Altawil, Shadi N A (2017) Multi-level knowledge extraction and modeling to support job hazard analysis process for oil and gas pipeline projects. PhD thesis, University of Alberta, Canada.
Abstract
Abstract: Construction projects are impacted negatively by construction safety incidents. Job hazard analysis (JHA) process is a critical process component of safety management system in the construction industry. The JHA process is a planning process that aims to address potential hazards associated with execution of construction activities. It involves collecting knowledge from several safety knowledge resources. Explicit resources such as safety manuals, safety codes and regulation, and safety best practices are the primary input knowledge. In addition, tacit safety knowledge that is related to the experience of construction professionals is a critical knowledge component that feeds into the JHA process. JHA documents is the output of each JHA process for each construction activity. The construction industry is a very dynamic and complex environment. Collecting knowledge to perform JHA process requires time and significant efforts. Construction personnel do not have the same experience and ability in identifying construction hazards. In addition, new construction manpower is continually joining the workforce and they lack sufficient experience and knowledge required for hazard identification. Previous JHA documents, which were prepared in previous projects, contain valuable knowledge related to construction hazards. Currently, documents are scattered and not reused for future JHA processes. Oil and Gas Pipeline Projects consist of risky construction activities that involve dynamic interaction between humans, heavy construction equipment, heavy material, and the complex surrounding environment. Currently, safety research related to nonbuilding construction projects is not sufficient. Nonbuilding projects such as pipeline construction and complex infrastructure need research focus due to their execution complexity and high potential risks. This research aims to introduce a method for hazard knowledge extraction and modeling to assist and make the JHA process more consistent and systematic. To reuse the hazards knowledge embedded in JHA forms, multi- levels of knowledge extraction are performed. Text mining is used to organize documents in classes by adopting two stages of machine learning algorithms, clustering and classification. Moreover, JHA forms' contents were analyzed to extract hazards' concepts and relationships to build a hazard dictionary and knowledge schema. Text mining for concept extraction is used along with qualitative approach to build hazard dictionary. Ontology modeling is used to model the extracted knowledge schema. The model aims to represent the knowledge concepts, taxonomies, and semantic relationships. The knowledge model will support the JHA process by enabling retrieval and communication of hazards knowledge in future projects.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Thesis advisor: | Yasser, Mohamed |
| Uncontrolled Keywords: | job hazard analysis; pipeline projects; machine learning; text mining |
| Index terms: | hazard identification, modelling, interaction, mining, qualitative approach, clustering, taxonomies, safety management system, construction professional, heavy construction, construction safety, documents, oil and gas, regulation, complexity, best practice, ontology, machine learning, construction activity, construction project, construction personnel, planning process, construction industry, dictionary, pipeline construction, safety research |
| Subjects: | health safety and environment, financial risk, systems engineering, data management, artificial intelligence, project controls, knowledge organization and systems, data science, industry analysis, environmental health, geotechnical engineering, behavioral psychology, occupational health and safety management, civil engineering, production management, infrastructure and transport systems, research methods, workforce, construction operations, professional development, business, political science, analytical methods, education and knowledge transfer |
| Topics: | Project Management, Research Practice, Cost Management, Health and Safety, Time Control, Engineering Principles, Business Strategy, Site Management, Human Resources, Digital Applications, Sustainability, Information Management, Governance |
| Descriptive scope: | 4 PCTA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here