Browsing by Subject "Activity analysis"

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Extension of activity analysis methodology to maintenance, shutdown, and turnarounds in petrochemical facilities
(2016-08) Shounak, Goodidar Hemmanoor Arjun; Caldas, Carlos H.; Borcherding, John D
Studies show that construction productivity has been stagnant for decades. Interestingly, other industries like manufacturing, automobile and agriculture have witnessed a steep increase in productivity, nearly twice, over the same period of time. It has been the norm for many continuous improvement methods, employed by these industries, to claim credit for this trend. While inadequacies in a range of parameters like management practices, organizational behavior, contractual differences, and other planning functions affect poor productivity, the first step towards any improvement program is to measure the existing condition. The importance of measuring and improving productivity has become increasingly critical and significant with raging project capital costs and complexity, especially in the petroleum industry. This research focusses on providing a productivity language for petrochemical owners and contractors. The developed methodology helps them to communicate improvement strategies with each other and within their organization beyond construction leading into maintenance and shutdown turnarounds. Activity Analysis is a productivity assessment and improvement method developed by the Construction Industry Institute (CII) in 2010. This thesis describes the adaptation of activity analysis methodology that was developed to measure productivity indicators at petrochemical facilities on construction, maintenance and shutdown turnaround activities between 2015 and 2016. It also provides an overview on the activity analysis software developed for data collection, which is a byproduct of this research. This study also provides a summary of expected trends and challenges in petrochemical industries, and strategies that could be implemented to enhance the direct work rate in both construction and maintenance environment.
Rapid and contextual activity analysis : a semi-automated activity category, time, location, and video data collection and analysis methodology
(2015-08) Kim, Jung Yeol; Caldas, Carlos H.; Borcherding, John D; Leite, Fernanda; Grauman, Kristen; Zhang, Zhanmin
The performance of construction projects is significantly impacted by on-site labor and the productivity thereof. Despite the benefits from technological advancements in recent decades, construction projects are still labor intensive, and labor is one of the most flexible and largest cost factors in a construction project. Thus, a major concern of construction project management has been labor productivity and its improvement. To improve it, labor productivity must be measured and analyzed. One way of doing so is through activity analysis - known as an extension of traditional work sampling. Activity analysis measures the efficiency of the workers' time usage at a construction site. Increasing labor efficiency usually has a positive relationship with higher construction labor productivity. Therefore, activity analysis is considered a major labor performance assessment technique in this research. The objective of this research is to develop a semi-automated data collection and analysis methodology to enable fast and contextual activity analysis. More specifically, this research focuses on the man-machine balanced on-site data collection and the automated data analysis with abundant contextual information to support the interpretation of analysis results for labor productivity improvement study. The prototype of the proposed methodology is implemented and validated with actual datasets from different construction sites. The prototype system proves capable of collecting data efficiently at construction sites and to analyze it in an automatic fashion. This system is shown to provide abundant contextual information related to the activity analysis results. A project manager can quickly and easily find issues related to their high or low labor performance with various scenarios. The indexed videos also successfully provide information about what/how construction workers were performing work at that point. This information can support productivity improvement planning and expedite the continuous evaluation and improvement process of activity analysis to improve labor productivity.