Repair Project Acceleration Strategy of Three Ship Units using Fuzzy Logic Analysis and Critical Path Method

Hidayatus Ubyani, Tuswan Tuswan, Hartono Yudo, Haris Nubli, Ocid Mursid, Muhammad Iqbal

Abstract

The project planning process, especially in ship repair projects, is essential to improving project completion. Ineffective planning of ship repair projects results in a lack of time and labour efficiency. Therefore, using project acceleration tools in scheduling ship repair activities is crucial to accelerate project completion and mitigate risk analysis of delays for each project activity. This research uses the critical path method (CPM) to analyze the main schedule of three combined ship repair projects. Then, shop-level planning is used to determine the productivity of each workshop so that each workshop knows the volume of work that needs to be completed daily. Furthermore, fuzzy logic is applied to analyze the risk of delays in repair project activities. The addition of working hours to critical work activities is accelerated from 30 days, the normal duration, to 23 days. Meanwhile, the addition of the workforce to critical work activities is accelerated from 30 days, the normal duration, to 22 days. The analysis of productivity values in each workshop results in the following productivity values: sandblasting and painting workshop 309.97 m2/person-days, piping workshop 4.12 units/person-days, fabrication workshop 407.16 kg/person-days, outfitting workshop 14.8 units/person-days, tank cleaning workshop 114.36 m3/person-days, and machining workshop 2.7 units/person-days. The fuzzy logic analysis results to determine the risk of delays in critical activities show that jobs with the codes SP1, SP2, SP3, SP4, M2, and SP5 have a high risk of delay. Additionally, the collaboration with other departments in the company, such as the marketing, finance, and human resources departments, is ongoing to complete assigned tasks.

Full Text:

PDF

References

1. H. Kerzner, Project Management: A System Approach to Planning, Scheduling, and Controlling, 12th ed. New Jersey: John Wiley and Sons, Inc., 2017.

2. I. Soeharto, Project Management from Conceptual to Operational, 2nd ed. Jakarta: Pernerbit Erlangga, 1999 (In Indonesian).

3. J. B. Yang, “How the critical chain scheduling method is working for construction,” Cost Eng, vol. 49, no. 4, pp. 25-32, 2007.

4. S. M. Fahimifard and A. A. Kehkha, “Application of Project Scheduling in Agriculture (Case Study : Grape Garden Stabilization),” Am. J. Agric. Environ. Sci., vol. 5, no. 3, pp. 313-321, 2009.

5. B. Pollack-Johnson and M. J. Liberatore, “Project management software usage patterns and suggested research directions for future development,” Proj Manag J, vol. 29, no. 2, pp. 19-28, 1998.

6. L. R. Foulds and J. M. Wilson, “Scheduling operations for the harvesting of renewable resources,” J Food Eng, vol. 70, no. 3, pp. 281-292, 2005.

7. A. Awani, Project management techniques. Petrocelli Books, 1983.

8. F. S. Hillier and G. J. Lieberman, Chapter 22: project management with PERT/CPM. Introduction to operations research, 8th ed. Boston: McGraw-Hill, 2005.

9. W. Duncan, Guide to the project management body of knowledge. Pennsylvania USA: Project management institute standard committee, 2000.

10. T. L. Fox and J. W. Spence, “Tools of the trade: a survey of project management tools,” Proj Manag J, vol. 29, no. 3, pp. 20-27, 1998.

11. P. Smith, Agricultural project management: monitoring and control of implementation. Springer Science and Business Media, 2012.

12. M. Zargar, Project control. Tehran, Iran: Parham, 2004.

13. H. Abdallah, H. M. Emara, H. T. Dorrah, and A. Bahgat, “Using Ant Colony Optimization algorithm for solving project management problems,” Expert Syst. Appl., vol. 36, no. 6, pp. 10004-10015, 2009.

14. S. Zareei, “Project scheduling for constructing biogas plant using critical path method.,” Renew. Sustain. Energy Rev., vol. 81, pp. 756-759, 2018.

15. S. Badri, Basics of Network Planning. Yogyakarta: Rineka Cipta, 2001 (In Indonesian).

16. T. J. Ross, Fuzzy Logic with Engineering Applications: Third Edition. USA: University of New Mexico, 2010.

17. W. Hadikurniawati, E. Winarno, A. B. Prabowo, and D. Abdullah, “Implementation of Tahani Fuzzy Logic Method for Selection of Optimal Tourism Site,” J. Phys. Conf. Ser., vol. 1361, no. 1, 2019.

18. W. D. Argiyan, I. P. Mulyatno, and S. Jokosisworo, “Shop Level Planning Analysis using the Critical Path Method in TB Repairs. Tanjung Buyut I-206 and TB. Arek Suroboyo-3,” J. Tek. Perkapalan, vol. 10, no. 4, pp. 62-70, 2022 (In Indonesian).

19. R. Taufiq, “Design and Development of a Decision Support System for Determining Production Quantities Using the Fuzzy Tsukamoto Method,” J. Tek., vol. 8, no. 1, pp. 6-10, 2019 (In Indonesian).

20. J. P. Lewis, Project Planning, Scheduling and Control, 5th ed. New York: The McGraw Hill, 2011.

21. M. Abimanyuaji, Analysis on Scheduling Acceleration for Construction Project Using Time-Cost Trade-Off Method. Thesis: Universitas Islam Indonesia, 2021 (In Indonesian).

22. F. Fachrurrazi and S. Husin, “Practical crash duration estimation for project schedule activities,” J. King Saud Univ. - Eng. Sci., vol. 33, no. 1, pp. 1-14, 2021.

23. A. Muharani, I. P. Mulyatno, and S. J. Sisworo, “Optimizing the Acceleration of Navigation Class I Ship Building Projects Using the Time Cost Trade Off Analysis Approach Method,” J. Tek. Perkapalan, vol. 8, no. 3, pp. 330-338, 2020 (In Indonesian).

24. D. Hooda and V. Raich, Fuzzy Logic Models and Fuzzy Control- An Itroduction. UK: Alpha Science, 2017.

25. B. Suprapty, R. Malani, and O. D. Nurhayati, “Design of Information System for Acceptance Selection of Prospective Employees Online Using Tahani Fuzzy Logic Method and Simple Additive Weighting (SAW ),” Int. J. Comput. Informatics., vol 1, no 1, pp. 17-28, 2016.

26. A. Setiawan, B. Yanto, and K. Yasdomi, Fuzzy Logic With Matlab. Jayapangus Press Books, 2018 (In Indonesian).

DOI: https://doi.org/10.20961/mekanika.v22i2.76502

Refbacks

  • There are currently no refbacks.