A review of the digital twin technology application in energy industry for performance improvement.

Abstract

The paper investigated the use of digital twin (DT) technologies in the energy industry. It analyzed the available digital twin technology used in the energy industry using the Strength, Weakness, Opportunity, Threat (SWOT) analysis method. The DT serves as the real-time presentation of the actual process or physical object with the Internet of Things (IoT). Typically, fabrication work productivity depends on the process flow and the human behaviors that contribute to delay or non-productive time (NPT) - digital technology to learn the overall process, human behavior, and machinery uptime. Visual learning was established to monitor the operation activity as well as the construction work and to capture the general behaviors of the human such as welding, resting, taking a break or even non-productive work such as break outside break hour, smoking, wrong sequence of the working process and other external interruptions. This study will explore all the available DT technology in the market and its function and capabilities and then identify five (5) DT technology applications that can improve performance in the energy industry. After that, to determine and summarize the strength, weakness, opportunity, and threat of all five (5) applications of DT technologies already used in the energy industry using SWOT methodology. The SWOT analysis found that the benefit in terms of Strength and Opportunity is more significant than the threat and weakness of the Digital Twin technology. Then, it is clearly indicated that the DT technology can utilize in many other areas of business in objective to understanding the overall system efficiency and capable of providing information for accurate and precise decision making for the company.