Design for Six Sigma: Approach for reliability and low-cost manufacturing (Diseño para Seis Sigma: Enfoque para la fiabilidad y fabricación de bajo costo)

Abstract. The aim of this study is to discuss new product development based on a traditional stage-gate process and to examine how new product development [NPD] tools, such as lean design for Six Sigma, can accelerate the achievement of the main goals of NPD: reliable product quality, cost-effective implementation, and desired time-to-market. These new tools must be incorporated into a new approach to NPD based on the Advanced Product and Quality Planning methodology. Resumen. El objetivo de la presente investigación es la promoción de una discusión teórica y practica sobre el enfoque tradicional de lanzamiento de nuevos productos bajo la metodología por fases. Una revisión a profundidad cómo las nuevas herramientas del desarrollo de nuevos productos en lo particular el diseño para seis sigma puede acelerar el tiempo de respuesta al mercado de forma exitosa y a una relación atractiva de costo – beneficio. Las nuevas herramientas pueden ser incorporadas dentro de la estrategia de desarrollo de nuevos productos bajo el enfoque de planeación avanzada de la calidad de nuevos productos

Design for Six Sigma: Approach for reliability and low-cost manufacturing

Abstract. The aim of this study is to discuss new product development based on a traditional stage-gate process and to examine how new product development [NPD] tools, such as lean design for Six Sigma, can accelerate the achievement of the main goals of NPD: reliable product quality, cost-effective implementation, and desired time-to-market. These new tools must be incorporated into a new approach to NPD based on the Advanced Product and Quality Planning methodology.Keywords: analysis of variance (ANOVA), design for Six Sigma, DMAIC, industrialexperimentation, robust designResumen. El objetivo de la presente investigación es la promoción de una discusión teórica y practica sobre el enfoque tradicional de lanzamiento de nuevos productos bajo la metodología por fases. Una revisión a profundidad cómo las nuevas herramientas del desarrollo de nuevos productos en lo particular el diseño para seis sigma puede acelerar el tiempo de respuesta al mercado de forma exitosa y a una relación atractiva de costo – beneficio. Las nuevas herramientas pueden ser incorporadas dentro de la estrategia dedesarrollo de nuevos productos bajo el enfoque de planeación avanzada de la calidad de nuevos productos.Palabras clave: análisis de varianza, diseño para seis sigma, diseño robusto,experimentación industrial, metodología DMAI

How to design and utilize online customer center to support new product concept generation

Websites can be effective vehicles for firms to communicate with their customers but the use of websites has been limited to pacifying complaint customers. To better use a website''''''''s information, this research presents a framework for extracting customer opinions from websites and transforming them into product specification data. For the purpose, firstly, customer opinions were collected from an online customer center and then transformed into customer needs using text-mining. Then, after customers were segmented into several groups based on their needs, relations among their needs were visualized by co-word analysis and product specifications to meet those needs t analyzed by decision tree. Lastly, a final target product specification for new products were determined and a target market was identified based on customer profile data. The suggested framework enables to incorporate customer opinions efficiently with new product development processes and to design online customer centers to better collect and analyze useful information. (C) 2011 Elsevier Ltd. All rights reserved.PARK Y, 2004, P 33 INT C COMP INDChen YL, 2003, EXPERT SYST APPL, V25, P199, DOI 10.1016/S0957-4174(03)00047-2Borner K, 2003, ANNU REV INFORM SCI, V37, P179PARK CH, 2003, BUSINESS PROCESS MAN, V9, P652Garcia-Murillo M, 2002, J OPER RES SOC, V53, P875, DOI 10.1057/palgrave.jors.2601365Cho Y, 2002, ADV CONSUM RES, V29, P318DYCHE J, 2002, HDB BUSINESS GUIDE CWIND Y, 2002, CONVERGENCE MARKETINDing Y, 2001, INFORM PROCESS MANAG, V37, P817Woo JY, 2005, EXPERT SYST APPL, V28, P763, DOI 10.1016/j.eswa.2004.12.041Sakurai S, 2005, APPL SOFT COMPUT, V6, P62, DOI 10.1016/j.asoc.2004.10.007Su CT, 2006, TECHNOVATION, V26, P784, DOI 10.1016/j.technovation.2005.05.005Kostoff RN, 2001, TECHNOL FORECAST SOC, V68, P223DAVENPORT TH, 2001, MIT SLOAN MANAGE REV, V52, P63Harding JA, 2001, COMPUT IND, V44, P51ICHIMURA Y, 2001, P PAC ASS COMP LING, P127NAMBISAN S, 2001, P PORTL INT C MAN EN, P354Losiewicz P, 2000, J INTELL INF SYST, V15, P99Mahajan V, 2000, INT J RES MARK, V17, P215CHAUDHURI A, 2005, P 3 IEEE INT C IND ICristiano JJ, 2000, J PROD INNOVAT MANAG, V17, P286APTE C, 2000, P 4 INT C EXH PRACT, P19BERRY M, 2000, MASTERING DATA MININLam NWW, 1999, TOTAL QUAL MANAGE, V10, P843Feldman R, 1998, J INTELL INF SYST, V10, P281BALA J, 1996, EVOLUTIONARY COMPUTA, V4, P297FUNG RYK, 1996, P 1996 IEEE INT C SYENGELSMAN EC, 1994, RES POLICY, V23, P1WEINSTEIN A, 1994, MARKET SEGMENTATIONGRIFFIN A, 1993, MARKET SCI, V12, P1PETERS HPF, 1993, RES POLICY, V22, P23HUNT KJ, 1993, INTELLIGENT SYSTEMS, V2, P231MITCHELL VW, 1993, INT J RETAIL DISTRIB, V21, P15CHOU PA, 1991, IEEE T PATTERN ANAL, V13, P340, DOI 10.1109/34.88569FORNELL C, 1987, J MARKETING RES, V24, P337KANO N, 1984, J JAPANESE SOC QUALI, V14, P39

Explain the Causes of Customer Dissatisfaction based on Text Mining Analysis

Customer satisfaction requires the customer to be happy both in daily and long-term and global interactions. People's opinions about the products of a company on websites and social media can provide useful information for companies to evaluate customer satisfaction. In this research, using the methodology text mining and k- means clustering, customers' opinions about the three brands of Snowa, Pakshoma and Parskhazar from domestic appliances and comments on the three brands of Samsung, LG, and Tefal from external home appliances in the website of Digikala.com were analyzed. The results of this study show that dissatisfaction factors were clustered in six attributes, product failure, and price proportions with performance, efficiency, design, manufacturing quality and after-sales services. In domestic appliances, the most dissatisfaction factors were the product failure, price proportions with performance, manufacturing quality, after-sales service, efficiency, and design. And the factors causing dissatisfaction in external home appliances were manufacturing quality, product failure, design, after-sales service, price proportions with performance, and efficiency

Natural Language Processing in-and-for Design Research

We review the scholarly contributions that utilise Natural Language Processing (NLP) methods to support the design process. Using a heuristic approach, we collected 223 articles published in 32 journals and within the period 1991-present. We present state-of-the-art NLP in-and-for design research by reviewing these articles according to the type of natural language text sources: internal reports, design concepts, discourse transcripts, technical publications, consumer opinions, and others. Upon summarizing and identifying the gaps in these contributions, we utilise an existing design innovation framework to identify the applications that are currently being supported by NLP. We then propose a few methodological and theoretical directions for future NLP in-and-for design research

Review on recent advances in information mining from big consumer opinion data for product design

In this paper, based on more than ten years' studies on this dedicated research thrust, a comprehensive review concerning information mining from big consumer opinion data in order to assist product design is presented. First, the research background and the essential terminologies regarding online consumer opinion data are introduced. Next, studies concerning information extraction and information utilization of big consumer opinion data for product design are reviewed. Studies on information extraction of big consumer opinion data are explained from various perspectives, including data acquisition, opinion target recognition, feature identification and sentiment analysis, opinion summarization and sampling, etc. Reviews on information utilization of big consumer opinion data for product design are explored in terms of how to extract critical customer needs from big consumer opinion data, how to connect the voice of the customers with product design, how to make effective comparisons and reasonable ranking on similar products, how to identify ever-evolving customer concerns efficiently, and so on. Furthermore, significant and practical aspects of research trends are highlighted for future studies. This survey will facilitate researchers and practitioners to understand the latest development of relevant studies and applications centered on how big consumer opinion data can be processed, analyzed, and exploited in aiding product design

Extracting product development intelligence from web reviews

Product development managers are constantly challenged to learn what the consumer product experience really is, and to learn specifically how the product is performing in the field. Traditionally, they have utilized methods such as prototype testing, customer quality monitoring instruments, field testing methods with sample customers, and independent assessment companies. These methods are limited in that (i) the number of customer evaluations is small, and (ii) the methods are driven by a restrictive structured format. Today the web has created a new source of product intelligence; these are unsolicited reviews from actual product users that are posted across hundreds of websites. The basic hypothesis of this research is that web reviews contain significant amount of information that is of value to the product design community. This research developed the DFOC (Design - Feature - Opinion - Cause Relationship) method for integrating the evaluation of unstructured web reviews into the structured product design process. The key data element in this research is a Web review and its associated opinion polarity (positive, negative, or neutral). Hundreds of Web reviews are collected to form a review database representing a population of customers. The DFOC method (a) identifies a set of design features that are of interest to the product design community, (b) mines the Web review database to identify which features are of significance to customer evaluations, (c) extracts and estimates the sentiment or opinion of the set of significant features, and (d) identifies the likely cause of the customer opinion. To support the DFOC method we develop an association rule based opinion mining procedure for capturing and extracting noun-verb-adjective relationships in the Web review database. This procedure exploits existing opinion mining methods to deconstruct the Web reviews and capture feature-opinion pair polarity. A Design Level Information Quality (DLIQ) measure which evaluates three components (a) Content (b) Complexity and (c) Relevancy is introduced. DLIQ is indicative of the content, complexity and relevancy of the design contextual information that can be extracted from an analysis of Web reviews for a given product. Application of this measure confirms the hypothesis that significant levels of quality design information can be efficiently extracted from Web reviews for a wide variety of product types. Application of the DFOC method and the DLIQ measure to a wide variety of product classes (electronic, automobile, service domain) is demonstrated. Specifically Web review databases for ten products/services are created from real data. Validation occurs by analyzing and presenting the extracted product design information. Examples of extracted features and feature-cause associations for negative polarity opinions are shown along with the observed significance

INTERVAL TYPE-2 FUZZY MODEL FOR CUSTOMER COMPLAINT HANDLING

Complaint management system (CMS) has become increasingly important for organizations, businesses, and government in Malaysia. The interaction between customers and business provider based on complaints which referring to perceptions and wording involves uncertainties and not an easy task in complaint handling process to rank the complaint

Possibilities of data-driven customer insight in B2B service development

The purpose of this thesis was to examine the possibilities of data-driven customer insight generation and leverage in business-to-business (B2B) service development. Previous research on data utilization in service development is scarce, and so, this study aimed to contribute to the building of theories on data and analytics leveraging. More specifically, the study concentrated on inspecting the direct and indirect benefits of data-driven customer insight for B2B service development as well as the related data management challenges and capabilities. The study’s theoretical framework was built on the interdisciplinary fields of service research, marketing, and management. To gain an extensive understanding of the phenomenon, the research followed a qualitative, multiple-case research design. The empirical research data was collected via case interviews in January 2023. Altogether, 17 experts working in eight different technology companies were interviewed for the study. The analysis of interview data was based on case and thematic analysis. The findings of the study showed that data-driven customer insight has versatile direct and indirect benefits for B2B service development: continuous insight generation, more comprehensive customer understanding, ideation and validation, behavioral customer segmentation and comparisons, data-based decision-making, more efficient customer integration projects, deeper customer relationships, and strengthened organizational memory. At the same time, to be successful in data-driven insight generation, the organization needs to have certain data and analytics capabilities related to standardized data management processes, expertise on data and business, decentralized decision-making, and collaboration between different experts and teams. Additionally, data and analytics seem to improve the organization’s customer insight generation as a dynamic capability. As a result of the analysis and discussion, the study proposes a theoretical model on how data-driven customer insight can be generated and leveraged for B2B service development. The model considers different sources of customer-related data, data analysis, benefits of data-driven insights, data management challenges, and capabilities. Lastly, the research presents managerial implications: the implications cover, for example, the steering role of the service business strategy in customer insight generation. Future research should continue to further examine the topic in different industries, especially among data usage pioneers, utilizing a variety of case study data collection methods

PROCESS-ORIENTED KNOWLEDGE DISCOVERY TO SUPPORT PRODUCT DESIGN USING TEXT MINING

Ph.DDOCTOR OF PHILOSOPH