1. Problem
recognition, definition and evaluation
In order to meet national energy needs and supply
chain of fuel in archipelago country, vessels with good performance is totally needed.
One of performance components that contained in vessels KPI is called “Slow
Speed Compliance” which is measure by comparison between actual speed and
agreed speed. However in day to day operation, slow speed could happen to any
type of ships. It’s important to figure out the main cause of slow speed.
Problem
statement: What is the main cause of slow speed?
2. Development
of the feasible alternatives
There are some conditions that make vessels
have slow speed, as follows:
·
Bad weather condition (examples: rough sea, strong
wind & current)
·
Poor condition of main engine which is the main propulsive
force of ship.
·
Lag of operations (examples: ignore or wrong procedure
& human errors)
·
Route selection
·
Ship design errors
3. Development
of the outcomes
To find the main cause of problem, we need
to collect all related data from vessel report and shore report. Various reports
that we use are:
·
Ship Performance Report (SPR):
Performance report that contain of all KPI
component of Ship such as: speed, pumping rate, transport loss, and bunker
consumption which reported every voyage or call for each vessels.
·
Noon report (daily vessels report)
·
Shore base claims
Report of every performance that not suitable or not
complied with agreement.
Recapitulation of
the data shown in the table below:
No
|
Causes of Problem
|
Frequency
|
Frequency Cumulative
|
Percentage
|
Percentage Cumulative
|
1
|
Bad weather
|
17
|
17
|
34.0%
|
34.0%
|
2
|
Poor Main Engine
performance
|
16
|
33
|
32.0%
|
66.0%
|
3
|
Lag of operations
|
10
|
43
|
20.0%
|
86.0%
|
4
|
Route selection
|
6
|
49
|
12.0%
|
98.0%
|
5
|
Ship Design errors
|
1
|
50
|
2.0%
|
100.0%
|
TOTAL
|
48
|
100%
|
Figure
1. Data collection (source: author)
4. Analysis and comparison of the
alternatives
We apply cause of the problem into Pareto Chart below with cause of problem in x axis and number of frequency in y axis.
We apply cause of the problem into Pareto Chart below with cause of problem in x axis and number of frequency in y axis.
5. Selection of the preferred alternative
Base on Figure 2 - Pareto Chart, show the highest frequency that cause
slow speed is bad weather with 17 point. But, Bad Weather is comes from natural
phenomenon that means it is totally out of our control, so we will focus on the
second option shown in Pareto Chart which is the poor main engine performance
(16 Point).
6. Performance
Monitoring & Post Evaluation of Result
We can conclude that poor main engine
performance is the main cause of slow speed in vessels. After we understand the
main cause, the next blog posting will be talk about how to solve or improve
M/E performance.
Reference:
i.
Brassard, M. & Ritter, D. (2010). The Memory
Jogger 2: Tools for Continuous Improvement and Effective Planning, pp. 122-135.
ii. Pareto Chart template, retrieved from:
iii. Implementasi Strategi Perkapalan Team (2010). Kamus
Perkapalan Pertamina.
Excellent topic, Pak Daniel!!! Nice work. You chose a case study for your blog posting that is exactly what I am looking for you to do.
ReplyDeleteYou followed our Step by Step process almost perfectly (You missed step 4, Selection of the Criteria)and you provided 3 citations as required, although the last one is not in APA format, as we don't know what pages you referenced. (Memory Jogger 2 was done correctly)
For future postings, I would urge you to look at Engineering Economy, Chapter 6, Comparing between Alternatives; Chapter 11, Breakeven and Sensitivity Analysis and Chapter 14, Multi Attribute Decision Making. I am confident you will find some tools and techniques in those chapters which you can apply to this same case study, getting credit for not only the blog posting, but also problems. Work smart, not hard...
Keep up the good work, but challenge yourself to explore using OTHER tools and techniques besides just Pareto.
BR,
Dr. PDG, Jakarta