Browsing by Author "Meyer, Ewald Mauritz"

Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    Development and testing of an automated time-motion detector for construction activities
    (Stellenbosch : Stellenbosch University, 2024-02) Meyer, Ewald Mauritz; Wium, Jan; Jurgens, Chris; Stellenbosch University. Faculty of Engineering. Dept. of Civil Engineering.
    ENGLISH ABSTRACT: This study looked into the intricacies of construction rework and the methods that have been used to identify, quantify and manage rework. From this research, a novel process of combining equipment, software and methodology is presented in the development of a concept of an automated time-motion detector system, with a proposed method to implement the system to quantify rework of structural elements on construction sites. The aim of this study is to develop and test a technological solution to detect time spent on construction activities and ultimately uncover un-announced rework on construction sites. This is achieved by completing the following objectives: (i) Determine the most feasible technological solution for the time-motion monitoring of construction activities that could lead to quality failures. (ii) Develop a time-motion detector that can be used to monitor construction activities remotely. (iii) Implement and test the system by performing simplified tests in a controlled environment to determine the accuracy of the system. (iv) Discuss results and future implementations. The motivation for this study was based on the challenge of efficient construction management and the inability to learn from quality failures on construction sites resulting from a lack of suitable data and documentation relating to the execution of construction activities. This lack of execution information hinders construction companies to become more efficient and profitable. In research, a shift is seen towards the gathering and analysis of data to improve the efficiency and profitability of construction companies after very successful implementation of data analysis and management in other fields of study. In this study, a proof of concept of an automated time-motion detector was developed in Python to record and analyse construction activities to determine the human capital required for these activities. The system was tested with several trial tests, where it was found that the system has an average accuracy of 84% while valuable operational data, limitations and recommendations for the use of this system were obtained.