The Effect of Ship Docking Variable Configuration on Ferry Docking Time

Ma. Arisandi () and A. A. B. Dinariyana
Additional contact information
Ma. Arisandi: Institut Teknologi Sepuluh Nopember, Interdiciplinary School of Management and Technology (SIMT)
A. A. B. Dinariyana: Institut Teknologi Sepuluh Nopember, Interdiciplinary School of Management and Technology (SIMT)

A chapter in Proceedings of the 3rd International Conference on Business and Engineering Management (IConBEM 2022), 2023, pp 117-136 from Springer

Abstract: Abstract One of the strategy models in maintaining the financial performance company that operates Ferry Ro-Ro is through increasing revenue and optimizing company expenses by creating cost efficiency. Maintenance cost especially ship docking cost is the second-largest company expense because to meet with regulatory requirements for all passenger ships such as Ferry Ro- Ro must be conducting docking work every year. Efficiency docking costs can be conducted by decreasing ship docking time thus decreasing ship docking cost and also could increase ship availability days to deliver operational excellence and maintain customer service levels. Optimizing ship docking time could be conducted by analyzing variable influence to ship docking time. The goal of this study is to discover factor characteristics that influence work time of docking work for ships by considering management perspective through questionnaires from Indonesia’s largest Ferry Ro-Ro company. Management assessment also aims to conduct weighting of variables then analyzed with Analytic Network Process (ANP) methods using Superdecision software. The result shows five priority variables that influence on docking time of Ferry Ro-Ro such as the age of the ship variable, the ship length variable, the steelwork variable, the work of engine variable, the propulsion work variable based on management perspective. Furthermore, the priority variables used to build variable configurations variation models by combining one variable with another variable until formed 25 configuration variable variation models. The variable configuration variation model was tested using sample data from 72 Ferry Ro-Ro ships owned by PT. ASDP Indonesia Ferry (Persero) with linear regression and multiple linear methods using Minitab software that aims to get the combination of variables that most affect on docking time of Ferry Ro-Ro ships. The analysis result shows that Ship Docking Variable Configuration (SDVC) models with configurations consisting such as the age of the ship variable, the ship length variable, the steelwork variable, the work of engine variable, the propulsion work variable have become the most influential configuration variables on ship docking time with a level of significance of 71,30%. The outcomes of the configuration variable identification could become management consideration for implementing planned maintenance management which aims to reduce the amount of work that must be done at the time of ship docking by optimizing docking work before ship conducting docking without affecting the ship’s operating day especially on steelwork, overhaul work & propeller work for a ship that has old age and has long dimension. Planned maintenance implementation, especially on steelwork, engine overhaul work, propeller work on older ships with large dimensions can make the company create plan material and labor needs at an optimal cost and also make long term relationships with suppliers thus could increase management opportunities to achieve economies of scale in the ship maintenance supply chain process. This result is also expected can enrich the literature on ship docking management and contribute to Ferry Ro-Ro company to minimize potential delays in docking time then could increase ship operating days thus increasing the company revenue and corporate performance.

Keywords: Ship Docking Time; Ship Docking Variable Configuration; Analytic Network Process; Linear Regression; Multiple Linear Regression (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-216-3_10

Ordering information: This item can be ordered from
http://www.springer.com/9789464632163

DOI: 10.2991/978-94-6463-216-3_10

Access Statistics for this chapter

More chapters in Advances in Economics, Business and Management Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().