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# JNB250 Chartering And Broking

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• Course Code: JNB250
• University: University Of Tasmania
• Country: Australia

## Question:

Estimation of shipping emissions using vessel Long Range Identification and Tracking data.

Development of Ship Allocation Models using Marine Logistics Data and its Application to Bulk Carrier Demand Forecasting and Basic Planning Support.

Estimating probabilities of arrival times for voyages.

Multidisciplinary Approach to Design and Analysis of Arctic Marine Transport Systems.

### Comparison and Justification for the choice of best Voyage charter

The overall recommendation for the widest emission has been made by consideration of the best combination of required expenses and Break-Even freight rate required to perform this voyage. Therefore, it is analysed from both options which rate is computed as less based on the given factors. As per the given background the overall for Task a it can be inferred that MV Kuntah is seen as a handy -sized bulk carrier owned by Max Shipping company. The details of the vessel show that in option one the wide charter can carry scrap metal from UK to Malaysia and in option two it can carry the same material from South Africa to Italy. Based on the details of task a we have been able to calculate that it will take 18 days to reach the cargo from Felixstowe to Port Klang. On the other hand, it will take a delivery time of 70 days for the same delivery at Port Cape Town and redelivery at port Genoa (Arifin et al. 2018).

The computation of sailing days for Task a can be inferred as 96 days. Additionally, the bunker and full cost have shown that the total sailing cost of bunker is seen to be \$ 6822335. Furthermore, the in-Port consumption cost has been computed as \$ 7068290.3. As per the some of the other details can be seen that the total distribution charges at port is computed as 4300 and further inclusion of the expense commission, the total expense can be clearly depicted as \$72,62,345 for the entire voyage (Tarovik et al. 2017). The consideration of Break-Even freight rate required to perform this voyage is identified by dividing the total expense by total tonnes of scrap metal in bulk (Duru, Mileski and Gunes 2017). This computation is identified as Break-Even freight rate required to perform this voyage with the cost of \$ 345.8 per metric ton. However, in the second part in case of option one the voyage charterer of has agreed to pay freight rate equal to the breakeven rate calculated as per the fixture details in Task a plus an additional 7% (Lu et al. 2015).

In case of the second option the time charter is further willing to hire MV Kuntah at a rate of USD \$ 7500 per day for a total duration of 70 days. This will significantly increase the port distribution charges. Therefore, despite of similar computations for the sailing days required and bunker cost there will be a surge in the overall discharge cost at the destination port. This computation can be clearly seen as increase in the port distribution charges from \$ 4300 to \$ 11800 (Otsuka et al. 2016). As it is stated that pay freight rate equal to the breakeven rate calculated as per the fixture details in Task a plus an additional 7%, this amount has further increased the Break-Even freight rate required to perform this voyage. A clear comparison of the overall expense in the previous option shows that the total operating expense of the voyage was \$72,62,345 which was significantly increased to \$72,70,183. At the same time, Break Even freight rate required to perform the first voyage was 345.8 PMT with significantly increased to \$370.4 PMT (Da Costa Simões, Caixeta-Filho and Palekar 2018). This consideration has led to the overall increment in the cost of the company. Therefore, MV Kuntah needs to employ more expenses in case the voyage charter is willing to pay freight rate equal to the breakeven rate calculated as per fixture details in Task a. In addition to this, in case of option to the time charterer is seen to be willing hiring of MV Kuntah at USD 7500 per day which is also increasing the overall discharge cost at the port (Duru, Mileski and Gunes 2017).

In order to optimise the cost associated with the final voyage MV Kuntah it needs to consider the factors which were provided in the initial setting. This will enable the charterer in accomplishing the best output in tonnes and at the same time keep the cost to the minimum level possible (Alessandrini et al. 2017). Furthermore, it needs to be seen that the total amount of commission is present in both options. Therefore, this is not fulfilling the objective of reducing the overall expenses which would have been made it favourable to opt for the second scenario. Therefore, it can be stated that it would be a wise decision to proceed with the voyage fixture as per including the network port from Felixstowe/Port Klang, Cape Town/Genoa, Load Port (Felixstowe) and Discharge Port (Genoa) (Back 2017).

## References

Alessandrini, A., Guizzardi, D., Janssens-Maenhout, G., Pisoni, E., Trombetti, M. and Vespe, M., 2017. Estimation of shipping emissions using vessel Long Range Identification and Tracking data. Journal of Maps, 13(2), pp.946-954.

Arifin, M.D., Hamada, K., Hirata, N., Ihara, K. and Koide, Y., 2018. Development of Ship Allocation Models using Marine Logistics Data and its Application to Bulk Carrier Demand Forecasting and Basic Planning Support. Journal of the Japan Society of Naval Architects and Ocean Engineers, 27, pp.139-148.

Back, P.M., 2017. Virtual fuel flow estimation in shipping: how to formulate and validate a model for time-dependent momentary fuel flow estimation by combining high-frequency GPS and meteorological data with low-frequency noon reports-a case study.

Chen, H., Ballou, P.J., Deng, L. and Elkin, J.D., Boeing Co, 2015. Estimating probabilities of arrival times for voyages. U.S. Patent 9,109,895.

Da Costa Simões, D., Caixeta-Filho, J.V. and Palekar, U.S., 2018. Fertilizer distribution flows and logistic costs in Brazil: changes and benefits arising from investments in port terminals. International Food and Agribusiness Management Review, 21(3), pp.407-422.

Duru, O., Mileski, J.P. and Gunes, E., 2017. Performance obligations for “revenue from contracts with customers” principle in the shipping industry. Maritime Business Review, 2(3), pp.211-223.

Duru, O., Mileski, J.P. and Gunes, E., 2017. Performance obligations for “revenue from contracts with customers” principle in the shipping industry. Maritime Business Review, 2(3), pp.211-223.

Lu, R., Turan, O., Boulougouris, E., Banks, C. and Incecik, A., 2015. A semi-empirical ship operational performance prediction model for voyage optimization towards energy efficient shipping. Ocean Engineering, 110, pp.18-28.

Mallidis, I., Iakovou, E., Dekker, R. and Vlachos, D., 2018. The impact of slow steaming on the carriers’ and shippers’ costs: The case of a global logistics network. Transportation Research Part E: Logistics and Transportation Review, 111, pp.18-39.

Otsuka, N., Imai, K., Nagakawa, K. and Furuichi, M., 2016, February. Northern Sea Route transport scenarios for various cargoes. In The 31th International Symposium on Okhotsk Sea & Sea Ice. Mombetsu Japan.

Tarovik, O.V., Topaj, A., Bakharev, A.A., Kosorotov, A.V., Krestyantsev, A.B. and Kondratenko, A.A., 2017, June. Multidisciplinary Approach to Design and Analysis of Arctic Marine Transport Systems. In ASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering (pp. V008T07A005-V008T07A005). American Society of Mechanical Engineers.

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[Accessed 26 May 2020].

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My Assignment Help. Chartering And Broking [Internet]. My Assignment Help. 2020 [cited 26 May 2020]. Available from: https://myassignmenthelp.com/free-samples/jnb250-chartering-and-broking.

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