Influence of malfunctions of the maintenance activities on the urban buses fuel consumption

2014 ◽  
Vol 4 (2) ◽  
Author(s):  
Crişan George ◽  
Filip Nicolae
Keyword(s):  
Fuel Consumption ◽  
Solid Base ◽  
Quality Service ◽  
Maintenance Activity ◽  
Maintenance System ◽  
Urban Public Transport ◽  
Maintenance Activities ◽  
Abc Method ◽  
Maintenance Process

AbstractOptimization of activities with the aim to provide quality service in conditions of high profitability, is one of the main objectives chased by managers in transportation companies. As a consequence, directing the attention towards monitoring of maintenance activities of vehicles fleet, can achieve desired results. Two of the most important issues related to the maintenance activity, is the increase of reliability and reduction of fuel consumption of the vehicles fleet. Aforementioned actions represents a way forward for raising the quality and profitability of services offered. In this paper, the main ways of monitoring the fuel consumption, in order to reduce it and increase the reliability of transportation vehicles fleet, are presented. For the evaluation of the maintenance system and the degree of influence of malfunctions recorded on the fuel consumption, using the Pareto -ABC method, following case study on a fleet of buses for urban public transport has been conducted. Results obtained highlights the deficiencies of the maintenance process carried out and constitutes a solid base for the reorganization of the maintenance activity, involving preventive maintenance activities, in order to contribute decisively to the results targeted by the management of transport companies.

Application of data mining for spare parts information in maintenance schedule: a case study

2019 ◽  
Vol 30 (7) ◽  
pp. 1055-1072
Author(s):  
U.C. Moharana ◽  
S.P. Sarmah ◽  
Pradeep Kumar Rathore
Keyword(s):  
Data Mining ◽  
Industrial Applications ◽  
Spare Parts ◽  
Sequential Patterns ◽  
Historical Records ◽  
Threshold Values ◽  
Content Type ◽  
Maintenance Activity ◽  
Maintenance Activities

Purpose The purpose of this paper is to suggest a framework for extracting the sequential patterns of maintenance activities and related spare parts information from historical records of maintenance data with pre-defined support or threshold values. Design/methodology/approach A data mining approach has been adopted for predicting the maintenance activity along with spare parts. It starts with a collection of spare parts and maintenance data, and then the development of sequential patterns followed by formation of frequent spare part groups, and finally, integration of sequential maintenance activities with the associated spare parts. Findings This study suggests a framework for extracting the sequential patterns of maintenance activities from historical records of maintenance data with pre-defined support or threshold values. A rule-based approach is proposed in this paper to predict the occurrence of next maintenance activity along with the information of spare parts consumption for that maintenance activity. Research limitations/implications Presented model can be extended for analyzing the failure maintenance activities and performing root cause analysis that can give more valuable suggestion to maintenance managers to take corrective actions prior to next occurrence of failures. In addition, the timestamp information can be utilized to prioritize the maintenance activity that is ignored in this study. Practical implications The proposed model has a high potential for industrial applications and is validated through a case study. The study suggests that the model gives a better approach for selecting spare parts based on their similarity or correlation, considering their actual occurrence during maintenance activities. Apart from this, the clustering of spare parts also trains maintenance manager to learn about the dependency among the spares for group stocking and maintaining the parts availability during maintenance activities. Originality/value This study has used the technique of data mining to find dependent spare parts itemset from the database of the company and developed the model for associated spare parts requirement for subsequent maintenance activity.

scholarly journals THE EFFECT OF IMPLEMENTATION PREVENTIVE MAINTENANCE SYSTEM AND THE VALUES OF AVAILABILITY, PERFORMANCE AND QUALITY TOWARDS OVERALL EQUIPMENT EFFECTIVENESS (Case Study in PT. Astra Honda Motor)

2017 ◽  
Vol 11 (2) ◽  
pp. 121
Author(s):  
Dicky Kurniawan
Keyword(s):  
Multiple Regression ◽  
Preventive Maintenance ◽  
Activity Data ◽  
System Effect ◽  
Maintenance Activity ◽  
Average Data ◽  
Maintenance System ◽  
Performance Quality ◽  
The Right

The background of this research refers to many companies that cannot identify about the system effect and overall equipment effectiveness (OEE) values, and cannot implement the right system continuously. So that, this research is to investigate some factors that influence the OEE values. <br />The objective of this research were to investigate the effects of preventive maintenance to OEE and to decide whether of availability, performance, quality that most contribute to OEE values at PT. <br />Astra Honda Motor. <br />The design of this research applies case study to examine all hypothesis in this study. The methods used in this study was simple and multiple regression between independent variables and dependent variable. Data analysis used in this research were collected from preventive maintenance activity data and machining crank case production data. There were 91 average data of preventive maintenance activity and usable for analyzed by simple regression and 578 average data of machining crank case production completed and usable for analyzed by multiple regression. <br />The result of research indicated that the first, preventive maintenance has no significant impact to OEE values. The second, availability give more contribution to OEE values than performance and quality.

Traffic Flow Management Impact on Delay and Fuel Consumption: an Atlanta Case Study

2012 ◽  
Vol 20 (3) ◽  
pp. 203-224 ◽  
Author(s):  
Shon R. Grabbe ◽  
Banavar Sridhar ◽  
Avijit Mukherjee ◽  
Alexander Morando
Keyword(s):  
Fuel Consumption ◽  
Traffic Flow ◽  
Flow Management ◽  
Traffic Flow Management

Assessing Pruning Knowledge towards Effective Tree Maintenance: A case study of four Local Authorities in Malaysia

2020 ◽  
Vol 5 (13) ◽  
pp. 223
Author(s):  
Norainiratna Badrulhisham ◽  
Noriah Othman
Keyword(s):  
Publishing House ◽  
Knowledge Level ◽  
Local Authorities ◽  
The Public ◽  
Risk Of Injury ◽  
International Publishing ◽  
Maintenance Activities ◽  
Tree Pruning ◽  
Open Access Article

Pruning is one of the most crucial tree maintenance activities which give an impact on the tree's health and structure. Besides, improper pruning will contribute to the risk of injury to property and the public. This study aims to assess pruning knowledge among four Local authorities in Malaysia. Results found that 69.3 percent of tree pruning workers have a Good pruning knowledge level. However, Topping, pruning types and pruning cut dimension shows the lowest mean percentage of the correct answer. The findings also show that there is a significant positive relationship between pruning knowledge and education level and frequency attending pruning courses.Keywords: Tree pruning; knowledge; sustainable practices; urban treeseISSN: 2398-4287 © 2020. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BYNC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia.DOI: https://doi.org/10.21834/e-bpj.v5i13.2054 

scholarly journals STANDARDISING MAINTENANCE JOBS TO IMPROVE GROUPING DECISION MAKING

2021 ◽  
Vol 1 ◽  
pp. 2701-2710
Author(s):  
Julie Krogh Agergaard ◽  
Kristoffer Vandrup Sigsgaard ◽  
Niels Henrik Mortensen ◽  
Jingrui Ge ◽  
Kasper Barslund Hansen ◽  
...  
Keyword(s):  
Decision Making ◽  
Tacit Knowledge ◽  
True Variance ◽  
Complex Decision ◽  
Maintenance Decision ◽  
Maintenance Activities

AbstractMaintenance decision making is an important part of managing the costs, effectiveness and risk of maintenance. One way to improve maintenance efficiency without affecting the risk picture is to group maintenance jobs. Literature includes many examples of algorithms for the grouping of maintenance activities. However, the data is not always available, and with increasing plant complexity comes increasingly complex decision requirements, making it difficult to leave the decision making up to algorithms.This paper suggests a framework for the standardisation of maintenance data as an aid for maintenance experts to make decisions on maintenance grouping. The standardisation improves the basis for decisions, giving an overview of true variance within the available data. The goal of the framework is to make it simpler to apply tacit knowledge and make right decisions.Applying the framework in a case study showed that groups can be identified and reconfigured and potential savings easily estimated when maintenance jobs are standardised. The case study enabled an estimated 7%-9% saved on the number of hours spent on the investigated jobs.

Unrelated Parallel-Machine Scheduling with Controllable Processing Times and Impact of Deteriorating Maintenance Activities under Consideration

2016 ◽  
Vol 33 (01) ◽  
pp. 1650001 ◽  
Author(s):  
Chun-Lai Liu ◽  
Jian-Jun Wang
Keyword(s):  
Processing Time ◽  
Machine Scheduling ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Controllable Processing Times ◽  
Maintenance Activity ◽  
Processing Times ◽  
Unrelated Parallel Machine Scheduling ◽  
Deteriorating Maintenance ◽  
Maintenance Activities

In this paper, we study the problem of unrelated parallel machine scheduling with controllable processing times and deteriorating maintenance activity. The jobs are nonresumable. The processing time of each job is a linear function of the amount of a continuously divisible resource allocated to the job. During the planning horizon, there is at most one maintenance activity scheduled on each machine. Additionally, if the starting time of maintenance activity is delayed, the length of the maintenance activity required to perform will increase. Considering the total completion times of all jobs, the impact of maintenance activity in the form of the variation in machine load and the amounts of compression, we need to determine the job sequence on each machine, the location of maintenance activities and processing time compression of each job simultaneously. Accordingly, a polynomial time solution to the problem is provided.

The WLTC vs NEDC: A Case Study on the Impacts of Driving Cycle on Engine Performance and Fuel Consumption

2021 ◽  
Vol 18 (3) ◽  
pp. 9071-9081
Author(s):  
Jakub Lasocki
Keyword(s):  
Fuel Consumption ◽  
Combustion Engine ◽  
Engine Performance ◽  
Driving Cycle ◽  
Performance Characteristics ◽  
Pollutant Emission ◽  
Strong Impact ◽  
Light Duty ◽  
Light Duty Vehicles

The World-wide harmonised Light-duty Test Cycle (WLTC) was developed internationally for the determination of pollutant emission and fuel consumption from combustion engines of light-duty vehicles. It replaced the New European Driving Cycle (NEDC) used in the European Union (EU) for type-approval testing purposes. This paper presents an extensive comparison of the WLTC and NEDC. The main specifications of both driving cycles are provided, and their advantages and limitations are analysed. The WLTC, compared to the NEDC, is more dynamic, covers a broader spectrum of engine working states and is more realistic in simulating typical real-world driving conditions. The expected impact of the WLTC on vehicle engine performance characteristics is discussed. It is further illustrated by a case study on two light-duty vehicles tested in the WLTC and NEDC. Findings from the investigation demonstrated that the driving cycle has a strong impact on the performance characteristics of the vehicle combustion engine. For the vehicles tested, the average engine speed, engine torque and fuel flow rate measured over the WLTC are higher than those measured over the NEDC. The opposite trend is observed in terms of fuel economy (expressed in l/100 km); the first vehicle achieved a 9% reduction, while the second – a 3% increase when switching from NEDC to WLTC. Several factors potentially contributing to this discrepancy have been pointed out. The implementation of the WLTC in the EU will force vehicle manufacturers to optimise engine control strategy according to the operating range of the new driving cycle.

Evaluation of urban public transport priority performance based on the improved TOPSIS method: A case study of Wuhan

2018 ◽  
Vol 43 ◽  
pp. 357-365 ◽  
Author(s):  
Xiuxia Zhang ◽  
Qingnian Zhang ◽  
Tingting Sun ◽  
Yongchao Zou ◽  
Huanwan Chen
Keyword(s):  
Public Transport ◽  
Topsis Method ◽  
Urban Public Transport
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