optimization of steering behavior through · pdf file1 toyota motor corporation, ... this...

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Chassis.tech 2007

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² Bernhard Schick, ² Stefan Resch, 1 Masaki Yamamoto, 1 Ikuo Kushiro, ³ Naoki Hagiwara* 1 Toyota Motor Corporation, Japan ² TÜV SÜD Automotive GmbH, Germany ³ TUV SÜD Japan, Japan

KEYWORDS Steering Behavior and Feeling, Customer Requirements, Translation into Technical Specifications, QFD – Process, IMPROVE by QFD

ABSTRACT Engineered emotion: A product should evoke positive emotions in the customer. During product development a vast array of interpretations of abstract customer requirements – which is nearly impossible to fathom – opens up to the engineer, who is used to focusing on facts and figures. This entails the risk of not meeting these requirements with absolute accuracy. The application of QFD – Quality Function Deployment - offers a means of guiding the engineer through customer’s’ requirements, which are usually expressed in rather subjective or emotional terms. In addition to addressing the manifold requirements as such, weighting them is another direct outcome of this method, allowing costs and efforts to be optimized. The multidimensional field of steering behavior and steering feeling offers a wide variety of interpretations of the type of vehicle the customer would wish for. In this context several, mutually influencing product aspects such as steering system design, kinematics, chassis design, or perhaps merely the selection of suitable tires, could be attributable to a customer requirement which might have been worded as “precise steering.”. The specification of target parameters for the items named as the basis for the design process is the job of the engineer. Between these poles, i.e. the customer’s’

OPTIMIZATION OF STEERING BEHAVIOR THROUGH SYSTEMATIC IMPLEMENTATION OF CUSTOMER REQUIREMENTS IN TECHNICAL TARGETS ON THE BASIS OF QUALITY FUNCTION DEPLOYMENT

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emotions and the facts and figures required by engineer’s, the application of QFD (Quality Function Deployment), a tried and tested method, is intended as a tool. Using the challenge to optimize steering behavior from the customer’s point of view, the authors apply the advanced method, IMPROVE by QFD (Integrated Market Related Product Optimisation for Vehicle Engineering), to the European market. Aside from the approaches and the method itself, the presentation describes the experience gathered in the sedan segment in particular, including statements by more than 230 customer’s and representives of the press at different European locations. The customer requirements were recorded according to statistical principles and processed further to show results in terms of target values for the engineer’s, using a QFD matrix specially adapted to the handling properties of vehicles. For this reason, a detailed subjective and objective benchmarking program, based on vehicle performance properties as well as chassis design parameters, was conducted, too. [5,6] The result: multidimensional influences on handling properties can be addressed by IMPROVE by QFD. Furthermore, unclear statements by customer’s can be translated into vocabulary suitable for engineer’s. “Over-engineering” is successfully detected by the methodical approach and allows maximum efficiency in the use of development / production budgets. The result is a time- and cost-optimized scenario for chassis design with optimized steering behavior from the customer’s point of view.. The objective was to achieve customer-oriented design of the handling properties – or simply stated: Engineered emotion.

1. INTRODUCTION All manufacturers strive to differentiate their products in order to distinguish themselves from potential competitors and to offer a product to their customer’s which are as attrac-tive as possible. In product development, outside of chassis engineering, methods such as bottle-neck engineering, TRIZ, QFD and others are widespread. On the one hand, the aim is to realize customer wishes as closely as possible and on the other, to mini-mize development as well as production costs. Usually, a known customer wish serves as the origin of a new product or functional feature which is directly derivable from this wish. The multi-dimensional field of driving dynamics offers a multitude of interpretations of the type of vehicle the customer would wish for. In this context several, mutually influ-encing product aspects such as the steering system, kinematics design of the chassis or perhaps merely the selection of suitable tires could be attributable to a customer wish, which might have been worded as “sporty handling.”

The specification of target parameters for the items named as the basis for the design process is the job of the engineer. Between these poles, i.e. the customer’s emotions and the facts and figures required by engineer’s, the application of QFD (Quality Func-tion Deployment), a tried and tested method, is intended as a tool.

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TÜV Automotive’s IMPROVE by QFD captures the customer’s wish according to statistical principles and processes this information into target parameters for engineer’s, using a QFD approach which has been specifically adapted to the aspect of handling and drivability. The investment of time and costs required to obtain the outcome, a scenario for fulfilling customer wishes through respective engineering, is optimized by the method itself. In collaboration with Toyota Motor Corporation the IMPROVE by QFD method was to be used for the first time to show the customer’s preferred choice in steering behavior in a prototype to be subsequently verified/confirmed again by the customer in a final Customer Test Ride. Previous studies had shown that the complex subject of steering behavior contributes significantly to an attractive driving experience and is one of the top priorities on customer’s wish lists. For the program, the lower and upper mid-sized car segments were selected and shown, using a suitable benchmark of a total of eight vehicles. The objective of the project was to create an attractive design of steering behavior, in other words: Engineered Emotion.

2. QFD Schematic Presentation: IMPROVE BY QFD Central element of the methodology presented in this paper is the House of Quality (HoQ). Quality in this context is defined as the fulfillment of customer wishes. Figure 2.1 shows a diagram of the House of Quality. While Figure 2.1 shows a total view of the HoQ, we are going to initially focus on the diagram. The graph shows the horizontal frame of the “customer language.” This is where the customer’s statements are cap-tured using statistical-psychological tools, and processed into a development objective from the customer’s perspective, the “3b Customer Targets.” This result obtained from steps 1-3 is intended to provide answers to a question which might be formulated like this: “How would we like to have customer’s rate our new product, or evolution of an existing product, during the next survey?” As a suitable tool for portraying these “cus-tomer targets” the Market Opportunity Map (MOM) has established itself. In the vertical frame the diagram shows the “engineer’s language.” In steps 4 to 5 the engineering options for product optimizations based on the stringent, methodical QFD approach are listed and linked to the collection of customer wishes. Steps 6 to 9 produce the effort- and cost-optimized generation of engineering measures needed to achieve a product evolution.

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Figure 2.1 – House of Quality (HoQ) – diagram

3. CUSTOMER/ WISHES/WEIGHTING/CUSTOMER TARGET The entire customer survey illustrated by the example of steering behavior was performed by chassis specialists with specific training in interviewing techniques at selected locations in Europe. The locations were selected so as to ensure a representative set of findings. Over 200 customer’s drove the benchmark vehicles while the specialist guided the interview and recorded the responses from the passenger’s seat. To complete the picture, a similar program was conducted with a group of 18 European media representatives from automotive magazines to TV journalists. The survey was conducted in a 3-level matrix with basically open questions and neutral key words. This was designed to avoid any influence being exerted on the customer’s choice of words which would have adulterated the customer’s language. Furthermore, this method offers the major benefit of being able to gather customer wishes which would not be reflected in a closed questionnaire. In addition, experience has shown that the compulsory response to questions which exceed the perception and ability to make judgments of some customer’s reduces the significance of the result. Among other things, the key words are derived from a functional model, “Steering Behavior / Steering Feeling,” created by a workshop team of specialists during the preparatory phase. This functional model reflects the interactions which may directly or indirectly influence the focal area of the study. As such, the seating position

Customes’ language

Customers’ wishes

1

Engineer’s’ language

Technical Specification

4

Linkage between customer’s’ wishes

versus Technical Specifications

5

Weighing TS 6

Tech. Benchmarking 7

Technical Targets 8

Cost Analysis 9

2

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Customer target

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considerably influences the steering feeling that is generated within the driver, although this aspect is difficult to influence by the chassis developer. As the level rose during the course of the interview, the customer’s previous responses were questioned and analyzed and thus became increasingly detailed. At this point, the value of the approach of using chassis specialists who are native speakers to perform the survey was confirmed. This proved to be a prerequisite for capturing the nuances (“reading between the lines”) of the customer’s’ statements, in other words recognizing the customer’s’ true intentions and evaluating and allocating the respective driving situation and vehicle response. Figure 3.1 below shows a section of the 3-level matrix.

On the left-hand side of the table the customer wishes expressed during the three, as-cending interview stages and their weighting (Imp = importance) is shown. The weight-ing scheme corresponds to a statistical spread of the total naming of items standard-ized to a column total of 100. On the right-hand side the fulfillment of the listed wishes by the various vehicles has been documented. Large numbers represent good levels of customer satisfaction. A good overview of these survey results is provided by the Market Opportunity Map (MOM). This graph groups all customer wishes as well as the rating awarded to the various vehicles within the four quadrants of the axial cross, “Satisfaction” vs. “Weighting.” Figure 3.2 depicts a respective MOM. The numbers in the symbols represent customer wishes. The Market Opportunity Map is suitable for use as a “quick-to-grasp” presentation to establish customer targets following the analysis of the surveys. The various quadrants contain the customer wishes with different priorities for optimization. The most impor-tant quadrant, no doubt, is the one on the upper left-hand side (1. Actions necessary). This is where customer wishes have been identified as being important, but are not be-ing met sufficiently by Car E. The items which tend to be less important in the second quadrant (2. Action useful), which might put the finishing touches on the product from

535432pleasant steering forces

665662steering without clearance

364658precise and direct steering

12overall good tractability

good lookingsteering wheel

safe steeringbehaviour

12good steering

Fzg EFzg CFzg DFzg BFzg AImp.3rd Level

of CRImp.

2nd Level of CR

Imp.1st Level of CR

Customer BenchmarkCustomer Requirements - Importance

535432pleasant steering forces

665662steering without clearance

364658precise and direct steering

12overall good tractability

good lookingsteering wheel

safe steeringbehaviour

12good steering

Fzg EFzg CFzg DFzg BFzg AImp.3rd Level

of CRImp.

2nd Level of CR

Imp.1st Level of CR

Customer BenchmarkCustomer Requirements - Importance

Figure 3.1 – 3-level matrix, result of survey

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the customer’s perspective, are contrasted by the third quadrant (3. Cost reduction possible). This quadrant shows customer wishes which tend to be less important to the customer but are being met excessively by Car E. An indicator for potential: “over-engineering.” In addition, the example shows the customer targets, which have been entered using the symbols of the “Target Car” on the right-hand side. They mark the objective of the optimization.

Figure 3.2. Market Opportunity Map (MOM) example v ersion The survey result shown in Figure 3.2 is a component of the horizontal frame in the HoQ as well. Figure 3.3 shows the survey result which in addition, for a better spread in columns 8-13, is multiplied with the customer’s’ weighting. To ensure that the informational content of this presentation remains equivalent to the MOM, the importance attributed by the customer is visualized in column 15, and the customer target recorded in column 16. This means that all relevant information has been captured in a transparent format. The most important customer wish by far, in terms of steering behavior, can be seen clearly in line 5 in this format as well: “precise and direct feedback (steering),” Column 16 (Actions) reflects a note: “Yes, action planned; objective: ‘best in class’.”

Market Opportunity Map (MOM)

1. Action necessary

Very Dissatisfied

8

7

6

5

4

3

2

7 6.5 6 5.5 5 4 3.5 3 2.5 2

Very Important

Very Satisfied

Less Important

13 13 13 13 13

21 21 21

20

35 34 10 23 23 23 23

16 16 8

5 4

7 7

4.5

2. Action useful

Symbol Legend

Car A

Car B

Car C

Car D

Reference

Target Car 17 17

14

4

8

14

17

3. Cost Reduction possible

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Figure 3.3. House of Quality

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4. Linking Customer Emotions to Technical Specific ations

The objective is to link the emotions and wishes of the customer’s to the Technical Specifications. For this purpose, the intersecting area of the horizontal customer frame is processed with the vertical engineer’s frame. The conventional QFD method exclusively uses directly quantifiable values [4]. The complex subject of handling and steering feeling, however, is described by means of a large number of individual parameters [2, 3] and, considering the customer’s very emo-tional and “compound” wishes cannot be addressed by the “conventional” QFD method. The significance of the identified point, “precise and direct steering” is very complex due to its very emotional component. The evolution of QFD into “IMPROVE by QFD” was therefore the next logical step. To perform the links within the matrix the columns were filled with supra-ordinate terms for entire groups of Technical Parameters. To illustrate the point, Figure 4.1 shows the Technical Specification, “Tire Characteristics” (column 2), representing such technical parameters as “longitudinal/lateral slip behavior”, “tire damping”, “uniformity”, etc. A crucial additional specialty is the inclusion of evaluation criteria from the subjective handling evaluation [1]. A robust method to form the subjective judgment of the test drivers was used in order to ensure the reproducibility of the evaluation. If the customer’s wish has been worded, “I want a smaller steering wheel,” this wish can be linked directly with the technical feature, “steering wheel diameter.” For “precise and direct steering,” the QFD evolution, “IMPROVE by QFD,” first performs a transla-tion into the subjective engineer’s language, to thus de-emotionalize the wish, before it is translated into objective parameters and specification values in further translation steps. When linking emotions and specifications, for each intersecting point, a question worded something like, “How strong is the influence of the Technical Specification, ‘steering response’ (column 5) on the customer’s wish of “precise and direct steering” (line 5) arises. The level of influence is expressed on the following scale:

0 = no influence 1 = low 3 = medium 9 = strong

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It becomes obvious quickly that an increasing number of Technical Specifications results in a disproportionate increase in the number of linking questions required, thus justifying the approach of using supra-ordinate terms. After the linking questions, a characteristic value is identified for each Technical Speci-fication, called “Calculation Relationship” in this case. For each column, the linked val-ues are multiplied by the importance of the customer wish, and a total for the column is created. The higher the value of a column, the more directly a change to this particular Technical Specification can serve to influence the sum total of all customer wishes. This procedure enables an optimization of costs and efforts to be achieved. If the Technical Specifications are sorted by the points score, this will result in a ranking as shown by example in Figure 4.2. These rankings are created in accordance with each translation step – from the customer’s wish to the subjective engineer’s evaluation, from the subjective engineer’s evaluation to vehicle performance properties and from vehicle performance properties to design parameters.

Figure 4.1 – Linking customer wishes and technical specifications

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good looking steering wheel

overall good tractability

precise and direct steering

steering without clearance

pleasant steering forces

1

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Now all the information is available which is required to answer the question: “What technical criteria influence customer wishes in the most positive way?” Figure 4.3 – Ranking comparison after translation, customer’s vs. media

Ranking Technical Specifications

0

20

40

60

80

100

120

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Figure 4.2 – Sorting of the Technical Specificati ons with the strongest influence

Customer Media

MEDIA Quasi Objective Specifications

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150

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Technical Specification Value Technical Specification Value Technical Specification Value Technical Specifications Value

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Steering

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Steering Impression Center Point Precision Ditch effe ct Steering Forces during driving

Customer Criteria Analysis Matrix

Most relevant customer Criteria 2nd most relevant cu stomer Criteria 3rd most relevant customer Criteria 4 th relevant customer Criteria

Highly interesting at this point were the differences in the ranking after the translation from the customer’s’ language into the engineer’s language compared with the media language into the customer’s language. In this case the top four engineer’s criteria in terms of naming, and even sequence, were identical. The evaluation of the correlations of the various translation steps within the engineer’s language is done in the “Customer Criteria Analysis Matrix (CCA Matrix) as shown in Figure 4.4. Figure 4.4 – Customer Criteria Analysis Matrix

The CCA Matrix shows those terms in the engineer’s’ language which positively influence customer’s wishes at the highest level of efficiency and the technical parameters from the individual functional groups which, in turn, have the major influence on them. Now the most important customer wish, “precise and direct steering,” has been effectively linked with the technical criteria identified from the individual functional groups (tire; brake; steering; K&C, vehicle performance properties, etc.).

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5. Technical benchmark 1 Using the correlations in Figures 4.1 and 4.2, it is now possible to derive changes from this data for the Technical Specifications with the strongest influences. As a result of working with supra-ordinate terms such as “tire characteristics” in the specifications, a program for a technical benchmark was put together, which enabled an objective description of the parameters relevant for steering behavior. This selection of technical parameters of the comparison vehicles was determined in order to obtain a complete picture for the subsequent definition of the parameters in the action plan. It was evident, though, that the conventional methods for objective evaluation of the most important criteria for steering behavior had to be insufficient. For this purpose, an expanded standard for objective measurement was developed. Aside from standard tests to determine the vehicle’s transfer performance, kinematics and elastokinematics as well as tire parameters, tests to assess important design factors such as the ditch effect and steering system hysteresis became a component of the test matrix. Using the results of the benchmarking, it was now possible to fill the development stage matrix, which is an important tool in the IMPROVE by QFD process. This matrix is depicted in Figure 5.1. In the horizontal lines it contains all technical criteria sorted by the individual functional groups. The vertical columns reflect the development process from the initial tests (benchmarking) on the left-hand side to the first prototype at the far right-hand side. Colored indicators show the degree of compliance of the respective technical criterion from one development step to the other and whether a criterion qualifies for very effective, effective or ineffective modification.

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BLUE MATRIX

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steering response

71 VP 1257 2 11 1 modified **)

72 DP 805 8 30 2 See Step Input modified **)

steering system

74 DP 799 9 31 2 [-] 16,70 15,00 20,80 16,0 - 16,5 16,9:1

75 DP 1170 3 15 1 See Ditch Mapping Test modified **)

76 DP 900 5 23 2 see Free Steer Behaviour modified **)

77 DP 1003 4 22 2

78 DP 70 24 161 3 [°] 522,08 539,09 637,58 550 - 600 modified **)

79 DP 114 18 142 3 [°] 35,39 34,60 35,11 k.v. *) modified **)

80 DP 1358 1 8 2 see Steering returnability Test modified **)

steering feedback

82 VP 891 6 24 2 modified **)

83 VP 815 7 29 2 modified **)

84 VP 492 10 55 3 modified **)

85 VP 207 17 115 3 see Steering returnability Test modified **)

86 DP 454 11 64 3 eval. in progress modified **)

87 Chassis

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K&C: Vertical test

89 DP 1228 6 13 1 see FTP Server modified modified modified **)

90 DP 1248 5 12 1 see FTP Server modified modified modified **)

91 DP RF Wheel Rate Slope 587 20 41 2 see FTP Server modified modified modified **)

92 DP LF Wheel Rate 1228 6 13 1 see FTP Server modified modified modified **)

93 DP LF Wheel Rate Slope 503 29 53 1 see FTP Server modified modified modified **)

94 DP Front Tire Radial Rate 630 18 38 2 see FTP Server modified modified modified **)

IMPROVE - Level 3IMPROVE - Level 2

Brief description of Segment

Segment A IMPROVE - Level 1

Figure 5.1 The blue matrix shows the development p rocess

6. – what criteria must be improved? – ACTION PLA N The action plan, as well, is tied to the blue matrix. It specifies target values and corridors for the individual technical specifications which have been identified. This preparation of a specifications book kicked off the development of the prototype which then had to pass the test of the customer’s critical eye. Prior to that, however, there was another step to be completed: The identification of the items which truly required improvement. The IMPROVE by QFD method initially reflects the most critical and most relevant technical specifications which have the most significant influence on customer satisfaction. At the same time, the objective benchmark shows the objective values of many parameters. Now it is time to identify those parameters which A) still leave major room for improvement and B) do not

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degrade customer wishes, which have already been met, as the result of a negative interaction. The project team discussed these issues and decided what functional groups need to be worked on to achieve the objectives. The content of the action plan, for one, consisted of an assessment of the target values/corridors to be complied with regarding the Technical Parameters of the supra-ordinate terms shown in Figure 4.2. For the other, the requisite investment of time and money was assessed. This resulted in an action plan which provided the basis for preparing a specifications book pertaining to this optimization of steering performance. The target values, as well, are listed in the blue development matrix.

7. DEVELOPMENT OF THE IMPROVED VEHICLE The following functional groups to be modified were identified as being highly effective: � Seat � Front axle kinematics � Steering kinematics � Steering ratio � Spring/damper adjustment Figure 7.1 Adjustable front axle

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The kinematic changes identified in the QFD process were developed using the ADAMS/Car and Carsim simulation tools, a decision supported by the desire to make efficient use pf the project time. In addition to the option of changing the steering ratio, the modifications made to the adjustable front axle shown in Figure 7.1 include an adjustment option of the instantaneous center of rotation and the steering kinematics (toe-in vs. spring travel). Furthermore, the project team – in accordance with the output of the QFD process – changed the suspension set-up (spring/damper) and the roll rate (stabilizer/anti-roll bar). Items which were very important to customer’s, such as “ride comfort,” were not impaired by the various chassis-related measures. Focussing on the specifications which according to the QFD process show the highest level of relevance was responsible for the high level of efficiency of the measures taken, as the final Customer Test ride was to show.

8. TECHNICAL BENCHMARK 2 In order to be able to assess the change of the technical specifications and to enable a comparison with the target values, a second technical benchmark had to be performed. Figure 8.1 by means of an example in the abscissa shows the most important items identified in the engineer’s language sorted by their importance and, above this, the degree of compliance achieved by the individual vehicles. Criteria of particular importance in terms of customer wishes should have a high degree of compliance, and thus a good performance from the customer’s perspective. The improvement in these relevant items documented in Figure 8.1 suggests that there is a good starting basis for the Customer Test Ride. High performance, particularly in the important items, is shown by the diagram. At least the engineer’s are now convinced of the project’s success. Yet the final success regarding improved and more attractive/delighting steering behavior can only be confirmed by the customer him-/or herself. The customer should have the final word in a concluding Customer Test Ride and confirm the value of the process and the project.

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Figure 8.1 Customer wishes and their level of com pliance

9. Verification in the Final Customer Test Ride Whether or not a significant improvement will actually be perceived by the customer is a question which, ultimately, can only be confirmed by the critical and unadulterated view of the customer in a final Customer Test Ride. The group of interviewers as well as the methodology, interviewing strategy and the type of questions and questionnaires used is identical to those of the Customer Test Rides conducted at the beginning of the project. This ensures maximum comparability. The vehicle matrix consists of the original vehicle and the designated benchmark vehicle of a competitor and, of course, the improved vehicle which, if not earlier, now has to pass the test of the critical eye of the consumer. This determines the success or failure of the project. To back the results by statistical means, a minimum of 25 participants in the designated customer segment have to look at the vehicles and, of course, drive them extensively. The customer wishes of the final Customer Test Ride, as well, are displayed in the 3-level matrix during the QFD process, and the questionnaires evaluated accordingly. A first result is the Market Opportunity Map (MOM) of the final Customer Test Ride. How are the items which are important to the customer complied with by the three comparison vehicles? The MOM’s of Figures 9.1, 9.2 and 9.3 provide information about

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the degree of compliance with the individual customer wishes. Criterion 1, for example, is the customer wish, “precise and direct steering.” The direct comparison shows that in terms of important customer criteria the improved vehicle (Figure 9.1) has seen a crucial improvement compared with the original vehicle (Figure 9.2). The comparison with the competitor’s vehicle (Figure 9.3), as well, shows the success of the project. Figure 9.1 MOM improved vehicle

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Figure 9.2 MOM original version

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Figure 9.3 MOM competitor’s vehicle

Reference [1] Heißing, B.; Brandl, H.J.; Subjektive Beurteilung des Fahrverhaltens. Würzburg : Vogel-Buchverlag, 2002 [2] Matschinsky, W; Radführungen der Straßenfahrzeuge: Kinematik, Elasto-Kinematik und Konstruktion. 2.Aufl. Berlin : Springer-Verlag, 1998 [3] Reimpell, J.; Betzler, J.; Fahrwerktechnik, Grundlagen. 5.Aufl. Würzburg : Vogel-Buchverlag, 2005 [4] Klein, B.; QFD - Quality Function Deployment. Renningen-Malmsheim : expert-Verlag, 1999 [5] Becker, K.; weitere; Subjektive Fahreindrücke sichtbar machen. Renningen-Malmsheim : expert-Verlag, 2000 [6] Becker, K.; weitere; Subjektive Fahreindrücke sichtbar machen II. Renningen-Malmsheim : expert-Verlag, 2002

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