- Problem Definition
BOR or Berth Occupancy Rate is one of key element to be used for any port investment assessment. Using BOR information, the Designer then able for designing the wharf size required for vessels berthing. Indeed, the composition of each port BOR depend on logistic planning for cargo and for our port the most important cargo will be sulphur pallets deliver in containers. For W18 blog i will exercise sulphur BOR using crystal ball software.
- Identify the Feasible Alternative
Initial simulation BOR from our logistic team indicated BOR result of 22.19% for sulphur cargo as part of total BOR. Logistic team currenctly looking for interval range with 90% probabilistic level of input BOR.
- Development of the Outcome for Alternative
In my understanding, for calculating BOR there are two keys parameters: a. Number of working days per year and b. Un-loading cargo time. Vessel size, crane capacity, abnormal time…etc are parts of data that i have to look for calculating BOR. Based on discussion with our logistic team, as present in Figure 2 the relevant informations for calculating BOR:
Figure 2 Logistic Team Information for Calculating BOR
Logistic team is planning to use 54.500 DWT vessel with 14 calls per year for sulphur cargo from overseas. This plan also include 5000 HP tug boat with 5 knots towing speed to port. Required time for berthing and un-berthing varies between 4 to 11 days for total 14 calls but this is not the most significant time. The most significant time will be un-loading time with abnormal time due to wave or rain time distubance which are varies between 60 to 70 days for total 14 calls. For total working days per year, logistic team estimated between 300 to 340 days per year.
- Selection Criteria
Logistic team is expecting some checking with their assumption that also include solution for 90% probabilistic level.
- Analysis and Comparison of the Alternative
Using Crystal Ball  &  software with triangular distribution mode for above given data, the result provides some answers as follows:
Figure 3 Probabilistic Level for Initial Simulation 22.19%
Figure 3 BOR Range for Probabilistic Level 90%
Figure 4 Sensitivity Chart
Figure 3, 4 and 5 show that initial simulation 22.19% BOR by logistic team connected with 43% probabilistic level. The range for 90% is most likely from 20 to 25% BOR. Sensitivity chart shows the most positive influence part of BOR is total un-loading cargo time [43% + 22% = 65%] compare to working days per year as negative infuence time [35%].
Logistic team should consider the main element influence for BOR: a. Un-loading time and b. Working days. They have to find the optimum time for BOR for the economic investment for our port. For instance, if we go for 25% BOR, then by reducing un-loading time instead 64 days but 60 days to produce total 71 days [with 7 days berthing and un-berthing time] they can go for 268 working days per year instead 320 days year.
- Selection of the Preferred Alternative
Considering that sulphur cargo is the most important cargo for processing plant then I recommend to use 20-25% BOR.
- Performance Monitoring and the Post Evaluation of Result
As previously stated the main part will be un-loading time. It would good also to consider add.investment of grab mobile crane [with bucket] to reduce un-loading time with benefit and cost analysis. I will let logistic team to do the advance exercise for their report to the Management.
WBN. (2013). Port Project Data. Jakarta, Indonesia.
BAM Decorient. (2002). Risk Analysis Training Material. Jakarta, Indonesia.
Oracle.com. (2013). Risk Analysis Overview. Retrieved from: http://www.oracle.com/us/products/applications/crystalball/risk-analysis-overview-404902.pdf