Use of MCDM and AI Techniques for Mechanization of In-Service Inspection Planning Process

Part 1: Knowledge-Based Performance ImprovementInternational audienceThe in-service inspection planning process for topside piping equipment of aging oil and gas (O&G) production and process facilities (P&PFs) involves personnel with different kinds of expertise, experience, and knowledge as well as a vast amount of data and information. To simplify the inspection planning process and increase the quality of an inspection program, various industrial organizations as well as researchers have been developing numerous techniques in an isolated fashion to address the challenges pertaining to different activities involved in the inspection planning process. In order to mechanize the overall inspection process, suitable techniques need to be identified for the different activities carried out in a generic inspection planning process. This manuscript discusses the potential use of multi-criteria decision analysis (MCDM) and artificial intelligence (AI) techniques. It also provides evidence about the suitability of AI techniques in relation to fuzzy logic and artificial neural networks for the mechanization of the inspection planning process in a dynamic manner