Artificial Intelligence HSE Monitoring & Digital Value Stream Mapping for Prefabrication Yard

Abstract

In the Oil and Gas (O&G) construction project, the most critical part is monitoring and tracking the overall productivity of prefabrication. Productivity measurement was previously done using a manual method, where the process and workers’ productivity were recorded and analyzed. With the rapid rise of the Industrial Revolution 4.0 (IR 4.0), applying digital technology will improve overall productivity and provide continuous process improvement. There is a lot of digital technology available in the era of IR 4.0; among the technologies potentially adopted in O&G prefabrication work is digitalization through the Internet of Things (IoT). With the various digital solutions in the market, the research study aims to understand and investigate the adoption and application of Digital Value Stream Mapping (DVSM) for monitoring and tracking overall prefabrication productivity through a questionnaire survey method. After the investigation, the Digital Value Stream Map (VSM) framework was developed for productivity monitoring and tracking for prefabrication work in the O&G industry. Then, validate the developed DVSM framework model through interviews with subject matter experts (SMEs) and pilot deployment of the DVSM framework model at a selected onshore prefabrication yard. The pilot deployment of the DVSM framework provided the outcome of the analysis of the existing process flow, then an enabler to predict the future state of the onshore prefabrication process flow by eliminating the waste produced from labor and material. Finally, the pilot deployment of the conceptual DVSM framework model has proven that the model has improved the overall onshore prefabrication productivity; the study recommends further expand the DVSM framework model in the offshore environment where to track and improve overall construction productivity during the hook-up and commissioning phase either for Brownfield projects or Greenfield projects.