Saipem recently took a more integrated approach at production data collection and elaboration recently launched an advanced pilot project: the deployment of a vast data collection and analysis system in the production lines of its Flagship CastorONE. Data is collected from multiple sources by means of communication infrastructures and articulated network systems that allow to connect to different machines and equipment. The most meaningful data are identified and pre-filtered. The data are then processed, aggregated and subject to advanced analytics in order to extract useful information on the productivity, the main process parameters, building on its already available tools to manage welding productivity.
This enables Saipem not only to build an integrated, real-time, comprehensive representation of the on-going activities, but also to gain new and valuable insights on the efficiency of its vessels during and after the execution of projects, across different phases, making it easier to compare the productivity estimations with the field performances. The advantages of data-driven continuous improvement are discussed too. This paper will provide a general overview of the system and of the results reached.
This paper will explore the process of conducting asset integrity management systems and the potential use for the existing facility data to analyze integrity status and predict any breach of integrity that would cause a direct major incident. In the dawn of the 4th industrial revolution and in the age of automation and artificial intelligence, asset integrity management systems are being integrated into a more sophisticated process of verification. Programs are being used to collect necessary risk-based data from inspection, maintenance programs and operational checklists in order to rationalize the integrity status and alert proponents of possible breach of integrity. These systems are more efficient than humans in predicting possible failures based on collective data from several critical elements from a facility and calculate the probability of failure based on the current integrity status. It is possible to optimize such systems to eliminate the human error factor and optimize inspection, maintenance and operation programs to better manage asset integrity. The result would be a software that would provide an overview of the plant’s integrity status and provide early alerts of any incoming incident event which allows the facility’s management to act accordingly and direct resources for effective prevention and mitigation.