MODEL BIAYA PEMELIHARAAN FASILITAS PADA BANDAR UDARA NGURAH RAI BALI

1970 ◽  
Author(s):  
Reni Dewita ◽  
I G. A. Adnyana Putera ◽  
I G. Putu Suparsa
Keyword(s):  
Linear Regression ◽  
Cost Model ◽  
Regression Equation ◽  
Maintenance Cost ◽  
Quality Level ◽  
Road Maintenance ◽  
Linear Regression Equation ◽  
Maintenance Costs ◽  
Facility Maintenance ◽  
The Cost

Facilities in an airport requires maintenance activity in order to achieve excellent quality level and able to support activities at the airport to avoid negative impacts, which is the declining quality of the facility that can lead to lower levels of the productivity carried out in an airport. Maintenance facilities at Bali's Ngurah Rai airport need the maintenance costs planning. To get proper maintenance actions,  the maintenance costs early stages of planning phase needs to develop a model of facility maintenance costs that can provide the maintenance costs estimates quickly and accurately. To produce a maintenance costs model we should identify the maintenance activities that exist at Ngurah Rai airport. Maintenance costs data used is within the last 5 years (2007-2011). Using the Cost Significant Model methode and the linear regression equation it showed that several of the facility maintenace significantly affect the facility maintenance costs in the Ngurah Rai Airport which is the cost of passenger terminal building maintenance (X6), the cost of runway maintenance (X1), the cost of taxiway maintenance (X2), the cost of air conditioning installation maintenance (X14), the cost of road maintenance (X4), the cost of vehicle parking maintenance (X5), and the cost of navigation and communication equipment maintenance (X10). There is 3  linear regression equation model which is 1) Y = 11873745878,77 + 0,993 X1 + 0,826 X2 + 0,334 X4 + 1,181 X6, 2) Y = -698840481,94 + 1,327 X1 + 1,716 X2 + 5,516 X5+ 3,060 X14, and 3) Y = 82110363478,07 + 1,013 X1 - 17,223X5 + 22,406 X10 - 12,035 X14. After doing the Cost Model Factor (CMF) test to the three linear regression equation, the most accurate equation is linear regression equation Y = 82110363478,07 + 1,013 X1 - 17,223X5 + 22,406 X10 - 12,035 X14 that has the average ratio 0.006% of the actual cost, so it is the best facility maintenance cost model at Bali's Ngurah Rai Airport.

Assessing Maintenance Cost for Design or Re-Design of Complex Machinery

2002 ◽  
Author(s):  
Alley Butler ◽  
Dan Baldwin ◽  
Mohit Kashyap
Keyword(s):  
Cost Model ◽  
Open Architecture ◽  
Maintenance Cost ◽  
Preventative Maintenance ◽  
Maintenance Costs ◽  
Time Value Of Money ◽  
Turbine Generators ◽  
System Data ◽  
The Cost

Maintenance costs are often significant for complex machinery, and organizations that are able to accurately assess maintenance costs for complex machinery can design or re-design the machinery to reduce maintenance expenses. This paper provides a review of relevant reliability theory to provide a background for model construction. The maintenance cost model is then developed from a probabilistic perspective, with a hierarchical breakdown of the complex machinery, and with consideration of the time value of money. A framework for the cost model is offered in which the cost of repair and preventative maintenance is considered along with the downtime costs for repair or preventative maintenance. As a proof of concept, maintenance costs for Ship Service Gas Turbine Generators (SSGTG) are developed from the Navy’s OARS (Open Architecture Retrieval System) data. Problems with data quality and heuristic adjustment of the data are discussed, recognizing that work is ongoing to improve the quality of the Navy’s maintenance data. Cognition Corporation’s Cost Advantage software is used for the modeling effort, providing an ability to focus on maintenance cost at any level of detail and to obtain cost roll up, as needed. Conclusions are drawn with respect to the modeling of maintenance costs for complex machinery.

scholarly journals Mass Rapid Transit Operation and Maintenance Cost Calculation Model

2020 ◽  
Vol 2020 ◽  
pp. 1-6
Author(s):  
Rahmat Nurcahyo ◽  
F. Farizal ◽  
Bimo M. I. Arifianto ◽  
Muhammad Habiburrahman
Keyword(s):  
Cost Model ◽  
Calculation Model ◽  
Maintenance Cost ◽  
Cost Calculation ◽  
Rapid Transit ◽  
Maintenance Costs ◽  
Operation And Maintenance ◽  
Transit Operation ◽  
The Cost ◽  
Mass Rapid Transit

Mass rapid transit (MRT) is an efficient transportation mode that is urgently needed by a growing city such as Jakarta, Indonesia. However, limited research has attempted to evaluate the system’s current performance through a comprehensive, unit-based calculation of the costs of MRT operation and maintenance. This research aimed to develop a system for calculating and comparing MRT operation and maintenance costs per kilometer per year. The cost model has three components, namely, capital, operation cost, and maintenance cost, which are, respectively, calculated based on their percentage toward total cost. The cost model calculation determined that Jakarta MRT operation and maintenance costs total USD 8.44 million per kilometer per year. This result was compared to other countries’ MRT operations.

scholarly journals Relationship between Cognitive Style and Habits of Mind

2019 ◽  
Vol 2 (1) ◽  
pp. 23
Author(s):  
Hayatun Nufus ◽  
Rezi Ariawan
Keyword(s):  
Linear Regression ◽  
Cognitive Style ◽  
Significance Test ◽  
Regression Equation ◽  
Coefficient Of Determination ◽  
Habits Of Mind ◽  
Linear Regression Equation ◽  
Research Subjects ◽  
Analysis Technique ◽  
The Relationship

This research is a correlational study that examines the relationship between cognitive style and habits of mind. The research subjects involved 4th semester students in the Department of Mathematics Education at the Faculty of Tarbiyah and Teacher Training of UIN Suska Riau which consisted of students with heterogeneous academic abilities. Cognitive style data was collected using the GEFT question instrument with test techniques. Habits of mind data were collected using a questionnaire instrument with a questionnaire distribution technique. The data analysis technique begins with the Pearson Product Moment correlation test which is continued with the significance test and the calculation of the magnitude of the relationship that occurs using the coefficient of determination. Because the data is positively correlated, it continues with determining the linear regression equation. The results showed that there was a significant weak correlation between cognitive style and habits of mind with a relationship score of 6% and a linear regression equation y '= 36.35 + 0.31 x.

Coronal Suture Pathology and Synostotic Progression in Rabbits with Congenital Craniosynostosis

1996 ◽  
Vol 33 (5) ◽  
pp. 369-378 ◽  
Author(s):  
Mark P. Mooney ◽  
Timothy D. Smith ◽  
Annie M. Burrows ◽  
Herbert L. Langdon ◽  
Cynthia E. Stone ◽  
...  
Keyword(s):  
Linear Regression ◽  
Inbred Strain ◽  
Rabbit Model ◽  
Regression Equation ◽  
Histologic Examination ◽  
Coronal Suture ◽  
Linear Regression Equation ◽  
Cross Sectional ◽  
High Tension ◽  
Single Focus

The purpose of the present study was to describe coronal suture pathology and cross sectional synostotic progression in an inbred strain of rabbits with congenital craniosynostosis. Calvaria from 102 perinatal rabbits (39 unaffected; 63 bilateral or unilateral synostosis) were collected at fetal days 21 (n = 12), 25 (n = 20), 27 (n = 22), 30 (term) (n = 32), and 3 days post-term (n = 16) for gross morphologic and histologic examination. Synostotic foci, the extent of relative bony bridging, and suture morphology were evaluated qualitatively and quantitatively. Of the 204 coronal sutures examined, 91 sutures were synostosed, and 113 were patent. All synostosed sutures showed similar foci by day 25, which originated as bony bridges in the middle of each suture on the ectocortic surface. Bony bridging width increased significantly (p < .001) from day 25 through 3 days post-term, and was best described by a linear regression equation. Osteogenic front areas of synostosed sutures were up to 2.5 times greater than patent sutures in term fetuses. Findings demonstrate that coronal suture synostosis in the congenital rabbit model (1) begins early during suture morphogenesis (before 25 days of gestation); (2) consistently radiates from a single focus corresponding to a normal interdigitating region (i.e., a high-tension environment); (3) varies in onset and rate as evidenced by low R2 value between age and extent of bony bridging; and (4) is the result of early hyperostosis of the osteogenic fronts and sutural agenesis. A number of possible pathogenetic mechanisms are discussed.

Preliminary Study on Prediction Model of Forming Tubular Bulge Height for a Thick-Plate

2011 ◽  
Vol 314-316 ◽  
pp. 763-766
Author(s):  
Dan Liu ◽  
Xiao Ting Xiao ◽  
Yi Juan Liao ◽  
Zheng Rong Zhang
Keyword(s):  
Linear Regression ◽  
Prediction Model ◽  
Sheet Metal ◽  
Process Parameters ◽  
Thick Plate ◽  
Regression Equation ◽  
Linear Regression Equation ◽  
Forward Extrusion ◽  
Inner Diameter ◽  
Bulge Height

To form the thick-plate with the tubular bulge, the backward and forward extrusion and punch process is proposed. The thickness of sheet metal, the inner diameter of tubular bulge, the diameter of punch-die, the forward extrusion depth and other process parameters are set by orthogonal regression design method and these groups of values are used respectively to simulate the combined extruding and punching process by the plastic analysis software DEFORM3D. And then, the linear regression equation is obtained between the bulge height and process parameters. The results indicate that the main factors affecting the bulge height are the thickness of sheet metal and diameter of punch-die within a certain range. However, the inner diameter of tubular bulge and the forward extrusion depth have a little contribute to bulge height. Also, the reliability of linear regression equation is not fine and the prediction model of tubular bulge needs to a more in-depth study.

Incisor growth in twins during the seventh and eighth months of foetal life

1963 ◽  
Vol 12 (3) ◽  
pp. 238-246 ◽  
Author(s):  
Maurice V. Stack
Keyword(s):  
Linear Regression ◽  
Regression Equation ◽  
Linear Regression Equation ◽  
Central Incisor ◽  
Dental Tissue ◽  
Lower Upper ◽  
Incisor Growth ◽  
Foetal Life ◽  
Similar Development

SUMMARYWeights of mineralized dental tissue have been determined in incisors dissected from ten pairs of twins failing to survive beyond 7-8 months' gestation. Logarithms of weights were compared as ratios (lower/upper) with data from foetuses of similar development. Intra-twin differences were thus shown to be significantly less than inter-twin differences when comparing central incisors. Lateral incisors were too variable to allow this demonstration. The linear regression equation combining logarithms of lower and upper central incisor weights was suitable for estimating foetal age to within one week of the recorded age.

Experiment of Artificial Floating Island Displacement Pile Fixation

2012 ◽  
Vol 220-223 ◽  
pp. 1670-1674
Author(s):  
Fang Li Su ◽  
Sheng Yu Shi ◽  
Hai Fu Li ◽  
Tie Liang Wang
Keyword(s):  
Experimental Data ◽  
Linear Regression ◽  
Flow Rate ◽  
Vertical Direction ◽  
Regression Equation ◽  
Maximum Force ◽  
Linear Regression Equation ◽  
Floating Island ◽  
The Impact

For providing refer to the experimental data of artificial floating island in river north, this study will get stability characteristics of artificial floating islands displacement pile fixation on simulating the impact of different flow rate of water. Analysising physical stress of artificial floating island displacement pile fixation and simulation, result shows that the sum of floating island of buoyancy and the maximum force of two fiber rope in the vertical direction should be greater than the maximum gravity of the floating island plants and ensure the maximum force of the two fiber rope in the horizontal direction must be greater than the flow momentum, the quality of floating island can be increased for improving stability. Depend on the different flow of water and linear regression equation, the distance between the floating island should be arranged reasonably.

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