Keywords

1 Introduction

Nowadays, the consumers’ demand for minicars changes from the functional requirements to the symbol of the consumers’ own value, so the minicar styling will become an important factor that must be taken into account. Due to the characteristic of minicar styling that it is the front face of car that is easily noticed, the front face design of minicars has a direct impact on the purchase of cars by the consumers. However, the creative ability of most of China’s self-owned enterprises on the automobile appearance design is still to be improved. In fact, many designs are suspected of copying, over-imitation or outsourcing to design companies with foreign capital, etc., such as Lifan 320 to MINI, Landwind X7 to Range Rover Evoque, Shuanghuan SCEO to BMW X5 and so on. Therefore, China’s automobile industry needs a method to make an optimal design of minicars’ front face originally and aesthetically.

In this paper, we adopt analytic hierarchy process (AHP) to analyze the factors of minicars’ front face design in China’s automobile market. Based on the above description, the purpose of this study is as follows: It adopts the document research and comparative analysis, to find the optimal methods and related technologies suitable for the front face design of minicars; it compares the factors in the optimal design of minicars’ front face through questionnaire; it uses the analytic hierarchy process as the analysis tool, to analyze the elements and standards needed by the early development and research of the optimal design of minicars’ front face; it finally carries out the sorting of factors in the optimal design of minicars’ front face, to help develop decision-making during the initial development.

2 Literature Review

2.1 Kansei Engineering

As a new subject that combining with social science and natural science, kansei engineering is rigorous and scientific. By means of engineering technology, it tries to quantify the various feelings of people (temporarily called “amount of sensibility”), and then it finds out the functional relation between the amount of sensibility and the various physical quantities used in engineering technology as the basis of engineering analysis and research [1]. Kansei engineering effectively quantifies the abstract problems, so as to help the researchers develop relevant quantitative criteria. The research on the application of kansei engineering in the car-related design has also achieved some progress. For example, based on the research on the appearance design of off-road vehicles with kansei image, the design reflects the integrity, coordination, balance, toughness and other kansei images of the off-road vehicle modeling [2]. Through the study on the matching of the shape and consumers’ emotional intention, it finds out the products that accord with the customers’ intention. For kansei assessment of the constituent elements and the overall interrelations in car steering wheel design [3], it design more intelligent and convenient vehicle-mounted steering wheel; based on the kansei engineering and TRIZ theory, it designs the car seat taking into account visual comfort [4], in order to meet the consumer’s requirements for the comfort of the car seat; the above studies all have used the method of kansei engineering, which provides decision-making conclusions for its related questions of design.

2.2 Analytic Hierarchy Process

Analytic hierarchy process (AHP) was formally proposed in the mid-1970s by Saaty, a US operational research expert. It is a qualitative, quantitative, systematic and hierarchical analysis method. Because of its practicality and effectiveness in dealing with complex decision-making problems, it has gained great attention all over the world [1]. Saaty [5, 6] and Vargas [7] pointed out that AHP can also be further applied to the analysis of thirteen categories of problems, including: prioritization, alternation, selection of preferred plans, requirements, resource allocation, predicting results, performance measurement, system design, system stability, optimization, planning, conflict resolution and risk assessment [8].

AHP is mainly to distinguish the complexity of the study, through a variety of different ways of simplified definition, to from a simple and clear hierarchical relationship. The factors to be studied are compared one by one, and the quantified values represent the weights of the factors at each level and are evaluated synthetically. The basic process of the analytic hierarchy process is as follows: (1) It simplifies the experimental object and constructs it into a hierarchical model; (2) It creates a quantization table of the comparison array; (3) It calculates the weight value and checks it, which is only effective after meeting the consistency; (4) It calculates the comprehensive weight value and carries out the consistency test of comprehensive weight. Then the decision is made through the use of the results.

Saaty and Vargas [9] proposed four approximate solutions to the eigenvectors in the AHP matrix, and the large eigenvalues were obtained by multiplying the pairwise comparison matrix A (hierarchy X) by the eigenvector W to obtain the new vector W′. Each large value (λmax) can be obtained by dividing each vector value of the vector W′ by the vector value of the original vector W, and then calculating all the values obtained. After the calculation of the large eigenvalues (λmax) of the pairwise comparison matrices, the consistency index (C.I.) is used as the indicator of whether the consistency is achieved and consistency ratio (C.R.) is used as the indicator of whether the degree of consistency is satisfactory. C.I. and C.R. are calculated as follows. C.I = λmax−x/(x−1) ≤ 0.1; C.R. = C.I./R.I. ≤ 0.1. In the above formula, R.I. is the random consistency index corresponding to the matrix; namely, according to the size of the normalization matrix (hierarchy) it selects the appropriate random consistency index [8].

2.3 Front Face Design of Cars

The front face design of cars has also made a lot of related achievements, such as the bionics design of the front face [10]. Through the discussion on the application of design bionics in the front face design of cars, it reveals a new design form of “bionic conceptual design”, which will lead the front face design of cars to the new trend. Based on the kansei engineering of the optimal design of cars’ front face shape [11], through the neural network structure and eye movement experiments, it provides product designers with reference for kansei design.

To sum up, it is not common to study the optimal design of the front face of cars by using the AHP to analyze the weight of the front face of many vehicle models. Therefore, there is much space for studies on this topic.

3 Experimental Process

According to the front face of more than 70 minicars, it draws the chart of shape affected by relevant factors; and then according to the chart, it develops the questionnaire of shape; the age of the participants of the questionnaire is between 18 and 40 years old. The sample questionnaire is taken. Among 30 candidates who have the intention of buying a car or have a car, it chooses 7 women and 7 men randomly to conduct a detailed questionnaire survey. The results of the questionnaire are analyzed by AHP analysis and the weight is obtained. It also obtains the comprehensive weight values, and then develops the product chain to which consumers pay attention. The following is the analysis process (all the values in the table are the weight value according to the questionnaire, so there is no unit of quantity), taking the seven factors of the front face of cars as an example.

First of all, it constructs the hierarchical model, including the formation of two hierarchical relations (see Table 1); the first layer is on behalf of the seven factors that consumers pay attention to when considering the front face of minicars, which are air-inlet grille of engine, knuckle line of the bonnet, front windshield, bumper, rearview mirror, frame of automotive lighting and fog light. The second layer chooses a single factor for overall comparison, according to the principle of AHP, to determine the weight relationship of each factor in the front face of minicars among seven elements. Then, it develops the description of the questionnaire evaluation scale (see Table 2) and designs the questionnaire (see Table 3).

Table 1. Hierarchical model
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Table 2. AHP evaluation scale description
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Table 3. Questionnaire design
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4 Experimental Results and Conclusions

4.1 From the Above Experimental Data, We Can Draw the Following Experimental Results

Because the validity of the questionnaire should meet the consistency of the questionnaire results, it is determined by the overall consistency ratio CI, RI, CR value. In this study, supposing that CR < 0.1 is the effective research result, 12 questionnaires (5 women, 7 men) are identified as valid reference questionnaires among the 14 questionnaires collected, and the data are calculated and analyzed according to the results of the study. After the normalization of the results, 8 copies are obtained. One of the survey results is shown in Table 4.

Table 4. Results of the weight of 7 factors in the car shape and of the consistency test based on the questionnaire survey results
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In this study, according to the above analysis of the results, can further develop the sorting of attention when the enterprise or design agencies conduct optimized combinational design of minicars’ front face, as in Table 5. Therefore, it can optimize the existing products accurately and efficiently, thereby enhancing the consumers’ desire to buy the products.

Table 5. Comparison results of effective experimental comprehensive weight value
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4.2 Conclusions of the Analysis

This study will provide useful reference for the early stages of the development and design of minicars’ front face. Taking the AHP as the analytical tool, the quantitative elements of the development strategy of minicars’ front face design should be established to determine the objectives when designing. Through the process and results of the analysis, it can be found in this study that the analytic hierarchy process can effectively reduce the complexity of many elements of irregular structures, to develop the quantitative criteria which are helpful for final decision, judgments and reference. With the process of gradual decomposition from high level to low level, it improves the existing procedure of decision that relies on the previous experience, and obtains the preferred weighted value of each factor index, providing a sufficient basis for the final decision-making program. The bigger the integrated weighted value is, the higher the priority of adoption is, and thus the risk of decision error reduces to some extent. Through this experiment, we can design the front face of minicars according to the results of the experiment so that the products to be put on the market will be recognized by consumers as much as possible, thereby increasing the market value of this product.

5 Conclusion

The paper takes the front face design of minicars as an example, with the basic principles of kansei engineering and simplifies the shape of front face of minicars through the experimental study by analytic hierarchy process. After the analysis and demonstration, it achieves the quantification of consumer’s desire for the factors in the front face styling of minicars. Finally, it designs and justifies the factors of shapes with the quantitative relationship.

Through this experiment, in addition to intuition and experience, it can also carry out mini-car design and research from another point of view which is more scientific and more effective; car design itself is of more complex relationship, so it is necessary to start from the consumers’ own demand and to find the quantitative criteria that accords with the actual situation; this analysis method of quantitative criteria not only meets the needs for minicars’ front face design decision-making, but also can be applied to any part of the minicars’ design decision-making. As the decision-makers of enterprises, it is necessary to use a more scientific and reasonable way to make decisions for providing the majority of consumers with better experience services.