scholarly journals Prediction of maintenance cost for road construction equipment: a case study

2016 ◽  
Vol 43 (5) ◽  
pp. 480-492 ◽  
Author(s):  
Sharif Mohammad Bayzid ◽  
Yasser Mohamed ◽  
Maria Al-Hussein
Keyword(s):  
Data Mining ◽  
Model Development ◽  
Road Construction ◽  
Study Data ◽  
Construction Equipment ◽  
Maintenance Cost ◽  
Cost Models ◽  
Construction Operations ◽  
Development Data

Equipment maintenance cost is significant in construction operations budgets. This study proposes a systematic approach to predict maintenance cost of road construction equipment. First, maintenance cost data over more than 10 years was collected from a partner company’s equipment management information system. Data was cleaned and analyzed to obtain a general understanding of maintenance costs trends. Next, traditional cumulative cost models and alternative data mining models were generated to predict maintenance cost based on available equipment and operation attributes. Data mining models were evaluated and validated using portions of the collected data that have not been used in model development. Data collection, analyses, modeling, and validation steps are discussed. The paper also presents the performance of different model types. Based on the case study data, regression model trees performed better than other model types with equipment work hours being the most significant parameter for predicting maintenance cost.

scholarly journals Uncertainty estimation in railway track life-cycle cost: a case study from Swedish National Rail Administration

2008 ◽  
Vol 223 (3) ◽  
pp. 285-293 ◽  
Author(s):  
A P Patra ◽  
P Söderholm ◽  
U Kumar
Keyword(s):  
Life Cycle ◽  
Life Cycle Cost ◽  
Cost Effective ◽  
Railway Track ◽  
Statistical Characteristics ◽  
Maintenance Cost ◽  
Cost Models ◽  
Effective Decision ◽  
Effective Decision Support

Life-cycle cost (LCC) is used as a cost-effective decision support for maintenance of railway track infrastructure. However, a fair degree of uncertainty associated with the estimation of LCC is due to the statistical characteristics of reliability and maintainability parameters. This paper presents a methodology for estimation of uncertainty linked with LCC, by a combination of design of experiment and Monte Carlo simulation. The proposed methodology is illustrated by a case study of Banverket (Swedish National Rail Administration). The paper also includes developed maintenance cost models for track.

scholarly journals Road Construction Equipment Management: A Case Study on Selected Industry

2016 ◽  
Vol 3 (1) ◽  
pp. 91-97
Author(s):  
Samson Mekbib Atnaw ◽  
Lakhveer Singh ◽  
Ftwi Yohaness Hagos ◽  
Abu Yousuf
Keyword(s):  
Electric Power ◽  
Road Construction ◽  
High Growth ◽  
Careful Consideration ◽  
Management Policy ◽  
Construction Equipment ◽  
Equipment Management ◽  
Hydro Power ◽  
The Government

The major share of capital and equipment intensive operation goes to the road sector and the hydro – electric power projects. The construction sector in Ethiopia is developing at a fast rate and its capital budget is increasing from year to year. One of the reasons for this high growth is the number of new construction projects underway and those in the pipeline. In addition, the hydro-electric power projects the government has given a great emphasis to increase the current installed power of 780Mw to a total of 10,000Mw in the coming few years. These hydro-power projects are known for using a great deal of high investment heavy machineries. Therefore, the construction equipment management plays a great role in finalizing the projects with fewer budgets and no time over run. Considering the higher operation, maintenance and investment cost of construction equipment, it is important to have a carefully optimized decision making model that will help in the sizing and selection of the right combination of equipment for a given project. Even the rental versus purchase evaluation needs careful consideration of the project requirement and its duration. This study tries to analyze the existing situation taking a selected company as a case study with regard to construction equipment management. The study tries to cover the equipment management policy of the company, suppliers/manufacturers evaluation and selection criteria, types of purchase processes employed, as well as different make types and capacities of equipment owned by the company. Moreover, capacities of standard facilities available for the central maintenance workshop and replacement plan of equipment of the company in the coming five years will be investigated and commented on.

Modelling the degradation of micropollutants in wastewater: parameter estimation and application to pilot (laboratory-scale) MBR data in the case of 2,6-NDSA and BTSA

2009 ◽  
Vol 59 (1) ◽  
pp. 149-157 ◽  
Author(s):  
M. Schönerklee ◽  
M. Peev ◽  
H. De Wever ◽  
T. Reemtsma ◽  
S. Weiss
Keyword(s):  
Parameter Estimation ◽  
Model Development ◽  
Experimental Parameter ◽  
Study Data ◽  
Laboratory Scale ◽  
Biokinetic Model ◽  
Definition Of ◽  
Operational Data ◽  
Case Study Data

The paper summarises the definition of an extended biokinetic model dedicated to micropollutant degradation in wastewater treatment and the parameter estimation methodology for this model. Additionally it describes results on experimental parameter estimation for two target micropollutants, naphthalene disulfonate (2,6-NDSA) and benzothiazole sulfonic acid (BTSA). Subsequently the parameterised model is applied to real operational data from two laboratory-scale (MBR) installations. The work presents the full chain of theoretical model development, model analysis and practical application to case study data for micropollutants.

scholarly journals Techno-Economic Assessment of Energy Retrofitting Educational Buildings: A Case Study in Saudi Arabia

2020 ◽  
Vol 13 (1) ◽  
pp. 179
Author(s):  
Mohammad B. Hamida ◽  
Wahhaj Ahmed ◽  
Muhammad Asif ◽  
Faris Abdullah Almaziad
Keyword(s):  
Saudi Arabia ◽  
Energy Consumption ◽  
Residential Buildings ◽  
Model Development ◽  
Economic Assessment ◽  
Study Data ◽  
Energy Assessment ◽  
Educational Buildings ◽  
Energy Auditing

The buildings and construction sector accounts for the majority of the energy consumption in the Kingdom of Saudi Arabia (KSA). For a sustainable future, energy consumption in the sector should be reduced and existing buildings need to be energy retrofitted. A number of studies present energy retrofitting of residential buildings in KSA; however, there is a lack of studies presenting retrofitting of educational buildings. Thus, the aim of this study is to adopt a BIM-based approach to assess Energy Conservation Measures (ECMs) in a prototypical Government-built educational building in Dammam, KSA. The methodology consists of six prime steps, (1) case study data collection, (2) energy auditing, (3) proposing ECMs, (4) BIM model development, (5) energy assessment, and (6) economic assessment. The energy audit revealed several inefficiencies in the building construction and operation and four ECMs were proposed and simulated. It was found that annual energy consumption can be reduced by 22.7% in the educational building, and the investment for the four ECMs is paid back in 2.7 years only. Therefore, implementing the proposed ECMs is a viable option to energy retrofit such educational buildings in the country, and the presented BIM-based approach can be adopted to efficiently conduct the energy retrofitting process.

scholarly journals Case Study: Data Mining of Associate Degree Accepted Candidates by Modular Method

2012 ◽  
Vol 04 (03) ◽  
pp. 261-268
Author(s):  
Behrouz Minaei Bidgoli ◽  
Maryam Nazaridoust
Keyword(s):  
Data Mining ◽  
Associate Degree ◽  
Study Data ◽  
Modular Method ◽  
Case Study Data

Literature Study –Data Mining Techniques on Detecting Fradulent Activities in Credit Card

2017 ◽  
Vol 6 (10) ◽  
pp. 60
Author(s):  
S. K. Saravanan ◽  
G. N. K. Suresh Babu
Keyword(s):  
Data Mining ◽  
Credit Card ◽  
Data Transfer ◽  
Study Data ◽  
Time Requirement ◽  
Literature Study ◽  
Data Mining Techniques ◽  
Online Transactions ◽  
Secured Data ◽  
Credit Card Usage

In contemporary days the more secured data transfer occurs almost through internet. At same duration the risk also augments in secure data transfer. Having the rise and also light progressiveness in e – commerce, the usage of credit card (CC) online transactions has been also dramatically augmenting. The CC (credit card) usage for a safety balance transfer has been a time requirement. Credit-card fraud finding is the most significant thing like fraudsters that are augmenting every day. The intention of this survey has been assaying regarding the issues associated with credit card deception behavior utilizing data-mining methodologies. Data mining has been a clear procedure which takes data like input and also proffers throughput in the models forms or patterns forms. This investigation is very beneficial for any credit card supplier for choosing a suitable solution for their issue and for the researchers for having a comprehensive assessment of the literature in this field.

Removing Self-stigma: The Successes of People with Schizophrenia in Removing Self-stigma Through Self-control

2018 ◽  
Vol 33 (3) ◽  
Author(s):  
Franciscus Adi Prasetyo ◽  
Jajang Gunawijaya
Keyword(s):  
Sampling Technique ◽  
Self Esteem ◽  
Study Data ◽  
Self Control ◽  
Study Quality ◽  
Data Display ◽  
Case Study Approach ◽  
Study Approach ◽  
Depth Interviews

Self-stigma experienced by people who experience schizophrenia has influence on reduced self-esteem, on powerlessness, the weakening of hope, and a motivation towards recovery. The aim of this study is to explain the efforts of people suffering schizophrenia to manage their self-stigma through self-control, using a case study approach. Based on the purposive sampling technique, five people with schizophrenia were selected as the cases to be studied. Data collection techniques utilized in-depth interviews, observation, and documentary studies. The analysis of the study data employed the stages of data reduction, data display, and data verification. Improvement in study quality employed the triangulation of data sources by checking the data to determine its consistency. The results of this study indicate that people with schizophrenia who have the ability to self-control can overcome self-stigma through changes in the manner of viewing themselves, self-training through activities, having endurance, having an honest approach, being able to explain schizophrenia from a positive viewpoint, having initiative, and having a positive attitude and the courage to face challenges.

Penerapan Metode Klasifikasi Decision Tree dan Algoritma C4.5 dalam Memprediksi Kriteria Nasabah Kredit Mega Auto Finance

2020 ◽  
Vol 7 (2) ◽  
pp. 200
Author(s):  
Puji Santoso ◽  
Rudy Setiawan
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Microsoft Excel ◽  
Customer Data ◽  
Data Mining Techniques ◽  
C4.5 Algorithm ◽  
Marketing Costs ◽  
Excel Format ◽  
Data Mining Application

One of the tasks in the field of marketing finance is to analyze customer data to find out which customers have the potential to do credit again. The method used to analyze customer data is by classifying all customers who have completed their credit installments into marketing targets, so this method causes high operational marketing costs. Therefore this research was conducted to help solve the above problems by designing a data mining application that serves to predict the criteria of credit customers with the potential to lend (credit) to Mega Auto Finance. The Mega Auto finance Fund Section located in Kotim Regency is a place chosen by researchers as a case study, assuming the Mega Auto finance Fund Section has experienced the same problems as described above. Data mining techniques that are applied to the application built is a classification while the classification method used is the Decision Tree (decision tree). While the algorithm used as a decision tree forming algorithm is the C4.5 Algorithm. The data processed in this study is the installment data of Mega Auto finance loan customers in July 2018 in Microsoft Excel format. The results of this study are an application that can facilitate the Mega Auto finance Funds Section in obtaining credit marketing targets in the future

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