The implementation of simultaneous engineering in the stage of product concept development: A process orientated improvement of quality function deployment

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH ELSEVIER

European Journal of Operational Research 100 (1997) 293-314

The implementation of simultaneous engineering in the stage of product concept development: A process orientated improvement of quality function deployment Ralf Schmidt * Lehrstuhlff~r Unternehmenspolitikund Marketing, RWTH Aachen, Templergraben 64, D-52056 Aachen, Germany

Abstract

Quality Function Deployment (QFD) has been introduced as a method of implementing Simultaneous Engineering. In spite of its achievements so far, QFD does not sufficiently link engineering to marketing and marketing science. The QFD procedure takes neither the development of market orientated or constructional product concepts, nor the coordination of both into account, although they play an important role in product definition. In order to overcome this and other deficiencies of the traditional QFD method, the author develops the process model of 'Integrated Concept Development' (ICoDe). It is proposed to fill the gap between marketing science and engineering by consequently relating market orientated concept development and testing to the House of Quality concept of QFD. The ICoDe process is described by refering to a 'simulated' application example of a wind turbines concept development. © 1997 Elsevier Science B.V. Keywords: Quality Function Deployment;Conceptdevelopment; R&D and Marketing

1. Introduction

The best concepts and strategies remain ineffective without successful implementation. In this sense the success of Simultaneous Engineering (SE) and Concurrent Development depends on the availability and performance of methods, which support their implementation. The application of Quality Function Deployment (QFD) by crossfunctional teams seems to be one of the most promising approaches to SE implementation. QFD, which is therefore refered to as the backbone o f SE (Brenner, 1992), is designed to support customer orientated product development by consequently translating customer needs into de-

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sign, feature and individual part characteristics, manufacturing processes and quality plans. Thus, by putting stress on early product definition and by preventing errors instead of detecting them, QFD is designed to avoid late and expensive pre- or even post launch changes. This helps to shorten development cycles, save budgets and improve product quality at the same time. Success stories spread about companies practising QFD report up to 50% of product changes and initial cost reductions of almost 60% as well as development time reductions in the range of 30-50% (ASI, 1989). In fact, these results are mostly repeated without revealing that it took Toyota more than 4 years to implement QFD and 7 years altogether to achieve their rather exceptional initial cost reduction (O'Neal and LaFief, 1992).

0377-2217/97/$17.00 © 1997 Elsevier Science B.V. All rights reserved. PII S0377-2217(96)00291-3

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In spite of these exceptional results and its ability to integrate different functions within a company, QFD still does not seem to sufficiently link product development and quality management to marketing and marketing science. Although QFD deals with product definition, existing methods of measuring customer needs are ignored as well as market orientated concept development and testing (Schmidt, 1996). The purpose of this article is to improve the implementation of SE by introducing the ICoDe model of 'Integrated COncept Development'. It suggests a process and team orientated model for further developing QFD by matching it with the procedures and methods of market orientated and constructional product concept development and testing. Firstly, the topic of the market orientated product concept and its development is introduced. Then some shortcomings of the American Supplier Institute's (ASI) approach to QFD are outlined, before the ICoDe model is introduced to overcome concept related problems, which the QFD user still has to face. Finally the conclusion reveals some clues for further research in the fields of integrated product definition and concept development. In order to test the feasibility of the ICoDe process and examine its advantages over the traditional QFD method, this article describes the ICoDe model by refering to its explorative application, using the product definition of a hypothetical wind turbine example. As the possibility of creating a 'real life application' cannot be undertaken (due to time and budget restrictions), a crossfunctional team, guided by the author, applied the ICoDe model to the early stages of a 'simulated' development process. This lead to the restriction, that not all methods refered to by the ICoDe process were applied in this study and that the applied methods were merely chosen out of pragmatic reasons.

2. The development of market orientated product concepts In marketing literature, the market orientated product concept is refered to as a further developed and somehow more specified product idea (Wind, 1982). It reflects a statement concerning the at-

tributes and features of a product, that are anticipated by the consumer and deal with an improvement to existing solutions (Crawford, 1994). Here it can be seen as a verbal, pictorial or physical description of a product in the language of the customer. The market orientated product concept may be interpreted as a goal description for product development because it determines which customer needs should be satisfied and to what extent. In order to come up with such a goal definition in terms of a selected product concept, alternative product concepts have to be developed. Following this, a customer orientated and (if possible) Conjoint Analysis based concept test detects the market orientated product concept, prefered by the target customers. Whereas literature deals mainly with improvements concerning concept testing, such as adaptive (Sawtooth, 1995), hybrid (Green, 1984; Green et al., 1981), or hierarchical (Oppewal et al., 1994) modifications of traditional Conjoint Analysis or the rapid prototyping based incorporation of physical stimuli into concept testing procedures (De Bont, 1992), the process of concept development has been rather neglected. Existing approaches, such as • the approach of STEFFLRE (see Stefflre, 1968), • the 'new procedure for concept evaluation' (see Wind, 1973), • the 'framework for concept evaluation and generation' (see Shocker and Srinivasan, 1979), • the lead user based concept development (see Urban and von Hippel, 1988; von Hippel, 1986) 'product strategy and -profile planning' (see Gick and Scholz, 1989), • the concept development, described by Kotler (see Kotler and Bliemel, 1992; Knoblich and Schubert, 1992), • the 'total design plan' (see Pugh, 1991), • the 'novel approach to product design and development in a concurrent engineering environment' (see Dowlatshahi, 1993), • the 'consumer idealized design' approach (see Ciccantelli and Magidson, 1993), and • the 'pretechnical evaluation' (see Crawford, 1994), are neither sufficiently method based nor adequate for complex multi-feature products. Additionally they do not integrate marketing science, quality management and product design concurrently (Schmidt,

R. Schmidt / European Journal of Operational Research 100 (1997) 293-314

1996), for example by matching the constructional product concept with the market orientated concept. They therefore are not able to support product definition within a concurrent approach to product development. In contrast, QFD - described in the following section - was introduced to fulfil these requirements and to overcome the deficiencies of today's procedures of product definition.

3. QFD and its shortcomings The approach of the American Supplier Institute (ASI) to QFD is a modified and standardized version of the original QFD model, introduced by AKAO in Japan in the sixties (Akao, 1992). It comprises of four stages, each of which is supported by a matrix (House of Quality) forming its central element. The output of the preceding matrix always serves as an input to the following House of Quality (HoQ). The first HoQ translates customer needs into design characteristics of the product. These design characteristics are then transfered into performance characteristics of product features by the second HoQ. The third House of Quality deals with process characteristics, related to the product features, whereas as the last matrix supports production planning by transfering the process requirements into quality plans (ASI, 1989). Up to now, only the first two Houses of Quality, which focus on the determination of design characteristics (performance characteristics) for the entire product and its features, have been applied in practice. The first House of Quality has especially received a lot of attention. Although it deals with customer needs (product attributes and their customer related importance weights) and their translation into technical design characteristics of the entire product (Saatweber, 1994), QFD literature does not address the aspect of concept development and concept testing. This results in some of the deficiencies of traditional QFD approaches. One of the main problems of QFD seems to be its complexity. For example, 20 customer needs and 45 design characteristics already lead to 900 different links, which have to be discussed within the team. As a result setting priorities is one of the most

295

important tasks, when implementing the QFD method (Akao, 1992). The second HoQ especially leads to a high degree of complexity. The relationship between each critical design characteristic and all feature characteristics must be examined, even if it is only relevant for a certain part of the product. This leads to a very complex second HoQ. A more serious problem concerning QFD relates to the consideration of customer needs. Although QFD is recommended because it is supposed to deploy customer needs throughout product development, QFD literature either ignores the sources of customer needs (e.g. Finley, 1992) or suggests completely unacceptable methods and procedures for their measurement (e.g. Reid and Hermann, 1989; Band and Huot, 1990; Kordupleski et al., 1993). Traditional methods of measuring customer needs are hardly considered, which seems to be absurd, refering to the intention of QFD to integrate marketing and quality management. Only recent publications take the potential of marketing science into account (e.g. Kamiske et al., 1994; Eversheim et al., 1994). In addition, QFD neglects the existence of feature and individual part related customer needs. In fact a lot of customer needs are related and restricted to certain parts of a product, such as the anti-glare effects of a car's rear view mirror or the required rust proofness of a chain saw blade. These needs get lost in traditional QFD applications (Hartung, 1994; Stauss, 1994). One of the most important decisions in QFD is the definition of target values for design characteristics. QFD offers no support to this decision (Schmidt, 1996). How these values should be determined, is not at issue at all (e.g. Streckfuss, 1994). Some authors don't even take present and important data into account, such as the importance of design characteristics (e.g. Kamiske et al., 1994). Another problem related to QFD concerns the determination of the weights of design characteristics. Different scales and weighting schemes, which measure the relationship between customer needs and design characteristics lead to different levels of importance for the design characteristics. In fact, each scale value of the relationship between a customer need and a design characteristic, represents a psychophysical transformation function with a slope, assumed to be constant (Schmidt, 1996). In addition,

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the weighting scheme application leads to crisp values, neglecting the high amount of uncertainty, the QFD team has to face. Due to the resulting crisp values, actual uncertainties and the influence of the weighting scheme on the HoQ results are ignored in traditional QFD literature and QFD applications. One possible QFD improvement, which might reduce the danger of pseudo crisp values is the implementation of f u z z y quality function deployment. It calls for the declaration of fuzzy relationships by the QFD team. These fuzzy values and the resulting fuzzy weights for the design characteristics may be reproduced by membership functions and lead to a quite low sensitivity of QFD. This loss of sensitivity is not at all crucial, as this procedure only reflects truly existing uncertainties and because a rank order of the weights of design characteristics is sufficient regarding the intention of QFD (Schmidt, 1996). Another assumption of QFD is founded by the linear additive model that transfers customer needs into design attribute measures. It contains the assumption of compensatory effects among the customer needs. Therefore QFD is not capable of adequately transforming customer need-related knock out factors into design characteristics (Schmidt, 1996). A major problem regarding QFD, which is mainly addressed in this article, is its insufficient coordination of quality planning and product concept selection. QFD does not address the problems and procedures of customer related or market orientated product concept development and testing at all. Although linking methods of customer based concept testing (such as Conjoint Analysis) to QFD produces radical improvements (Schmidt, 1996), a consideration of customer orientated product concepts is almost completely lacking in QFD literature and QFD applications (for an exception see Eversheim et al., 1994). Instead, the question of concept selection is restricted to the evaluation of constructional concepts by 'Pugh Concept Selection', applied in the second stage of the ASI-approach. 'Pugh Concept Selection' is not at all convincing, as it selects a constructional concept by applying certain criteria without even weighting them (see Pugh, 1991) and without integrating the selected concept into the HoQ sequence. The IcoDe process addresses these deficiencies of

the traditional QFD method. It aims to link QFD to the question of selecting market orientated product concepts under consideration of constructional rough drafts or concepts. Without giving up the advantages of QFD, such as the improvement of internal cross functional communication (Griffin and Hauser, 1992), • the focus on customer orientation in all phases of product development (Griffin, 1992), the structure and transparence it brings to product development (O'Neal and LaFief, 1992), and the standardized documentation (Schuler, 1993), which improves motivation and eases the introduction of new team members to the project (Schr5der and Zens, 1996), the ICoDe process especially connects marketing research to the HoQ. It modifies the procedure of traditional QFD by directly relating it to market orientated concept development and testing as well as by connecting marketing and constructional concept selection. In this context, this article outlines the potential and the benefits of relating marketing research to the 'HoQ concept'. However, it does not show or prove these benefits in an empirical study.

4. The ICoDe model

The ICoDe model in Fig. 1 is made up of 23 stages altogether. The 11 unshaded stages on the left refer to the entire product, whereas the 12 shaded stages on the right relate to product features. The ICoDe model and most of its stages have been applied only on a 'simulation' basis to the example product of a wind turbine. This means firstly, that the marketing science methods applied in this study - for example for structuring customer needs and measuring their importance - were selected only out o f pragmatic reasons and not out of methodical or validity related concems. Secondly, some o f the methods - for example Cluster Analysis in stage 4 (segmentation) or Conjoint Analysis in stage 12 (concept test) - have not been applied at all. Instead, due to the process related goal of this study, the ICoDe team selected a target group and a product concept and thus 'simulated' the application of these methods by just assuming their results and

R. Schmidt / European Journal of Operational Research 100 (1997) 293-314

being aware of methodical problems, such as the major problem of Conjoint Analysis, given by its inability to handle large numbers of attributes. However it was not intended to solve these methodical problems within this explorative 1CoDe application.

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The ICoDe process starts with the elicitation of product attributes (stage 1), which are relevant to the customer. Besides analysing for example existing publications (Gensch and Golob, 1975), product folders (Mohler, 1985), customer complaints and

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Fig. 1. The ICoDe model and its stages (see Schmidt, 1994, 1996).

R. Schmidt / European Journal of Operational Research 100 (1997) 293-314

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proposals (Kordupleski et al., 1993), or expert knowledge (Gensch and Golob, 1975), the ICoDe team may choose between the Rep-Test (MtillerHagedorn and Vornberger, 1979; Riemann, 1981), group discussions (McQuarrie and McIntyre, 1986), and in-depth interviews (Bortz, 1984; Griffin and Hauser, 1993; Salcher, 1995). The in-depth interviews refer to different techniques, such as • problem related tasks (Tauber, 1973), • problem related tasks in combination with Problem Detecting (Bruhn and Hennig, 1993), • the Critical Incident Technique (Stauss and Hentschel, 1992), • Decision Sequence Analysis (Day et al., 1979), • the Thinking Aloud-Technique (Hopf, 1985; Kroeber-Riel, 1992), or • methods of projection (Grunert, 1990). Griffin and Hauser (1993) show that in the case of similar involvements of time, group discussions and

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in-depth interviews amount to the same number of product attributes. In the wind turbine case, a group discussion within the ICoDe team resulted in 36 product attributes (see Fig. 2). As customer based attribute elicitation may easily lead to a list of 166 attributes (in case of a motor carrier, see Lambert et al., 1993) or even 200 or 400 attributes (Griffin and Hauser, 1993), structuring the attributes (stage 2) is essential for the subsequent stages. Structuring techniques, which reduce the amount of elicitated attributes by arranging them into a hierarchy, include the laddering procedure (Reynolds and Gutman, 1988), factor analysis (Urban and Hauser, 1993), the Group Consensus Process, and the Customer Sort and Cluster Process (Griffin and Hauser, 1993). The Group Consensus Process and the Customer Sort and Cluster Process lead to a structure of Primary, Secondary, and Tertiary Attributes. Fig. 2 shows the final attribute structure of Primary and Secondary Attributes for the wind turbine case, resulting from a Group Consensus Process. After the Primary and Secondary Attributes have been identified, stage 3 of the ICoDe process deals with the measurement of customer requirements on a Primary Attribute level. Primary Needs (Primary Attributes and their importance) and consumers' attitudes towards competitors' products and the company's present products have to be measured. Therefore direct methods, such as • the elicitation of'categorial importance-statements (Schmidt, 1996), rank ordering of the attributes (e.g. Salcher, 1995), paired comparisons (Schmidt, 1996), rating scales (e.g. Schertzer and Keman, 1985), Magnitude Scaling (e.g. Lodge, 1981), Dual Questioning (e.g. Myers and Alpert, 1968), Constant Sums (e.g. Heeler et al., 1979), and the Analytic Hierarchy Process (e.g. Saaty, 1990; Tscheulin, 1992), or indirect methods, such as • the sequence of reproduction (Heemeyer, 1981), • the Information Display Board (Quelch, 1977), • traditional Conjoint Analysis (Green and Rao, 1971), • Adaptive Conjoint Analysis (Sawtooth, 1995), • Hybrid Conjoint Analysis (Green et al., 1981; Green, 1984),

R. Schmidt / European Journal of Operational Research 100 (1997) 293-314

Hierarchical Conjoint Analysis (Oppewal et al., 1994), Multidimensional Scaling (Green and Wind, 1973; Quack, 1980; Schmidt, 1996), Preference Regression (Urban and Hauser, 1993), • the Preference-Matrix-Method (Schmidt, 1996), and •von Neumann-Morgenstern based procedures (Hauser and Urban, 1979; Eisenfi~hr and Weber, 1993) are applicable (Schmidt, 1996). In the wind turbine case, the Constant Sum Scale (applied within the ICoDe team and selected merely out of pragmatic reasons) lead to the Primary Needs, revealed in Fig. 3. A subsequent benefit based customer segmentation (stage 4) may lead to the identification of the target group and may be achieved by Cluster Analysis a n d / o r Benefit Segmentation (Schmidt, 1996). The rough concept (stage 5) refers to the Primary Needs within the target group and takes the conditions of the intended product use into account. It could for example describe the wind turbine as a product, which will be used by farmers, who give priority to a profitable, safe and easy use on their large or medium-sized farm. The constructional concept of the wind turbine is selected in stage 6 of ICoDe. Within this stage it is

299

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possible to evaluate innovative solutions and to compare them with rather traditional constructional product concepts. The constructional concept selection takes Primary Needs as well as internal requirements into account. They refer to the know-how, which exists within the organization of the ICoDe applicant and the compatibility of the constructional concept to the present product range. Fig. 5 shows the Primary Need related evaluation of the constructional con-

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Fulfilment of internal requirements (present know-how for the development/ production/marketing of the constructional concepts in relation to competitors, ...) Fig. 6. The constructional concept evaluation matrix (see Schmidt, 1996).

cepts 'H-rotor', 'Darrieus', and 'Horizontal Axis Plant', which are sketched in Fig. 4. The constructional concept evaluation matrix (Fig. 6) combines both evaluated dimensions. As the Horizontal Axis Plant is obviously superior, it is selected and refered to in the following sections. In stage 7 the product features and individual parts are defined for the Horizontal Axis Plant. Stage 8 deals with the evaluation of the importance of the product features relating to the Primary Needs. HoQ 2 in Fig. 7 shows the wind turbine features and their weights of importance. They give early pointers for an appropriate cost structure for the product and may serve as an input to the Target Costing process (see Coenenberg et al., 1994). Here, the rotor, the output drive, and the tower are identified as the most important features of the Horizontal Axis Plant, according to the Primary Needs. The roof of House of Quality 2 reveals the interdependence of the product features, which is important information for the organization of the development project and the determination of personnel resources. In the wind turbine case especially the development of the plant's control unit, the cabinet and the output drive demand a high level of coordi-

nation. Because of its high level of interdependence with other product features and its high importance value, the following description of the feature related ICoDe steps (steps 14-23) will focus on the output drive, namely the gear unit. In stage 9 the Secondary Needs and attitudes to the entire product are measured in detail using the same methods applied to the Primary Need level (see stage 3). Because there is a higher amount of Secondary Needs, compared to the Primary Needs, the selected method has to be able to deal with a high number of attributes. A Constant Sum application within in the ICoDe team resulted in the Secondary Needs of Fig. 8. The Secondary Needs (which could be used to modify the feature weights of step 8) are converted into design characteristics by HoQ 3 in stage 10 of the ICoDe process. This stage basically corresponds to the first House of Quality of the traditional QFD approach, omitting however a target definition for the design characteristics. Fig. 9 shows HoQ 3 of the wind turbine case (for a detailed description of this step see Schmidt, 1996). The attribute 'price' should not be included in HoQ 3, because it determines the frame of possible solutions. In this context it provides an important information for Target Costing.

R. Schmidt /European Journal of Operational Research 100 (1997) 293-314

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assist in this crucial step. So stage 11 aims to identify attribute levels, which represent the range of ambitious but realistic product positions in relation to the competitors. The identification of attribute levels is supported by the following information, which is contained in HoQ 3: • Secondary Needs; • competitor related strengths and weaknesses in terms of Secondary Attributes; • weights of design characteristics; • the competitor related strengths and weaknesses in terms of design characteristics; and

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The exact determination of the price, a potential customer is willing to pay for the product (or its features) is subject to the concept tests in stage 12 (and stage 22 for the features). In contrast to traditional QFD approaches, the transformation of Secondary Needs into design characteristics has to be processed twice within ICoDe. In HoQ 3 this transformation is applied to the Secondary Needs in the traditional way of QFD. Later on, in HoQ 4 (stage 13) the selected market orientated product concept, described by attribute levels and their part worths is transformed into design characteristics. Before for example Conjoint Analysis can identify the product concept, which potential customers will prefer (stage 12), alternative product concepts have to be developed. This is the subject of stage 11. Whereas the Conjoint literature does not deal with the problem of generating attribute levels and product concepts, ICoDe uses the competitive advantage matrix (see for example Sebastian and Simon, 1989) and the design attribute advantage matrix to

Fig. 8. The Secondary Needs in the wind turbine case (see Schmidt, 1996).

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the correlations between these design characteristics. The first two points of information are represented by the competitive advantage matrix in Fig. 10. The present inferior attribute levels of the Secondary Attributes in field 1 of the competitive advantage matrix are not critical because they fall into the low importance category. The Secondary Attributes in field 2 represent requirements, which have been overmet by present products. In this case a decline in quality may be achieved without expecting this to disturb customers' preferences. In contrast, field 3 addresses real quality problems of present products, because here the competitors' products are superior concerning important Secondary Attributes. In addition real competitive advantages are characterized by superiority relating to important attributes (field 4). Although it seems reasonable, to set ambitious attribute levels in case of field 4 attributes and rather defensive targets in the case of field 3, these rules of thumb do not sufficiently support the determination of appropriate attribute levels. In case of a quality problem (field 3) it should for example be investigated, whether the present products really face a constructional quality problem or if a mere communication deficiency causes the inferiority. This analysis is assisted by the design characteristic advantage matrix in Fig. 11. high

If the competitive power is weak concerning the design characteristics that are strongly related to a Secondary Need, which represents a quality problem, a technical problem of the product is the reason (upper part of Fig. 11). In this case a careful and rather modest definition of attribute levels should be conducted as long as the technical problems have not been resolved. In contrast, a strong technical competitive power concerning these design characteristics indicates a communication problem, which marketing should take care of (lower part of Fig. 11). The Secondary Needs of field 4 should be analysed in the same way. The attribute levels should for example only be ambitiously defined, when the advantage attested by the customers is due to technical superiority. Otherwise the communicative advantage is not stable enough to reason a highly ambitious definition of attribute levels within concept development. Furthermore, the compilation of attribute levels in terms of alternative product concepts has to take constraints, representing unrealistic attribute level combinations, into account. Fig. 12 shows the resulting attribute levels for the wind turbine case (for a more detailed description and an example for the procedure of attribute level definition see Schmidt, 1996). The subsequent concept test of stage 12 should be Conjoint based, as long as the amount of realistic

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attribute level combinations does not overload the Conjoint design (Schmidt, 1996), This is certainly the case for the 28 Secondary Need-attributes in Fig. 12. In this case even Adaptive or Hybrid Conjoint Analysis will not be able to detect the part worths of the attribute levels, listed in

Fig. 12. Instead direct procedures, which estimate part worths could be used. The transformation of the selected product concept (desribed by attribute levels) into design characteristics and their targets is the subject of stage 13. It is assisted by HoQ 4, which is a modification of

The Secondary Need related c o m p e t i t i v e d i s a d v a n t a g e from the c u s t o m e r s ' p o i n t - o f - v i e w (field 3 of the competitive-advantage-matrix) is based on ... ... a c o n s t r u c t i o n a l problem of the product: high

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Fig. 1 l. Analysis of quality problems (see Schmidt, 1996).

R. Schmidt / European Journal of Operational Research 100 (1997) 293-314 Second. Need Attribtff~

remarks

long life cycle energy supply )ossible ~flloiency ow operational costs

OWlocal

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up to 260 km/h

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Fig. 12. Secondary Need-attribute levels in the wind turbine case (see Schmidt, 1996).

HoQ 3 of ICoDe and the first HoQ of the traditional QFD approach. As shown in Fig. 13, the lines of HoQ 4 contain the attribute levels and their part worths, which describe the selected product concept. In HoQ 4 the Secondary Needs 'capacity expansion' and 'adequate for windparks' are not considered, because the selected product concept does not include these features. Although the weights for the links between customer needs and design characteristics in HoQ 3 do

305

not differ from those in HoQ 4, taking attribute levels and their part worths into account instead of attribute importances, this will definitely change the importance weights of design characteristics. The modified weights of the design characteristics in HoQ 4 refer directly to the selected product concept. Therefore they implicate a higher target orientation than the weights, generated in HoQ 3 and the first HoQ of traditional QFD. Compared to traditional QFD, taking part worths of different attribute levels into account also makes it easier to define target values for design characteristics. Furthermore, the consideration of attribute levels and their part worths supports the decision of the designer. By taking part worth functions into consideration, he knows how much utility may be gained by for example extending the life cycle of the wind turbine from 20 to 25 years. Apart from the systematic approach to concept development for the entire product, which has been described so far, another focus of the ICoDe model is the explicit consideration of product features within the process of product definition. In the following sections, the process of feature concept development is described for the example of the gear unit of the Horizontal Axis Plant. For the elicitation (and if necessary the structuring) of the feature related customer needs (stage 14) the same techniques are available as for the entire product. In stage 15 the customer needs and attitudes towards existing product features are measured by the methods, mentioned above. Depending on the complexity of the product feature in question, methodical restrictions, due to the high amount of attributes, become less important in this stage, with the result, that for example Conjoint Analysis may be easily applicable, in comparison to the case of the entire product. The feature related customer needs are shown in HoQ 5 of stage 16 (see Fig. 14), which deals with their transformation into design characteristics of the feature. Before a customer orientated feature concept can be selected and transfered into design characteristics in a modified HoQ (HoQ 7, in stage 23), the following have to be ensured: the compatibility of the feature and the entire product (stages 17 and 19);

306

R. Schmidt / European Journal of Operational Research 100 (1997) 293-314

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R. Schmidt / European Journal of Operational Research 100 (1997) 293-314

• the compatibility of different product features (stage 20); and • the selection of a constructional feature concept (stage 20). The so-called relevancy test (stage 17) identifies the product's design characteristics, which are relevant to the product feature. The question whether the design of a product feature may ease the target value realization of the product's design characteristics, or not, must be asked. Only those design characteristics of the entire product, which may be influenced by the product feature design will be taken into account within the further analysis of the compatibility between the product and its features (stage 19). In addition to the product's design characteristics,

which are relevant to the product feature (stage 17), the selection of a constructional feature concept (stage 18) also takes its design characteristics, the estimated cost of the constructional concepts, and the internal requirements, the feature has to meet into account (e.g. 'easy to mount' or 'easy to produce'; see HoQ 6 in Fig. 15). Within this evaluation procedure, innovative constructional feature concepts should be included in order to prevent the ICoDe process from developing rather conservative feature concepts. In the wind turbine case, six different constructional concepts have been generated and evaluated in HoQ 6. Fig. 16 summarizes these evaluations. The constructional feature concept 'spur gear unit

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R. Schmidt / European Journal of Operational Research 100 (1997) 293-314

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on top' has been selected by the ICoDe-team. The following conflict analysis (stage 19) refers to this constructional concept. The conflict analysis identifies conflicts between the product and the feature on the level of design characteristics, by simply comparing the tendencies of the optimization of design characteristics. Fig. 17 shows a cutting of the conflict analysis matrix, as a result of stage 19. For the identification of conflict areas refering to the development of different product features (stage 20) the conflict analysis matrix may be applied to a feature to feature coordination as well. In order to reach a solution to the feature-to-feature conflicts the following information, developed within the ICoDe process, is available: the weights of the features' design characteristics (out of HoQ 5); the features' importances regarding the customer needs (out of HoQ 2), and the results of the

conflict analysis. (Because of the restriction to only one product feature, the ICoDe application described here does not include a validation in stage 20.) The development of different customer related concepts for the product feature (stage 21) follows the same procedure as the concept development for the entire product (stage 11). Fig. 18 shows the attribute levels for the gear unit, generated by the ICoDe-team, including the surcharge, the potential customer might be willing to pay for a concept in relation to a standard variant. As far as possible, the stimuli of the subsequent customer orientated concept test (stage 22) should show the feature concepts as a part of the entire product concept. The application of Conjoint Analysis may generate part worths for attribute levels, which are important for the concept transformation in stage 23. In comparison to a Conjoint application

R. Schmidt / European Journal of Operational Research 100 (1997) 293-314

309

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to the entire product (stage 12), the number of

formed into design characteristics and their target values, in the same way as for the entire product (see stage 13). Fig. 19 shows a part of HoQ 7 for the wind turbine case. After completing stage 23, the ICoDe process

attributes a n d a t t r i b u t e l e v e l s will b e l o w e r o n this

feature level. This leads to better conditions for a Conjoint design. In stage 23, the selected feature concept is trans-

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R. Schmidt / European Journal of Operational Research 100 (1997) 293-314

ends with the definition of detailed customer orientated and constructional concepts for the entire product and the product features. Whereas the customer orientated product concepts are determined by the attribute levels and their part worths, the constructional concepts are described by the target values of the design characteristics. The resulting Houses of Quality 4 and 7 specify customer orientated and constructional concepts, which are reconciled with each other. In case the potential customers are not able to estimate a product feature concept, steps 14 to 17 should be omitted. In this case the second House of Quality of traditional QFD may be applied, before HoQ 6 takes care of the subsequent selection of a feature concept (stage 18). After the completion of ICoDe's HoQ 23, the Houses 3 and 4 of traditional QFD are still applicable.

5. Summary and conclusion In contrast to existing procedures of concept development, the ICoDe process contributes to a better integration of marketing, marketing science, quality management, and product design. In comparison to QFD, the ICoDe model improves concept development and product definition. It extends the traditional QFD model to a universal approach of concept development, by: linking it to marketing science methods that are applicable in the early phases of concept development and testing; explicitly taking customer needs related to product features or parts of the product into account; supporting the crucial step of target value definition for design characteristics; directly addressing the evaluation and selection of product innovations in terms of new constructional product and feature concepts; improving the selection of constructional product and feature concepts; improving and completing the documentation of the results in form of diagnostic and evaluation tools; and • reducing the complexity of the traditional second House of Quality.

The interface of marketing science and quality management may be improved by especially realizing the potential of combining Conjoint Analysis and the House of Quality. The transformation of attribute levels into design characteristics of the product and its features and the radical consequences for the design of new products have so far not been discussed in literature and practice (Schmidt, 1996). It leads to a better understanding and translation of the voice of the customer and puts the task of the project team and the designers into concrete terms. However, the high potential of combining Conjoint Analysis and QFD is still restricted because of methodical shortcomings. For example, Conjoint Analysis is still not able to handle the 28 Secondary Need-attributes of a wind turbine. More research has yet to be conducted to realize the potential and benefits of linking Conjoint Analysis to QFD. Furthermore, restrictions of the positive results of the ICoDe application described here are evident. Up to now, the ICoDe has not been applied to a 'real world' example and development process. The hypo-

Attributes

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A

attributelevels B

tO years

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fulfil minimum requirements

none

paaly

+I" 0

-1000,- DM

sharp edges surcharge

+1000,- DM

i

Fig. 18. Attribute levels of the product feature 'gear unit' (see Schmidt, 1996).

R. Schmidt / European Journal o f Operational Research 100 (1997) 293-314

thetical ICoDe application described here only aimed at the validation of the theoretical feasability of the ICoDe model. So, the positive results presented here, only refer to those steps, which were applied within this study. The restriction of only taking one product feature into account means, that the coordination of different product features has not been analysed in this article. However, the ICoDe process leads to high involvements of work. This may cause motivation problems, even compared to traditional QFD. Although this study gives some interesting advice for the improvement of the traditional QFD method, further studies have to be undertaken to test ICoDe under 'real world conditions' using different product

31 I

categories. In the case of positive results the ICoDe process may be improved by linking it to Target Costing, Rapid Prototyping, and the development of product related services. This article does not solve all the problems related to product concept development. Nevertheless it contributes to the guidance of the project team within the implementation of Simultaneous Engineering.

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Fig. 19. The attribute levels of the selected feature concept as an input into HoQ 7.

312

R. Schmidt / European Journal of Operational Research 100 (1997) 293-314

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