Predictive maintenance (PdM) analysis matrix: A tool to determine technical specifications for PdM ready-equipment

Abstract

Predictive maintenance (PdM) and operations optimisation are expected to generate the highest industrial and societal impact within the oil and gas industry. Such an optimistic expectation requires several changes in asset design and maintenance management. Nowadays, design for maintenance and maintenance support needs are mainly guided by the IEC 60706-2 standard. However, Designing for PdM ready-equipment is not yet part of that standard. To design PdM ready-equipment a specific analysis method shall be performed to evaluate the technical requirements and specifications of designed equipment to be PdM ready. Therefore, the purpose of this paper is to propose and demonstrate a PdM analysis method that helps to specify the technical specifications to monitor and predict the health of a specific physical asset. The proposed matrix is an evolution of further development of failure Mode, effect and criticality analysis (FMECA) and failure mode symptoms analysis (FMSA) rather than a revolutionary analysis. The case study method is used to extract stakeholders needs of what they expect from PdM analysis (PdMA) and how practical such type of analysis shall be. The developed PdMA matrix shows a simple relation between failure (their modes/levels) and measured abnormal symptoms and tracking and prediction indicators. The electric generator is used to demonstrate the use of the matrix. The PdMA matrix can be developed further to be more quantitative by including the probability of detection and probability of prediction.