Article citation information:Basaria, F.T. The analysis of work shift patterns and risk of fatigue in aircraft maintenance personnel: a case study. Scientific Journal of Silesian University of Technology. Series Transport. 2023, 118, 5-16. ISSN: 0209-3324. DOI: https://doi.org/10.20858/sjsutst.2023.118.1. Fransisca Tiur BASARIATHE ANALYSIS OF WORK SHIFT PATTERNS AND RISK OF FATIGUE IN AIRCRAFT MAINTENANCE PERSONNEL: A CASE STUDYSummary. In response to the COVID-19 pandemic in 2020, PT. XYZ, the biggest aircraft maintenance, repair, and overhaul (MRO) company in Indonesia, implemented a new shift pattern for line-maintenance personnel. The new shift pattern allows maintenance personnel to have fewer working hours per day (7-hour shifts) in more shift varieties for 5 consecutive days. Maintenance personnel will have 2-morning shifts, 1-noon shift, and 2-night shifts followed by 3 rest days. This study aims to explore the risk of fatigue caused by the newly implemented shift pattern. Data were collected through electronic questionnaires from a total of 303 respondents. This study found that at the time of the survey, many respondents (78 of 303, 26%) felt tired and had difficulty concentrating, regardless of the shift they were in. Based on the duty time, the highest scores of level 6 (tired, difficult to concentrate) were discovered on night shift day 5. This result shows that although the organization had provided the maintenance personnel with the opportunity to obtain sleep during rest days, tiredness and fatigue were still experienced by the aircraft maintenance personnel. This study recommends necessary actions to be taken to prevent fatigue, especially from the noon shift afterwards, where fatigue level is increasing, and alertness level is decreasing.Keywords: fatigue, work shift patterns, aircraft maintenance, risk analysis1. INTRODUCTIONIn November 2020, a transition of the previous 2-2 shift pattern to a 5-3 new shift pattern was carried out at PT. XYZ. The previous 2-2 shift pattern allows line-maintenance personnel to have a 12-hour shift which starts in the morning on day 1 and starts in the evening on day 2. Following that, maintenance personnel are supposed to have 2 rest days afterwards.The new 5-3 shift pattern, however, allows maintenance personnel to have fewer working hours per day (7-hour shifts) in more shift varieties. The morning shift on days 1 and 2 starts at 6 AM to 8 AM, the noon shift starts at 2 PM on day 3, and the night shift on days 4 and 5 starts at 9 PM to 11 PM. Maintenance personnel will then have 3 consecutive rest days. These resting days were intended to be used by the maintenance personnel to recover from their previous working days. However, the changing shift work may cause disrupted sleep, which could result in health and safety issues and the risk of fatigue.Based on previous research ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"author":[{"dropping-particle":"","family":"Federal Aviation Administration","given":"","non-dropping-particle":"","parse-names":false,"suffix":""}],"id":"ITEM-1","issued":{"date-parts":[["2016"]]},"page":"87-88","title":"Advisory Circular Subject: Maintainer Fatigue Risk Management","type":"article-journal","volume":"2"},"uris":["http://www.mendeley.com/documents/?uuid=9867b03b-3d57-4dea-8fbd-86e3a7595f5b"]}],"mendeley":{"formattedCitation":"[1]","plainTextFormattedCitation":"[1]","previouslyFormattedCitation":"[1]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[1], sleepiness and fatigue associated with a sleep debt are cumulative. Losing an hour of sleep every other night for a week could result in situations that impair performance. Much research has focused on flight crew shift patterns and their ramifications, but there is currently little evidence on how work patterns may affect aviation maintenance personnel's sleep and the problems that may result. Thus, this research aims to analyse the effect of changing shift patterns toward the risk of fatigue of aviation maintenance personnel.2. LITERATURE REVIEWFatigueReferring to ICAO ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"ISBN":"9789292492144","abstract":"This manual is intended to provide States with guidance to develop the regulatory framework and the supporting guidance material for the implementation of safety management systems (SMS) by service providers. It also provides guidance for the development of a State safety programme (SSP), in accordance with the International Standards and Recommended Practices (SARPs) contained in Annex 1 Personnel Licensing, Annex 6 Operation of Aircraft, Annex 8 Airworthiness of Aircraft, Annex 11 Air Traffic Services, Annex 13 Aircraft Accident and Incident Investigation and Annex 14 Aerodromes. 1.2","author":[{"dropping-particle":"","family":"ICAO","given":"","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"International Civil Aviation Organization","id":"ITEM-1","issued":{"date-parts":[["2018"]]},"number-of-pages":"1-182","title":"Safety Management Manual- Doc 9859","type":"book"},"uris":["http://www.mendeley.com/documents/?uuid=86a6448d-d601-4b7f-97f5-7e04018b68ec"]}],"mendeley":{"formattedCitation":"[2]","plainTextFormattedCitation":"[2]","previouslyFormattedCitation":"[2]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[2], fatigue is a physiological state of reduced mental or physical performance capability resulting from sleep loss, extended wakefulness, circadian phase, and/or workload (mental and/or physical activity) that can impair a person’s alertness and ability to adequately perform safety-related operational duties. The chief cause of fatigue is not having obtained adequate rest or recovery from previous activities. Research conducted by Transport Canada ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1016/S0925-7535(97)00052-0","ISSN":"09257535","abstract":"In spite of all efforts to design safer systems, we still witness severe, large-scale accidents. A basic question is: Do we actually have adequate models of accident causation in the present dynamic society? The socio-technical system involved in risk management includes several levels ranging from legislators, over managers and work planners, to system operators this system is presently stressed by a fast pace of technological change, by an increasingly aggressive, competitive environment, and by changing regulatory practices and public pressure. Traditionally, each level of this is studied separately by a particular academic discipline, and modelling is done by generalising across systems and their particular hazard sources. It is argued that risk management must be modelled by cross- disciplinary studies, considering risk management to be a control problem and serving to represent the control structure involving all levels of society for each particular hazard category. Furthermore, it is argued that this requires a system-oriented approach based on functional abstraction rather than structural decomposition. Therefore task analysis focused on action sequences and occasional deviation in terms of human errors should be replaced by a model of behaviour shaping mechanisms in terms of work system constraints, boundaries of acceptable performance, and subjective criteria guiding adaptation to change. It is found that at present a convergence of research paradigms of human sciences guided by cognitive science concepts supports this approach. A review of this convergence within decision theory and management research is presented in comparison with the evolution of paradigms within safety research.","author":[{"dropping-particle":"","family":"Canada","given":"Transport","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Transport Canada","id":"ITEM-1","issued":{"date-parts":[["2008"]]},"title":"Fatigue Risk Management System for the Canadian Aviation Industry Developing and Implementing a Fatigue Risk Management System","type":"book"},"uris":["http://www.mendeley.com/documents/?uuid=c4a697f0-89d3-407f-8dd8-8b903bb3c221"]}],"mendeley":{"formattedCitation":"[3]","plainTextFormattedCitation":"[3]","previouslyFormattedCitation":"[3]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[3] stated that there are three major categories of fatigue consequences – physical (for example, abruptly nodding off for a few seconds, called a microsleep), mental (for example, lapses in attention) and emotional (for example, irritability).Managing FatigueFatigue management is a crucial aspect of safety management since it is a significant and preventable element in transportation incidents or accidents. Sometimes, organizations and regulators manage fatigue indirectly through prescriptive limits on work hours, often because it is seen as the only available option ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.2105/ajph.7.3.322","ISBN":"1509358781","ISSN":"00396125","PMID":"20293317","author":[{"dropping-particle":"","family":"Kimberly A. Honn, Hans P.A. Van Dongen","given":"Drew Dawson","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Industrial Health","id":"ITEM-1","issued":{"date-parts":[["2019"]]},"title":"Working Time Society consensus statements: Prescriptive rule sets and risk management-based approaches for the management of fatigue-related risk in working time arrangements","type":"article-journal","volume":"SW-8"},"uris":["http://www.mendeley.com/documents/?uuid=fa734dc2-1e03-4abb-8244-5a8e404e9a7f"]}],"mendeley":{"formattedCitation":"[4]","plainTextFormattedCitation":"[4]","previouslyFormattedCitation":"[4]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[4]. However, a given amount of break from work does not necessarily provide a given level of fatigue recovery as the length of the break is not the main factor but rather the amount and quality of sleep obtained ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1016/j.smrv.2005.03.002","ISSN":"10870792","PMID":"16099184","abstract":"Fatigue has increasingly been viewed by society as a safety hazard. This has lead to increased regulation of fatigue by governments. The most common control process has been compliance with prescriptive hours of service (HOS) rule sets. Despite the frequent use of prescriptive rule sets, there is an emerging consensus that they are an ineffective hazard control, based on poor scientific defensibility and lack of operational flexibility. In exploring potential alternatives, we propose a shift from prescriptive HOS limitations toward a broader Safety management system (SMS) approach. Rather than limiting HOS, this approach provides multiple layers of defence, whereby fatigue-related incidents are the final layer of many in an error trajectory. This review presents a conceptual basis for managing the first two levels of an error trajectory for fatigue. The concept is based upon a prior sleep/wake model, which determines fatigue-risk thresholds by the amount of sleep individuals have acquired in the prior 24 and 48 h. In doing so, managing level 1 of the error trajectory involves the implementation of systems that determine probabilistic sleep opportunity, such as prescriptive HOS rules or fatigue modelling. Managing level 2, requires individuals to be responsible for monitoring their own prior sleep and wake to determine individual fitness for duty. Existing subjective, neurobehavioral and electrophysiological research is reviewed to make preliminary recommendations for sleep and wake thresholds. However, given the lack of task- and industry-specific data, any definitive conclusions will rely in post-implementation research to refine the thresholds. © 2005 Elsevier Ltd. All rights reserved.","author":[{"dropping-particle":"","family":"Dawson","given":"Drew","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"McCulloch","given":"Kirsty","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Sleep Medicine Reviews","id":"ITEM-1","issue":"5","issued":{"date-parts":[["2005"]]},"page":"365-380","title":"Managing fatigue: It's about sleep","type":"article-journal","volume":"9"},"uris":["http://www.mendeley.com/documents/?uuid=33e84cd5-1dec-4584-89a5-fcd610c29601"]}],"mendeley":{"formattedCitation":"[5]","plainTextFormattedCitation":"[5]","previouslyFormattedCitation":"[5]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[5]. Both work and non-work factors can affect sleep ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.18502/kls.v4i5.2554","abstract":".","author":[{"dropping-particle":"","family":"Azwar","given":"A","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Susilowati","given":"I H","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Dinar","given":"A","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Indriyani","given":"K","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wirawan","given":"M","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"KnE Life Sciences","id":"ITEM-1","issue":"5","issued":{"date-parts":[["2018"]]},"page":"213","title":"Impact of Work-related and Non-work-related Factors on Fatigue in Production/Shift Workers","type":"article-journal","volume":"4"},"uris":["http://www.mendeley.com/documents/?uuid=af81b7a5-9ab8-4d8d-9b3d-dcc45cd268db"]}],"mendeley":{"formattedCitation":"[6]","plainTextFormattedCitation":"[6]","previouslyFormattedCitation":"[6]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[6]. Work-related factors such as shift length, work type, workload, work environment, and breaks within a shift can affect the quantity of sleep and time awake acquired in a 24-hour period. Also, non-work-related issues, such as sleep disorders, family duties, social and leisure activities, and mental stress, can impact the amount and quality of sleep people get. These factors can also influence how long people stay up, which can lead to fatigue. The graph below depicts the association between these variables.center173935Work-related factorsNon-work-related factorsCircadian rhythmsSleep/time awakeFatigue00Work-related factorsNon-work-related factorsCircadian rhythmsSleep/time awakeFatigueFig. 1. Factors affecting fatigueFAA ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"AFS-800 AC 91-97","ISBN":"7034873100","ISSN":"0021-8669","PMID":"25246403","abstract":"The Federal Aviation Administration (FAA) regulations that govern today’s aircraft are found in Title 14 of the Code of Federal Regulations (14 CFR). [Figure 12-2] There are 68 regulations organized into three volumes under Title 14, Aeronautics and Space.","author":[{"dropping-particle":"","family":"U.S. Department of Trasnport Federal Aviation Administration","given":"","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Electronic Code of Federal Regulations","id":"ITEM-1","issue":"Title 48","issued":{"date-parts":[["2016"]]},"number-of-pages":"12-46","title":"Overview — Title 14 of the Code of Federal Regulations (14 CFR )","type":"report"},"uris":["http://www.mendeley.com/documents/?uuid=c8fdfc57-cee5-41a5-bfe5-239d82139985"]}],"mendeley":{"formattedCitation":"[7]","plainTextFormattedCitation":"[7]","previouslyFormattedCitation":"[7]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[7] issued Advisory Circular AC 120-115 stating that the causes of fatigue in aviation maintenance are shared by the organization and by the maintenance personnel. It is because both the organization and maintenance personnel have factors that they can control. For example, the organization can control the start time and duration of a shift, schedule changes, rotation of shift schedules, sufficient breaks for employees, and workplace environment such as lighting, temperatures, etc. On the other hand, maintenance personnel also can control the amount of sleep they obtain during break days, quality of sleep, and activities outside work. To be able to take responsibility for themselves, maintenance personnel must have a thorough grasp of the causes and effects of fatigue ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.3357/AMHP.5000.2019","ISSN":"23756322","PMID":"31558194","abstract":"BACKGROUND: The study aimed to identify factors associated with an increased likelihood of aircraft maintenance personnel reporting a fatigue-related error. METHODS: There were 966 maintenance engineering personnel (mean age 5 42 yr, 98% male) who completed a survey with items on personal factors, work factors and a question asking whether during the last month they had made an error in their work due to tiredness. Logistic regression analyses were used to determine factors independently associated with making an error at work due to tiredness. RESULTS: Respondents obtained on average 7.0 h sleep and nearly half (45%) reported that they had felt close to falling asleep while driving home from work in the past 12 mo. Most respondents (70%) had received no education on strategies for coping with shift work. Among respondents, 22% agreed/strongly agreed with the statement \"During the last month, I have made an error in my work due to tiredness.\" Unexpected roster changes independently predicted the likelihood of reporting an error in work due to tiredness and for certain groups of aircraft maintenance personnel, < 6.5 h sleep increased the odds of an error in work due to tiredness fivefold, whereas > 7.5 h sleep almost halved the odds of reporting such an error. DISCUSSION: These findings indicate the importance of stable and predictable work patterns to minimize the risk of fatigue-related errors in this safety critical environment, and also the need for education on coping with shift work to ensure the workforce are best placed to manage their sleep away from work.","author":[{"dropping-particle":"","family":"Signal","given":"T. Leigh","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Berg","given":"Margo J.","non-dropping-particle":"van den","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mulrine","given":"Hannah M.","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Aerospace Medicine and Human Performance","id":"ITEM-1","issue":"10","issued":{"date-parts":[["2019"]]},"page":"860-866","title":"Personal and work factors that predict fatigue-related errors in aircraft maintenance engineering","type":"article-journal","volume":"90"},"uris":["http://www.mendeley.com/documents/?uuid=05b4e599-40b3-4452-8466-deab5735de59"]}],"mendeley":{"formattedCitation":"[8]","plainTextFormattedCitation":"[8]","previouslyFormattedCitation":"[8]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[8]. Conceptually, managing fatigue can help organizations identify hazards related to fatigue and mitigate any associated risks beforehand. The ICAO SARPs ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"ISBN":"9789292492144","abstract":"This manual is intended to provide States with guidance to develop the regulatory framework and the supporting guidance material for the implementation of safety management systems (SMS) by service providers. It also provides guidance for the development of a State safety programme (SSP), in accordance with the International Standards and Recommended Practices (SARPs) contained in Annex 1 Personnel Licensing, Annex 6 Operation of Aircraft, Annex 8 Airworthiness of Aircraft, Annex 11 Air Traffic Services, Annex 13 Aircraft Accident and Incident Investigation and Annex 14 Aerodromes. 1.2","author":[{"dropping-particle":"","family":"ICAO","given":"","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"International Civil Aviation Organization","id":"ITEM-1","issued":{"date-parts":[["2018"]]},"number-of-pages":"1-182","title":"Safety Management Manual- Doc 9859","type":"book"},"uris":["http://www.mendeley.com/documents/?uuid=86a6448d-d601-4b7f-97f5-7e04018b68ec"]}],"mendeley":{"formattedCitation":"[2]","plainTextFormattedCitation":"[2]","previouslyFormattedCitation":"[2]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[2] require three types of hazard identification, which are predictive, proactive, and reactive. In predictive hazard identification, fatigue could be discovered by reviewing anticipated work schedules (rosters) and considering the elements known to affect sleep and fatigue. Then in proactive hazard identification, fatigue can be identified by monitoring the tiredness level in current operations. Meanwhile, fatigue hazard identified by examining the role of fatigue in safety reports and past events is classified in reactive hazard identification.Aligning with ICAO, Transport Canada applied Reason’s ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"ISBN":"9781840141054","abstract":"This is a practical book aimed at those whose daily task it is to think about and manage or regulate the risks of hazardous technologies. The book is not targeted at any one domain, but attempts to identify general tools and principles that are applicable to all organizations facing dangers of one sort or another. This could include banks and building societies just as much as nuclear power plants, oil exploration and production, chemical process plants, and air, sea and rail transport. The emphasis is placed upon the principles and practicalities of defenses against accidents, and how to meet the challenges and minimize risk. 1. Hazards, Defences and Losses -- 2. Defeating the Defences -- 3. Dangerous Defences -- 4. The Human Contribution -- 5. Maintenance can Seriously Damage your System -- 6. Navigating the Safety Space -- 7. A Practical Guide to Error Management -- 8. The Regulator's Unhappy Lot -- 9. Engineering a Safety Culture -- 10. Reconciling the Different Approaches to Safety Management.","author":[{"dropping-particle":"","family":"Reason","given":"J. T.","non-dropping-particle":"","parse-names":false,"suffix":""}],"id":"ITEM-1","issued":{"date-parts":[["1997"]]},"publisher":"Ashgate","publisher-place":"Burlington, VT","title":"Managing the risks of organizational accidents","type":"book"},"uris":["http://www.mendeley.com/documents/?uuid=afe6a683-6e3d-4044-8133-b78943439c99"]}],"mendeley":{"formattedCitation":"[9]","plainTextFormattedCitation":"[9]","previouslyFormattedCitation":"[9]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[9] principle of hazard identification in Safety Management System (SMS) to Fatigue Risk Management System (FRMS). There are five major levels of control for managing fatigue risk that an organization can follow:Level 1 (organizational): work schedule gives employees adequate opportunity to sleep,Level 2 (individual): personal responsibilities of employees to actually get sufficient sleep,Level 3 (behavioral): monitoring or systems to detect fatigue symptoms,Level 4 (error): strategies to prevent workplace fatigue from causing errors or mishaps,Level 5 (incident): identifying the role of fatigue in workplace errors or incidents.A defense system around each level is necessary to support a successful fatigue risk management system.Many studies use the Samn-Perelli fatigue scale and other objective tools to measure pilot fatigue levels at work ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1016/J.AAP.2015.10.005","ISSN":"0001-4575","PMID":"26590506","abstract":"Fatigue is a risk factor for flight performance and safety in commercial aviation. In US commercial aviation, to help to curb fatigue, the maximum duration of flight duty periods is regulated based on the scheduled start time and the number of flight segments to be flown. There is scientific support for regulating maximum duty duration based on scheduled start time; fatigue is well established to be modulated by circadian rhythms. However, it has not been established scientifically whether the number of flight segments, per se, affects fatigue. To address this science gap, we conducted a randomized, counterbalanced, cross-over study with 24 active-duty regional airline pilots. Objective and subjective fatigue was compared between a 9-hour duty day with multiple take-offs and landings versus a duty day of equal duration with a single take-off and landing. To standardize experimental conditions and isolate the fatiguing effect of the number of segments flown, the entire duty schedules were carried out in a high-fidelity, moving-base, full-flight, regional jet flight simulator. Steps were taken to maintain operational realism, including simulated airplane inspections and acceptance checks, use of realistic dispatch releases and airport charts, real-world air traffic control interactions, etc. During each of the two duty days, 10 fatigue test bouts were administered, which included a 10-minute Psychomotor Vigilance Test (PVT) assessment of objective fatigue and Samn-Perelli (SP) and Karolinska Sleepiness Scale (KSS) assessments of subjective sleepiness/fatigue. Results showed a greater build-up of objective and subjective fatigue in the multi-segment duty day than in the single-segment duty day. With duty start time and duration and other variables that could impact fatigue levels held constant, the greater build-up of fatigue in the multi-segment duty day was attributable specifically to the difference in the number of flight segments flown. Compared to findings in previously published laboratory studies of simulated night shifts and nighttime sleep deprivation, the magnitude of the fatiguing effect of the multiple take-offs and landings was modest. Ratings of flight performance were not significantly reduced for the simulated multi-segment duty day. The US duty and flight time regulations for commercial aviation shorten the maximum duty duration in multi-segment operations by up to 25% depending on the duty start time. The present results represent an imp…","author":[{"dropping-particle":"","family":"Honn","given":"Kimberly A","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Satterfield","given":"Brieann C","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"McCauley","given":"Peter","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Caldwell","given":"J Lynn","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"Van","family":"Dongen","given":"Hans P A","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Accident Analysis & Prevention","id":"ITEM-1","issued":{"date-parts":[["2016"]]},"page":"199-208","publisher":"Pergamon","title":"Fatiguing effect of multiple take-offs and landings in regional airline operations","type":"article-journal","volume":"86"},"uris":["http://www.mendeley.com/documents/?uuid=9c7ffe59-0940-4386-b172-b9bc875eb382"]},{"id":"ITEM-2","itemData":{"ISSN":"00956562","PMID":"17679568","abstract":"Introduction: There is little research on what factors are associated with fatigue in short-haul pilots. The aim was to investigate how length of duty, number of sectors, time of day, and departure airport affect fatigue levels in short-haul operations. Methods: Pilots completed Samn-Perelli fatigue ratings prior to descent at the end of each rostered short-haul duty over a 12-wk period. Overall, 1370 usable responses were collected (67% of rostered duties) and fatigue scores were examined in relation to the departure airport, the number of sectors flown, time, and the length of duty period. Results: The most important influences on fatigue were the number of sectors and duty length. These were associated with fatigue in a linear fashion. Time of day had a weaker influence, with lower levels at midday and increased fatigue later in the day. Fatigue was also higher during duties originating from an airport where pilots needed to position the night before and spend the night in a hotel. Discussion: Data from the study enabled the quantification of fatigue at this critical phase of flight in duties lasting between 2 and 12 h and finishing between 08:00 to 24:00. The data obtained may be useful for identifying factors associated with fatigue, evaluating existing fatigue models, and identifying or predicting problem duties within an airline operation. The methodology used in the study may be successfully applied to gather fatigue data in other airline operations. Copyright © by Aerospace Medical Association.","author":[{"dropping-particle":"","family":"Powell","given":"David M C","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Spencer","given":"Mick B","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Holland","given":"David","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Broadbent","given":"Elizabeth","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Petrie","given":"Keith J","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Aviation Space and Environmental Medicine","id":"ITEM-2","issue":"7","issued":{"date-parts":[["2007"]]},"page":"698-701","title":"Pilot fatigue in short-haul operations: Effects of number of sectors, duty length, and time of day","type":"article-journal","volume":"78"},"uris":["http://www.mendeley.com/documents/?uuid=bf4e31b8-b225-40ba-a7a9-7faaae454381"]},{"id":"ITEM-3","itemData":{"DOI":"10.3357/ASEM.2362.2008","ISSN":"00956562","PMID":"18998486","abstract":"Objectives: Two-pilot operations make up the majority of commercial flights. Fatigue is an important consideration in these operations as there is little opportunity for in-flight rest. We investigated the role of duty length, time of day, and whether one or two sectors were flown on reported fatigue at the top of descent in two-pilot regional operations. Methods: Pilots flying two-pilot operations ranging from 3-12 h completed Samn-Perelli fatigue ratings prior to descent at the end of each rostered duty over a 12-wk period. We collected 3023 usable ratings (72% of rostered duties) comprising 26% single and 74% double sector duties. Results: We found that time of day has a marked effect on the pattern of fatigue at the start of the duty and on the rate at which fatigue levels increased, with the highest levels in the window of circadian low (0200-0600). Fatigue also increased with the length of duty and was 0.56 higher at the end of a two-sector compared with a single-sector duty. Discussion: The results imply authorities should consider increasing existing limits for daytime duties and reducing those for nighttime two-pilot operations. Copyright © by the Aerospace Medical Association.","author":[{"dropping-particle":"","family":"Powell","given":"David","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Spencer","given":"Mick B","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Holland","given":"David","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Petrie","given":"Keith J","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Aviation Space and Environmental Medicine","id":"ITEM-3","issue":"11","issued":{"date-parts":[["2008"]]},"page":"1047-1050","title":"Fatigue in two-pilot operations: Implications for flight and duty time limitations","type":"article-journal","volume":"79"},"uris":["http://www.mendeley.com/documents/?uuid=085b5ac6-57db-4b25-9f18-bbd05f0f1a70"]},{"id":"ITEM-4","itemData":{"DOI":"10.3357/ASEM.2804.2010","ISSN":"00956562","PMID":"21043297","abstract":"We investigated the effect of an additional day's layover on reducing fatigue in two different duties: a two-pilot crew fl ying between Auckland and Brisbane, and a three-pilot crew fl ying between Auckland and Los Angeles. Methods: Pilots completed a reaction time task, the Samn-Perelli fatigue scale, and the Karolinska Sleepiness Scale on both outward and return fl ights. The fl ights were conducted with and without a 1-d layover (Brisbane) and with a 1- or 2-d layover (Los Angeles). Results: On the Brisbane route, the addition of a layover resulted in a signifi cant reduction of fatigue, sleepiness, and reaction time. At top of descent, Samn-Perelli fatigue was reduced from over 5.0 to under 4.5. In contrast, the addition of an extra day layover in Los Angeles had no signifi cant effect on the same measures during the return fl ight; on both fl ights Samn-Perelli fatigue was over 5.0 at top of descent. Discussion: The results suggest that the addition of an extra night's layover has different effects depending on the type of operation. Layover periods need to ensure adequate opportunity to recover from any sleep defi cit arising from the outbound journey, but the benefi t of increased layover time may be limited if time-zone shifts cause a mismatch between local time and the circadian rhythm of sleep.","author":[{"dropping-particle":"","family":"Powell","given":"David M C","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Spencer","given":"Mick B","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Petrie","given":"Keith J","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Aviation Space and Environmental Medicine","id":"ITEM-4","issue":"11","issued":{"date-parts":[["2010"]]},"page":"1013-1017","title":"Fatigue in airline pilots after an additional day's layover period","type":"article-journal","volume":"81"},"uris":["http://www.mendeley.com/documents/?uuid=abe89b94-bbb3-4a35-a409-ab74d01ab992"]},{"id":"ITEM-5","itemData":{"DOI":"10.1016/J.AAP.2011.09.020","ISSN":"0001-4575","PMID":"22239926","abstract":"Most of the research related to human fatigue in the aviation industry has focussed on long-haul pilots, but short-haul pilots also experience elevated levels of fatigue. The aim of this study was to examine the impact of early start times on the amount of sleep obtained prior to duty and on fatigue levels at the start of duty. Seventy short-haul pilots collected data regarding their duty schedule and sleep/wake behaviour for at least two weeks. Data were collected using self-report duty/sleep diaries and wrist activity monitors. Mixed-effects regression analyses were used to examine the effects of duty start time (04:00-10:00 h) on (i) the total amount of sleep obtained in the 12 h prior to the start of duty and (ii) self-rated fatigue level at the start of duty. Both analyses indicated significant main effects of duty start time. In particular, the amount of sleep obtained in the 12 h prior to duty was lowest for duty periods that commenced between 04:00 and 05:00 h (i.e. 5.4 h), and greatest for duty periods that commenced between 09:00 and 10:00 h (i.e. 6.6 h). These data indicate that approximately 15 min of sleep is lost for every hour that the start of duty is advanced prior to 09:00 h. In addition, self-rated fatigue at the start of duty was highest for duty periods that commenced between 04:00 and 05:00 h, and lowest for duty periods that commenced between 09:00 and 10:00 h. Airlines should implement a fatigue risk management system (FRMS) for short-haul pilots required to work early-morning shifts. One component of the FRMS should be focussed on the production of 'fatigue-friendly' rosters. A second component of the FRMS should be focussed on training pilots to optimise sleep opportunities, to identify circumstances where the likelihood of fatigue is elevated, and to manage the risks associated with fatigue-related impairment. © 2011 Elsevier Ltd. All rights reserved.","author":[{"dropping-particle":"","family":"Roach","given":"Gregory D","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sargent","given":"Charli","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Darwent","given":"David","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Dawson","given":"Drew","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Accident Analysis & Prevention","id":"ITEM-5","issue":"SUPPL.","issued":{"date-parts":[["2012"]]},"page":"22-26","publisher":"Pergamon","title":"Duty periods with early start times restrict the amount of sleep obtained by short-haul airline pilots","type":"article-journal","volume":"45"},"uris":["http://www.mendeley.com/documents/?uuid=ce4fb82f-2f28-488f-ae96-c3d9b0b3e00b"]},{"id":"ITEM-6","itemData":{"DOI":"10.1016/J.PROMFG.2015.07.383","ISSN":"2351-9789","abstract":"In an effort to better understand the impact of fatigue on commercial flight operations, we collected physiological and performance data from commercial flight crews performing simulated operations under both rested and fatigued conditions. The purpose of this research was 1) to evaluate the effects of varying levels of fatigue and workload on pilot performance and physiological responses, and 2) to determine whether any technology exists to detect symptoms of fatigue in real time. Thirty-two airline pilots were fitted with a variety of physiological measurement devices to measure characteristics that are affected by fatigue. Each crew of two pilots flew a “rested” and a “fatigued” session in a high-fidelity B-777 simulator. Crews were assigned to one of two flight scenarios: either one 6.5 hour “long-haul” flight or four consecutive 0.5 to 1.5 hour “short haul” flights. Subjective fatigue ratings accurately reflected the rested and fatigued conditions; however, performance on a psychomotor vigilance task did not vary significantly between rested and fatigued conditions or between short and long haul flights. Further, although physiological data allowed a general distinction between larger and smaller fatigue effects for most individuals, no single measurement device was found to reliably indicate fatigue levels with enough granularity to allow for useful fatigue detection. However, a statistical/machine learning model was constructed that was able to accurately categorize fatigued data for each individual pilots using that pilot's combined sensor data with a success rate greater than 95%. It is probable that by optimizing the parameters of the model and improving the quality of sensor data, an algorithm-based solution to real-time fatigue detection can be developed. The applicability of this type of approach extends beyond the commercial flight deck to any work environment that requires multi-shift or other non-traditional scheduling.","author":[{"dropping-particle":"","family":"Thomas","given":"Lisa C","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gast","given":"Christopher","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Grube","given":"Robert","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Craig","given":"Kimberly","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Procedia Manufacturing","id":"ITEM-6","issued":{"date-parts":[["2015"]]},"page":"2357-2364","publisher":"Elsevier","title":"Fatigue Detection in Commercial Flight Operations: Results Using Physiological Measures","type":"article-journal","volume":"3"},"uris":["http://www.mendeley.com/documents/?uuid=f7218a6e-b73e-4834-8a0c-1d11a34dc295"]}],"mendeley":{"formattedCitation":"[10–15]","plainTextFormattedCitation":"[10–15]","previouslyFormattedCitation":"[10]–[15]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[10–15]; however, none of these studies has used aircraft maintenance personnel as the target to survey their fatigue levels under the various shift schedules.3. METHODOLOGYThis research used the Samn-Perelli Status Check, Fatigue Likelihood Score, and Individual Fatigue Likelihood in determining the risk of fatigue for the newly implemented shift pattern. Data were collected through electronic questionnaires. The questionnaire consists of 6 questions that were sent to a total of 303 aviation maintenance personnel distributed in each work shift.Samn-Perelli Status CheckThe Samn-Perelli Status Check is a 7-point scale that subjectively measures the respondent’s level of fatigue at that moment in time ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"author":[{"dropping-particle":"","family":"Samn","given":"Sherwood W","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Perelli","given":"P","non-dropping-particle":"","parse-names":false,"suffix":""}],"id":"ITEM-1","issued":{"date-parts":[["1981"]]},"title":"Estimating Aircrew Fatigue : a Technique","type":"article-journal"},"uris":["http://www.mendeley.com/documents/?uuid=0eada66d-58a8-48b0-90fe-e50ba57e4272"]}],"mendeley":{"formattedCitation":"[16]","plainTextFormattedCitation":"[16]","previouslyFormattedCitation":"[16]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[16]. Possible scores range from 1 (“fully alert, wide awake”) to 7 (“completely exhausted, unable to function effectively”). This scale was initially designed to test pilot fatigue and alertness before takeoff.Fatigue Likelihood Score (based on work schedules)The primary goal of reviewing work schedules is to understand the possible effects that particular hours of work will have on sleep opportunities, in addition to making sure that they adhere to industry standards and other regulations. In the context of a Fatigue Risk Management System (FRMS), the company is responsible for ensuring that appropriate opportunity for sleep is provided between work shifts. It is the obligation of the maintenance employees to take advantage of the available possibilities for recovery sleep.Tab. 1Fatigue Likelihood Scoring Matrix for Work ScheduleScore01248Total hours per 7 days (hours)< 36 36.1 – 43.944 – 47.948 – 54.955+Maximum shift duration (hours)< 8 8.1 – 9.910 – 11.912 – 13.914+Minimum short break duration (hours)> 16 15.9 – 1312.9 – 109.9 – 8< 8Maximum night work per 7 days (hours)0 0.1 – 88.1 – 1616.1 – 24> 24Long break frequency (days)> 1 in 7 < 1 in 7 < 1 in 14 <1 in 21 < 1 in 28 Referring to Transport Canada ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1016/S0925-7535(97)00052-0","ISSN":"09257535","abstract":"In spite of all efforts to design safer systems, we still witness severe, large-scale accidents. A basic question is: Do we actually have adequate models of accident causation in the present dynamic society? The socio-technical system involved in risk management includes several levels ranging from legislators, over managers and work planners, to system operators this system is presently stressed by a fast pace of technological change, by an increasingly aggressive, competitive environment, and by changing regulatory practices and public pressure. Traditionally, each level of this is studied separately by a particular academic discipline, and modelling is done by generalising across systems and their particular hazard sources. It is argued that risk management must be modelled by cross- disciplinary studies, considering risk management to be a control problem and serving to represent the control structure involving all levels of society for each particular hazard category. Furthermore, it is argued that this requires a system-oriented approach based on functional abstraction rather than structural decomposition. Therefore task analysis focused on action sequences and occasional deviation in terms of human errors should be replaced by a model of behaviour shaping mechanisms in terms of work system constraints, boundaries of acceptable performance, and subjective criteria guiding adaptation to change. It is found that at present a convergence of research paradigms of human sciences guided by cognitive science concepts supports this approach. A review of this convergence within decision theory and management research is presented in comparison with the evolution of paradigms within safety research.","author":[{"dropping-particle":"","family":"Canada","given":"Transport","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Transport Canada","id":"ITEM-1","issued":{"date-parts":[["2008"]]},"title":"Fatigue Risk Management System for the Canadian Aviation Industry Developing and Implementing a Fatigue Risk Management System","type":"book"},"uris":["http://www.mendeley.com/documents/?uuid=c4a697f0-89d3-407f-8dd8-8b903bb3c221"]}],"mendeley":{"formattedCitation":"[3]","plainTextFormattedCitation":"[3]","previouslyFormattedCitation":"[3]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[3], this is level 1 control for managing fatigue. To assess sleep opportunity and potential fatigue, the following questions should be answered:1.Hours worked per seven-day period2.Maximum shift length3.Minimum length of time off between shifts4.Hours worked on night shift per 7 days5.Long break frequencyTable 1 shows the scoring matrix of the Fatigue Likelihood Score. Based on Table 1, an ordinary 9 to 5 working hours (5 days consecutively) would produce a score of zero. On the other hand, a work schedule of seven 12-hour night shifts, followed by seven days off, would produce a score of 21, which would be considered high. This approach is further described in Figure 2.71057724768800Fig. 2. Examples of work schedules scoredIndividual Fatigue Likelihood (based on time asleep and awake)Level 2 control for managing fatigue is to make sure maintenance personnel actually have sufficient sleep. This level aims at the individual level rather than the organizational level. The score calculation and decision tree are shown in Tables 2 and 3.Tab. 2Individual fatigue likelihood scoringPrior sleep/wake factorThresholdvalueScoringX (sleep in prior 24 hours)5 hoursAdd 4 points for every hour below thresholdY (sleep in prior 48 hours)12 hoursAdd 2 points for each hour below thresholdZ (time awake since last sleep)YAdd 1 point for each hour of wakefulness greater than YTab. 3Individual fatigue likelihood score, risk level, and approved controlsIndividual Fatigue ScoreRisk LevelApproved ControlsZeroAcceptableNo additional controls are necessary except in the presence of higher-level indicators of fatigue (that is, symptoms, errors, or incidents)1-4MinorInform the line supervisor and document it in the daily logbook. Self-monitor for fatigue-related symptoms, and apply individual controls such as strategic use of caffeine, task rotation, working in pairs, and additional rest breaks5-8ModerateInform the local manager and document it in a fatigue report. Implement additional fatigue controls such as task reallocation, napping, and increased level of peer and supervisory monitoring9+SignificantCall the manager before driving to work. Document in a fatigue report on the next work shift. Do not engage in safety-critical tasks (including driving to work), and do not return to work until sufficiently rested as per sleep/time awake rules4. RESULTS AND DISCUSSIONThis survey was conducted on 3 units (A, B, C) which were directly affected by the New Patterns Shift 5-3. The distribution of the number of surveys can be seen in the demography below:Units of RespondentsA total of 303 respondents were separated into 3 units. A unit consisting of 216 employees sent 61 responses, achieving 28.2% of respondents. Then C unit totaling 149 employees, sent 66 responses, achieving 44.2% of respondents. While B unit comprising 276 employees sent 176 responses, achieving 63.7% of respondents.Shifts of RespondentsBased on shifts carried out in these 3 units, it was divided into 5 parts of shift, namely morning shift 1 (P1), morning shift 2 (P2), noon (S), night shift 1 (M1), and night shift 2 (M2). The response results obtained at the P1 shift were 54 or 18% of respondents; on the P2 shift, 38 or 12% of respondents; on the S shift, 60 or 20% of respondents; on the M1 shift, 45 or 15% of respondents; and the M2 shift, 106 or 35% of respondents (Figure 3). center16667800Fig. 3. Work shifts of respondents4.1 Survey Result4.1.1 Samn-Perelli Status CheckSurvey question number 4 is a simplified version of the Samn-Perelli Checklist, which asked respondents to rate their level of fatigue at the time the survey was taken. As illustrated in Figure 4, many respondents (78 out of 303, 26%) felt tired and had difficulty concentrating, regardless of the shift they were in. Further, 20% of the respondents felt extremely exhausted and unable to concentrate (60 out of 303), followed by 19% who felt moderately tired (57 out of 303). Fig. 4. Respondents’ Samn-Perelli status resultsFigure 5 shows an increasing fatigue level of the current condition during each shift. The numbers marked ‘X’ in the middle of the boxes are the average scores (mean) for each shift, and the numbers with lines inside the boxes are the median of each shift.Most respondents on morning shift day 1 (P1) felt “okay, somewhat fresh” or equal to level 3. This average score then increases for respondents on morning day 2 (P2) to level 4 (“a little tired, less than fresh”). On the noon shift day 3 (S) and night shift day 4 (M1), many respondents felt “Moderately tired, let down” or equal to level 5. Data on night shift day 5 (M2) has the highest average score (level 6), which stands for “extremely tired, very difficult to concentrate”. This figure supports the Circadian Rhythms body clock, where human alertness tends to be higher, and sleepiness levels are lower at 3 PM than at 3 AM ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1007/978-88-470-5388-5_2","ISBN":"978-88-470-5388-5","abstract":"Most of our behavioral and physiological activities are modulated or regulated by endogenous clocks, chief among them the circadian (i.e., about a day) clock. Optimally located in the suprachiasmatic nuclei (SCN) of the anterior hypothalamus [1, 2], the circadian pacemaker in the SCN receives light information via the retinohypothalamic tract [3] directly from the retina’s classical and nonclassical photoreceptors [4–6].","author":[{"dropping-particle":"","family":"Cajochen","given":"Christian","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chellappa","given":"Sarah L","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Schmidt","given":"Christina","non-dropping-particle":"","parse-names":false,"suffix":""}],"editor":[{"dropping-particle":"","family":"Garbarino","given":"Sergio","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Nobili","given":"Lino","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Costa","given":"Giovanni","non-dropping-particle":"","parse-names":false,"suffix":""}],"id":"ITEM-1","issued":{"date-parts":[["2014"]]},"page":"9-22","publisher":"Springer Milan","publisher-place":"Milano","title":"Circadian and Light Effects on Human Sleepiness–Alertness BT - Sleepiness and Human Impact Assessment","type":"chapter"},"uris":["http://www.mendeley.com/documents/?uuid=1b860f74-f5c0-441c-a893-ecb604ab47cd"]},{"id":"ITEM-2","itemData":{"DOI":"10.1002/ppul.1065","ISSN":"87556863","abstract":"Both wakefulness and sleep are modulated by an endogenous regulating system, the biological clock, located in the suprachiasmatic nuclei of the hypothalamus. The impact of the biological clock goes beyond compelling the body to fall asleep and to wake up again. The biological clock also modulates our hour-to-hour waking behavior, as reflected in fatigue, alertness and performance, generating circadian rhythmicity in almost all neurobehavioral variables. Before focusing on circadian rhythmicity in waking functions, it is appropriate to give a brief description of the three variables mentioned in the title of this chapter. In the literature, various definitions of fatigue, alertness and performance can be found (e.g., [1, 2]) and differences of opinion exist about their meaning. For the purposes of this chapter, the term performance comprises cognitive functions ranging in complexity from simple psychomotor reaction time, to logical reasoning, working memory and complex executive functions. By alertness is meant selective attention, vigilance, and attentional control (after [3]). Fatigue refers to subjective reports of loss of desire or ability to continue performing. Additionally, subjective sleepiness is used here for subjective reports of sleepiness or the desire to sleep. The meanings of fatigue and subjective sleepiness given above express the relationship that exists between alertness and performance during wakefulness on the one hand and sleep on the other hand. The interaction of the circadian and sleep–wake systems in regulating fatigue, alertness and performance is described in the second part of this chapter. It is important to note that this chapter does not cover sleep propensity [4, 5], but rather focuses on circadian regulation in effortful performance and its corresponding subjective states.","author":[{"dropping-particle":"","family":"Dongen","given":"Hans P. A. Van;","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Dinges","given":"David F.","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Principles and practice of sleep medicine","id":"ITEM-2","issued":{"date-parts":[["2000"]]},"page":"391-399","title":"Circadian Rhythms in Fatigue, Alertness and Performance","type":"article-journal","volume":"20"},"uris":["http://www.mendeley.com/documents/?uuid=e5ee6dc3-8897-4748-b37f-38e38f96806f"]},{"id":"ITEM-3","itemData":{"DOI":"10.1051/matecconf/202134100006","abstract":"Maintenance staff fatigue is one of the key factors contributing to the occurrence of errors in the maintenance. The problem of maintenance staff fatigue is a serious challenge for aircraft maintenance organizations, and its solution is directly related to the impact on flight safety. The authors consider the issues of the fatigue effect on the maintenance staff performance and related consequences. The article provides the results of the maintenance staff fatigue research, obtained through a survey of one of the organizations` employees. According to the survey, errors are the most likely outcome of work in a state of fatigue in aircraft maintenance. The obtained results made it necessary to develop a methodology for managing maintenance staff fatigue in aircraft maintenance. The methodology is based on a questionnaire, where the respondents are asked to answer questions regarding their state of fatigue, and fatigue assessment criteria. The assessment results make it possible to develop the necessary corrective and preventive measures, including the privilege limitation and suspension to perform maintenance tasks.","author":[{"dropping-particle":"","family":"Rybalkina","given":"Alexandra","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Enikeev","given":"Ruslan","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"MATEC Web of Conferences","id":"ITEM-3","issued":{"date-parts":[["2021"]]},"page":"00006","title":"Fatigue management methodology in aircraft maintenance as a way of reducing errors related to the human factor","type":"article-journal","volume":"341"},"uris":["http://www.mendeley.com/documents/?uuid=5e69c0b4-02ae-42a3-8e8b-69199f33049d"]}],"mendeley":{"formattedCitation":"[17–19]","plainTextFormattedCitation":"[17–19]","previouslyFormattedCitation":"[17]–[19]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[17–19]. Aircraft maintenance personnel performance reaches its minimum in the early dawn, referred to as the ‘window of circadian low’ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"author":[{"dropping-particle":"","family":"Dinges","given":"David F.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Graeber","given":"RC","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Rosekind","given":"RM","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Samel","given":"A","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Flight Safety Digest","id":"ITEM-1","issue":"February","issued":{"date-parts":[["1997"]]},"title":"Principles and Guidelines For Duty and Rest Scheduling in Corporate and Business Aviation","type":"article-journal","volume":"16 No.2"},"uris":["http://www.mendeley.com/documents/?uuid=32b3ca7a-2e90-4631-828e-3df6c42776fb"]}],"mendeley":{"formattedCitation":"[20]","plainTextFormattedCitation":"[20]","previouslyFormattedCitation":"[20]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[20]. The circadian body clock does not adapt fully to altered schedules such as rotating shifts or night work, although each maintenance personnel have more break time between shifts.4.1.2 Fatigue Likelihood ScoresEvery maintenance personnel experienced the same new shift pattern; therefore, it could be assumed that the company gives equal opportunity for maintenance employees to rest. This fatigue likelihood score assesses whether the current schedule provides the maintenance personnel with sufficient sleep opportunities to reduce the risk of fatigue.10414021717000Fig. 5. Samn-Perelli Status CheckAssuming each maintenance personnel have 5 working days in which each day comprises 7 working hours, therefore, the total hours per 7 days is 35 hours (score 0).The maximum shift duration of each shift is ideally 7 working hours, which also produces a 0 score.The time between shifts ranges between 16 to 23 hours; therefore, the score for minimum short break duration is also 0.There are 2 consecutive night shifts of this new shift pattern. This produces a maximum score of 2 for maximum night work per 7 days.The break frequency is 2 in 7 days, which also contributes to 0 scores for this calculation.In total, the fatigue likelihood score of this new pattern ranges between 0 to 2. Based on the theory, the new shift pattern of 5-3 in line with the maintenance department is still considered a low-risk category.4.1.3 Individual Fatigue Likelihood ScoresFigure 6 describes the individual fatigue likelihood score based on the FRMS Survey question numbers 5, 6 and 7. The numbers marked ‘X’ in the middle of the boxes are the average scores (mean) for each shift, and the numbers with lines inside the boxes are the median of each shift.Based on the data survey, individual fatigue likelihood scores are distributed in moderate risk levels. Most respondents on morning day 1 have an average total individual fatigue score of 6, which fall into the moderate risk level. Respondents who filled out the survey on morning day 2 duty have a higher individual fatigue likelihood score (8) compared to respondents on the morning day 1 shift. However, this is also categorized as a moderate risk level.On the other hand, respondents with duty on the noon shift have a smaller average total individual fatigue score, which is score 6 and equals to moderate risk level. The average total individual fatigue score rises for respondents who participated in the night shift day 4 (total score of 7, moderate risk level). And the highest average total individual fatigue score (score 9) was discovered in respondents whose duty is on night shift day 5. This average score is considered a significant risk level and should be eliminated immediately.-4953016700500Fig. 6. Individual fatigue likelihood score resultsFrom the results and analysis, it is known that at the time of the survey, many respondents (78 out of 303, 26%) felt tired and had difficulty concentrating, regardless of the shift they were in. Then 20% of the respondents felt extremely exhausted and unable to concentrate (60 out of 303), followed by 19% feeling moderately tired (57 out of 303). Based on the duty time, the highest scores of level 6 (tired, difficult to concentrate) were discovered on the night shift day 5, followed by level 5 (moderately tired) on night shift day 4 and noon shift. This result shows that necessary actions are required to be taken to prevent fatigue, especially from the noon shift afterwards, where fatigue levels are increasing, and alertness levels are decreasing.Nevertheless, the fatigue likelihood score shows the contrary. This method of assessment is showing level 1 fatigue control; ensure organizations give a sufficient day off time for maintenance personnel to sleep. The risk level of the new shift pattern is considered low risk based on hours worked per seven-day period, maximum shift length, minimum length of time off between shifts, hours worked on night shift per seven-day, and long break frequency. There was no significant case resulting in a higher score of fatigue likelihood. This is due to the assumptions of no overwork during shifts, maximum of 16 hours of night shifts per seven-day, and no consideration of the circadian rhythm and its effect. Chang et al. ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1016/j.jairtraman.2019.01.013","ISSN":"09696997","abstract":"Fatigue is one of the most important issues since it is considered to be a potential risk factor for human error. Most research related to human fatigue in the aviation industry targets pilots, yet air traffic controllers also experience elevated levels of fatigue that affects aviation safety. Despite this, fatigue is often ignored in literature, as it is a mental and physical status that is difficult to measure. The International Civil Aviation Organization (ICAO) announced the concept of the Fatigue Risk Management System (FRMS) in Annex 6 in 2011, which provides suggestions to reduce aircrew fatigue. In 2016, the Civil Air Navigation Services Organization (CANSO), ICAO, and the International Federation of Air Traffic Controllers’ Associations (IFATCA) published the Fatigue Management Guide for Air Traffic Service Providers and for the first time proposed recommendations for air traffic controllers (ATCs) to address this issue. Based on the management guide, this research used the Samn-Perelli fatigue scale to measure air traffic controllers’ fatigue levels in an international aerodrome control tower in Taiwan. The results indicated that there were significant differences between day/night shifts, time periods (shift start time, before break time, after break time, and shift end time), and various work schedules. The results also revealed the importance of the timing of the breaks and time on task when arranging work schedules. This research contributes to aviation safety by investigating ATCs’ fatigue levels in current work shifts, thereby helping related units to improve and adjust shift schedules in order to reduce the risks related to fatigue.","author":[{"dropping-particle":"","family":"Chang","given":"Yu Hern","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Yang","given":"Hui Hua","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Hsu","given":"Wan Jou","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Journal of Air Transport Management","id":"ITEM-1","issue":"December 2017","issued":{"date-parts":[["2019"]]},"page":"1-9","title":"Effects of work shifts on fatigue levels of air traffic controllers","type":"article-journal","volume":"76"},"uris":["http://www.mendeley.com/documents/?uuid=c3f6ce3d-70f0-4627-a9dd-53e1e37c0fa5"]}],"mendeley":{"formattedCitation":"[21]","plainTextFormattedCitation":"[21]","previouslyFormattedCitation":"[21]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[21] revealed that people adapt their work-rest cycles based on their work days, which prevents fatigue levels from increasing over successive work days of the same schedule since employees may plan their work days ahead of time. However, uneven morning and afternoon work hours could result in excessive weariness with particular shift types.Thus, the calculation of fatigue likelihood scores should be detailed in the next control, which is level 2; the quality of sleep obtained by the maintenance personnel. Individual fatigue likelihood score describes whether the sleep obtained during off-duty time is good quality sleep. From the result of the Individual Fatigue Likelihood Scores, it is known that the respondents on the night shift day 2 experienced significant fatigue (score 9), whereas, on other shifts, respondents underwent moderate fatigue ranging from a total score of 5 to 8. It can be concluded that although an organization has provided the maintenance personnel with the opportunity to obtain sleep during rest days, it does not necessarily mean that the maintenance personnel will actually have good quality sleep to recover from the fatigue they are experiencing. Although the break time between each shift is longer than 12 hours; however, regarding the Circadian Rhythms, it might be difficult for the maintenance personnel to sleep when the body clock tends to be on the peak level of alertness.Based on the survey results and analysis, it is suggested that an organization should have sufficient fatigue controls in place to reduce the likelihood of fatigue-related incidents. This can be done by evaluating the possibility of overwork in each shift due to the unavailability of a supporting system (for example, tools, equipment, and next-shift personnel), which could contribute to a higher fatigue likelihood score. It is necessary to review the new shift pattern of 5-3 in the Line Maintenance Department and focus more on the actual working hours of the maintenance personnel. Manpower planning corresponding to daily load should be considered to minimize the gap between each shift.Moreover, fatigue awareness training and promotion need to be performed to enhance the knowledge of fatigue and the importance of having good quality sleep. Managing fatigue responsibility is shared between the organization and the maintenance personnel as an individual. Therefore, the maintenance personnel should be better aware of the fatigue conditions they experience. Periodic promotion events such as webinars, email publications, and banners are favorable as a fresh start.5. CONCLUSIONThe new 5-3 work shift pattern allows maintenance personnel to have fewer working hours per day (7-hour shifts) in more shift varieties. The morning shift on days 1 and 2 starts at 6 AM to 8 AM, the noon shift at 2 PM on day 3, and the night shift on days 4 and 5 starts at 9 PM to 11 PM. Subsequently, the maintenance personnel will then have 3 consecutive rest days. Based on the Samn-Perelli Status Check, fatigue likelihood scores, and individual fatigue likelihood scores, this study finds that at the time of the survey, many respondents (78 out of 303, 26%) felt tired and had difficulty concentrating, regardless of the shift they were in. Based on the duty time, the highest score of level 6 (tired, difficult to concentrate) was discovered on night shift day 5. This result shows that necessary actions are required to be taken to prevent fatigue and further implications on safety, especially from the noon shift afterwards, where fatigue levels are increasing, and alertness levels are decreasing.Consequently, this study recommends several actions to be taken. The first action is to provide sufficient fatigue controls in place to reduce the likelihood of fatigue-related accidents. This can be done by evaluating the possibility of overwork in each shift due to the unavailability of a supporting system, providing a better rest area and environment. The second action is to consider the importance of the circadian rhythm and break time between shifts in future scheduling. The break time between scheduling should ensure that the aircraft maintenance personnel have sufficient time to sleep or rest during their off-duty time. Finally, the third action is to offer fatigue awareness training and promotion to enhance maintenance personnel’s knowledge of fatigue and the importance of having good quality sleep. Future research should consider the effect of work shifts on aircraft maintenance personnel's work performance. Measurements or techniques that can capture and evaluate the impact of sleep quality obtained by the maintenance personnel, break time, and work performance, should be explored.ReferencesADDIN Mendeley Bibliography CSL_BIBLIOGRAPHY Federal Aviation Administration. U.S. Department of Transportation. Advisory Circular. Subject: Maintainer Fatigue Risk Management. 2016. ICAO. Safety Management Manual- Doc 9859. 2018. 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Samel. 1997. "Principles and Guidelines For Duty and Rest Scheduling in Corporate and Business Aviation". Flight Safety Digest 16(2). Chang Y.H., H.H. Yang, W.J. Hsu. 2019. "Effects of work shifts on fatigue levels of air traffic controllers". Journal of Air Transport Management 76: 1-9. ISSN: 09696997. DOI: 10.1016/j.jairtraman.2019.01.013.Received 28.09.2022; accepted in revised form 11.11.2022Scientific Journal of Silesian University of Technology. Series Transport is licensed under a Creative Commons Attribution 4.0 International LicenseThe analysis of work shift patterns and risk of… PAGE 15. Industrial Engineering Department, Faculty of Engineering, Bina Nusantara University, Jakarta, Indonesia 11480. Email: fransisca.tiur@binus.ac.id. ORCID: https://orcid.org/0000-0001-7445-8688Scientific Journal of Silesian University of Technology. Series TransportZeszyty Naukowe Politechniki Śląskiej. Seria TransportVolume 118 2023p-ISSN: 0209-3324e-ISSN: 2450-1549DOI: https://doi.org/10.20858/sjsutst.2023.118.1Journal homepage: http://sjsutst.polsl.pl PAGE 16F.T. 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Jay14JournalArticle{78847417-C7D6-4DDE-8CF8-B976F232225D}JayantA.,Gupta, P., Garg, S.K. and Khan, M.TOPSIS-AHP based approach for selection of reverse logistics service provider: a case study of mobile phone industry.2014Procedia Engineering2147-2156971Pak17InternetSite{26F27E69-3E35-4B54-8919-09F53D07045E}PBSPakistan Bureau of Statistics, Population Census 2017, Government of Pakistan, Islamabad, Pakistan2017http://www.pbscensus.gov.pk/21December20172Sou18InternetSite{34BB1F91-464E-4B1A-80C2-2A7774E8084E}South Asia Terrorism Portal, Institute for Conflict Management, New Delhi, Delhi, India, Asia-Pacific (APAC)2018http://www.satp.org/2017December21SATP3Abb18Misc{9B8BFA9B-8126-458A-9B52-F50DC39751FA}2018http://morning.pk/2017/12/pakistan-railways-makes-record-loss-80b-rupees/AbbasShahidPakistan Railways Makes Record Loss of 80b RupeesDaily Morning Mail, Newspaper, December 18, 20172018March294PRC15Misc{4DDF6F05-C42A-417E-B7CE-45A0A903D253}PRCPeople Republic of China, Offical WebsiteChronology of China’s Belt and Road Initiative2015The State Council, the People'S Republic of China2018March29http://english.gov.cn/news/top_news/2015/04/20/content_281475092566326.htm5PC18InternetSite{DFC2AB07-2D4A-4FD8-9CB2-CC47F5040F19}Planning Commission, China Pakistan Economic Corridor (CPEC) offical Websitehttp://cpec.gov.pk/infrastructurePC2018Feburary222018Goverment of Pakistan, Islamabad, Pakistan6Dis10JournalArticle{B97640B9-8C45-4CB8-8DF3-89EE6500B970}DissanayakeDMorikawTakayukInvestigating Household Vehicle Ownership, Mode Choice, And Trip Sharing Decisions Using A Combined Revealed Preference/Stated Preference Nested Logit model: Case Study In Bangkok Metropolitan RegionJournal of Transport Geography2010402-4101837Lar13JournalArticle{44667924-069F-4366-8FE8-B5AA764A9DF6}LarsenK.BuliungR.FaulknerG.Safety and School Travel: How Does the Environment Along the Route Relate to Safety and Mode Choice?Transportation Research Record: Journal of the Transportation Research Board20139-18Transportation Research Board of the National Academies23278Joh06JournalArticle{AE03F1DD-ECED-4493-BE8A-0F699BC0FAF5}The Effects of Attitudes And Personality Traits On Mode Choice2006406JohanssonabM.v.HeldtT.JohanssonPer.Transportation Research Part A: Policy and Practice507-52539Bha06JournalArticle{6AFC1D23-37B6-43A4-BD4B-A8ADC7875942}BhatChandraR.SardesaiR.The Impact Of Stop-Making And Travel Time Reliability On Commute Mode ChoiceTransportation Research Part B: Methodological2006709-73040910Sch13JournalArticle{C520DC7E-4875-44F5-874B-D9C0266A3833}ScheinerJ.Holz-RauC.A comprehensive Study Of Life Course, Cohort, And Period Effects On Changes In Travel Mode UseTransportation Research Part A: Policy and Practice2013167-1814711Pra09JournalArticle{49193CDF-096F-49F5-99BD-C4E872107160}Route Choice Modeling: Past, Present and Future Research Directions2009PratoC.,GJournal of Choice Modelling65-1002112McF74BookSection{5595771F-7A70-48C5-AA13-14D94606361F}McFaddenD.ZarembkaP.Conditional Logit Analysis Of Qualitative Choice Behavior1974Academic Press, New York, USAFrontiers in Econometrics105-14213Ben85Book{05ED7905-E9A2-4E17-B75E-E36AEC5479D5}Ben-AkivaM.E.LermanS.R.Discrete Choice Analysis: Theory and Application to Travel Demand1985MIT Press14Hen07Book{36D919AC-C535-4A19-AF6F-094387C614A2}Applied Choice Analysis A Primer (Third Edition)2007Cambridge University PressHensherA.,D.RoseJ.M.GreeneW.H.15Tra09Book{ABF0AD82-089E-47AB-B927-72061DB8A17D}TrainE.K.Discrete Choice Methods With Simulation2009Cambridge University Press, UK16PR18InternetSite{5334F3A1-6E17-4E15-AFF0-0B95CBA002A6}Pakistan Railways, Government of Pakistan, Ministry of Railways, Islamabad, Pakistan.2018Pakistan Railwayshttps://www.pakrail.gov.pk/AboutUs.aspx2018Feburary1917MoF18Misc{0C75E6F7-8CCE-479C-A498-DF9D5C33A358}2018MoFEconomic Survey 2017-18Ministry of Finance, Government of Pakistan, Islamabad2018March3http://www.finance.gov.pk/survey/chapters_17/13-Transport_and_Communications.pdf18Kar17JournalArticle{C0FCA57D-3792-4553-A586-81F3E8F03B65}KarahaliosH.The application of the AHP-TOPSIS for evaluating ballast water treatment systems by ship operators2017Transportation Research Part D: Transport and Environment pp.172-1845219Mei08JournalArticle{FC593DA1-B80A-4760-BECA-7FC59F5595B8}A Review Of The Transportation Mode Choice And Carrier Selection LiteratureThe International Journal of Logistics Management2008183-211MeixellMaryJNorbisMario19220Bor09Report{87B8A83E-D024-4BBB-9DFB-D756AA639B41}BoranF.E.,Genç, S., Kurt, M. and Akay, D. 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