A Case for Applications of Machine-Vision-Aided Industrial Robotics in Pipeline Bolting

Abstract This paper addresses the case for a practical application of AI by incorporating it into the process of installing and removing bolts from piping joints. The major cases identified are reducing human error and bridging the construction labor gap. This paper then discusses the application of AI by describing the 3 guiding objectives in tool-design identified by industry, safety, speed, and quality, and the various industries where this application is immediately relevant. The current process for industrial bolting is still heavily reliant on human labor, and thus prone to human error. As industrial assets age, they become less forgiving of human error and thus more prone to risk of incident. There is a direct correlation between the quality of bolting labor and bolting reliability. Bolting labor quality needs to improve to mitigate risk of industrial incidents. Emerging research and development has identified machine vision, a form of AI, as a key opportunity to improve bolting reliability by automating select components of bolting labor. In parallel, there is a continued increase in demand for bolting labor projected across industrial construction. It will be difficult for construction crews to meet industry needs at the current staffing levels. Continuing to pursue research and development of machine-vision enabled industrial robotics to improve the safety, speed, and quality of bolting labor is also a step in bridging the construction labor gap. After surveying over 75 industry leaders, it became apparent that bolting labor is analyzed by 3 major factors: safety, speed, and quality. These factors are significant in piping alignment, worker safety, flange seal integrity, equipment reliability, and worker efficiency. Not only is the quality of bolting labor important for the duration of the work, but the impact of the labor is in effect over the course of the equipment runtime until the next turnaround cycle (often 4+ years) long after the bolting crew has left the jobsite. In pursuit of delivering improved quality bolting labor to piping joints, emerging research and development has led to new designs of a hands-free bolting robot. This new approach has been intentionally designed following industry guidance along the same 3 criteria: safety, speed, and quality. The research and product development addressed in this paper is initially targeted towards industrial infrastructure in the following areas: facility maintenance, capital projects, facility retrofits, and new facility construction. This positions the emerging technology strategically across all types of energy infrastructure and in a variety of relevant industries: oil & gas, chemical/petrochemical, pharmaceuticals, food & beverage, water/wastewater/water treatment/sewage, agriculture, cosmetics, irrigation, nuclear, mining, and green/sustainable manufacturing. There is a strong case for improving bolting reliability and bridging the construction labor gap across all of these industries.