS) evidence theory and intuitionistic fuzzy -Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) considering the ambiguity semantic variables fusion is proposed. Firstly, by incorporating semantic variables of intuitionistic fuzzy sets (IFSs), the diversified semantic judgments and its belief will be taken into account to form an ambiguity semantic initial decision matrix; secondly, the DS combination rule will be used to fuse the different semantic variables of multi-DMs in each scheme, update the belief of each semantic variable, and then the semantic fusion value matrix of the scheme will be constructed; finally, the weight of each evaluation objective will be calculated based on the value matrix and information entropy model, IFS-VIKOR model will be constructed to rank the concepts. A case study of the tree climbing and trimming machine will be employed to verify the proposed decision model. This decision model considering diversifying semantic variables and the conflict belief is proven to be effective compared with the IFS-SAW and ISF-TOPSIS.