Bains Thesis

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  • CO-RELATION OF VARIABLES INVOLVED IN THE OCCURRENCE OF

    CRANE ACCIDENTS IN THE U.S. THROUGH LOGIT MODELING

    A Thesis

    by

    AMRIT ANOOP SINGH BAINS

    Submitted to the Office of Graduate Studies of Texas A&M University

    in partial fulfillment of the requirements for the degree of

    MASTER OF SCIENCE

    August 2010

    Major Subject: Construction Management

  • CO-RELATION OF VARIABLES INVOLVED IN THE OCCURRENCE OF

    CRANE ACCIDENTS IN THE U.S. THROUGH LOGIT MODELING

    A Thesis

    by

    AMRIT ANOOP SINGH BAINS

    Submitted to the Office of Graduate Studies of Texas A&M University

    in partial fulfillment of the requirements for the degree of

    MASTER OF SCIENCE

    Approved by:

    Co-Chairs of Committee, Boong Yeol Ryoo Ho-Yeong Kang Committee Member, Mark Clayton Head of Department, Joe Horlen

    August 2010

    Major Subject: Construction Management

  • iii

    ABSTRACT

    Co-relation of Variables Involved in the Occurrence of Crane Accidents in the U.S.

    through Logit Modeling. (August 2010)

    Amrit Anoop Singh Bains, B.Arch., Panjab University, India

    Co-Chairs of Advisory Committee: Dr. Boong Yeol Ryoo Dr. Ho-Yeong Kang

    One of the primary reasons of the escalating rates of injuries and fatalities in the

    construction industry is the ever so complex, dynamic and continually changing nature of

    construction work. Use of cranes has become imperative to overcome technical

    challenges, which has lead to escalation of danger on a construction site. Data from

    OSHA show that crane accidents have increased rapidly from 2000 to 2004. By analyzing

    the characteristics of all the crane accident inspections, we can better understand the

    significance of the many variables involved in a crane accident.

    For this research, data were collected from the U.S. Department of Labor website via the

    OSHA database. The data encompass crane accident inspections for all the states. The

    data were divided into categories with respect to accident types, construction operations,

    degree of accident, fault, contributing factors, crane types, victims occupation, organs

    affected and load. Descriptive analysis was performed to compliment the previous

    studies, the only difference being that both fatal and non-fatal accidents have been

    considered.

  • iv Multinomial regression has been applied to derive probability models and correlation

    between different accident types and the factors involved for each crane accident type. A

    log likelihood test as well as chi-square test was performed to validate the models. The

    results show that electrocution, crane tip over and crushed during assembly/disassembly

    have more probability of occurrence than other accident types. Load is not a significant

    factor for the crane accidents, and manual fault is more probable a cause for crane

    accident than is technical fault. Construction operations identified in the research were

    found to be significant for all the crane accident types. Mobile crawler crane, mobile

    truck crane and tower crane were found to be more susceptible. These probability models

    are limited as far as the inculcation of unforeseen variables in construction accidents are

    concerned. In fact, these models utilize the past to portray the future, and therefore

    significant change in the variables involved is required to be added to attain correct and

    expedient results.

  • v

    DEDICATION

    This thesis is dedicated to my wonderful parents, Daljeet Kaur Bains and Balwinder

    Singh Bains, who have raised me to be the person I am today. You have been with me

    every step of the way, through good times and bad. Thank you for all the unconditional

    love, guidance, and support that you have always given me, helping me to succeed, and

    instilling in me the confidence that I am capable of doing anything I put my mind

    to. Thank you for everything. I love you!

  • vi

    ACKNOWLEDGEMENTS

    I would like to express gratitude to my advisor, Dr. Boong Yeol Ryoo, for the guidance

    and support throughout the course of this research. I have thoroughly enjoyed the last 18

    months working and learning a lot from you. I would also like to thank my committee

    members, Dr. Julian Kang and Dr. Mark Clayton for their support.

    Special thanks go to my special friends Rahul Goel and Mandeep Singh Pannu, their

    technical knowledge and guidance were absolute quintessence for the completion of this

    thesis. They truly are friends indeed. I am highly grateful to Dr. Derya Akelman for

    imparting such a useful knowledge of statistics to me. I would also like to take this

    opportunity to thank all those guys who have made my experience at Texas A&M

    University a great one.

    There are other debts more of a personal nature I must acknowledge. Throughout the

    writing and learning process of this thesis, spiritual music and holy recitations by Bhai

    Harjinder Singh (Srinagar Wale) and Nusrat Fateh Ali Khan have been a constant source

    of strength to focus and concentrate resulting in work produced to the best of my ability.

  • vii

    TABLE OF CONTENTS

    Page

    ABSTRACT ...................................................................................................................... iii

    DEDICATION .....................................................................................................................v

    ACKNOWLEDGEMENTS ............................................................................................... vi

    TABLE OF CONTENTS ................................................................................................. vii

    LIST OF FIGURES .............................................................................................................x

    LIST OF TABLES ............................................................................................................ xii

    NOMENCLATURE ........................................................................................................ xiv

    1. INTRODUCTION ........................................................................................................1

    1.1. Background .......................................................................................................... 1 1.2. Problem Statement ............................................................................................... 3 1.3. Research Objective ............................................................................................... 4 1.4. Research Approach .............................................................................................. 6 1.5. Thesis Organization .............................................................................................. 6

    2. LITERATURE REVIEW .............................................................................................8

    2.1 Analysis of Crane Accidents ................................................................................ 8 2.2 Types of Cranes .................................................................................................. 10 2.3 Summary ............................................................................................................ 17 2.4 Application of Mathematical Models ................................................................. 18

    2.4.1 Fuzzy Logic ................................................................................................ 19 2.5 Logit Modeling ................................................................................................... 24

    2.5.1 Concept ....................................................................................................... 24 2.5.2 Significance Tests for Multinomial Logistic Regression ............................ 26

  • viii

    Page

    2.5.3 Interpreting Probability Models .................................................................. 29 2.6 Summary of Literature Review .......................................................................... 31

    3. DATA .........................................................................................................................34

    3.1 Data Collection ................................................................................................... 34 3.2 Data Samples ...................................................................................................... 35 3.3 Descriptive Analysis .......................................................................................... 50

    3.3.1 Findings....................................................................................................... 55 3.4 Summary ............................................................................................................ 59 3.5 Why Logit Modeling .......................................................................................... 61

    4. METHODOLOGY .....................................................................................................63

    4.1 Data Collection ................................................................................................... 63 4.2 Coding and Output ............................................................................................. 63 4.3 Logit Modeling ................................................................................................... 66 4.4 Significance Tests ...................