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Information structure of the design methodology
The methodology proposes the following information structure, as shown in Figure.2-5: For the needs stage, the methods Kano model and QFD are used:
Kano model classifies customer needs according to their importance and effect on customer satisfaction. Input information consists of the needs and the responds of customer to a questionnaire. The questionnaire contains a functional and a dysfunctional question related to each need and it enables the classification of them into four categories: must-be needs, one-dimensional needs, attractive needs and indifferent needs. Output information consists of the needs classified in categories. These categories enable to give relevance to those needs with high priority (must-be needs and one-dimensional needs) in the case that it is necessary to do trade-offs.
QFD is an information structure used to translate needs into product specifications. Input information consists of needs already analyzed with Kano model and information from customer and experts to perform the translation. Experts are asked to relate needs with a set of possible product specifications proposed based on a literature search. Simultaneously, customers are asked about the relation of some of the needs (those related to customer feelings and perceptions) with selected product samples. Based on answers of experts and customers, it is possible to define product specifications and target values. Output information consists of product specifications with their respectively target value and level of importance defined based on Kano categories. This output corresponds to the definition of the design problem that will be fed to the design stage.
For the design stage, two matrices containing interrelated information about the product structure and product ingredients were proposed in this study. The first enables the classification of product specifications into general sub-problems and the connection of the latter with a set of predefined solutions strategies. The second enables the connection of solution strategies with ingredients and process conditions. Input information consists of the product specifications defined in previous stage. Output information corresponds to sets of product concepts, i.e., sets of ingredients and process conditions, each of them being an alternative of solution. For the application of this method four elements were proposed:
A list of sub-problems and 2) a list of solution strategies, defined based on a literature review of emulsion science publications.
The first relational matrix connecting previous mentioned elements, which is formed by a relational score between each sub-problem and each solution strategy. Scores can be strong, weak, zero and can be positive or negative, to indicate when a solution strategy has a positive or negative effect into a sub-problem.
The second matrix is formed by a data base of cosmetic ingredients. Ingredients are classified into functional cosmetic groups as emollients, surfactants and rheological modifiers, among others, and they can be searched by their physical, chemical and performance properties.
For the selection stage, a selection framework comprising a set of sustainability indicators and a multi-criteria decision method is proposed. The input consist of product alternatives and the output corresponds to assessed alternatives, based on which product designers can take an informed decision on the product to be developed. The indicators are defined based on the H-statements of the Globally Harmonized System of Classification (United Nations, 2011a). This is done because the information is worldwide valid, and it is very accessible to compare ingredients at early design stages. For the integration of indicators, the multi-criteria method AHP is proposed, because of its high flexibility for the treatment of complex decision problems.
Needs analysis and translation
Needs stage comprises needs identification, analysis and translations. It is the first part of this methodology. Needs are not only the beginning but also the reason d’être of the design. They can be defined as any characteristic of an individual or a group of people, who feels a lack that generates a dependency, affecting he/she/their experiences or activities (Boly et al., 2016). If the element on which there is dependency is present, the person can benefit of it: if not, the person suffers pain and dissatisfaction (Boly et al., 2016).
Designers’ first tasks are to identify customer needs, to define their importance and to devise product characteristics able to respond to them. Those steps are called in this work needs identification, needs analysis and needs translation, respectively. From these three tasks, the last two are treated in more detail in this chapter.
The first section of this chapter begins with the explanation of the three steps of the needs stage and two methods for the development of the last two: Kano model for needs analysis and Quality Functional Deployment (QFD) for needs translation into product specifications. The second section introduces the study case: a facial moisturizing cream with calendula oil. The third section shows the application of the methods into the study case.
Framework for needs identification, analysis and translation
Needs identification
Needs can be identified by interviewing users, groups of users and/or user leaders (Cussler and Moggridge, 2011). They can also be found by market studies, data mining or they can be suggested by experienced designers or experts from different professions (for example, dermatologists may play an important role in cosmetics development). After raw needs are collected, they are organized and interpreted by designers, who express them in terms of what the product has to do. Interpretation of raw data to define needs requires a very good understanding of users, their words and meanings. The study of methods for needs identification are beyond the scope of this research.
In this work, needs for the study case were collected through customer survey, literature search and ideas of the design team.
Kano model for need analysis
Once needs are identified, it is necessary to analyze them to define which of them require more attention during the design process. The list of needs related to a product design project has many items: some of them can be interrelated and even, some of them can be contradictory. Thus, it is necessary to identify those needs that have a great effect on customer satisfaction and those that bring a competitive advantage in order to focus in their inclusion within the product (Gérson Tontini, 2007).
With this purpose, implementation of Kano model is suggested. This method classifies needs according to their effect in customer satisfaction into the following groups (Rejeb et al., 2008):
One-dimensional: For this type of need, user satisfaction is directly proportional to the functional performance of the product. From a mathematical point of view, one-dimensional needs can be interpreted as objective variables to be optimized in a design problem. An example is the price in non-luxurious products, where satisfaction increases as product gets cheaper.
Must-be: For this type of need, user is very dissatisfied when a minimum required performance is not achieved. Once this minimum is reached, user satisfaction does not increases and remains unchanged with an extra improvement in performance.
From a mathematical point of view, must-be needs can be interpreted as constrains in an optimization problem. An example is the stability of a cosmetic cream. If the product becomes unstable and separates into phases before the expiration date, the user will be very displeased. However, a product with an average use time of one year will not bring further satisfaction if it can remain stable for much more time.
Attractive: For this type of need, the customer satisfaction increases with product performance, but it does not decreases when the performance is reduced or it is absent. These attributes are not necessary requirements, but they may become a competitive advantage to attract customers. They are key aspects in innovative products, because they may become differentiation factors. An example is a sunscreen with foundation, which may surprise the users for the additional function. Attractive needs tend to become must-be needs with time, once the customer has used them for long time (Gérson Tontini, 2007).
Indifferent: For this type of need, customer satisfaction is neutral in relation to the improvement in performance of the product. They are normally not especially important for customer, thus resources should not be invested on them. An example is a moisturizing cream with an additional insect repellent function that may not be interesting for people living in climates where insects are not especially present.
Considering previous definitions, must-be needs have to be achieved but not optimized, one-dimensional needs can be optimized to increase customer satisfaction, attractive needs can bring a competitive advantage and time should not be expended with indifferent needs (Gerson Tontini, 2007).
Kano classification is done based on a questionnaire applied to customers and on the analysis of their answers. The questionnaire has two questions related to each need: The first question identifies the reaction of a customer if the need under investigation is fulfilled, while the second identifies the reaction if it is not (Rejeb et al., 2008). Answers are rated and used to calculate scores for each need. An example of the questionnaire applied to the design of a sunscreen and adapted from Rejeb et al. (2008) is shown in Table 3-1.
Methods for needs translation
In this section two approaches to translate customer needs into product specifications are presented: one, to translate needs with the help of experts, and another, to translate needs with the help of customers. Both are implemented in a complementary way within the framework for need analysis and translation. In addition, Quality Function Deployment is used as an information structure to combine the results both approaches. They are explained below.
Translation with the aid of experts
Expert’s knowledge about products, customer needs and their interrelation can be used to formalize needs translation. This study presents a method comprising three steps: First, a list of product specifications as wide as possible is built based on a literature review. Second, experts are consulted about the representativeness of those specifications in relation to customer needs. This relation can be measured in a four point scale: high (9), medium (3), low (1) and none (0), although other scales are also possible. Third, expert answers are analyzed to select the smallest possible number of specifications that best represent customer needs. For the third step, two multivariate analysis are proposed: Principal Component Analysis (PCA) and clustering, as explained below.
Principal component analysis:
It is a multivariate analysis tool that enables the reduction of high dimensional data while maintaining most of the original information (Lever et al., 2017). This analysis is frequently used in systems where many dependent and highly interrelated variables are measured for each sample, making difficult a direct analysis of data.
PCA projects data into a set of new non-correlated (orthogonal) dimensions, called principal components (PC), which are linear combinations of the original data that can explain most of the original variance with less dimensions (Lever et al., 2017). The first PC is calculated to explain most of the variance of the samples, the second explains as most of the remaining variance with the restriction it is orthogonal to the first PC and so on, until equal number of PC than original dimensions are calculated. Once all PC are calculated, a number of them explaining a desired percentage of variance is selected.
Steps for the application of PCA are explained below (Smith, 2002):
Organize data: Data are organized in a matrix, where the rows are observations (n) and the columns are the dependent variables or dimensions (m).
Table of contents :
Introduction
1. Context and research problem statement
1.1. Some chemical market trends
1.2. Research problem
1.3 Hypothesis
1.4 Objectives
1.5 General methodology
2. Workflow of the design methodology
2.1 Theoretical framework: Chemical product and related concepts
2.1.1 Chemical products
2.1.2 Chemical products classification systems
2.1.3 Micro-structured chemical products
2.2 Methodologies for chemical product design
2.2.1 Customer needs
2.2.2 Simultaneous chemical product-process design
2.2.3 Sustainability
2.2.4 Other design aspects
2.3 Tools and solution approaches for chemical product design
2.4 Workflow and information structure of the proposed methodology
2.4.1 Workflow of product design methodology
2.4.2 Information structure of the design methodology
3. Needs analysis and translation
3.1 Framework for needs identification, analysis and translation
3.1.1 Needs identification
3.1.2 Kano model for need analysis
3.1.3 Methods for needs translation
3.2 Case study
3.2.1 Case study presentation
3.2.2 Calendula oil characteristics
3.3 Application of framework for need stage in the study case
3.3.1 Needs definition for the study case
3.3.2 Needs analysis with Kano model in the case study
3.3.3 Needs translation into specifications for the case study
3.3.4 Partial results of the needs stage
3.4 Conclusion
4. Product design
4.1 Methodological framework for product design stage
4.1.1 Sub-problems and solutions strategies for emulsion based product design
4.1.2 First relational matrix
4.1.3 Ingredients for application in the cosmetic sector
4.1.4 Second relational matrix –ingredients data base
4.1.5 Combining the two relational matrices to create product concepts
4.2. Application of the approach for product design stage in the case study
4.2.1. Definition of the design problem for the case study
4.3. Application of the methods for product design stage in the case study – experimental results
4.4. Conclusions
5. Sustainability analysis
5.1 Framework for the sustainability analysis of products and ingredients
5.1.1. Identification of alternatives:
5.1.2. Assessment of alternatives
5.1.3. Integration of assessment
5.2. Application of the sustainability assessment to the case study
5.2.1. Identification of alternatives:
5.2.2. Assessment of product alternatives:
5.2.3. Integration of assessments
5.3. Conclusions
6. Conclusions and recommendations
6.1. Conclusions
6.2. Recommendations
Bibliography
