Ocean going vessels
Fluctuation of the number of accidents
by damaged facility

Cases

450

12.5%

400

11.3%

11.4%

324

328

12

Accident Rate

10.3%

342

350

11

10.0%
9.4%

9.2%

10.2%

10.2%

10
9

283

300

%
13

257
250

246

232

230

8

239

7
6

200

5
150

4

209

100

196

180

3

160

132

132

122

50
0

2008 PY

2009 PY

2010 PY

2011 PY

2012 PY

FenderFacility and structure located on quay

Quay

Graph 41

Ocean going vessels

2013 PY

2

2014 PY

76

69

2015 PY

2016 PY

OthersBuoy

10

Fishery facility

Fluctuation of the number of accidents (by damaged facility)

Unit of insurance money: JPY one million

2008 PY 2009 PY 2010 PY 2011 PY 2012 PY 2013 PY 2014 PY 2015 PY 2016 PY

Total

%

Quay

209

180

196

160

132

132

122

76

69

1,276

51%

Facility and structure located on quay

17

25

20

15

22

20

18

59

76

272

11%

Fender

53

61

60

63

50

45

48

65

52

497

20%

Buoy

20

19

23

23

16

12

17

18

12

160

6%

Others

2

2

1

3

2

1

1

0

0

12

1%

Fishery facility

41

37

28

19

35

20

26

28

30

264

11%
100%

342

324

328

283

257

230

232

246

239

2,481

Number of entered vessels at the
beginning of the policy year

2,745

2,866

2,880

2,757

2,576

2,500

2,475

2,406

2,333

23,538

Accident rate (Number of accidents divided
by number of entered vessels ×100%)

12.5

11.3

11.4

10.3

10.0

9.2

9.4

10.2

10.2

10.5

Total

Table 42

Ocean going vessels

Ocean going vessels
Damaged facility
Ratio of number ofaccidents by facility

Fishery facility 264
Others 12
Buoy160

Fluctuation of the number of accidents (by damaged facility)

11%

1%
6%

Unit: JPY one million

51%
Fender
497

20%

11%

Quay
1,276

Facility andstructure locatedon quay272

Graph 43 Ocean going vessels Damage facility Ratio of number of accidents (by facility)− 21 −

Similar to coastal vessels, regarding thenumber of accidents by damaged facility
in ocean going vessels including accidents
that occurred outside of Japan also, the sum
total of quay damaged accidents (51%) andstructure damage accidents including quay
facilities (11%) occupy more than half of thetotal number of accidents. However, fenderdamage accidents account for a large percentage (20%) which is different to that of coastal
vessels.

Regarding fender damage accidents, it includes fender accidents which occur as a result of wear and tear. It is notfair to include all of these causes with vessel miss-maneuvering. Especially, if the aged fender is damaged at a public
quay, then renewal by repair may be all that is needed. This kind of work is troublesome.
5,863

6000

Ocean going vessels,QVXUDQFHPRQH\ñXFWXDWLRQ
E\GDPDJHGIDFLOLW\

4,855

5000

8QLW-3<RQHPLOOLRQ

4000

3,572

3,632

3,418

3000
1,968

1,851

2000
1,424

1,222
1000

0

2008 PY

2009 PY

2010 PY

2011 PY

2012 PY
FenderFacility and structure located on quay

Quay

Graph 44

Ocean going vessels

2013 PY

2014 PY

2015 PY

2016 PY

OthersBuoy

Fishery facility

Insurance money ﬂ uctuation (by damaged facility)

2008 PY 2009 PY 2010 PY 2011 PY 2012 PY 2013 PY 2014 PY 2015 PY 2016 PY

Total

%

Quay

692

2,686

3,004

3,219

5,444

4,464

961

285

179

20,93475%

Facility and structure located on quay

95

114

70

98

92

35

132

1,045

1,160

2,840

10%

Fender

59

633

83

223

73

184

123

533

95

2,007

7%

Buoy

151

44

102

59

40

47

101

62

326

933

3%

Others

1

0

0

3

1

1

0

0

0

5

1%

Fishery facility

224

95

159

29

213

124

107

44

91

1,086

4%

Total

1,222

3,572

3,418

3,632

5,863

4,855

1,424

1,968

1,851

27,805

100%

%

4%

13%

12%

13%

21%

17%

5%

7%

7%

100%

Table 45 Ocean going vessel

Insurance money ﬂuctuation (by damaged facility)

Ocean going vessels
Insurance money ratio
By damaged facility

Fishery facility 1,086
Others5

Buoy 933

0% 4%
7%

Unit: JPY one million

Fender 2,007

10%

75%

Facility andstructure locatedon quay

Quay
20,9342,840

Graph 46

Graph 46

Ocean going vessels

Insurance money ratio (by damaged facility)− 22 −

§３−５ Statistics on the number of accidents by ship type

Coastal vessels By type of ship Accident rate
（Number of accidents ÷ number of entered vessels at the beginning of the policy year）
30%

25%

RO/RO・PCC
21.72%

20%

15%

Passenger ship
and ferry

10.11%

10%

General cargo ship
8.5%

Overall
5.33%

Tanker5%

2.95%

Tugboat
3.29%

Others
1.56%

0%2008 PY

2009 PY

2010 PY

2011 PY

2012 PY

2013 PY

2014 PY

2015 PY

2016 PY

Average overnine years

Graph 47 Coastal vessels
By type of ship
accident rate（Number of accidents ÷ number of entered vessels at the beginning of the policy year）

Looking closely at the accidents regarding harbour and fishery facilities of coastal vessels by ship type along withaccident rate, the following characteristics are found.
• The accident rate for all ship types over the last nine years is 5.33% and, as for simple average, one out of twenty
vessels caused an accident.
• However, ship types above this average value are Ro-Ro ships, passenger ships and general cargo ships. In
particular, the accident rate of Ro-Ro ships is four times that of the mean value.

− 23 −

Ocean Going vessels Accident rate (by type of ship)（Number of accidents ÷ number of entered vessels at the beginning of the policy year）
％
40

35

30

25

RO/RO・PCC
24.29%
Ferry andpassenger ship

12.94%

20

Generalcargo ship

12.12%Overall

15

10.54%

Tanker
9.79%

Container

10

8.90%

Bulker
8.06%

5

Others4.88%

02008 PY

2009 PY

2010 PY

2011 PY

2012 PY

2013 PY

2014 PY

2015 PY

2016 PY

Average overnine years

Graph 48 Ocean going vessels
By type of ship
accident rate（Number of accidents ÷ number of entered vessels at the beginning of the policy year）

On the other hand, the total accident rate for ocean going vessels is 10.54% over an average of nine years. The shiptypes above this average value are, similar to those of coastal vessels, Ro-Ro ships and PCCs, which are prominent at
2.3 times (24.29%) that of the mean value.
There is a trend that general cargo ships, ferries and passenger ships are higher than the average value, however, thedifference is not so dramatic when compared to coastal vessels.

− 24 −

＝ Reason as to why accident rates for PCCs and Ro-Ro ships are higher than other ship types ＝
The wind pressure area of PCCs and Ro-Ro ships
is larger than other ships of the same length (lengthof hull), which require maneuvering with caution.
Above all, they tend to be affected by the wind at
the time of leaving the wharf and docking.

R ＝ 1/2（LーPB）× sin1°
Ｌ
PB

Also, the ship’s hull construction is, as shown in
Fig. 49, the Parallel Body (PB: the part contacting
to quay) and it is short. And, if the mooring lines
at fore and aft station were not rolled up evenly,
the fore and aft parts may run aground on thequay (Over Hang) if the PB part loses balance
during docking at this point. Consequently, it cancause damage to the edge of the quay, mooring
bit, car stopper etc. According to the ship’s hullconstruction shown below in Fig. 49-2, we cansee that Over Hung (R) is approximately 1 m 38
cm. This was caused by shifting towards the quayby only one degree.

Ｒ
L＝ 210m PB＝ 52m
Fig. 49-1

R ＝ 1/2（LーPB）× sin1°≒1.3ｍ
Ｌ
PB

Ｒ
L＝ 210m PB＝ 52m
Fig. 49-2

In the event that this part isover hung on the quay,
this causes damage to the quayedge, car stopper, bit and hull.

Fig. 49-3§３−６ Statistics on the number of accidents by size of ship (G/T)
Accidents regarding harbour and fishery facilities of coastal vessels were compared according to the insurance
amount.
Because most entered coastal vessels are mainly less than 1,000 G/T, this size of ship occupies the largest number ofaccidents. Ideally, we should have carried out a more detailed evaluation, by comparing the accident rate that indicatesas to how many times each vessel entered and departed the port and how many damaged accidents were caused oneach occasion. Also, it is unfortunate that only the comparison of number of accidents and insurance money weremainly discussed in this section, and that there was a lack of data regarding numbers of those entering / leaving ports,
similar to “§3-2 Statistics on the number of accidents by accident occurrence area in Japan”− 25 −

Unit of insurance money : JPY one million
Amount band (insurance)

More than 3,000 tons but More than 1,000 tons More than 500 tons but
Less than 500 tons
More than 10,000 tons
less than 10,000 tons but less than 3,000 tons less than 1,000 tons

Total

Number ofaccidents

Insurancemoney

Number ofaccidents

Insurancemoney

Number ofaccidents

Insurancemoney

Number ofaccidents

Insurancemoney

Number ofaccidents

Insurancemoney

Number ofaccidents

Insurance
money

1

929

1

101

1

154

2

409

8

1,288

13

2,882

1

94

0

0

3

251

3

211

10

719

17

1,275

6

100

10

219

7

162

17

383

56

1,097

96

1,961

More than JPY ten million

8

1,123

11

320

11

568

22

1,003

74

3,104

126

6,118

% of total amount

1%

14%

1%

4%

1%

7%

2%

13%

6%

40%

10%

79%

4

28

13

102

7

46

8

59

50

344

82

580

16

45

48

108

35

85

53

128

202

459

354

825

Less than JPY one million

40

14

101

34

62

24

90

33

436

156

729

261

Less than JPY ten million

60

87

162

245

104

156

151

220

688

959

1,165

1,666

Ratio of total amount

3%

0%

8%

0%

5%

0%

7%

0%

34%

2%

56%

3%

Total

68

1,211

173

565

115

723

173

1,223

762

4,062

1,291

7,784

Ratio of total amount

6%

16%

13%

7%

9%

9%

13%

16%

59%

52%

100%

100%

More than JPY 100 million
but less than JPY one billion
More than JPY 50 million
but less than JPY 100 million
More than JPY ten million
but less than JPY 50 million

More than JPY five million
but less than JPY ten million
More than JPY one million
but less than JPY five million

Table 50

Coastal vessels

By band of insurance amount and G/T

Number of accidents and insurance money

Coastal vessels

Accident rate by G/T（Number of accidents ÷ Number of entered vessels at the beginning of the policy year）

%
30

25

20

More than 10,000 tons
13.99%

More than 3,000 tons but
less than 10,000 tons
8.89%

15

More than 500 tons but
less than 1,000 tons
10

6.76%

More than 1,000 tons but
less than 3,000 tons
5.88%

5

Overall
5.33%
Less than 500 tons

0

4.41%

2008 PY

2009 PY

2010 PY

2011 PY

2012 PY

Graph 51

2013 PY

Coastal vessels

2014 PY

2015 PY

over2016 PY Averagenine years

Accident rate by G/TWhen comparing this with accident rate and the number of entered vessels denominator at the beginning of the policy
year, coastal vessels of more than 10,000 G/T greatly fluctuated every Policy Year. And, we can understand that there
is a tendency for the accident rate to be higher than for ships less than 10,000 G/T over a nine year average.

− 26 −

Unit of insurance money : JPY one million
More than 30,000
tons but less than
50,000 tons

More than
50,000 tons

Amount band (insurance)

More than 10,000
tons but less than
30,000 tons

More than 5,000
tons but less than
10,000 tons

More than 1,000
tons but less than
5,000 tons

Less than
1,000 tons

TOTAL

Number of Insurance Number of Insurance Number of Insurance Number of Insurance Number of Insurance Number of Insurance Number ofaccidents
money
accidents
money
accidents
money
accidents
money
accidents
money
accidents
money
accidents

More than JPY one billion
More than JPY 100 million
but less than JPY one billion
More than JPY 50 million
but less than JPY 100 million
More than JPY ten million
but less than JPY 50 million

3

9,435

1

1,096

1

1,207

6

1,648

5

2,356

8

3,197

6

1,430

2

4

317

3

190

9

653

8

566

20

398

37

682

27

589

Insurancemoney

5

11,739

392

27

9,022

4

267

28

1,992

27

536

11

133

2,727

21

511

More than JPY ten million

34

11,911

29

4,040

55

5,738

41

2,585

33

1,196

1

11

193

25,481% of total amount

1%

43%

1%

15%

2%

21%

2%

9%

1%

4%

0%

0%

8%

92%

17

128

23

164

29

208

23

161

25

167

4

24

121

851

73

168

77

179

110

264

84

193

74

170

13

30

431

1,005

More than JPY five million
but less than JPY ten million
More than JPY one million
but less than JPY five million

1Less than JPY one million

365

85

364

95

495

136

303

88

189

57

20

7

1,736

468

Less than JPY ten million

455

382

464

439

634

607

410

442

288

394

37

61

2,288

2,324

% of total amount

18%

1%

19%

2%

26%

2%

17%

2%

12%

1%

1%

0%

92%

8%

Total

489

12,293

493

4,478

689

6,346

451

3,027

321

1,590

38

72

2,481

27,805% of total amount

20%

44%

20%

16%

28%

23%

18%

11%

13%

6%

1%

0%

100%

100%

Table 52

Ocean going vessels

Number of accidents and insurance money (by band of insurance amount and G/T)

Ocean going vessels Accident rate by G/T%
20

Fluctuation（Number of accidents ÷ Number of entered vessels at the beginning of the policy year）
More than 5,000 tons but
less than 10,000 tons
12.95%

15

More than 1,000 tons but
less than 5,000 tons
12.05%
More than 10,000 tons but
less than 30,000 tons
10.90%

10

Overall
10.54%
More than 50,000 tons
9.46%

More than 30,000 tons but
less than 50,000 tons
9.14%

5

Less than 1,000 tons
7.47%

0

2008 PY

2009 PY

2010 PY

2011 PY

2012 PY

2013 PY

2014 PY

2015 PY

over2016 PY Averagenine years

Graph 53 Graph 53 Ocean going vessels Accident rate by G/T Fluctuation（Number of accidents ÷ Number of entered vessels at the beginning of the policy year）

Meanwhile, on examining ocean going vessels, it was revealed that large accidents of more than JPY 10 million of
insurance money were concentrated on vessels of more than 10,000 G/T. Statistically, even if it makes contact with aquay at the same speed, a large ship will sustain huge damage.
On the other hand, regarding the accident rate of vessels that are more than 1,000 G/T but less than 10,000 G/T it isgreater because these vessels are larger than other large vessels. Though there is this kind of tendency, details into thecauses remain unknown.
− 27 −

§4

Accidents regarding harbour andﬁshery facilities Causes§ ４−１ Statistics on accident causes

Accident Cause
Classification

Equipment trouble

Human factor

Ocean goingvessels

Coastalvessels

Sum total%

Mooring winch trouble

11

5

16

1.2%

Onshore equipment trouble

16

16

1.2%

Cause

Other ship's equipment trouble

8

6

14

1.0%

Equipment trouble during cargo handling

12

1

13

0.9%

Main engine and generator trouble

9

3

12

0.9%

Hatch cover trouble

1

1

0.1%

Other equipment trouble

2

2

0.1%

Equipment trouble subtotal

59

15

74

5.3%

Miss-maneuvering by ship

394

459

853

61.4%

Miss-maneuvering by pilot

106

1

107

7.7%

Other human-induced mistakes

38

53

91

6.5%

Insufficient lookout

12

26

38

2.7%

Miss-maneuvering of tug boat

29

29

2.1%

Miss-maneuvering by other ships

25

25

1.8%

Mistake by workers on shore

29

29

2.1%

1

0.1%

1

0.1%

Falling asleep

Weather and sea
conditions

1

Lack of knowledge and information

1

Human factor subtotal

634

540

1,174

84.5%

Weather and sea conditions

98

44

142

10.2%

791

599

1,390

100.0%

Sum total
Table 54

Statistics on accident causes

Ratio by accident cause

Equipment trouble
Weather andsea conditions

74 Cases5％

142 Cases
10％

Total: 1,390 cases

Human factor

1,174 cases
85％

Graph 55

Ratio by accident cause− 28 −

We analysed 1,390 cases where the causes of the accidents could be investigated. Consequently, human factor causes(human error) came to 84% (1,174 cases) of the total number of cases. In the figure, miss-maneuvering by crew onboard (including Master) and the pilot occupies 69.1%.
Also, on analysing the accident report, 10% (142 cases) of the total number of accidents were caused by unforeseensquall and tidal streams. These are mainly caused by a lack of weather chart checking and weather information, and alack of thorough investigation concerning tidal stream information.
Because we are experienced crew and pilots, it is possible for us to be prepared if we are privy to such information,and can predict squalls with weather lore. Thus it follows that these accidents caused by weather and sea conditions
can also be regarded as human error.
Moreover, although equipment trouble (e.g. main engine stoppage and black out, etc.) induced accidents, these devices
are also maintained by humans. Thus, causes of damage to harbour and fishery facilities can be said to be 100% down
to human error.

Causes of damage to harbour and fishery facilities can be said

Human factor (Human error)

１００％
§ ４−２

Human Error Concept

Please refer to the details which were introduced in our Loss Prevention Bulletin Vol.35 “Thinking Safety”

Twelve human characteristics❶ Human beings sometimes make mistakes❷ Human beings are sometimes careless❸ Human beings sometimes forget❹ Human beings sometimes do not notice❺ Human beings have moments of inattention❻ Human beings are sometimes only able tosee or think about one thing at a time
Table 56

❼ Human beings are sometimes in a hurry❽ Human beings sometimes become emotional❾ Human beings sometimes make assumptions❿ Human beings are sometimes lazy
⓫ Human beings sometimes panic⓬ Human beings sometimes transgress when
no one is looking

Twelve human characteristics− 29 −

Human Characteristics : Information Processing in case of taking action

Human Characteristics

Past Experience

Result of Training

・ Information Processing
Large amount ofInformation obtained
from external Sources

Table 57

Evaluate which
information to use

Take Action

Human Characteristics : Information Processing in case of taking action

Table 56 shows the 12 Human characteristics which may cause human errors. Everyone has these characteristics.
Table 57 shows how people behave when they act.
In other words, human beings process a large amount of information using the five senses and take action dependingon what information they believe should be used. In addition, because taking new action requires additional new
information, the cycle repeats.
When considering how to use the information, you look back at the outcome of past experience and training. For
example, in the event of attempting to walk on a rough road, we are careful so as not to fall over. Why are wecautious? One reason is that this comes from our common experience of feeling pain when we fell over and grazed
our knees when we were children. And, our memory of pain is stored somewhere in the brain. Even when we havebecome adults, we recall that information of the rough road experience from memory automatically and a message istransmitted telling us to “please be careful”.
It is said that the brain automatically lets us deal with almost 80% of the humanbehaviours unconsciously. However, if there is an error in the memory source, thewrong signal will be transmitted. That is, unconscious errors are triggered, whichleads to accidents.
Also, regarding the remaining 20%, we think for a moment before taking action, or
think about it deeply prior to taking action. However, the fundamental is also thesame in this case, and errors that cause accidents are induced by wrong judgement,
if there were mistakes in past experience and memory. This root cause is shown in
the 12 Human characteristics indicated in Table 56.
Therefore, most accidents can be prevented by calmly recognizing the Human
characteristics that everyone has and measures can be taken to prevent the causes ofthe errors.

− 30 −

§ ４−３

BTM (Bridge Team Management)/ETM (Engine Room Team Management)

Approximately 90% of total
marine accidents are causedby human error

12 Human characteristics
which induce human error.

Selecting wrong information causedby one of or some of the 12 Human characteristics,

this can cause human error which
can cause an accident and trouble.

There are various causes for marine accidents, however, in the event of a collision accident, for example, it is said thatapproximately 80 to 90% of all accidents are caused by a mistake made by a person, in other words, “human error”(as mentioned above) such as “Insufficient Look-out”. In addition, even though the vessel collided into a harbour andfishery facilities, not another vessel, such an accident regarding harbour and fishery facilities is also classified as anaccident. The cause can be treated the same as other collision accidents, namely, that it was down to “human error”.
Most of these accidents were not caused by only one error, rather, the error was part of chain of other errors.
On the premise that “human beings are error-prone”, BTM and ETM were established with the purpose of “achieving
safe navigation” in order to further prevent human error chains and to bolster team ability at the bridge and in theengine room.
In other words, the utmost purpose of BTM and ETM is to eliminate “one-man error” through mutual support in orderto maintain safe operation of the ship together with the all members and resources in the bridge and engine room. And,
it aims “to achieve safe navigation” by improving team ability in the bridge and engine room as always.
This is shown in Table 58. The person at the centre (Liveware: person responsible for the accident) is surrounded by
the following four resources.

− 31 −

If there is a gap in the system,
an error will occur: Liveware
Livew
(You)
: Hardware
Hard: Software
Softw: Environment
EnviroError
M

M(People Around You)
: Liveware
Livew： Management（managing andd utilizing
tilii iＳＨＥＬＬ）BTM・ETM
Fig. 58①

M-SHELL Model

Liveware:(Persons other than the person responsible
for the accident.）②

S: Software.
Brieﬂy, this will be in the form of a book or document,such as the Maritime Collisions Prevention Act(COLREGs) or the Safety Management Manual.

Liveware（You）③

H: Hardware:
Equipment on the vessel.

④

E: Environment:
In this case, it is rather external information such asroute control, weather charts, weather informationand so on.

Fig. 59

Four resources.

− 32 −L (you), the person at the centre of model, is required to always communicate with these resources and to manage
them (management). Each initial in the model collectively form the acronym M-SHELL.
People around us communicate with each other via speaking and listening. They also communicate via other voicelessmeans such as books: Maritime Collisions Prevention Act (COLREGs) and the safety management manual.
Also, although the hardware (equipment) does not utter any words, it provides us with a variety of information.
Automatic Radar Plotting Aids (ARPA) display the Closest Point of Approach (CPA) of other vessels or Time to
the Closest Point of Approach (TCPA). The action of confirming this information can be said to be communicatingwith ARPA. Or, crew in the engine department, including the chief engineer, in the engine room confirm using
their five senses to check the sound, for vibration, temperature and pressure generated by the main engine to assess
as to whether or not fuel is burning at a normal state. This is also a form of communication: communication withequipment.
Moreover, Environment means external information. It can be regarded a communication when one is speaking andlistening via VHF or reading a weather chart.
In addition, because each resource including the position of oneself (L) is constantly changeable, it can be represented
as a fluctuating square. If cooperation between oneself (L) and each resource is not adequate, a gap between the
resources is created, human error enters and safety is compromised. Then a chain of errors causes an accident.
On the other hand, if communication and cooperation is satisfactory, there will be no gap to cause error because eachresource is connected. Thus, it can be said that safety has been established.
For instance, let’s suppose that the Master gave a wrong steering order to the Helmsman. At that moment, if the duty
officer confirms the possible mistake with the Master and the Master admits and corrects the steering order, the error“careless mistake” (wrong steering order) will no longer pose a problem there and then.
Unfortunately, if the duty officer who even felt question did not confirm this, the Helmsman, who specialises innavigating, would steer following the wrong steering order. The Master noticed this after the vessel had started turning
round, but it was too late. That is, a gap into which an error could enter was generated.

− 33 −

§5Case study

Through the following three cases, preventive measures will be postulated.

§５−１ Case ① Quay contact

Case ①

Quay contact

LOA: 108mGT: 4,740 G/T

Draft: Ｆ4.37m▶ Date and time of occurrence :Ａ4.80mOn an unspeciﬁed day of March 2011,
approximately 07:53 Japan time (JST)）

NE/3

07:47 2.9Kts▶ Accident site :At an unspeciﬁed port in Tokyo Bay

07:49 2.1Kts▶ Vessel particulars :4,440GT, Loa 108 ｍ General cargo ship
Fore draft 4.37 m Aft draft 4.80 m Loaded
Steel product with half-loaded

07:51 1.7Kts

07:53 1.7Kts（Collision）▶ Weather and sea conditions :Fine, NE wind, wind force 3, No inﬂuence
from tidal current, and good visibility▶ Crew members :Korean Master, chief engineer and othercrew were Indonesian (16 members on
board in total)

South Korean Master and Indonesian crew

Fig. 60− 34 −

§５−１−１ Chain of events leading up to the accident
Time

Movement

Who

06:55

Pilot embarks. Presents Pilot Card. Confirms ship's particulars and draft. Pilot remarks that
there is only one tug boat on port side alongside. There was no explanation regarding shipmanoeuvring instructions. On questioning the pilot following the accident, the pilot explained"We planned a manoeuvre to turn round in front of the berth and then set parallel condition
with the berth as close as possible. "Master and pilot

07:47

Speed 2.9 kts. D.Slow ah’d、 Leeway 3°Leeward direction. The straight-line distance from thebow to quay is 320 ｍ eters（3L which is approximately three times that of hull length (L).

Pilot

07:49

Speed 2.1 kts. Stop Eng.. While allowing the tug boat to push on her starboard quarter, Start
right turn. Linear distance is at 220 meters (approximately 2L) from bow to quay

Pilot

07:51

Speed 1.7 kts. Stop Eng.. Continues starboard turning round. Linear distance is at 120
meters (approximately 1L) from bow to quay

Pilot

07:52

Because the Master felt anxious Half Ast.Eng..is ordered.

Master

07:53

Keeps Speed at 1.7 kts. collision into quay

Master and pilot

Table 61 Chain of events leading up to the accident

Table 61 shows the chain of events leading up to the accident. The pilot let the tug boat report the distance from thebow to the quay, but did not explain this to the captain. On the other hand, the chief officer who was allocated at thebow had a duty to report the distance between the bow and the quay to the Master, but the Master did not relay this tothe pilot, and he continued to entrust navigation entirely to the pilot.
The Master, now feeling anxious, ordered astern with engine only one minute before the accident was to occur and thevessel, unable to take corrective action, collided into the quay at 1.7 kts.

§５−１−２ Judgement and cause analysis by Marine Accident Tribunal
Judgement and cause analysis by Marine Accident Tribunal is as follows.
Main text of judgement:

Operation suspension as pilot for a month

Cause:The pilot did not sufficiently confirm the approaching state between the
bow and quay and delayed in carrying out speed reduction arrangement. In
addition, he did not adequately confirm the speed, despite the fact that it waseasy for the tug boat to push stronger into the half-loaded vessel which led tothe situation of increasing Head way. Also, he over relied on the approachingcondition reported by the tug boat.

− 35 −

§５−１−３ Analysis according to Human characteristics
and Preventive Measures＝

Analysis＝

Accident causes were analysed along with §4-2 Human Error Concept and §4-3 BTM (Bridge Team Management)/
ETM (Engine Room Team Management).
Firstly, we dealt with the direct and indirect causes separately.

Direct cause

Miss-maneuvering by the pilot caused the following trouble. This is the same as the Marine Accident Tribunal
cause analysis.
▶ Insuﬃciently conﬁrmed approaching condition between the bow and quay.
▶ Did not reduce speed at a distance of 1L (approximately 100 meters) from the approaching quay.

Indirect cause

The cause was not only triggered by the pilot but by the Master also.

＝ Pilot ＝▶ Did not explain berthing plan to the Master▶ Used only the distance reported by the tug boat (Immediately before the collision, although the
distance from the tug boat was 60 meters, the chief oﬃcer reported it as being 35 meters.)＝ The Master ＝▶ Although the chief officer (Indonesian) who was allocated at the bow had a duty to report the
distance between the bow and the quay to the Master, the Master did not relay this to the pilot.
▶ He continued to entrust navigation entirely to the pilot.

In addition, we examined the “root cause” lurking behind the “direct cause” and “indirect cause” mentioned above
against the “Human characteristics” shown in Table 56 on page 29. We conclude that the error chain was broken
as a result of human error, when Human characteristics are applied. (Each number is applicable to that of Human
characteristics shown in Table 56)＝ Root cause ＝❿ Human beings are sometimes lazy (Master and Pilot)
After the pilot got on board, the Master continued to entrust navigation entirely to the pilot. Also, regardless of the factthat the chief officer, who was allocated at the bow had a duty to report the distance between the bow and the quay, theMaster did not relay this to the pilot. Immediately before the collision, the tug boat reported the distance at 60 meters to
the pilot, however, at the same time, the chief officer reported it as 35 meters. At this point in time, had they noticed that
there was a conflict between the two reports, and had the Master and the pilot communicated with one another, they
could have reconfirmed the correct distance to the quay.

− 36 −

❺ Human beings have moments of inattention （Master and pilot）
Finally, the Master ordered Astern engine, however, time did not permit this. On confirming Head way against the log and
GPS and deducing that the speed was excessive, the Master should have advised the pilot of this at that time.

❾ Human beings sometimes make assumptions (Master)
The Master assumed that the pilot would not miss-maneuver.

Summarizing these time sequences, chiefly, the root cause can be attributed to insufficient communication between
the crew on board (officer at the watch of the 3rd officer) and the pilot. We can deduce that BTM including the pilot
was not functional. In addition, the 3rd officer arranged at the bridge was expected to report the hull speed and theinformation relayed by the chief officer, who was allocated at the bow, to both the Master and the pilot, but was
negligent in doing this. Collapse of BTM caused this accident.

Lack of communication between crew onboard (including Master) and pilot

BTM is not functioning.
Generally, the tug boat and the pilot were communicating in the local language (Japanese in this case) usingtransceivers. In particular, because the Master and pilot stand alongside at the final stage of berthing maneuvering,
it is not possible to confirm visually the tug boat’s movement. Also, without an understanding of the local language,
it may be difficult to grasp what is going on between the pilot and the tug boat. Then, in the event that something
unpredictable occurs during the operation process that is different to what the Master intended, one of the humancharacteristics ⑪ Human beings sometimes panic may be triggered and this can induce human error.
Another reason may be that there is not enough time for the pilot to keep interpreting the tugboat’s instructions to the
Master. Therefore, as a precaution, it may be wise that the chief or 2nd officers, who are allocated at the bow, briefly
report when the tug boat changes movement. (A brief description such as “Started pushing (pulling) in the direction of
XX o’clock” is perfectly acceptable.)＝ Preventive measures ＝As described above, BTM collapse including the pilot can be considered a root cause. For this reason, both the Masterand the pilot should have fully recognised the importance of BTM, but again: ② Human beings are sometimes careless, ③ Human beings sometimes forget and ⑩ Human beings are sometimes lazy apply.
There should have been no problem with the ship maneuvering skills of the pilot and the Master. However, in light of
the Human characteristics mentioned above that can be the root cause, forgetfulness may suggest that re-training of
BTM in order to remember be one of the effective preventive measures taken.

− 37 −

Photograph 62 BTM training

Photograph 63 Ship handling and manoeuvring simulator§５−２ Case ② Oyster raft accident that sustained damage

Case ②Oyster raft accident thatsustained damage▶ Date and time of occurrence:
On an unspeciﬁed day of December 2015,
approximately 18:37 Japan time (JST)▶ Accident site:
Near Miyajima Seto, Eastern sea area of
Itsukushima, Inland sea▶ Vessel particulars:
2,988GTL × B × D = 118.03m × 16.60m × 11.99m
Pure Car Carrier (PCC) Fore draft 3.54m Aft draft
3.85m Loaded with 447 cars

▶ Port of departure:
Departed Uno Port, Okayama prefecture. Cleared out
Kurushima Strait at approximately 15:00.

▶ Port of destination:
Ujina Port, Hiroshima prefecture▶ Crew members:
A Japanese Master age 63, a 3rd marine oﬃcer(navigation) and crew were Japanese (10 members
on board in total)▶ Weather and sea conditions:
The weather was cloudy, WNW wind, wind force 5
and the tide was at the middle stage of ebb
At that time, gales and high wave advisory were
continuously being announced for Hatsukaichi cityand Edajima in Hiroshima.

＝ Arrangement in place when the accident occurred ＝▶ Bridge:▶ Stern:

Master operated the ship, Chief Engineer operated
the engine and the 3rd Oﬃcer steered

The Chief Oﬃcer, Boatswain and Able Seaman (3 intotal) were preparing for entering port.

− 38 −

Oyster rafts area

18:45

18:35

18:40
18:37

Itsukushima
Miyajima Seto

Onasabi Island

18:3

0

Wind from
W-NW
Windspeed５

18

:10

18:0

5

5

5

18:1

18:2

Turns round once

18:

20

for time adjustment.

Fig. 64

Aki Eno Shima light

18:44

Eno Island

Accident position

18:43

On an unspeciﬁed day of December 2015
18:42

light beacon
light beacon

18:35

light beacon
18

:36

18

Oyster rafts area

18:41

18:40

18:37

:34

18:3

3

light beacon

18:38

39

18:

light beacon

18:3

Onasabi Island

2

500

18:3

1

Fig. 65− 39 −