INTITUIONISTIC FUZZY TLX (IF-TLX): IMPLEMENTATION OF INTITUIONISTIC FUZZY SET THEORY FOR EVALUATING SUBJECTIVE WORKLOAD

Year 2018, Volume: 2 Issue: 1, 79 - 90, 30.06.2018

Gülin Feryal Can

Abstract

The determination of subjective workload (SWL) imposed on an employee plays an important role in designing and evaluating an existing work and work environment. Additionally, it is a hard problem since SWL evaluation is typically a multi-dimensional problem involving several work demands on which employee’s evaluation is usually vague and imprecise. In this study, NASA TLX (National Aeronautics and Space Administration Task Load Index) method used widely in different work types combined with intuitionistic fuzzy set (IFS) theory to determine SWL in an industrial sailing firm. The integrated method is named as Intuitionistic Fuzzy TLX (IF-TLX). IFS theory is a powerful tool to model the uncertainty because of degree of hesitation in human decision system. It is worth pointing out that proposed method also considers work experience effect on SWL evaluation. This improves objectivity of final SWL scores for the whole work. This paper also develops a new intuitionistic evaluation scale for rating of SWL dimensions and work experience. As a result of this study it is determined that industrial salespeople who have more than 15 years of work experience feel the highest SWL with the effect of increasing age

Keywords

Subjective Workload, Intuitionistic Fuzzy Sets, Intuitionistic Triangular Fuzzy Numbers

References

• [1] Rubio S, Díaz E, Martín J, et al. Evaluation of subjective mental workload: A comparison of SWAT, NASA TLX, and workload profile methods. Applied Psychology. 2004, 53(1): 61-86. [2] Reid GB, Nygren TE. The subjective workload assessment technique: A scaling procedure for measuring mental workload. Advances in psychology. 1988, 52: 185-218. [3] Vidulich MA. The use of judgment matrices in subjective workload assessment: The subjective workload dominance (SWORD) technique. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 1989 October, 33(20): 1406-1410. [4] Hart SG, Battiste V, Lester PT. Popcorn: A supervisory control simulation for workload and performance research. 1984. [5] Hart SG, Hauser JR. Inflight application of three pilot workload measurement techniques. Aviation, space, and environmental medicine. 1987. [6] Käppler WD, Godthelp H, Pitrella FD. Psychometric and performance measurement of light weight truck handling qualities. 1988. [7] Hart SG, Staveland LE. Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research. Advances in psychology. 1988, 52: 139-183. [8] Reilley S, Grasha AF, Filburn J. Generalizing to real world phenomena: Perceived workload among pharmacists and stimulation participants. 12th annual meeting of the American Psychological Society. 2000, Miami, Florida. [9] Schmidt FL, Hunter, JE, Outerbridge, AN. Impact of job experience and ability on job knowledge, work sample performance, and supervisory ratings of job performance. Journal of applied psychology.1986, 71(3): 432. [10] Zadeh LA. Fuzzy sets as a basis for a theory of possibility. Fuzzy sets and systems. 1978, 1(1): 3-28. [11] Atanassov KT. Intuitionistic fuzzy sets. Fuzzy sets and Systems. 1986, 20(1): 87-96. [12] Herrera F, Martınez L, Sánchez PJ. Managing non-homogeneous information in group decision making. European Journal of Operational Research 2005, 166(1): 115-132. [13] Li D. Fuzzy multiattribute decision-making models and methods with incomplete preference information. Fuzzy Sets and Systems. 1999, 106(2): 113-119. [14] Szmidt E, Kacprzyk J. Group decision making under intuitionistic fuzzy preference relations. In Traitement d’information et gestion d’incertitudes dans les systèmes à base de connaissances. Conférence international. 1998, 172-178. [15] Hussain RJ, Kumar PS. Algorithmic approach for solving intuitionistic fuzzy transportation problem. Applied mathematical sciences. 2012, 6(77-80): 3981-3989. [16] Dubois D, Prade H. Systems of linear fuzzy constraints. Fuzzy Sets and Systems.1980, 3(1): 37-48. [17] Grzegorzewski P. Distances between intuitionistic fuzzy sets and/or interval-valued fuzzy sets based on the Hausdorff metric. Fuzzy sets and systems. 2004, 148(2): 319-328. [18] Mouzé-Amady M, Raufaste E, Prade H, Meyer JP. Fuzzy-TLX: using fuzzy integrals for evaluating human mental workload with NASA-Task Load index in laboratory and field studies. Ergonomics. 2013, 56(5): 752-763. [19] Lee YH, Liu BS. Inflight workload assessment: Comparison of subjective and physiological measurements. Aviation, space, and environmental medicine, 74(10): 2003, 1078-1084. [20] Matthews R, Legg S, Charlton S. The effect of cell phone type on drivers’ subjective workload during concurrent driving and conversing. Accident Analysis & Prevention. 2003, 35(4): 451-457. [21] Stefanidis D, Wang F, Korndorffer Jr, JR, Dunne JB, Scott DJ. Robotic assistance improves intracorporeal suturing performance and safety in the operating room while decreasing operator workload. Surgical endoscopy, 2010, 24(2): 377-382. [22] Zheng B, Jiang X, Tien G, Meneghetti A, Panton ONM, Atkins MS. Workload assessment of surgeons: correlation between NASA TLX and blinks. Surgical endoscopy, 2012, 26(10): 2746-2750. [23] Mazur, L. M., Mosaly, P. R., Hoyle, L. M., Jones, E. L., & Marks, L. B. (2013). Subjective and objective quantification of physician’s workload and performance during radiation therapy planning tasks. Practical radiation oncology, 3(4), e171-e177. [24] Durantin G, Gagnon JF, Tremblay S, Dehais F. Using near infrared spectroscopy and heart rate variability to detect mental overload. Behavioural brain research. 2014, 259: 16-23. [25] Ruiz-Rabelo JF, Navarro-Rodriguez E, Di-Stasi LL, Diaz-Jimenez N, Cabrera-Bermon J, Diaz-Iglesias C, ... & Briceño-Delgado J. Validation of the NASA-TLX Score in Ongoing Assessment of Mental Workload During a Laparoscopic Learning Curve in Bariatric Surgery. Obesity surgery, 2015, 25(12): 2451-2456. [26] Colligan L, Potts HW, Finn CT, Sinkin RA. Cognitive workload changes for nurses transitioning from a legacy system with paper documentation to a commercial electronic health record. International journal of medical informatics. 2015, 84(7): 469-476. [27] Park JINKYUN, Jung W, Ko JONGHYUN. Investigating the appropriateness of the TACOM measure– application to the complexity of proceduralized tasks for high speed train drivers. Nuclear Engineering and Technology. 2009, 42(1): 115-124. [28] Kuehn KA, Chourasia AO, Wiegmann DA, Sesto ME. Effects of Orientation on Workload during Touch Screen Operation among Individuals with and without Disabilities. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 57(1): 1580-1584. [29] Akyeampong J, Udoka S, Caruso G, Bordegoni M. Evaluation of hydraulic excavator Human–Machine Interface concepts using NASA TLX. International Journal of Industrial Ergonomics, 2014, 44(3): 374-382. [30] Zhang SF, Liu SY. A GRA-based intuitionistic fuzzy multi-criteria group decision making method for personnel selection. Expert Systems with Applications. 2010, 38(9): 11401-11405. [31] Abdullah L, Najib L. A new preference scale of intuitionistic fuzzy analytic hierarchy process in multicriteria decision making problems. Journal of Intelligent & Fuzzy Systems. 2014, 26(2): 1039-1049.