Use Case of Quay Crane Container Handling Operations Monitoring

using ICT to Detect Abnormalities in Operator Actions

Sergej Jakovlev

1,2 a

, Tomas Eglynas

, Mindaugas Jusis

1,3 c

, Saulius Gudas

, Valdas Jankunas

and Miroslav Voznak

Klaipeda University, Bijunu str. 17 – 206, Klaipeda, Lithuania

VŠB-Technical University of Ostrava, 17, Listopadu 15, 708 33, Ostrava-Poruba, Czech Republic

Vilnius University, Akademijos str. 4, LT-04812 Vilnius, Lithuania

Keywords: Data Acquisition, Communication Technology, Engineering, Systems Design.

Abstract: This paper presents the initial research findings from the Klaipeda port monitoring action related to Blue

economy development initiative in the Baltic Sea. Use case study demonstrates the possibility to address the

problem of information system deployment in harsh industrial environment to gather valuable statistical

knowledge. Custom made monitoring and data transmission units were developed to utilize the best practice

of engineering to solve real problems of Klaipeda Port. Several key operations and parameters were monitored

during the research, including containers spreader movements, physical characteristics of the cables, metal

constructions. Initial results suggested that crane operators’ involvement in the control of the cargo movement

produced incorrect control patterns (joystick movements) that delayed port operations. Each control

movement of the joystick needs to have a direct real-time feedback from the spreader (actual movement of

the cargo). Feedback control functionality will allow adjusting the spreader movement according to the

operator and will decrease the cargo transportation time during constant breaks.

1 INTRODUCTION

Klaipeda Sea Port has distinguished itself in the

Baltic Region due to its rapid increase in cargo flows

and adoption of Blue Economy regulations and

strategies, that require decrease of CO2 and other

harmful gasses in industry surrounding the Sea Port

and related to Port activities (including shipbuilding,

bulk cargo transit, fossil fuel transship, fishing and

production).

Many practioners’ and action methodology

developers in the transport chain did research in this

area. Ranging from communication and control

systems application with deep insights and relevant

reviews, economical calculations and practical use

cases (Tuan et al., 2018; Golovin and Palis, 2019;

Henikl et al., 2012; Sha et al., 2017). Overall,

possibility to adopt new technologies in such closed

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environments is a rare opportunity. In practice, the

realization of complex control solutions limited by

the cost efficiency in comparison to standardized and

commonly used solutions (Jakovlev et al., 2012;

Andziulis et al., 2012).

Adoption of new ideas is difficult even to

“modern minds” (Eglynas et al., 2013). In practice, it

is difficult to come close to working equipment and

to acquire agreement for their monitoring on-site.

Initial visual analysis suggested developing new ideas

how to lower fluctuations of the containers gripper.

Its movements are random in nature, due to external

impacts, such as wind or physical contact with other

objects. It is difficult to predict such random

deviations in practice (Golovin and Palis, 2019;

Trabke, 2014).

In comparison, European ports such as Rotterdam

or Hanover apply new systems for vibration decrease

Jakovlev, S., Eglynas, T., Jusis, M., Gudas, S., Jankunas, V. and Voznak, M.

Use Case of Quay Crane Container Handling Operations Monitoring using ICT to Detect Abnormalities in Operator Actions.

DOI: 10.5220/0008880700630067

In Proceedings of the 6th International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS 2020), pages 63-67

ISBN: 978-989-758-419-0

in the cables during lowering procedures. Dampening

control systems decrease unnecessary strains arising

during accelerated movement of containers by

synchronizing operators’ actions with the total

lowering process engines and control units. Artificial

Intelligence (AI) systems with stochastic algorithms

for efficient learning and fast adoption to unlikely

events used in scenarios with high risks (Tuan et al.,

2012). Control and coordination of operator movement

is a task for unconventional systems, mainly used to

solve competence shortage problems in engineering,

medicine and explorations environments (Jakovlev et

al., 2011; Jakovlev et al., 2013).

Today, most Baltic Sea Region Ports handled

automated systems, but only on the surface. Context

procedures and IT operations automated in most

“brutal” fashion. Equipment is bought, but not relied

upon to solve critical tasks. That is why inclusion of

the quay crane even in modern ports is still

innovation-theoretical. In reality, the crane operator

has to wait for the Automated Guided Vehicle (AGV)

or the AGV has to wait for the operator to finish his

unloading routine, even when the most modern

control systems are used.

Depending on the actual position of the AGV or

the crane, decisions made systematically to slow

down the speed of movement so that the target point

reached at the same time by all involved bodies. This

saves both energy resources and technical resources,

and increases crane and consequently, the entire port

efficiency.

2 DESCRIPTION OF THE

MONITORING EQUIPMENT

In the experimental research DL1 - MK2 data

logger/analyzer was used to acquire and transfer

statistical data. It uses three-axis accelerometer.

Dynamical characteristics examined, including

acceleration, speed and position. GPS antenna used to

increase the accuracy. Movement speed detection

accuracy set to 0.16 km/h due to technological

reasons and data logging accuracy set to 1% due to

irregularities in the electronics.

Figure 1 demonstrates the used equipment. In

addition, horizontal and vertical acceleration sensors

have standard industry set accuracy level of 0.05 m/s

with maximum detection acceleration set to 20 m/s

Higher speeds and accelerations are statistically

unlikely due to technological and structural reasons.

Mounting point was set on the spreader, shown in

Figure 2.

Figure 1: Demonstration of the secured case with DL-1

MK2 Data logger, GPS antenna and additional connector

for output connections.

Figure 2: Demonstration of the Data Acquisition sensory

hardware placement on the crane spreader.

This position chosen as a more reliable and safe

due to constant movements and obstructions,

unnecessary hits in all areas. Battery life was not an

essential part of the equipment. Its full capacity

lifetime was enough to function on a regular basis for

the entire period of experimentation (8 000 mAh).

DL1 – MK2 data logger chosen because it allows

all the data to be referenced to not just time, but also

to a position during 3D movement. This allows the

data to be interpreted in a strict understandable way,

referenced clearly to the actual position and time

stamp. Braking points and gripper usage was

analysed with the built in 3-axis accelerometer

enhanced for high downforce applications. It is

VEHITS 2020 - 6th International Conference on Vehicle Technology and Intelligent Transport Systems

capable of detecting minute changes with 100Hz

update rate on all attached sensors and accelerometer

channels. It also provides an 8 analogue channels

(with 0-20 V battery voltage) for sensor inputs ready

for additional measurements and 2 CAN channels

with up to 1 M baud rate with 14 CAN filters per

channel (CAN 2.0 compatible). Logger itself has an

IP50 environmental protection, but due to the harsh

working environment, it was decided to add

additional protection via the secured hard plastic

mounting case. Maximum power consumption set to

1.6 W.

3 EXPERIMENTAL

MEASUREMENT RESULTS

Number of container loading and unloading

measurements set to 278, due to port operations strict

rules and cooperation agreements for the

measurement period. Crane operators were warned

that measurements took place during their working

hours to avoid legal problems. During the meeting

with the working crane operators and truck drivers

(who are also AGV operators), discussions were

made to address the importance of these

measurements and to see the vector of improvement.

Some of the crane operators even expressed

appreciation for the research. The following Figures

provide casual measurements from the loading and

unloading procedures.

Each measurement had its own deviation and

irregularity, considering the operator “best choice”

scenario set by the operational manual. Figure 3

demonstrates the positional movement of the

container unloading procedure. Each container varied

in mass, therefore, average mass of 20 metric tons

considered for the mean calculations. At this exact

measurement, the mass of the container measured at

19.220 kg.

Figure 3 and the following Figures 4-5

demonstrate 7 stages of operational consideration:

 1. Container raising with hooking;

 2. Vertical raising of container;

 3. Bias raising of container;

 4. Horizontal transportation of container;

 5. Bias lowering of the container;

 6. Vertical lowering of the container;

 7. Container placement on the transport means

(truck or AGV).

The following Figure 4 demonstrates the actual

speed values during these 7 stages for the process,

described in Figure 3.

The following Figure 5 demonstrates spreader and

container sway oscillation values. These values are of

high importance, because higher values correlate with

the actual speed of the operation during the 7

stage,

by lowering the speed of container positioning on the

transport means or AGV.

Figure 3: Spreader position detection and movement points during the container unloading operation from the ship.

Use Case of Quay Crane Container Handling Operations Monitoring using ICT to Detect Abnormalities in Operator Actions

Figure 4: Demonstration of spreader speed actual values during the 7 stages of operation.

Figure 5: Demonstration of spreader and container sway oscillation during the 7 stages of operation.

The overall transportation process is then

prolonged in order to compensate the sway and keep

up with the work standard for safety of cargo and

security of operation. These operations are mostly

synchronized with the on-site AGV operators and

working standards to keep up with the ship unloading

procedure. Yet, due to technological reasons, delays

occur on a daily basis.

4 RESULTS AND DISCUSSION

Initial results suggest that during the operator did not

maintain the same speed during the horizontal

transfer of the container. Operator made sudden

joystick control movements to stop the transportation

process for a short period. Figure 4 demonstrates the

ladder shape of the speed values, which correlates

with the initial suggestion. This is due to operator

mistake, lack of experience and unsynchronized

actions between AGV or truck and the crane. Each

ladder produces additional oscillation, which is kept

up to the final 7

stage.

Operational standard regulates the maximum

speed of the spreader movement. Due to these factors,

each container transported with an average of 8.1

seconds delay for the 278 measurements and the

average speed of operation calculated as 40.4

VEHITS 2020 - 6th International Conference on Vehicle Technology and Intelligent Transport Systems

seconds. This indicates that the working efficiency of

the operation is only 80%. Each crane is capable of

delivering much more container if the operator

movement controlled by AI system with pre-defined

algorithms for optimal movement of containers with

different masses and environmental conditions.

5 CONCLUSIONS

Authors indicate the importance of these researches

in terms of the new Blue Economy regulations for

Ports CO2 decrease (Kavakeb et al., 2013).

Autonomous and electrical AGVs and trucks are now

in operation in several ports of the world, and their

synchronization with the operational standards is still

a real “headache” for engineers and operators on-site.

That is why these problems need to be addressed and

real operational statistical data collected.

The containers handling operational actions of the

Klaipeda port were analysed in detail. Use case study

proved possible to deploy and use information system

in harsh conditions to gather valuable statistical

knowledge.

Custom monitoring and data transmission units

were developed to detect the problem areas of the

Klaipeda Port. Containers spreader movements,

physical characteristics of the cables, metal

constructions and crane operators’ involvement were

monitored.

It was detected that each operator made control

mistakes when handling cargo, which in return

delayed overall port operations.

DECLARATION OF

CONFLICTING INTERESTS

The authors declared no potential conflicts of interest

with respect to the research, authorship, and/or

publication of this article.

ACKNOWLEDGEMENTS

This research is/was funded by the European

Regional Development Fund according to the

supported activity ‘Research Projects Implemented

by World-class Researcher Groups’ under Measure

No. 01.2.2-LMT-K-718-01-0081.

Authors would also like to express deep gratitude

for the insights and help to project members: A.

Andziulis, R. Didziokas, J. Januteniene, E.

Guseinoviene, M. Bogdevicius, D. Cirtautas, A.

Senulis, M. Kurmis, D. Drungilas, Z. Lukosius.

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Use Case of Quay Crane Container Handling Operations Monitoring using ICT to Detect Abnormalities in Operator Actions