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International Journal of Industrial Ergonomics 44 (2014) 107e113

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International Journal of Industrial Ergonomics

journal homepage: www.elsevier .com/locate/ergon

Psychological and physiological fatigue variation and fatigue factorsin aircraft line maintenance crews

Ta-Chung Wang*, Lu-Han ChuangInstitute of Civil Aviation, National Cheng Kung University, No. 1 University Road, Tainan 701, Taiwan

a r t i c l e i n f o

Article history:Received 30 October 2012Received in revised form5 November 2013Accepted 24 November 2013Available online 14 December 2013

Keywords:SchedulingFactor analysisAircraft maintenance crewFatigue variation

* Corresponding author. Tel: þ886 6 275 7575x636E-mail addresses: tachung@mail.ncku.edu.tw (T

hotmail.com (L.-H. Chuang).

0169-8141/$ e see front matter � 2013 Elsevier B.V.http://dx.doi.org/10.1016/j.ergon.2013.11.003

a b s t r a c t

Aircraft maintenance is an integral component of an aviation system. 21% of all reported incidents in theAviation Safety Reporting System (ASRS) are fatigue-related, and 18% of all accidents have maintenancefactors involved. Guidelines for Maintenance Resource Management (MRM) are hence developed tocombine human factors knowledge with interpersonal skills and personal maintenance skills in order toimprove communication effectiveness and safety in aircraft maintenance operations. One of the iden-tified human factors that lead to maintenance errors is fatigue. This paper examined the psychologicaland physiological fatigue variation in shift workers and the subjective factors affecting the fatigue of linemaintenance crews. Questionnaires collected from two major airlines in Taiwan are used to investigatethe underlying fatigue factors.Relevance to Industry: Based on the analysis results, several suggestions are provided to airlines to furtherimprove line maintenance crews’ work mood and fatigue.

� 2013 Elsevier B.V. All rights reserved.

1. Introduction

Safety is an important issue in air transport. Some of the factorsthat affect flight safety are pilot behavior, aircraft design, mainte-nance quality, terminal management, meteorology, and flightcontrol. Workers with fatigue cost employers an estimated $136billion annually in terms of lost productivity for all industries (Ricciet al., 2007) in the US. Fatigue-related drowsiness on the highwaysresults in more than 1500 fatalities, 100,000 crashes, and 76,000injuries annually (Caldwell, 2001) in the US. As for aviation, 21percent of all reported incidents (reported by both pilots andcontrollers) in the Aviation Safety Reporting System (ASRS) arefatigue-related (Roske-Hofstrand, 1995), and 18% of all accidentshave maintenance factors involved (Phillips, 1994) in the US. InTaiwan, based on a report from the Aviation Safety Council (ASC),73% of the aviation incidents in the past 10 years have had humanfactors involved. These statistics show the importance of address-ing fatigue to ensure continuing safety and risk management.

Early research of human factors in aviation focused on pilots,and maintenance factors were considered as contributing factors topilot-errors (McFadden and Towell, 1999). However, the increasingnumber of maintenance and inspection errors reveals the impor-tance of human factors research in the area of safety management(Gramopadhye and Drury, 2000). The NASA Aviation Safety and

20; fax: þ886 6 238 9940..-C. Wang), rebecca07122@

All rights reserved.

Security Program (AvSSP) was subsequently initiated to decreasethe rate of aircraft fatal accidents. Among forty high priority safetyareas of the AvSSP, many were relevant to maintenance humanfactors (Kanki, 2010). It has also been shown that maintenance-related accidents in aviation are approximately 6.5 times morelikely to be fatal than accidents in general, and maintenance acci-dents result in approximately 3.5 times more fatalities than averagefatal accidents (Marais and Robichaud, 2012).

Aircraft maintenance crews play an important role in the airlineindustry. The efficiency and quality of their work are shown by thepunctuality of aircraft maintenance and by reductions in the flightaccident rates. Maintenance crews are divided into two groups:those who work at the hangar and those who work on the airportflight line. The maintenance crews in the former group areresponsible for routine aircraft maintenance, including periodicmaintenance checks and engine overhauls. In the latter group, themaintenance crews are responsible for preflight checks, transitchecks, overnight checks, and daily inspections. Line maintenancecrews work a 24-h rotating shift at airports to ensure flight punc-tuality. Unregulated hours and frequent night work altered thesleep/wake cycle and affects both the ability to remain alert and theability to sleep (Caldwell et al., 2008). As a consequence, thecircadian rhythms of the workers are disrupted, which is one of themajor factors contributing to fatigue (Schutte, 2009). The increasedfatigue levels then result in risks related to maintenanceerrors (Hobbs et al., 2011). Unlike the errors made by pilots and airtraffic controllers, the mistakes that happen during the aircraft

Table 1Contents of the questionnaire.

Question sections Time to answer

Beforeduty

Afterduty

1. Sleeping pattern X2. Workload conditions X3. Shift rotation conditions X4. Relationships with directors, colleagues

and subordinatesX

5. Level of physical fatigue X6. Level of psychological fatigue X7. Information on current duties X8. Level of physical fatigue X9. Level of psychological fatigue X10. Personal information X

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maintenance process may not reveal their real threat to aviationsafety until several days or months later; hence, they become po-tential flight safety threats. For example, the incident of JapanAirlines Flight 123 in 1985, which caused 520 fatalities, was foundto be the result of metal fatigue caused by improper maintenanceafter a previous tailstrike incident in 1978 (AAIC, 1987).

Defining fatigue has been a challenging task for scientists. Ac-cording to ICAO Annex 6, Part 1, fatigue is defined as: “A physio-logical state of reduced mental or physical performance capabilityresulting from sleep loss or extended wakefulness, circadian phase, orworkload (mental and/or physical activity) that can impair a crewmembers alertness and ability to safely operate an aircraft or performsafety related duties.” As a result, fatigue may be categorized ashaving both psychological and physiological aspects (Shen et al.,2006). Research on psychological and physiological human factorsmay help in the prediction of the maintenance crews’ work per-formance (Gramopadhye and Drury, 2000). It is also known thatpsychosocial factors also influence workers performance (Dollardet al., 2000; Choobineh et al., 2011; Abbe et al., 2011; Boschmanet al., 2013). Analysis of the relationship between psychosocialfactors and multiple dimensions of fatigue showed that psychoso-cial factors are significantly associated with changes in mental,physical, and total fatigue levels (Parhizi et al., 2013). High psy-chological distress, poorer health perception, greater sleep debt,and higher exposure to physical work factors were found to beassociated with higher levels of acute fatigue (Laberge et al., 2011).

Several methods have previously been used to obtain datarelated to the fatigue of air transport operation crews. One methodrecords physiological data, such as electrooculographic (Morris andMiller, 1996), electroencephalogram, and electrocardiogram data(Gander et al., 1994; Gillberg et al., 2003). Another method involvesasking crew members to report their subjective fatigue status,which is usually done by using some type of predefined form, suchas the Crew Status Check Card (SAM Form 202) developed by theU.S. Air Force School of Aerospace Medicine (Perelli, 1981; Stormand Merrifield, 1980), the Stanford Sleepiness Scale (SSS) (Hoddeset al., 1973), the Swedish Occupational Fatigue Inventory (SOFI)(Åhsberg et al., 2000), and the scaled level used by the Laboratory ofApplied Anthropology (LAA) (LAA, 2008) and Airbus (Aubin et al.,2001). Depending on the scope of the research and limitations inregarding to resources, researchers may either apply both methodsin the same samples or focus on one method.

Taiwan Taoyuan International Airport is the busiest airport inTaiwan and is one of the top 30 major airports in the world, ac-cording to Airports Council International (ACI) statistics for the year2011. Hence, the line maintenance crews working at this airport arelikely to encounter serious fatigue problems. For this reason, thisstudy uses data from line maintenance crews of two major inter-national airlines in Taiwan. We used questionnaires to collect thesubjective perceptions related to both psychological and physio-logical fatigue-related measures. Data from questionnaires admin-istered at two major airlines in Taiwan are used to find the fatiguestatus and factors affecting fatigue in line maintenance crews.

The structure of the paper is stated as follows: Section 2 pro-vides a discussion of the questionnaire design. The analysis of thequestionnaires and a discussion of the analysis results are given inSection 3. We then conclude the paper in Section 4.

2. Questionnaire design and survey procedures

Instead of conducting a pilot survey, we requested opinions fromseveral managers in the aviation industry regarding the format andcontent of the questionnaire. Based on their recommendations, thequestionnaire we used is paper-based and consists of 10 sections,which are listed in Table 1. Sections 1e6 are answered before the

respondents start theirwork shift. Sections 7e10 are answered afterthe respondents have finished their work shift. It takes about 5 minto answer either thefirst or the second half of the questionnaire. Thefirst section includes 11 questions about the respondent’s everydaysleep pattern. The second section asks seven questions regardingthe respondent’s opinions on whether certain factors may affecttheir perceived fatigue buildup speed, such as unfamiliar aircrafttypes, unfamiliar maintenance tasks, and the number of aircraftbeing inspected during theirwork shift. The third section focuses onshift rotation conditions. The fourth section contains questionsabout the relationships of the subjects with their colleagues. Thefifth and sixth sections determine the physiological and psycho-logical fatigue level of the respondents before duty. The seventhsection includes six questions about the respondent’s workload onthe shift under consideration, such as the number of aircraft to bemaintained and whether or not the respondent is working over-time, having short breaks during the shift, or experiencing un-scheduledmaintenance plans. The eighth and ninth sections ask therespondents to rate their physiological and psychological fatiguecondition after duty. Questions related to the characteristics of therespondents are placed in the last section to allow respondentsmore time to answer these questions after duty. These questionsinclude gender, age, marital status, educational status, for whichaircraft types they have received training, total training times, yearsof aircraft maintenance experience, and working positions.

Physiological and psychological fatigue conditions are evaluatedbased on two corresponding forms, which contain 20 physiologicaland 19 psychological items modified from similar forms developedby the LAA and Airbus (LAA, 2008; Aubin et al., 2001). This formatallows respondents to quickly evaluate their fatigue levels, andprovides us with enough information for analysis purposes. Theline maintenance crews need to rate their fatigue level using four-point interval scales, labeled from none to very high (none-some-what high-high-very high). Other sections regarding the percep-tions of line maintenance crews toward fatigue are measured usinga five-point Likert scale (disagree-somewhat disagree-neutral-somewhat agreeeagree) that allows employees to express neutralopinions toward these items. Because two responses are obtainedfrom each respondent, one before duty and the other after duty, thedifference in the fatigue level recorded before and after duty can beused to represent the increase in fatigue (i.e., decrease in wake-fulness or motivation) due to maintenance operations. For the de-tails of the questionnaire, interested readers can contact theauthors for a copy of the questionnaire.

The survey was conducted from November 2009 to January2010. A total of 150 line maintenance crew members from the twoairlines under consideration were sampled, of which 112 werewilling to participate in the survey; 104 questionnaires were

Table 2Information on the participating airlines.

Airlines A Airlines B

Fleet size 70 55Number of flights per month 5218 3714Market share of passengers in Taiwan 43% 30%Market share of cargo in Taiwan 46% 47%Hub location Taoyuan Taoyuan

Table 4Data on the respondents.

Item Category Number of respondents Percentage (%)

Gender Male 104 100Female 0 0

Age (year) 20e30 6 631e40 48 4841e50 39 3861e60 11 10

Education High School 34 33College 69 66Graduate 1 1

Years of work <1 1 11e5 13 136e10 24 2311e15 32 3116e20 19 18>20 15 14

Job title Technician 87 84Senior technician 3 3Chief technician 10 9Engineer 2 2Manager 2 2

T.-C. Wang, L.-H. Chuang / International Journal of Industrial Ergonomics 44 (2014) 107e113 109

considered valid samples. Table 2 shows the information regardingthe participating airlines. These two airlines have similar marketshares, and both have their hub located in Taoyuan. Tables 3 and 4present the details of the collected data.

3. Results

3.1. Subjective factors of fatigue

An exploratory factor analysis was conducted to extract theimportant dimensions from the perception of the line maintenancecrews toward fatigue. This technique is used to reduce a largevariable set to a smaller set of underlying factors, which helps todetect the presence of meaningful patterns among the originalvariables. The study uses the KMO (Kaiser-Meyer-Olkin) values andBartletts test of sphericity to examine whether or not the ques-tionnaire data are suitable for factor analysis. As shown in Table 5,the KMO value is greater than 0.7, and the p-value is less than 0.05.Hence, the data are suitable for factor analysis. These factors wereextracted using the principal component method with a varimaxrotation (Sharma, 1996). Four major factors were found based onthe analysis results. Table 6 shows the information regarding thefour major factors and their respective factor loadings.

As shown in Table 6, the Cronbach’s alpha values for the factordimensions are 0.847, 0.839, 0.784, and 0.682. Although the valuefor the fourth factor is not higher than 0.7, it is within the range of0.6e0.7 and thus is considered within the acceptable range.

Using all the above tools and observing the results, four factorswere determined from the questions that we developed. Thesefactors are as follows:

Factor 1: Adequacy of rest. The first factor is related to theadequacy of rest of the respondents and has an associated eigen-value of 5.705. This factor is the major cause of five items: “Sleepduration may affect the fatigue level while on duty,” “Sleep timemay affect the fatigue level while on duty,” “Sleep quality mayaffect the fatigue level while on duty,” “Shift rotation may affect thefatigue level while on duty,” and “Number of maintained aircraftmay affect the fatigue level while on duty.” Sleep duration is themost highly correlated item in this factor. It is considered that if theworkers have to maintain more aircraft, there will be less time forthem to recover during their shift. This factor accounts for 33.56% ofthe total variance. Thus, it confirms that whether or not theworkersreceive adequate rest is the most important fatigue factor in regardto line maintenance crews, as perceived by the respondents.

Factor 2: Work proficiency. The second factor is the workproficiency of the respondents, which greatly affects four items

Table 3Details of the collected data.

Airlines Sampledrespondents

Returnedquestionnaire

Validsamples

Percentage

A 100 64 63 63.0%B 50 48 41 82.0%Total 150 112 104 69.33%

with an associated eigenvalue of 2.224. The four items are: “Unfa-miliar maintenance tasks may increase the fatigue level while onduty,” “Unfamiliar maintenance tools may increase the fatigue levelwhile on duty,” “Unfamiliar maintained aircraft types may increasethe fatigue level while on duty,” and “Unfamiliar maintenanceterminologies may increase the fatigue level while on duty.” Thisfactor accounts for 13.081% of the total variance and is the secondmost important factor contributing to fatigue in line maintenancecrews, as perceived by the respondents.

Factor 3: Communication and coordination. The third factor islabeled as communication and coordination. It affects five items:“Communication and coordination with colleagues may affect thefatigue levelwhile on duty,” “Directorswho explain themaintenancetasks clearly may reduce the fatigue level while on duty,” “Commu-nication and coordination with directors may affect the fatigue levelwhile on duty,” “Communication and coordination with sub-ordinates may affect the fatigue level while on duty,” and “Commu-nication and coordination with pilots may affect the fatigue levelwhile on duty.” Communication and coordination has an associatedeigenvalue of 1.694 and accounts for 9.966% of the total variance.

Factor 4: Work shift. The associated eigenvalue for the factorwork shift is 1.385. This factor consists of three items: “I will feelparticularly tired during the evening shift,” “I think a good or a badmood will affect the fatigue level while on duty,” and “Increasedduty hours (overtime) may increase the fatigue level while onduty.” All of the above items are considered work shift-related, and“I will feel particularly tired during the evening shift” is the mosthighly correlated factor.

3.2. Effects of fatigue factors

In the following, we split the respondents into different groupsand use ANOVA to analyze whether their perceptions about theaforementioned fatigue factors are different. The average scores,rated from 1 to 5, of the fatigue factor-related items for different

Table 5KMO and Bartlett’s test results.

Kaiser-Meyer-Olkin measure of sampling adequacy 0.804Bartlett’s test of sphericity Approx. chi-square 809.841

Degrees of freedom 136Significance <0.001

Table 6Factor loadings of the four major factors. Factor loadings of the items that are grouped together under the same factor are marked in bold.

Contents of item Factor loading

Adequacy of rest Workproficiency

Comm.and coord.

Work shift

2. Sleep duration may affect the fatigue level while on duty. 0.843 0.080 0.075 0.1791. Sleep time may affect the fatigue level while on duty. 0.829 0.118 0.067 0.2253. Sleep quality may affect the fatigue level while on duty. 0.826 0.179 0.077 �0.08619. Shift rotation may affect the fatigue level while on duty. 0.635 0.217 0.263 0.21115. Number of maintained aircraft may affect the fatigue level while on duty. 0.490 0.454 0.175 0.12713. Unfamiliar maintenance tasks may increase the fatigue level while on duty. 0.291 0.855 0.070 0.08714.Unfamiliar maintenance tools may increase the fatigue level while on duty. 0.066 0.852 0.079 0.06012. Unfamiliar maintained aircraft types may increase the fatigue level while on duty. 0.317 0.746 0.157 0.16418. Unfamiliar maintenance terminologies may increase the fatigue level while on duty. 0.028 0.657 0.139 0.13727. Communication and coordination with colleagues may affect the fatigue level while on duty. 0.132 0.149 0.836 �0.11126. Directors explain maintenance tasks clearly may reduce the fatigue level while on duty. 0.106 �0.008 0.755 �0.22025. Communication and coordination with directors may affect the fatigue level while on duty. 0.150 0.051 0.717 0.10829. Communication and coordination with subordinates may affect the fatigue level while on duty. 0.047 0.297 0.651 0.22830. Communication and coordination with pilots may affect the fatigue level while on duty. �0.051 0.243 0.553 0.54023. I will feel particularly tired during the evening shift. 0.089 0.127 �0.036 0.78810. I think good or bad mood will affect the fatigue level while on duty. 0.256 0.117 �0.020 0.68420. Increase duty hours (overtime) may increase the fatigue level while on duty. 0.527 0.114 0.015 0.569Eigenvalues 5.705 2.224 1.694 1.385Cumulative variance (%) 33.560 46.641 56.607 64.752Cronbach’s Alpha 0.847 0.839 0.783 0.682

Table 7ANOVA of average fatigue factors vs. number of maintained aircraft. Factor loadingsof the items that are grouped together under the same factor are marked in bold.

Factors �5n ¼ 54

<5n ¼ 50

F Value p-Value

Adequacy of rest 4.437 4.316 1.324 0.253Work proficiency 4.056 3.760 6.502 0.012Comm. and coord. 3.774 3.316 14.376 <0.001Work shift 3.803 3.800 <0.001 0.984

n : number of respondents.

Table 9ANOVA of average fatigue factors vs. having short breaks during shift or not. Factorloadings of the items that are grouped together under the same factor are marked inbold.

Factors Breakn ¼ 59

No breakn ¼ 45

F Value p-Value

Adequacy of rest 4.387 4.357 0.062 0.804Work proficiency 3.908 3.929 0.024 0.878Comm. and coord. 3.611 3.400 2.142 0.146Work shift 3.719 4.024 4.759 0.031

n: number of respondents.

Table 10Significance of the variations in physical fatigue related items (df ¼ 103). Factorloadings of the items that are grouped together under the same factor are marked inbold.

Physical items Mean t Value p Value

Sore eyes, eye irritation �0.106 �1.653 0.101Yawning �0.106 �1.225 0.223Droopy eyelids L0.163 L2.048 0.043Paleness �0.135 �1.740 0.085Headache �0.067 �1.216 0.210Loss of interest and motivation �0.115 �1.314 0.192Feel depressed �0.029 �0.376 0.707

T.-C. Wang, L.-H. Chuang / International Journal of Industrial Ergonomics 44 (2014) 107e113110

groups are listed in Tables 7e9. The items having statistical sig-nificance are shown in boldface.

As the data in these tables indicate, the “adequacy of rest” factorshows no differences among groups. This means that “adequacy ofrest” is equally important among groups. In our analyses, differentshifts do not affect workers’ opinions related to the four major fa-tigue factors, and hence the result is not listed here. However, inTable 7, the factors “work proficiency” and “communication andcoordination” are perceived differently among the groups. This mayindicate that when the workload is high, the workers’ work profi-ciency and coordination with others become important. Tables 8and 9 both present work time-related data. The results show thatwork shift does affect the workers’ fatigue levels. Overtime workmay be a result of worker’s inability to finish work on time or froman unsatisfactory work schedule. Hence, significance is shown inthe factors “work proficiency” and “work shift” (Table 8). The re-sults shown in Table 9 imply that allowing short breaks during eachshift may reduce the differences in perceived fatigue among thedifferent shifts.

Table 8ANOVA of average fatigue factors vs. working overtime or not. Factor loadings of theitems that are grouped together under the same factor are marked in bold.

Factors Overtimen ¼ 59

Normaln ¼ 45

F Value p-Value

Adequacy of rest 4.468 4.262 3.848 0.053Work proficiency 4.017 3.778 4.094 0.046Comm. and coord. 3.607 3.484 0.891 0.347Work shift 3.921 3.644 4.901 0.029

n: number of respondents.

3.3. Fatigue variation

In this section, we first identify the items that are significantlydifferent before and after work. These items are divided into twoparts: physiological and psychological. Paired two-tailed t-tests areused to evaluate the significance of the differences. Tables 10 and 11show the p-value of the physical and psychological fatigue levels

General feeling of getting tired L0.250 L2.766 0.007Easy to get irritated �0.135 �1.713 0.090Fixed stare L0.144 L2.016 0.046Growing and irresistible need to sleep L0.288 L3.090 0.003Efforts to maintain wakefulness L0.337 L3.497 0.001Frequent desire to drink or eat �0.058 �0.653 0.515Feeling confused �0.125 �1.651 0.102Decrease in verbal communications �0.115 �1.421 0.158Drowsiness L0.288 L3.693 <0.0001Voluntary closing of eyes for 5 min L0.260 L3.124 0.002Becoming apathetic or inert L0.192 L2.525 0.013Becoming impatient �0.106 �1.692 0.094Difficulty with evaluating time L0.221 L3.454 0.001

Table 11Significance of the variations in psychological fatigue related items (df¼ 103). Factorloadings of the items that are grouped together under the same factor are marked inbold.

Psychological items Mean t Value p Value

Repetition of some actions �0.481 �0.713 0.478Desire to get rid of duties L0.269 L3.368 0.001Feeling lack of anticipation 0.192 0.253 0.801Apparent ignorance L0.154 L2.309 0.023Slow instinctive reactions L0.183 L2.687 0.008Difficulty to make decisions 0 <0.001 1.000Lack of coherence in reasoning �0.106 �1.734 0.086Slips, lapses or minor errors 0.029 0.537 0.592Lack of precision during work �0.058 �0.786 0.433Minor data interpretation errors �0.02 �0.323 0.747Slow actions and movements L0.135 L2.009 0.047Tendency to delay decision-making �0.087 �1.154 0.251Bad coordination of actions and movements L0.192 L3.310 0.001Difficulty with oral expression L0.173 L2.562 0.012Difficulty in reading and writing �0.048 �0.728 0.468Slow reasoning �0.115 �1.560 0.122Difficulty with speaking foreign language �0.029 �0.403 0.688Substantial effort to maintain attention L0.212 L2.842 0.005Easily distracted �0.962 �1.198 0.234

Table 12Fatigue scores before and after duty.

Category n Before duty After duty Increment

Day shifta 50 10.3 14.66 4.36 (42.3%)Evening shifta 19 9.53 12.32 2.79 (29.3%)Midnight shifta 35 11.83 14.37 2.54 (21.5%)Maintain � 5 aircraft 54 11.43 15.13 3.7 (32.4%)Maintain < 5 aircraft 50 9.86 13.06 3.2 (32.5%)Work overtime 59 12.03 17.25 4.5 (34.6%)No work overtime 45 8.89 11.44 2.55 (28.7%)No break during shift 28 12.75 17.25 4.5 (35.2%)Have voluntary break during shift 76 9.91 12.99 3.08 (31.1%)All respondents 104 10.67 14.13 3.46 (32.4%)

n: number of respondents.a These airlines have a 30-min difference in the three shifts.

T.-C. Wang, L.-H. Chuang / International Journal of Industrial Ergonomics 44 (2014) 107e113 111

before and after duty obtained from the respondents. Here, a p-value less than 0.05 represent a significant difference before andafter work. The most significant items are shown in boldface.

Table 10 shows significant differences before and after duty in thefollowing physiological fatigue items: “Droopy eyelids,” “General

Fig. 1. The histogram of fatigue

feeling of getting tired,” “Fixed stare,” “Growing and irresistible needto sleep,” “Efforts tomaintainwakefulness,” “Drowsiness,” “Voluntaryclosing of eyes for 5 min,” “Becoming apathetic or inert,” and “Diffi-culty with evaluating time.” Similarly, the data in Table 11 indicatesignificant differences before and after duty in the following psycho-logical fatigue-related items: “Desire to get rid of duties,” “Apparentignorance,” “Slow instinctive reactions,” “Slow actions and move-ments,” “Bad coordination of actions and movements,” “Difficultywith oral expression,” and “Substantial effort to maintain attention.”

After obtaining the fatigue items with sufficient significance, wethen use them to quantify the differences in fatigue levels. Here weuse the summation of both the psychological and physiologicalfatigue scores that were found to be significant to represent thefatigue level of the workers before and after duty. The highestpossible fatigue score is 48. Table 12 shows the average fatiguescore for each group. Fig. 1 shows the histogram of fatigue scores ofdifferent groups. It should be noted that there is a 30-min differ-ence in the time of the three shifts for Airline A and Airline B. Forexample, the day shift for Airline A is from 0800 to 1600 while theday shift for Airline B is from 0730 to 1530. Comparing the fatiguechanges between different shifts, the day shift workers are shownto have the greatest increment of fatigue. This may indicate that theworkload during the day time is the heaviest among the threedifferent shifts. On the other hand, the midnight shift workers havethe least increment of fatigue; however, they start their duty withthe highest fatigue scores. This may indicate that midnight shiftworkers work in a highly fatigued state, but fortunately, theirworkload is not as heavy as that during the day shift so they are stillable to maintain a suitable fatigue level. The workers whomaintainmore than five aircraft have a slightly larger increment of fatiguethan those who maintain less than five aircraft. Also, the fatiguescore after duty of the workers maintaining fewer aircraft is muchlower than that of workers maintaining more aircraft. In addition,there is a higher increment of fatigue scores in workers who workovertime compared to those who do not. It should also be notedthat Table 12 also shows having short breaks during the work shiftsubstantially decreases the increment of fatigue scores.

3.4. Suggestions

From the respondents’ subjective opinions toward fatigue, fourlatent factors were identified. Based on the findings of this study,

scores of different groups.

T.-C. Wang, L.-H. Chuang / International Journal of Industrial Ergonomics 44 (2014) 107e113112

there are several ways to decrease the fatigue level of maintenancecrews.

For organizations: The “adequacy of rest” factor shows thatgiving workers enough rest may reduce fatigue levels. Moreover,from Table 12, allowing short break during shifts also helps reducefatigue. Table 12 also shows that working overtime significantlyincreases fatigue. Therefore, airlines should assign enough main-tenance crews based on manpower requirements to reduce thenecessity of working overtime. Working overtime may also resultfrom insufficient work proficiency of workers, which is the secondlatent factor identified in this study. Each airline may have four orfive different types of fleets to maintain. Different types of aircrafthave different maintenance items and procedures. Therefore, air-lines should give maintenance crews adequate training to ensurethat each maintenance crew has enough knowledge to face all thedifficulties that may occur during the maintenance process. Fromthe third identified factor, “communication and coordination,” weknow that interpersonal relationships also affect the fatigue level ofcrew members. Hence, other than assigning suitable work shifts toworkers, we suggest that employers open communication channelsbetween colleagues or between supervisors and subordinates, thatthey pay attention to how crew members interact with each otherand that they make necessary shift changes to avoid related prob-lems. The fourth identified factor, “work shift,” also indicates theimportance of assigning suitable shifts to workers. The employershould try different approaches to minimize the possible fatigueincrement, such as using optimization method (Wang and Ke,2013), or compressed work schedules (Paley et al., 1998). To alle-viate the impact of unavoidable improper shift assignments,allowing short breaks during shifts may be a suitable approach.

For technicians: The “adequacy of rest” factor shows theimportance of having a good quality of sleep before duty. Therefore,workers should pay attention to using their off-duty hours to getadequate rest before starting their duty. From Table 12, we haveseen that a short break during shift can reduce the fatigue incre-ment. Hence, we suggest that employees should use possible op-portunities to get short breaks during their shift. The second factor“work proficiency” shows the importance of getting acquainted tothe tools and terminologies of the maintained aircraft. Therefore,we suggest employees to take time to review the training materialsthey have regarding to the aircraft being maintained before duty.“Communication and coordination” is also important to reducingfatigue, which corresponds to the close relationships betweenpsychosocial factors and fatigue (Parhizi et al., 2013). The workersshould not hesitate to report their problems and opinions to theircolleagues. This allows supervisor to quickly know the problemstheir subordinates have, and supervisors can swiftly respond totheir requests to make the maintenance process go smoothly.“Work shift” is one important factors affecting fatigue. Employeesshould report their problems regarding to the work shift assign-ments whenever possible. Again, if the employer cannot adjust theshift assignments, the employee should be allowed to get someshort breaks during shifts.

4. Conclusions

In this work, we used questionnaires to collect data from themaintenance crews of two major airlines in order to analyze thesubjective factors affecting the fatigue of crew members. Fourmajor factors were identified, including adequacy of rest, workproficiency, communication and coordination, and work shift. Wealso analyzed the perception of these factors among differentgroups of maintenance crews, such as workers of different workshifts, workers maintaining different numbers of aircraft, workerswith or without short breaks during their shift, and workers who

work overtime or not. The results show that several fatigue factor-related items are perceived differently among the groups underconsideration. Using these results, it was concluded that improvingwork environments related to these factors may further reduce theperceived fatigue of maintenance crews. For example, givingmaintenance crews enough training may help them becomefamiliar with the tools and maintenance tasks involved in theirjobs. This may contribute to the reduction of the second fatiguefactor, work proficiency, and may result in a reduction in fatigue.How the changes in these fatigue related items affects the actualfatigue variation will be considered in future research.

This paper also presents a method for evaluating variations in fa-tigue levels. Comparisons of the variations in fatigue level amongdifferent groups ofmaintenance crewswere conducted. Based on theresults, we determined that different groups have different levels offatigue. This information is helpful in designing a sound work shifttable so that all maintenance crews canwork under suitable states offatigue. Future studieswill focus onhow the current results should beintegrated into automated scheduling programs.

Acknowledgments

This research was supported by the National Science Council ofTaiwan under Grant NSC-99-2221-E-006-057.

References

Åhsberg, E., Kecklund, G., Åkerstedt, T., Gamberale, F., 2000. Shiftwork and differentdimensions of fatigue. Int. J. Ind. Ergon. 26, 457e465.

AAIC, 1987. Aircraft Accident Investigation Report on Japan air lines JA8119, Boeing747 SR-100. Aircraft Accident Investigation Commission Ministry of Transport.

Abbe, O.O., Harvey, C.M., Ikuma, L.H., Aghazadeh, F., 2011. Modeling the relationshipbetween occupational stressors, psychosocial/physical symptoms and injuriesin the construction industry. Int. J. Ind. Ergon. 41, 106e117.

Aubin, A., Bourgeois-Bougrine, S., Mollard, R., Coblentz, A., Speyer, J.-J., 2001. A newquestionnaire on fatigue and stress for flight crew. In: Proceedings of the Hu-man Issues in Aviation Systems Symposium 2001, Toulouse, France.

Boschman, J., van der Molen, H., Sluiter, J., Frings-Dresen, M., 2013. Psychosocialwork environment and mental health among construction workers. Appl.Ergon. 44, 748e755.

Caldwell, J.A., 2001. The impact of fatigue in air medical and other types of oper-ations: a review of fatigue facts and potential countermeasures. Air. Med. J. 20,25e32.

Caldwell, J.A., Caldwell, J.L., Schmidt, R.M., 2008. Alertness management strategiesfor operational contexts. Sleep Med. Rev. 12, 257e273.

Choobineh, A., Motamedzade, M., Kazemi, M., Moghimbeigi, A., Pahlavian, A.H., 2011.The impact of ergonomics intervention on psychosocial factors and musculo-skeletal symptoms among office workers. Int. J. Ind. Ergon. 41, 671e676.

Dollard, M.F., Winefield, H.R., Winefield, A.H., de Jonge, J., 2000. Psychosocial jobstrain and productivity in human service workers: a test of the demand-control-support model. J. Occup. Organizat. Psychol. 73, 501e510.

Gander, P.H., Graeber, R.C., Foushee, H.C., Lauber, J.K., Connell, L.J., 1994. Crew factorsin flight operation ii: psychophysiological responses to short-haul air transportoperations. In: NASA Technical Memorandum 108856.

Gillberg, M., Kecklund, G., Gransson, B., kerstedt, T., 2003. Operator performanceand signs of sleepiness during day and night work in a simulated thermalpower plant. Int. J. Ind. Ergon. 31, 101e109.

Gramopadhye, A.K., Drury, C.G., 2000. Human factors in aviation maintenance: howwe got to where we are. Int. J. Ind. Ergon. 26, 125e131.

Hobbs, A., Avers, K.B., Hiles, J.J., 2011. Fatigue Risk Management in Aviation Main-tenance: Current Best Practices and Potential Future Countermeasures. Tech-nical Report Office of aerospace medicine technical report. DOT/FAA/AM-11/10.

Hoddes, E., Zarcone, V., Smythe, H., Phillips, R., Dement, W., 1973. Quantification ofsleepiness: a new approach. Psychophysiology 10, 431e436.

Kanki, B.G., 2010. Chapter 21-maintenance human factors: a brief history. In:Salas, E., Maurino, D. (Eds.), Human Factors in Aviation, second ed. AcademicPress, San Diego, pp. 659e697.

LAA, 2008. Use of Erroneous Parameters at Takeoff. Technical Report Laboratory ofApplied Anthropology. DOC AA 556/2008.

Laberge, L., Ledoux, É., Auclair, J., Thuilier, C., Gaudreault, M., Gaudreault, M.,Veillette, S., Perron, M., 2011. Risk factors for work-related fatigue in studentswith school-year employment. J. Adolesc. Health. 48, 289e294.

Marais, K.B., Robichaud, M.R., 2012. Analysis of trends in aviation maintenance risk:an empirical approach. Reliabil. Eng. Sys. Safe. 106, 104e118.

McFadden, K.L., Towell, E.R., 1999. Aviation human factors: a framework for the newmillennium. J. Air Trans. Manage. 5, 177e184.

T.-C. Wang, L.-H. Chuang / International Journal of Industrial Ergonomics 44 (2014) 107e113 113

Morris, T., Miller, J., 1996. Electrooculographic and performance indices of fatigueduring simulated flight. Biol. Psychol. 42, 343e360.

Paley, M.J., Price, J.M., Tepas, D.I., 1998. The impact of a change in rotating shiftschedules: a comparison of the effects of 8, 10 and 14 h work shifts. Int. J. Ind.Ergon. 21, 293e305.

Parhizi, S., Steege, L.M., Pasupathy, K.S., 2013. Mining the relationships betweenpsychosocial factors and fatigue dimensions among registered nurses. Int. J. Ind.Ergon. 43, 82e90.

Perelli, L., 1981. Human Factors Evaluation of C-141 Fuel Savings Advisory System.Technical Report Brooks Air Force Base. USAF School of Aerospace Medicine,Aerospace Medical Division, TX. Tech. Report 81-37.

Phillips, E.H., 1994. Focus on accident prevention key to future airline safety. Aviat.Week. Space. Technol., 52e53.

Ricci, J.A., Chee, E., Lorandeau, A.L., Berger, J., 2007. Fatigue in the u.s. workforce:prevalence and implications for lost productive work time. J. Occup. Environ.Med. 49, 1e10.

Roske-Hofstrand, R., 1995. Raising awareness for fatigue among air trafficcontrollers. In: International Symposium on Aviation Psychology, pp. 985e991.

Schutte, S., 2009. Fatigue risk management: charting a path to a safer workplace. In:Proceedings of Hard Rock Safe Safety Conference 2009: a Sense of Safety Ur-gency, pp. 245e250.

Sharma, S., 1996. Applied Multivariate Techniques. John Wiley & Sons, Inc.Shen, J., Barbera, J., Shapiro, C.M., 2006. Distinguishing sleepiness and fatigue: focus

on definition and measurement. Sleep Med. Rev. 10, 63e76.Storm, W., Merrifield, J., 1980. Fatigue and Workload in Four-man C-5A Cockpit

Crews. Technical Report Brooks Air Force Base. USAF School of AerospaceMedicine, Aerospace Medical Division, TX. Tech. Report 80-23.

Wang, T.-C., Ke, G.-C., 2013. Fatigue minimization work shift scheduling for airtraffic controller. Int. J. Automat. Smart Technol. 3, 91e99.