College - Author 1
College of Architecture and Environmental Design
Department - Author 1
Construction Management Department
Degree Name - Author 1
BS in Construction Management
Date
12-2018
Primary Advisor/Subject Matter Expert (SME)
Paul Redden, College of Architecture and Environmental Design, Construction Management Department
Abstract/Summary
In the construction industry we are timelessly looking to increase productivity and find the most cost-efficient way to finish a given project. Like any other sector of the construction industry large earth moving contractors look to find the most advantageous way to move dirt and at the cheapest cost per cubic yard. To obtain this goal of calculating and imagining the best way to move dirt, I have created a prototype program that analyzes scraper productivity and cost comparisons through excel sheets. These excel sheets allow a contractor to enter information such as cycles times, load calculations, and costs to create a cost and productivity comparison between rental equipment and in-house equipment as well as different models and sizes of scrapers. By inputting data into these excel sheets it aids industry in making key decisions when selecting a fleet of scrapers for their project. The purpose of this project is to analyze the different types of scraper and the best ways to obtain the greatest productivity through them. Then, by incorporating this knowledge into excel sheets that will be able to help the industry make the best decisions when selecting a scraper or an entire fleet for their individual project. These excel sheets will be beneficial in the aspect of comparing different models of scrapers (twin engine and single engine) by their productivity and then cost. The program will then allow the contractor to generate which combination of scrapers will produce the greatest cost and time efficient approach. If successful this program will benefit contractors looking to obtain a better understanding of their fleet and make the right decisions to create the most time and cost-efficient approach.
URL: https://digitalcommons.calpoly.edu/cmsp/323