《感性工程》课程教学课件（Kansei Engineering）01Day Kansei Evaluation

感性工程Kansei EngineeringDay 1: Kansei EvaluationNovember20,2017YoshiteruNAKAMORl,ProfessorEmeritusJapanAdvanced Institute of ScienceandTechnology

Kansei Engineering Day 1: Kansei Evaluation November 20, 2017 Yoshiteru NAKAMORI, Professor Emeritus Japan Advanced Institute of Science and Technology 感性工程

Lecturer:NAKAMORl,Yoshiteru中森义辉石川Academicbackground:Ishikawa东京神户Tokyo.PhDinAppliedMathematics,KyotoUniversity,1980KobeKyoto京都Professionalcareer:Osaka大阪:AppliedMathematics,KonanUniversity,Kobe,1981-1997.KnowledgeScience,JapanAdvancedInstituteofScienceandTechnology,Ishikawa,1998-2015:(VisitingProfessor,InstituteofSystemsEngineering,DalianUniversityofTechnology,Dalian,since1992).(Lecturer,SchoolofManagement,UniversityofChineseAcademyofSciences,Beijing,since2014).Internationalsocieties::President,InternationalSocietyforKnowledgeandSystemsSciences,2003-2008:VicePresident,InternationalFederationofSystemsResearch,2008-2010.Fellow,theInternationalAcademyforSystemsandCyberneticsSciences,2010-

• Academic background: • PhD in Applied Mathematics, Kyoto University, 1980 • Professional career: • Applied Mathematics, Konan University, Kobe, 1981-1997 • Knowledge Science, Japan Advanced Institute of Science and Technology, Ishikawa, 1998-2015 • (Visiting Professor, Institute of Systems Engineering, Dalian University of Technology, Dalian, since 1992) • (Lecturer, School of Management, University of Chinese Academy of Sciences, Beijing, since 2014) • International societies: • President, International Society for Knowledge and Systems Sciences, 2003-2008 • Vice President, International Federation of Systems Research, 2008-2010 • Fellow, the International Academy for Systems and Cybernetics Sciences, 2010- Lecturer: NAKAMORI, Yoshiteru 2 中森义辉 Tokyo Ishikawa Osaka 东京 大阪 石川 Kobe 神户 Kyoto 京都

Keywords·Kansei(Japanesepronunciationof感性)·(English)sensibility,sensitivity,emotion,affection,feeling,impression:An individualsubjectiveimpressionfromacertainartifact,environmentorsituationusingallsensesofsight,hearing,feeling,smell,andtaste紧漆Compact,butrelaxing但放松·KanseiEngineering（感性工程）:Anacademicfieldtryingtoclarifythecorrelationbetweenconsumers'impressionsforproducts and the physical characteristics of products, and utilize it for productdesign

• Kansei (Japanese pronunciation of 感性) • (English) sensibility, sensitivity, emotion, affection, feeling, impression • An individual subjective impression from a certain artifact, environment or situation using all senses of sight, hearing, feeling, smell, and taste. • Kansei Engineering (感性工程) • An academic field trying to clarify the correlation between consumers’ impressions for products and the physical characteristics of products, and utilize it for product design. Keywords 3 Compact, but relaxing 紧凑 但放松

A recommendation system (for Electronic CommerceKanseiEvaluationProduct typesDataATueSearchwordsWedMathematicalKanseiengine bannerModelsconnectedtoourcomputerPriorityThuApotterydealerwebsiteRecommendedproducts (Top5)ProductDetailsFrRecommendationPromotionStoriesMethods

A recommendation system (for Electronic Commerce) Kansei engine banner connected to our computer A pottery dealer website Product types Search words Priority Recommended products (Top 5) Product Details 4 Kansei Evaluation Data Mathematical Models Promotion Stories Recommendation Methods Tue Wed Thu Fri

Schedule08:00-08:45;08:55-09:4010:10-10:55;11:05-11:5014:00-14:45;14:55-15:4016:00-16:45;16:55-17:40(Introduction）感性工程(Method)多变量分析(Exercise)评级量表Day1Kansei EngineeringMultivariate AnalysisCreation of Rating Scales(Introduction）模糊集理论(Exercise)模糊推理(Method)可能性模型(Experiment）感性评价实验Day2Fuzzy ReasoningPossibility ModelsFuzzy Set TheoryKansei Evaluation ExperimentDay(Experiment）感性建模(Groupwork）感性推荐(Presentation）模型和推荐3ModelsandRecommendationKansei Modeling inGroupsKansei Recommendation(Exercise)产品推荐(Method)非加性聚集Day(Method)）有序加权平均(Exercise)产品推荐4ProductRecommendationProductRecommendationOrderedWeighted AveragingNon-additiveAggregation(Method)感性故事(Introduction）知识创造(Groupwork）感性故事(Presentation）感性故事Day5KnowledgeCreationCreation of KanseiStoriesCreation of KanseiStoriesCreationof KanseiStoriesExercise:10points×4ReportofExperiment:20points×1Presentation:20points×25

Schedule 08:00-08:45; 08:55-09:40 10:10-10:55; 11:05-11:50 14:00-14:45; 14:55-15:40 16:00-16:45; 16:55-17:40 Day 1 (Introduction) 感性工程 Kansei Engineering (Method) 多变量分析 Multivariate Analysis (Exercise) 评级量表 Creation of Rating Scales Day 2 (Introduction) 模糊集理论 Fuzzy Set Theory (Exercise) 模糊推理 Fuzzy Reasoning (Method) 可能性模型 Possibility Models (Experiment) 感性评价实验 Kansei Evaluation Experiment Day 3 (Experiment) 感性建模 Kansei Modeling in Groups (Group work) 感性推荐 Kansei Recommendation (Presentation) 模型和推荐 Models and Recommendation Day 4 (Method) 有序加权平均 Ordered Weighted Averaging (Exercise) 产品推荐 Product Recommendation (Method) 非加性聚集 Non-additive Aggregation (Exercise) 产品推荐 Product Recommendation Day 5 (Introduction) 知识创造 Knowledge Creation (Method) 感性故事 Creation of Kansei Stories (Group work) 感性故事 Creation of Kansei Stories (Presentation) 感性故事 Creation of Kansei Stories 5 Exercise: 10 points×4 Report of Experiment: 20 points×1 Presentation: 20 points×2

Today's Contents1.KanseiEngineering感性工程.The processes of Kansei Engineering and examples2.MultivariateAnalysis多变量分析: From Kansei evaluation data to models (knowledge)3.Exercise1:CreationofRatingScales评级量表Kanseiwords感性词愁绪MelancholyCheerful快乐1234567Rating scaleBipolarscale双极规模

1. Kansei Engineering 感性工程 • The processes of Kansei Engineering and examples 2. Multivariate Analysis 多变量分析 • From Kansei evaluation data to models (knowledge) 3. Exercise 1: Creation of Rating Scales 评级量表 Today’s Contents Melancholy Cheerful 1 2 3 4 5 6 7 Rating scale 愁绪 快乐 6 Kansei words 感性词 Bipolar scale 双极规模

1. Kansei EngineeringFriendlyA)PreparationofproductsamplesGorgeousB)PreparationofKanseiwordsC) Evaluation experimentsFeminineD) Data analysis:Relationshipsbetweenproduct samplesOld-fashioned:RelationshipsbetweenKanseiwords:RelationshipsbetweenKanseievaluationandproductdesign(Mainpurpose)E)Utilizationofknowledgeobtained:Designingnewproductsanddevelopingsalesstrategies重要！DevelopingrecommendationsystemsforElectronicCommerce

A) Preparation of product samples B) Preparation of Kansei words C) Evaluation experiments D) Data analysis • Relationships between product samples • Relationships between Kansei words • Relationships between Kansei evaluation and product design (Main purpose) E) Utilization of knowledge obtained • Designing new products and developing sales strategies • Developing recommendation systems for Electronic Commerce 7 1. Kansei Engineering Gorgeous Old-fashioned Feminine Friendly

Kansei evaluation and modeling (Overview)WarmSoftKanseiwordsCloudyWhatkindsof wordcanbe usedto:RepresentativeKanseifactorstoevaluatethiscup?evaluatetheproducts·RelationshipsbetweenKansei多变量分析evaluationanddesignelementsMultivariateWhatkindsofanalysisknowledgecanbeProbabilitymodelsofproductsderivedfromthewithrespecttoKanseiwordsProbabilityevaluation data?(Ex.)Theprobabilitythatthismodelingcupisrated"Warm"is70%.概率建模

Kansei evaluation and modeling (Overview) What kinds of word can be used to evaluate this cup? Soft Warm Cloudy What kinds of knowledge can be derived from the evaluation data? Multivariate analysis Probability modeling • Representative Kansei factors to evaluate the products • Relationships between Kansei evaluation and design elements • Probability models of products with respect to Kansei words • (Ex.) The probability that this cup is rated “Warm” is 70%. 8 Kansei words 多变量分析 概率建模

Data collection and data screening·Preparation:Thefirsttaskistoprepareproductsforevaluationbythebipolarscales used in the semantic differential method (Osgood, et al.,1957)..OsgoodCE,SuciGJ,TannenbaumPH(1957)TheMeasurementofMeaning,Universityof IllinoisPress·Experiment:The evaluation experiment should be designed carefully.Dependingontheproducts to be evaluated, wemust collectappropriateevaluators..Notethatthetimeand costtogetgooddataisverylarge.·Screening:Thedata screeningissometimesnecessarybecauseoferrorsorbiased scoring.Moreover,thosewhoarefamiliarwiththeproductsandthosewhodonotknowthemwouldmakedifferentscoresinsomescales.9

Data collection and data screening • Preparation: The first task is to prepare products for evaluation by the bipolar scales used in the semantic differential method (Osgood, et al., 1957). • Osgood CE, Suci GJ, Tannenbaum PH (1957) The Measurement of Meaning, University of Illinois Press. • Experiment: The evaluation experiment should be designed carefully. Depending on the products to be evaluated, we must collect appropriate evaluators. • Note that the time and cost to get good data is very large. • Screening: The data screening is sometimes necessary because of errors or biased scoring. Moreover, those who are familiar with the products and those who do not know them would make different scores in some scales. 9

Bipolar scales1-6CuteTasteful口品口口口QuietBusyOOOOOOOOOODOLightHeavyDelicateOOLODOOSmartStatic000ODynamic口口SemanticDifferentialMethod(Osgood,1957)Kanseievaluationexperiment10

Bipolar scales 1 2 3 4 5 6 7 Cute □■□□□□□ Tasteful Busy □□□□□■□ Quiet Heavy □□□□□□■ Light Delicate □□■□□□□ Smart Static □□□□■□□ Dynamic Semantic Differential Method (Osgood, 1957) Kansei evaluation experiment 10