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Designing project schedule using crashing method to compress the fiber to the home project schedule
International Journal of Industrial Optimization ; 2(1):51-62, 2021.
Article in English | ProQuest Central | ID: covidwho-1818754
ABSTRACT
ABC Company is an agent of network construction, operation, and maintenance. ABC Company is currently implementing the STTF (Shit to the Front) project, which is the project to add FTTH (Fiber to the Home) networks in areas that can have high customer demand. One of the STTF project construction sites is the Indra Prahasta II housing location. However, the project is currently experiencing work delays due to the Covid-19 disaster in Indonesia. Delays in project execution can result in potential prospects choosing another company that provides similar services. The project schedule can be accelerated using the crashing method and TCTO (Time Cost Trade-Off) analysis to solve this problem. This research's acceleration will be carried out with alternatives for adding 3 hours, 2 hours, 1 hour, and an alternative to increasing workers' number. This project has an average duration of 55 working days with a total cost of Rp 604,124,460. The results obtained from data processing, on the alternative of adding 1 hour of overtime work, the total duration becomes 54 working days with total project cost is Rp 605,734,138. In addition to 2 hours of overtime work, the project's total duration can be reduced to 54 days with a total project cost Rp 606,803,619. And for the addition of 3 hours overtime, the total duration can be shortened to 54 days with a total cost of Rp 606,803,619. As for increasing the number of workers, project work duration can be shortened to 54 working days with a total project cost Rp 604,556,748.
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Full text: Available Collection: Databases of international organizations Database: ProQuest Central Language: English Journal: International Journal of Industrial Optimization Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: ProQuest Central Language: English Journal: International Journal of Industrial Optimization Year: 2021 Document Type: Article