Y. Luo (Ed.): CDVE 2006, LNCS 4101, pp. 141 – 148, 2006. © Springer-Verlag Berlin Heidelberg 2006

Usability Ranking of Intercity Bus Passenger Seats Using Fuzzy Axiomatic Design Theory

Ergun Eraslan1, Diyar Akay2, and Mustafa Kurt3

1 Department of Industrial Engineering, Baskent University, 06530 Ankara, Turkey

eraslan@baskent.edu.tr 2,3 Department of Industrial Engineering, Gazi University,

06570 Ankara, Turkey {diyar, mkurt}@gazi.edu.tr

Abstract. Usability, considering user satisfaction along with the user perfor-mance, is one of the key factors in determining the success of a product in today’s competitive market. Designing usable intercity bus seats is important for passengers during the long hours of traveling. Comfort, aesthetic, safety, convenience to the body posture, durability, harmoniousness with the seat accessories and operability are expected usability dimensions of seats for both user and the designers. Aim of this study is to identify and rank ten alternative seats of an intercity bus manufacturing company according to these usability attributes. The products are evaluated by five subjects and assessed for each usability attributes by using linguistic variables. Then Fuzzy Axiomatic Design Theory (FADT), which is the combination of second axiom, is used as a multi attribute decision making tool to determine most usable seat design solution. Design range is defined by design engineers and system ranges for seats are obtained from linguistic assessment of five subjects for applying conformance testing in cooperative engineering.

Keywords: Usability, Fuzzy Axiomatic Design, Conformance Testing, Cooperative Engineering.

1 Introduction

Traveling becomes an integral part of human life nowadays. Among the travel options, traveling by bus is preferred commonly as it is economical compared to others. Passengers spend most of their time on seats of bus during the long travel hours. Therefore, seats are an important factor in seating industry to meet customer expectations. Generally the main task of the ergonomic seat design is increasing the seat conformance which is a complex and subjective notation related to a good physical and psychological well being of the interface between the passenger and the seat. Comfort and discomfort, which are not antonymous, are two main elements of seat design. They are related since it is necessary, but not sufficient to be “not uncomfortable” in order for a seat to be comfortable. While comfort is a subjective notation, and is hard to quantify, discomfort is an objective notation and is related to specific methods (e.g. pressure distribution, electromyography or posture analysis). Hence, discomfort is not only a feature of a seat, but also it expresses to what extent the seat is not sufficient [1],[2],[3].

142 E. Eraslan, D. Akay , and M. Kurt

Therefore evaluation of seat design in literature is mostly related to the discomfort aspect [3],[4],[5],[6],[7]. However, comfort - discomfort related studies are not the only main design factors nowadays. Usability, a holistic view to ergonomic and collaborative product design, is seen as a critical dimension of which importance is increasing swiftly in product design [8],[9]. Usability is defined as effectiveness, efficiency, and satisfaction of a product for achieving specified goals for specified users in a particular environment. Designing usable products is seen a company philosophy for firms in today’s competitive business environment [10]. It is an important stage to observe and analyze multi dimensional product usability attributes in product design. Aesthetic, safety, convenience to the body posture, durability, harmoniousness with the seat accessories and operability of seat are also expected features which are important usability factors for bus manufacturers. Manufacturers want to obtain seats from suppliers which satisfy those usability factors.

In this paper it is tried to identify the best seat among ten available alternative seats considering many usability factors for a factory producing passenger buses. Such problems are referred to as multi-attribute decision making problems in concurrent manufacturing. This study uses FADT to solve this multi attribute decision making problem. This paper is organized as follows. In section 2, FADT method is presented briefly. Section 3 discusses the implementation of FADT to cooperative seat usability decision problem, and the study ends in with section 4 with conclusion and discussions.

2 Fuzzy Axiomatic Design for Multi-attribute Decision Making

A key factor in cooperative product design is the optimization of product development decisions such as the costs, the quality and the time required to design a product. These factors are interrelated and an improvement of one factor may result in a decline in the others. Therefore all these issues have to be considered simultaneously to make the product design more successful. Axiomatic Design (AD) forms a scientific basis to design and improves designing activities by providing the designer with a theoretical foundation based on logical and traditional thought process and tools. AD provides a systematic search process through the design space to minimize the random search process and determine best design solution among many alternatives considering all product development decisions. In the literature, AD theory and principles are used to design products, systems, organizations and software [11]. In ergonomics, Helander and Lin (2002) used axiomatic design as a foundation of ergonomic design and demonstrated examples on how axiomatic design can be used for biomechanics design of hand tools and anthropometric design of workplaces [12]. Lo and Helander (2004) proposed axiomatic design as a formal method for usability analysis for consumer products [13]. Karwowski (2005) also emphasized the applicability of axiomatic design for solving complex ergonomics design problems [14].

Design axioms, namely independence axiom and information axiom, are two key stones of AD. Independence axiom is related to maintaining the independence of functional requirements (FRs), i.e., design solution must be such that each one of FRs can be satisfied without affecting the other FRs. Therefore, a correct set of design parameters have to be chosen to be able to satisfy the FRs and maintain their independences. Among the design solutions satisfying independence axiom, the design with the smallest information content must be chosen. This is the second

Usability Ranking of Intercity Bus Passenger Seats Using FADT 143

axiom, information axiom, of AD. Information content, I, is defined in terms of the probabilities (pi) of satisfying FRi below.

iplog)p

1(logI 2

i2i −== . (1)

In case of having FRs, information content of overall system,Isys, is defined in formula 2.

∑∑∑===

−===n

1ii2

n

1i i2

n

1iisys )(plog)

p1

(logII . (2)

Suh (2001) specifies the second axiom as a decision making tool for complex engineering design problems [11]. Design with the smallest “I ” is the best design as it requires the least amount of information to achieve design goals. If all probabilities are large enough, near to one, then information content is minimum. Probability of satisfying a FR is specified by design range (tolerance) defined by designer and generating ability of the systems (system range). Fig. 1 illustrates these two ranges graphically. In Fig. 1, overlap between the design range and system range is called common range (cr) and this is the only region where FR is satisfied. Therefore area under common range, Acr, is the design’s probability of achieving the specified FRs.

Fig. 1. System range, design range and common range

Many decision making and problem solving tasks are too complicate to be understood quantitatively, however people succeed by using knowledge that is imprecision rather than precise. Fuzzy set theory resembles human reasoning in its use of approximate information and uncertainty to generate decisions. This fact may also be true for engineering decision. System and design ranges may not be defined precisely. If system cannot be defined by using traditional quantitative terms, it is more plausible to use fuzzy linguistic terms. Linguistic terms can be transformed into fuzzy numbers. The fuzzy sets in Fig. 2 are used for converting linguistic terms into fuzzy numbers respectively.

144 E. Eraslan, D. Akay , and M. Kurt

Fig. 2. Fuzzy sets for intangible factors

Fig. 3. Common area for fuzzy case

In the case of having system and design ranges in linguistic terms, ranges will be expressed by using “around a number” , “between two numbers” or “over a number”, which can be explained by using fuzzy numbers. Common area in fuzzy case is the intersection area of fuzzy numbers which are ranges of system and design. Fig. 3 shows common area for a triangular fuzzy number (tfn). Hence, information content for fuzzy case is defined in formula 3.

)area commondesign system of tfn

(logI2

= (3)

Fuzzy case of information axiom is successfully applied to different areas such as; information project selection [15], comparison of advanced manufacturing systems [16], transportation company selection [17], and material handling equipment selection [18].

3 Usability Ranking of Intercity Bus Passenger Seats Using FADT

Ten alternative seats used in the manufacturing facility are chosen for usability study. Seats are shown in Fig. 4. 5 subjects, representing a broad range of body sizes, evaluated

Usability Ranking of Intercity Bus Passenger Seats Using FADT 145

ten different seats during a short-term seating session. The subjects were volunteers of working age with no health problems. Anthropometric measurements of subjects are taken. Mean stature cm is 1.73, mean body mass is 69 kg, and mean age is 29.

A B C D E

F G H I J

Fig. 4. Alternative seats

Table 1. System range data for alternative seats

S Comf. Aesthetic Safety

Conven. to the body

posture

Durability

Harmon. with the

seat acces.

Operability

A Good Fair Good Good Fair Good Fair

B Very Good

Good Good Good Good Good Good

C Very Good

Good Good Very Good

Fair Fair Fair

D Good Fair Good Good Good Good Fair

E Good Good Fair Very Good

Good Good Fair

F Very Good

Poor Good Good Good Good Good

G Good Good Good Fair Fair Fair Good

H Very Good

Fair Fair Good Fair Fair Fair

I Good Good Fair Good Poor Fair Good

J Fair Fair Fair Very Good

Good Good Good

As, vibration effect is not considered in the experiment, data collection was conducted in an environmentally controlled laboratory, rather than a bus. In experiment, effects of seat cover are also neglected.

146 E. Eraslan, D. Akay , and M. Kurt

Before starting the experiment, the subjects were given instructions on the method and experimental procedures. The subject is seated and watches a video on a screen in front of him during experiment. Entire procedure took approximately 50 minutes per subject and evaluating each seat took about 5 minutes. Usability factors used in the study are determined through the focus group study performed with both users and designers in order to measure the effectiveness, efficiency, and satisfaction dimensions of usability. Each subject evaluated each seat for each usability dimension by using one of the linguistic terms; poor, fair, good, very good or excellent. A focus group study was performed to aggregate five subjects’ assessment opinions. Evaluation results, obtained from focus study is shown in Table 1, which corresponds to the system ranges of usability factors. Design ranges (DR) for usability factors are determined by design department of manufacturing facility. DR’s in Table 2. Cooperative engineering approach, which makes the decision making process both more effective and more efficient, is utilized by taking the opinions of users and designers into account.

Table 2. Design range data for usability factors

Usability Factors Design requirements

Comfort Comfort must be very good

Aesthetic Aesthetic must be good Safety Safety must be good

Convenience to the body posture Convenience to the body posture must very good

Durability Durability must be good Harmoniousness with the seat accessories

Harmoniousness with the seat accessories must be good

Operability Operability must be good

Fig. 5. System and design ranges of seat A for “comfort” criteria

55620.0.3708*)2

11-14(area Common == . (4)

Usability Ranking of Intercity Bus Passenger Seats Using FADT 147

4== 1*)2

6-14(area System . (5)

8462.)0.5562

4(log)

area commondesign system of tfn

(logI 22 === (6)

A sample calculation for obtaining information content is shown for “comfort” requirement of seat A. TFNs in Fig. 2. is used for intangible factors. It is observed from Fig. 5 that system range is good and design range is very good for comfort criterion. Common area and system area are 0.5562 and 4 respectively calculated from formulas 4-6. The value 0.3708 in equality 4, is the height of shaded triangle in Fig. 5 which is referred to as common area. Fig. 5. shows common area of seat A for “comfort” criteria.

Information contents for other usability factors for each alternative seat are given in Table 3. Alternative seat with the minimum information content is Seat B. According to those usability factors, the most usable seat is Seat B and the most unusable seats are F,G,I and J. Usability ranking obtained by using FADT is B>E>C>D>A>H>F=G=I=J. If Table 3. is investigated deeply it can be shown that seat F together with seat B have the minimum information content in total except for “aesthetic” factor. However, seat F is not selected because design range and system range for that factor is not overlapped. In this problem, it is assumed that all usability factors have equal importance. It is also possible to give different importance weights to usability factors to obtain different rankings.

Table 3. Information contents for alternative seats

S IComf. IAesthetic ISafety IConvenience

to the body

posture IDurability

IHarmon.

with the

seat acces. IOperability ∑ I

A 2.846 1.732 0 2.846 1.732 0 1.732 10.888 B 0 0 0 2.846 0 0 0 2.846 C 0 0 0 0 1.732 1.732 1.732 5.196 D 2.846 1.732 0 2.846 0 0 1.732 9.156 E 2.846 0 1.73 0 0 0 1.732 6.31 F 0 Infinite 0 2.846 0 0 0 infinite G 2.846 0 0 Infinite 1.732 1.732 0 infinite H 0 1.732 1.73 2.846 1.732 1.732 1.732 11.506 I 2.846 0 1.732 2.846 Infinite 1.732 0 infinite J infinite 1.732 1.73 0 0 0 0 infinite

4 Discussions and Conclusion

It is desired in the cooperative approach that designer and user (or customer) be present in engineering application and decision making processes. Such a cooperative approach will increase the success and effectiveness of the decisions made. In this article, a new multi-attribute cooperative decision making tool, FADT, is used for ranking alternative seats considering usability factors. Usability factors presented for this research is almost subjective. Therefore it will be advantageous to use FADT which cover fuzzy aspect. Designer and user requirements are taken into account by

148 E. Eraslan, D. Akay , and M. Kurt

using system range and design range concepts which are the key stones of axiomatic design. FADT enables cooperating user and designer requirements into design selection process. In this sense, strength of FADT is very clear. Except for the usability factors, engineering data related to seat (such as pressure distribution) or monetary value of bus seats can be integrated to seat selection process in order to increase the effectiveness of decision process.

References

1. Levrat, E., Voisin, A., Bombardier, S., Bremont, J.: Subjective evaluation of car seat com- fort with fuzzy set techniques. International Journal of Intelligent Systems 12 (1997) 891-913

2. Zhang, L., Helander, M.G., Drury, C.G.: Identifying factors of comfort and discomfort in sitting. Human Factors 38 (1996) 377-389

3. Looze, M.P. de, Kuijt-Evers, L.F.M., Dieën, J. van.: Sitting comfort and discomfort and the relationship with objective measures. Ergonomics 46 (2003) 985-997

4. Jianghong, Z., Long, T.: An evaluation of comfort of a bus seat. Applied Ergonomics 25 (1994) 386-392

5. Kolich, M.: Ergonomic modeling and evaluation of automobile seat comfort. Ph.D. Dissertation, Windsor, ON (2000)

6. Kolich, M.: Automobile seat comfort: occupant preference vs. anthropometric accommodation. Applied Ergonomics 34 (2003) 177–184

7. Kolich, M., Taboun, S.M.: Ergonomics modeling and evaluation of automobile seat comfort. Ergonomics 47 (2004) 841–863

8. March, A.: Usability: the new dimension of product design. Harvard Business Review 72 (1994) 144-149

9. Han, S.H., Yun, M.H., Kim, K.J., Kwahk, J.: Evaluation of product usability: development and validation of usability dimensions and design elements based on empirical models. International Journal of Industrial Ergonomics, 26 (2000) 477-488

10. Rubin, J.: The Handbook of Usability Testing: How to Plan, Design, and Conduct Effective Tests. John Wiley & Sons, New York (1994)

11. Suh, N.P: Axiomatic design, advances and applications, Oxford University Press (2001) 12. Helander, M.G., Lin, L.: Axiomatic design in ergonomics and an extension of the

information axiom, Journal of Engineering Design 13 (2002) 321-339 13. Lo, S., Helander, M.G.: Developing a formal usability analysis method for consumer

products. Proceedings of ICAD, The Third International Conference on Axiomatic Design, Vol. 26 (2004) 1-8

14. Karwowski, W.: Ergonomics and human factors: the paradigms for science, engineering, design, technology and management of human-compatible systems. Ergonomics 48 (2005) 436-463

15. Kulak, O., Kahraman, C., Öztayşi, B., Tanyaş, M.: Multi attribute information project selec- tion using fuzzy axiomatic design. The Journal of Enterprise Management 18 (2005) 275-288

16. Kulak, O., Kahraman, C.: Multi-attribute comprasion of advanced manufacturing systems using fuzzy vs. crisp axiomatic design approach. International Journal of Production Economics 95 (2005a) 415-424

17. Kulak, O. and Kahraman, C.: Fuzzy multi-attribute selection among transportation companies using axiomatic design and analytic hierarchy process. Information Sciences 170 (2005b) 191-210

18. Kulak, O.: A decision support system for fuzzy multi-attribute selection of material handling equipments. Expert Systems with Applications 29 (2005) 310-319