Information for Interest | Pilot Advisory Notes | Restricted Access
Impact on Wives and Families | Work and Sleep Patterns | Implications for Fatigue Management
An analysis of the work schedules of Great Barrier Reef pilots
Results and Discussion
Great Barrier Reef pilots service both the Great Barrier Reef and Torres Strait regions, thereby covering an area in excess of 345,000 square kilometers (Queensland Department of Transport & AMSA 1996). As a consequence, substantial amounts of work related travel are incurred by pilots. Given that such travel may significantly infringe upon rest time and hence, potentially impact on fatigue, as part of the present investigation an analysis of the effects of travel on the work and rest times of Great Barrier Reef pilots was performed.
7.1 Travel Time from all Sources per Tour
Figure 7.0 displays the mean hours of travel from all sources (to and from ships and between ports) per tour in the three time periods for each company separately. A summary of the analysis of this data in terms of company and time period differences is shown in Table 7.0. The results indicate significant differences between all of the pilotage companies in travel time per tour. The longest travel hours were recorded by Company B (17.9 hours), followed by Company A (11.7 hours) and then Company C (3.4 hours).
Between company differences in total travel time from all sources per tour are also apparent when data is presented in frequency distribution format (Figure 7.1a and Figure 7.1b). Company A’s data presents as a distinct bell shaped curve, whereas data for Company B is markedly skewed. These results clearly indicate that greater amounts of travel are engaged in by Company B personnel. Given that previous sections of this report have detailed that Company B pilots perform more work assignments per tour (Table 3.3), the present finding was not unexpected.
Over the 18 months, significantly more travel was undertaken during the second 6-month period (12.2 hours) compared to the third period (10.42 hours). No clear distinction for the first period was identified from post hoc testing. Similar temporal changes in travel hours from all sources were observed for each of the companies. These results are consistent with previous findings showing an increase in work availability during the second time period.
Figure 7.0 Mean total travel time (hours) from all sources per tour by company and period (1 Jan 1996 - 30 June 1997)
Note: Data analysis based on n values shown in Methods (Section 3.2).
Table 7.0 Analysis of the mean total travel time (hours) from all sources per tour (1 Jan 1996 - 30 June 1997) (1)
|
Effect |
Post hoc results (2) |
Mean (sem) |
F Statistics |
p-value |
|---|---|---|---|---|
| Company (main effect) | 66.02 |
0.0001 |
||
A |
1 |
11.73 (0.471) |
||
B |
2 |
17.93 (0.454) |
||
C |
3 |
3.47 (0.512) |
||
| Period (main effect) | 9.37 |
0.0001 |
||
1 |
1/2 |
10.32 (2.294) |
||
2 |
1 |
12.39 (0.861) |
||
3 |
2 |
10.42 (0.858) |
||
| Company * Period interaction | 2.07 |
0.0831 |
- Results of full two-way analysis of variance (ANOVA) model including company and period effects. p < 0.01 considered statistically significant.
- Results of Tukey’s Studentised Range Test for post-hoc differences (Type I Experimental Error Rate = .01).
Figure 7.1a Frequency distribution - Travel time (hours) from all sources per tour per period - Company A
Figure 7.1b Frequency distribution - Travel time (hours) from all sources per tour per period - Company B
7.2 Travel Time To and From Ships per Tour
Mean travel hours to and from ships per tour for each company per 6-month period are shown in Figure 7.2, while Table 7.1 presents a summary of the analysis of this data in terms of company and time period differences. Significant differences existed with pilots from Company B spending the most time travelling to and from ships per tour of duty each 6 month period (15.2 hours), followed by pilots from Company A (10.0 hours) and then pilots from Company C (3.5 hours). These findings are consistent with the results of the previous section (Section 7.1).
When travel time to and from ships per tour for each company is presented as frequency distributions (Figure 7.3a, Figure 7.3b and Figure 7.3c), a clearer insight into company differences can be obtained. The bell shape curve depicted in Figure 7.3a shows that in most situations, tours performed by pilots from Company A involved between 4 and16 hours of travel to and from ships. In contrast, data for Company B (Figure 7.3b) presents as a flatter, more even distribution, with travel hours to and from ships per tour mostly ranging between 4 to more than 24 hours. This finding suggests that there is greater diversity in travel hours to and from ships during tours undertaken by personnel from Company B.
Data for Company C shows very little variability (Figure 7.3c), with travel time to and from ships for all tours performed during the analysis period totalling no more than 8 hours. This result is consistent with the single operational region of this company.
Changes across time were apparent with more travel being undertaken during the second time period (10.6 hours). This finding is consistent with the results of previous sections detailing an increase in work availability during the second 6-months of the 18 month analysis. The same temporal pattern was exhibited by all companies.
Figure 7.2 Mean total travel time (hours) to and from ships per tour by company and period (1 Jan 1996 - 30 June 1997)
Note: Data analysis based on n values shown in Methods (Section 3.2).
Table 7.1 Analysis of the mean total travel time (hours) to and from ships per tour (1 Jan 1996 - 30 June 1997) (1)
|
Effect |
Post hoc results (2) |
Mean + (sem) |
F Statistics |
p-value |
|---|---|---|---|---|
| Company (main effect) | 67.25 |
0.0001 |
||
A |
1 |
10.00 (0.384) |
||
B |
2 |
15.17 (0.370) |
||
C |
3 |
3.47 (2.047) |
||
| Period (main effect) | 7.65 |
0.0005 |
||
1 |
1/2 |
8.86 (1.870) |
||
2 |
1 |
10.57 (0.701) |
||
3 |
2 |
9.22 (0.700) |
||
| Company * Period interaction | 2.03 |
0.0884 |
- Results of full two-way analysis of variance (ANOVA) model including company and period effects. P < 0.01 considered statistically significant.
- Results of Tukey’s Studentised Range Test for post-hoc differences (Type I Experimental Error Rate = .01).
Figure 7.3a Frequency distribution - Travel time (hours) to and from ships per tour per period - Company A
Figure 7.3b Frequency distribution - Travel time (hours) to and from ships per tour per period - Company B
Figure 7.3c Frequency distribution - Travel time (hours) to and from ships per tour per period - Company C
7.3 Travel Time between Ports per Tour
Pilotage in the Great Barrier Reef - Torres Strait region involves joining ships at various ports and boarding grounds along Queensland’s north-eastern coastline. As a consequence, after completing a work assignment, pilots are frequently required to travel (via aircraft) to another location for embarkation on the next ship.
For each of the pilotage companies the mean hours of travel between ports per tour across the three time periods is presented in Figure 7.4. Table 7.2 shows a summary of the analysis of this data indicating company and period differences. Post hoc testing indicated Company B pilots experienced significantly greater hours of travel between ports (2.76) than Company A (1.72). The absence of travel between ports for Company C reflects the single operational region of this company. That pilots from Company B have also been found to perform more work assignments per tour (Table 5.0) most likely contributes to the greater amount of travel between ports per tour recorded for this group of pilots.
The frequency distributions of travel time between ports show that for both Companies A and B, the majority of tours involved 4 hours or less travel between ports (Figure 7.5a and Figure 7.5b). However, a small number of tours, particularly in the data for Company B, can be identified in which travel between ports totalled 8 hours or more. This extra travel could potentially encroach on recovery time between work assignments and hence may contribute to an increased risk of fatigue development.
In terms of changes across time, longer hours of travel between ports were recorded in the second time period (1.82) compared with the third period (1.2). No clear distinction for the first period was made from post hoc testing. The pattern of temporal changes was similar for the two companies which travelled between ports (Table 7.2) and is clearly depicted in Figure 7.4. This result is consistent with the increased work availability during the second 6 month period.
Figure 7.4 Mean total travel time (hours) between ports, per tour (1 Jan 1996 - 30 June 1997)
Note: Data analysis based on n values shown in Methods (Section 3.2).
Table 7.2 Analysis of the mean total travel time (hours) between ports per tour by company and period (1 Jan 1996 - 30 June 1997) (1)
|
Effect |
Post hoc results (2) |
Mean + (sem) |
F Statistics |
p-value |
|---|---|---|---|---|
| Company (main effect) | 26.43 |
0.0001 |
||
A |
1 |
1.72 (0.133) |
||
B |
2 |
2.76 (0.128) |
||
C |
3 |
0.00 |
||
| Period (main effect) | 8.43 |
0.0002 |
||
1 |
1/2 |
1.46 (0.649) |
||
2 |
1 |
1.82 (0.243) |
||
3 |
2 |
1.20 (0.243 |
||
| Company * Period interaction | 1.92 |
0.1054 |
- Results of full two-way analysis of variance (ANOVA) model including company and period effects. p < 0.01 considered statistically significant.
- Results of Tukey’s Studentised Range Test for post-hoc differences (Type I Experimental Error Rate = .01).
Figure 7.5a Frequency distribution - Travel time (hours) between ports per tour per period - Company A
Figure 7.5b Frequency distribution - Travel time (hours) between ports per tour per period - Company B
7.4 Travel Time To and From Ships per Work Assignment
One of the unique features of pilotage work in the Great Barrier Reef - Torres Strait region is the duration of travel to and from boarding grounds. Launch trips can take up to 3 hours in duration, while some helicopter flight times involve around 2 hours of travel.
Figure 7.6 depicts average travel time to and from ships per assignment for each company across the three 6 month periods, while Table 7.3 presents a summary of the analysis of company and period differences in this data. Post hoc testing revealed the source of the significant inter-company difference in travel. Pilots from Company B engaged in more hours of travel per work assignment (2.9 hours), compared with pilots from Companies A (2.2 hours) and C (2.2 hours), which were similar. This result is consistent with the greater amounts of travel (Table 7.1 and Table 7.2) and greater number of work assignments (Table 5.0) previously reported for Company B pilots.
Several possible factors could contribute to the longer hours of travel per work assignment recorded by pilots from Company B. Firstly, it is possible that personnel from Companies A and C may more frequently board vessels when they are docked at ports and in this way avoid travelling out to boarding grounds. Secondly, differences between companies in the mode of transport used to reach particular boarding grounds could substantially influence travel time. For example, if Company A used helicopters where Company B used launch vessels, travel time for the former group would be substantially shorter. Thirdly, Company B personnel may perform a greater number of work assignments which begin or end at more distant boarding grounds in the Torres Strait and North East Channel regions than pilots from Companies A and C.
In terms of changes in travel time to and from work assignments over the three by 6 month periods, no significant differences were found (Table 7.3). This result was observed for each of the pilot companies.
Figure 7.6 Mean travel time (hours) to and from ship per work assignment by company and period (1 Jan 1996 - 30 June 1997)
Note: Data analysis based on n values shown in Methods (Section 3.2).
Table 7.3 Mean total travel time (hours) to and from ships, per work assignment (1 Jan 1996 - 30 June 1997) (1)
|
Effect |
Post hoc results (2) |
Mean (sem) |
F Statistics |
p-value |
|---|---|---|---|---|
| Company (main effect) | 444.32 |
0.001 |
||
A |
1 |
2.18 (0.0.19) |
||
B |
2 |
2.91 (0.017) |
||
C |
1 |
2.19 (0.203) |
||
| Period (main effect) | 1.24 |
0.2889 |
||
1 |
n/a |
2.42 (0.192) |
||
2 |
n/a |
2.41 (0.053) |
||
3 |
n/a |
2.443 (0.047) |
||
| Company * Period interaction | 3.66 |
0.005 |
- Results of full two-way analysis of variance (ANOVA) model including company and period effects. p < 0.01 considered statistically significant.
- Results of Tukey’s Studentised Range Test for post-hoc differences (Type I Experimental Error Rate = .01) n/a Post hoc testing not performed when main effect not significant.
7.5 Percent of Breaks between Assignments spent Travelling (to and from ships and between ports)
Figure 7.7 reveals the percent of breaks between ships spent travelling for each 6-month period for each company separately. Table 7.4 summarises the analysis of this data in terms of between company and time period differences. A greater percentage of Company B’s breaks between work assignments were spent travelling (9.2%), followed by Company A (7.0%) and then Company C (4.4%). These results are consistent with the findings reported previously (Sections 7.1, 7.2 and 7.3).
On average, pilots from Companies A and B spend just under 10% of their breaks between work assignments travelling. Hence, if a pilot had 24 hours between time of disembarkation to time of next embarkation, it could be estimated that around 2 hours of travel would be engaged in. While this does not sound like a substantial amount, travel tends to be fragmented throughout the rest period. This in turn limits the pilot’s opportunity for continuous rest and/or sleep and diminishes the recuperative value of the recovery period. Hence it is the fragmented nature of travel, rather than the actual volume of travel which most likely has the greatest impact on the pilot’s recovery.
There were no significant differences in the percent of breaks between work assignments spent travelling across the 18 month analysis period. It is therefore apparent that the increased amounts of travel engaged in by pilots during the second 6 month period were negated by the increased work availability in this period. The same temporal pattern was observed in each of the pilotage companies.
Figure 7.7 Mean percent of breaks between work assignments spent travelling per Company per period
Note: Data analysis based on n values shown in Methods (Section 3.2).
Table 7.4 Analysis of the percent of breaks between work assignments spent travelling (1 Jan 1996 - 30 June 1997) (1)
|
Effect |
Post hoc results (2) |
Mean (sem) |
F Statistics |
p-value |
|---|---|---|---|---|
| Company (main effect) | 4.68 |
0.009 |
||
A |
1 |
7.04 (0.800) |
||
B |
1 |
9.23 (0.212) |
||
C |
1 |
4.42 (0.652) |
||
| Period (main effect) | 1.05 |
0.348 |
||
1 |
n/a |
7.47 (0.181) |
||
2 |
n/a |
8.29 (0.165) |
||
3 |
n/a |
8.76 (1.068) |
||
| Company * Period interaction | 0.79 |
0.499 |
- Results of full two-way analysis of variance (ANOVA) model including company and period effects.
- Results of Tukey’s Studentised Range Test for post-hoc differences (Type I Experimental Error Rate = .01) n/a Post hoc testing not performed main effect not significant.
7.6 Summary
The description of travel indicates a significant provider effect with pilots from Company B experiencing greater amounts of travel to and from ships, between ports and from all sources. It was also noted that a greater percentage of Company B’s breaks between assignments was spent travelling. These findings are consistent with the greater time spent on tours, greater number of work assignments and shorter rest breaks reported for this pilotage group. That Company B personnel experienced significantly longer hours of travel to and from ships per work assignment suggests that company differences exist in either the mode of transport used to reach boarding grounds or the number of assignments performed which begin or end at more distant boarding grounds.
While on average, less than 10% of break times were spent travelling, that travel is probably fragmented throughout the recovery period most likely creates the greatest impact on the pilot’s recovery. The fragmented nature of the travel causes rest and sleep to be discontinuous, thereby reducing the recuperative value of breaks.
With regards to changes across time, travel hours to and from ships per tour and between work assignments per tour significantly increased during the busy second 6 month period. However, no variations across time were found in the relative amount of break time spent travelling. Thus it would appear that the increased travel reported for the second time period directly related to the increased work availability during this period.
SECTION 8
Overall Summary
Recent marine investigations have shown an increase in the number of fatigue related incidents. Given the environmental sensitivity of the Great Barrier Reef pilotage region, the Australian Maritime Safety Authority initiated a study to investigate the fatigue aspects of the work practices of Great Barrier Reef pilots. Three pilotage companies representing 60 pilots work in this region.
The initial step in identifying the fatigue aspects of the work practices involved analysing retrospective work schedule files for an 18 month period (January 1, 1996 to June 30, 1997). The files were based on 4310 work assignments performed during 902 tours of duty. Essentially, the analysis developed a description of ship and non-ship time of Great Barrier Reef pilots and highlighted the characteristics of tours of duty, work assignments, shipping routes and work-related travel.
Tours of duty involve pilots undertaking one or more work assignments and alternating between living at sea and ashore while on tour. In general, pilots spent around 18 days on a tour and had 10 to 20 days at home between tours. Approximately 50 percent of tour time was spent undertaking work assignments (ship time).
Work assignments represent a continuous period of time when pilots are on board ships. There were significant company differences on several measures. For example, Company B performed 31% more work overall, and 51% more work on the Inner Route than Company A. For all three pilotage companies, approximately 50% of work assignment time was at night. Starting times of work assignments and breaks for all three companies were fairly evenly distributed across all 4 hour time periods within the 24 hour cycle. This finding highlights the irregularity of marine pilotage work.
Characteristics of the three main shipping routes serviced by Great Barrier Reef marine pilots also have the potential to impact on fatigue status. For example, Inner Route assignments were significantly longer and involved a higher percentage of night work than the other two routes, while assignments on the Great North East Channel involved significantly greater amounts of travel.
A unique feature of Great Barrier Reef pilotage is the extensive amount of work-related travel incurred, particularly to and from ships. After inclusion of travel in the work schedule analysis, it was shown that work assignment duration and percentage of night work significantly increased, while breaks between assignments decreased.
The work schedules findings identified a significant number of instances when considerably greater workloads and shorter breaks were experienced by pilots. While these instances were not commonplace, the heightened fatigue potential and increased risk of accident associated with such work conditions makes these findings of concern, particularly in view of the competition in pilotage operations in this region.
Based only on ship time and non-ship time, the analysis showed a high presence in the work schedules of potential fatigue indicators. These included the irregularity of work and rest breaks, the percentage of ship time performed at night and work and sleep displacement from the normal circadian cycle. There were also a number of situations in which workloads considerably greater than that shown in group data was found. Additionally in many situations, the duration of breaks between assignments was unlikely to accommodate complete recovery from the fragmented sleep patterns experienced by pilots while at sea.