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Title:The impact of visual production management on construction project controls: a case-based reasoning
Author(s):Patidar, Manish
Advisor(s):Golparvar-Fard, Mani
Department / Program:Civil & Environmental Eng
Discipline:Civil Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Visual production management system
Construction monitoring tool
Abstract:Over the past decade, production control theories such as the Last Planner System by Ballard, G., (2000) have emerged that stabilize workflows by shielding the direct work from upstream variation and uncertainty. Although theories have been well documented, yet their full-scale implementation is not realized, and the root-causes for this are not entirely understood. A large body of empirical observations suggest that successful implementation of control mechanisms requires dedicated facilitators and engages practitioners in a relatively deep learning process. Sustaining this level of commitment for the duration of a project is difficult, and in its absence, project teams revert to traditional project control practices. These barriers are in part attributed to the people and organizational processes involved in implementing lean principles, however there is a growing recognition among researchers that the functional aspects of production control techniques need close re-examination to understand better, predict, and analyze reliability in performance, and preserve effective and timely flow of information both to and from the workforce. To address these knowledge gaps, Lin and Golparvar-Fard (2016) proposes a visual project control system that a) improves understanding of how construction performance can be captured, communicated, and analyzed in form of a production system; b) predicts the reliability of the weekly work plan and look-ahead schedule, supports root-cause assessment on plan failure at both project and task-levels; c) facilitates information flows; and d) decentralizes decision-making. The web-based system which is built on visual data analytics maps the current state of production on construction sites in 3D and exposes waste at both project and task-levels and it then forecasts reliability in the future state of production to highlight potential issues in a location-driven scheme. The platform also supports collaborative decision making that eliminates root causes of waste and provides visual interfaces between people and information that enable effective pull flow, decentralize work tracking, and facilitate in-process quality control and hand-overs among contractors. To ensure their implementation does not take away from actual productivity, it extends the value of 4D Building Information Models (BIM) commonly used for constructability review as a benchmark for performance. It also leverages images and videos frequently collected by project participants or professional services via consumer-grade, time-lapse, smartphone cameras and Unmanned Aerial Vehicles (UAVs) to visually document actual performance. To better understand, assess, and improve the performance of this visual production system, a case-based reasoning study is conducted in this thesis using case studies based on two real-world construction projects. The use of simple and effective visuals of work-in-progress and at risk locations on construction sites offered through visual production management is assessed to better understand if such systems can improve reliability of short-term planning, enhance situational awareness, enable easy and quick root-cause assessment of plan failures, and facilitate flow of information onsite and during coordination sessions. The lessons learned and areas for further development in theory and technology are discussed in detail.
Issue Date:2016-12-07
Rights Information:Copyright 2016 Manish Patidar
Date Available in IDEALS:2017-03-01
Date Deposited:2016-12

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