Cost and Time Optimization in Fleet Management- Case Study of Sinnar Shirdi Highway

Abstract

The aim of the study is to show how fleet management can help in saving time and cost by comparing the current onsite equipment to optimised results. The detailed study of fleet of equipment and their related parameters and specifications is important because it helps to determine requirement of equipments for a particular activity. All the cost including labor, maintenance, operating costs, machine capacity were considered to find out the productivity as well as expenses. Based on the site visit and data collection various parameters such as productivity of excavator, production rate, cycle time and other parameters of activities such as earthmoving equipment, hauling of trucks as well as productivity of paver were also calculated. The parameters were obtained for various combinations of different truck sizes as shown in the MS- Excel sheet. For different truck sizes and different combinations we get different cost index.

Introduction

I. INTRODUCTION

Fleet operation is the system which uses operation or technology to track and manage different kinds of vehicles similar as buses, weight logistic assignment, luxury motorcars, ambulance assignment, vessels etc. The fleet management system also keeps records of vehicles similar as purchase, reimbursement or parcel information, motorist records, energy information, GPS records and so on. Private builders and trace drivers are also enforcing major systems. numerous of moment's large- scale systems calculate on a line of heavy- duty vehicles and means pavers, excavators, tractors, bulldozers, backhoes, cranes, you name it - each vehicle within the line has a specific use case and serves a unique purpose in support of operations and during a construction design.

A. Need of the study

In construction industry construction management is important in operation of equipments as per the operations carried out. Price hike in fuel and energy in last many years has become a reason for need of proper fleet management. The detailed study of machines i.e fleet and their affiliated parameters and specifications is important because it helps to determine demand of equipment for a particular exertion e.g. DBM, earthwork activity. This kind of management not only saves the cost but also helps in optimizing time.

B. Objectives

1. To study fleet management in road construction projects.
2. To do a case study on Sinnar - Shirdi Highway and analyze the data.
3. To determine production rate, cycle time and other parameters of activities such as earthmoving equipment, hauling of trucks, and provide optimum solution to save time and cost.

II. REVIEW OF LITERATURE

Some theoretical and analytical investigations performed in this field are presented in the following literature survey.

1. Lalitesh Sinha and Atul Tripathi (2019) have shown in this paper that Time and cost are the main ideal to be bandied in the present optimization study using inheritable Algorithm (GA) for trace design. For scheduling of design has been used which gives the correct and accurate schedule of the design while GA optimization solver in MATLAB are used to optimize time and cost of the design. The Performance of the solvers substantially depends upon the parameters of GA which are used according to target and factual duration of design. The present case study shows that GA can be applied in establishing an optimal cost- time balance for trace systems. By considering incitement and penalty costs into the consideration, the cost- time relationship would come more dependent and complex on data. Still, GAs show better results in working this type of problem in small and huge construction systems. 
2. The purpose of this paper of Adam Redmer (2020) is to develop an original model and a  result procedure for working concertedly three main strategic line operation problems (line composition,  relief and make- or- buy), taking into account interdependencies between them. The presented CSFMP result system (the model and the result procedure) allows for defining the line operation strategy in transportation and non transportation companies and institutions exploiting small and large lines of vehicles. The strategy results in the reduction of the total costs of transportation and the enhancement of a specialized and a profitable condition of a line. 
3. Saeed Karshena and Foad Farid (June 1989) studied that Loaders and exchanges are frequently used in channel systems. In major earth- moving operations, careful selection of the number of machines used and the size of the outfit can produce substantial savings in both time and cost presently, the only  system available for determining the optimum size- number combination for  payload is comparison of all possible  druthers. This is a tedious and time- consuming task, especially if a large volume of soil must be hauled, taking several lading units. In this study, optimal multiloader- truck lines are delved, and perceptivity of the product cost to the crucial variables is anatomized. The cost- capacity and capacity-power connections for exchanges and payload are delved by using published outfit specifications and cost data.
4. C.B. Tatum, Michael Vorster, Mac G. Klingler, Boyd C. Paulson Jr. (2006) studied the specialized advancement of earthmoving  outfit during the 20th century that includes  numerous advancements in  crucial  corridor of machines. This paper uses five systems that make up earthmoving outfit (apply, traction, structure, power train, and control and information) to assay this specialized advancement. The analysis of each system includes its purpose and operation, specialized limitations and crucial technologies, and a report of major advancements. The findings are the benefits of using the five systems for analysis of specialized change, the sequence and timing of crucial specialized advances in each system, the abecedarian technologies that fostered these advances, and the integration of systems into balanced outfit designs. This increased understanding from this analysis results in significant counteraccusations  and applicability for civil contrivers working on intertwined  brigades, contractors  opting   styles and planning operations,  outfit suppliers developing new machines, construction  preceptors  tutoring the specialized basics of  outfit, and experimenters developing advanced modelling and simulation tools.

III. METHODOLOGY

At present case it has been observed that there was unplanned management of the equipments. The data was obtained from Monthly Progress reports as well as site study from engineers and workers on the site. Study of equipment as well as site visit was done to analyse the data and a model was developed by using Saeed Karshena truck loader and R.L Peurifoys construction planning and methods. The model was used for calculations on M.S excel.

IV. RESULTS ANALYSIS AND DISCUSSIONS

In the current case the hot mix plant is located at Pimpalwadi which can produce about 160 tons per hour. Chainage is 29.00 to 30.00 and the distance between actual site and hot mix plant was about 9 km to and fro. The project was requiring a paving individual 12.5 m lane of 1 km and 115mm thickness having a density of 2.45 tonnes/cum. The maximum speed of paver is about 15m per minute. Efficiency of Asphalt paver is 0.8 and density of 2453 kg/sq.m-m.

Operational cost of paver is Rs. 8000 per hour and total cost of various associated labors is Rs. 3500 per day. In the case study the trucks are variable in sizes as they are rented for the whole duration of project. As there are various costs associated with the equipments, there is a need to select best equipment mix best fleet that will improve the productivity and satisfy the constraints of the project.

Table 1. Data collection for DBM fleet

Conclusion

The factual on point line composition is grounded on the assumed thumb rules and no special optimization ways are employed and also the figures of units employed won’t with their maximum productivity. From the result and discussion, we conclude that, the mix possibilities of equipments give economical and profitable solution as per site condition. The parameters similar as cycle time, total cost, Cost indicator, total time needed for completing exertion are determined easily. Grounded upon the comparison of values, mentioned in an irregular format, in result chapter are as follows, 1) In earthwork fleet- Actual time required is 118.28 days whereas optimized time is 83 days. Actual cost index is Rs. 78.56 per m3 and optimized cost index is Rs. 67.24 m3. So the profitability is Rs. 16,97,818 which is achieved. 2) Paver (DBM) fleet- Actual cost index is 143.94 Rs/cum and optimized cost index is Rs. 117.52 m3. So the profitability is Rs. 18,164 which is achieved. The parameters such as cycle time, total cost, Cost Index, total time required for completing activity will be changed as per site conditions. The limitation of this study is, only two constructions activities are considered for this case study to analyze the data for actual distance. However, we can change the parameters and easily calculate more profitable options. Distance as well as equipment details can be changed and results can be obtained for any type of truck combinations. The calculations can be implemented for other types of fleet and other hauling material such as Aggregate, GSB, WMM, BC etc. It can be very useful in pre-planning phase of the project and help to save time as well as achieve better economy.

References

[1] Construction Methods and Management by S. W. Nunnally Consulting Engineer, Professor Emeritus, North Carolina State University, Upper Saddle. [2] Construction planning, equipment and method, Robert. L Peurifoy, Clifford J.Schexnayder, Aviad Shapira, 7th edition, McGraw Hill Publishers. [3] Construction equipment management for engineers, estimators, and owners, Gransberg, Popescu& Ryan, Taylor & Francis Group, 2006. [4] Civil Engineering Department, University of Business and Technology (UBT), Jeddah, Saudi Arabia, Hesham A. Abdelkhalek, Hesham S. Refaie, Remon F. Aziz, Optimization of time and cost through learning curve analysis, Department of Structural Engineering, Faculty of Engineering, Alexandria University, Alexandria, Egypt. [5] (NH 24-B, Phase-I) Construction, Atul Tripathi, Lalitesh Sinha, Cost and Time Optimization of Highway, Volume 4, Issue 7, July – 2019 International Journal of Innovative Science and Research Technology ISSN No:-2456-2165. [6] Methodology of introducing fleet management system, Intelligent Transport Systems (ITS), Review Accepted: Oct. 2, 2007Approved: Mar. 13,2008. [7] Amir Tavakoli, Johannes J. Masehi and Cynthia S. Collyard, “Fleet: Equipment Management System” Journal of Management in Engineering, Vol. 6, No. 2, April, 1990. 211-220. [8] Amir Tavakoli “Productivity Analysis of Construction Operations” Journal of Construction Engineering and Management, Vol. 11 , No. 1, March, 1985. [9] Saeed Karshenas, “Truck Capacity Selection for Earthmoving” Journal of Construction Engineering and Management, Vol. 115, No. 2, June, 1989. [10] S. W. Nunnally. Managing Construction Equipment. Prentice Hall, Englewood Cliffs, N.J., 1977. [11] R. L. Peurifoy and W. B. Ledbetter. Construction Planning, Equipment, and Methods. 4th ed., McGraw-Hill, New York, 1985. [12] 3. H. A. Taha. Operations Research. 3rd ed., MacMillan, New York, 1982.. [13] J.B. O\'Shea, G. N. Slutkin, and L. R. Shaffer. Construction Research Series 3. Department of Civil Engineering, University of Illinois, Urbana, Ill., June 1964. [14] Production and Cost Estimating of Material Movement With Earthmoving Equipment. TEREX Division, General Motors Corporation, Hudson, Ohio, 1981. [15] Adam Redmer Vol. 28 No. 2, 2022 pp. 327-349 Emerald Publishing Limited 1355-2511.

Copyright

Copyright © 2023 Pranav Mhaisdhune, Madhura Aher. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.