A work process model for PdM evaluation in study phase: A case study

Abstract

To a large degree, the fluctuation in oil prices has forced Oil & Gas (O&G) companies to invest in technologies that can aid lower costs and mitigate risk. This financial stability depends on a big extent on the performance of the equipment. One of the most meaningful innovative solutions is without doubt Predictive Maintenance (PdM). Due to predictive maintenance, failures can be foreseen and maintenance activities can be scheduled only when required. The reward would be increased equipment effectiveness and reduced unscheduled downtime. There are two approaches for establishing the PdM solution: retrofit at the operating phase and design at project phase. Aker Solutions identified this opportunity and provided the groundwork for this master thesis. There is very limited and fragmented information on how to design for PdM in new projects, especially in the study phase. Therefore, the main purpose of this project is to contribute with developing work processes which can help assess the integration of predictive maintenance engineering in projects. A work process model was developed to fit in the study phase (earliest project phase) of Aker Solutions current model. The new model was developed after analyzing Aker Solutions work processes and with the help of standards and literature. The results and feedback obtained from the supervisors and Aker Solutions maintenance engineering personnel were critical and valuable, which were adapted to the new model to generate even more realistic work processes. The developed model serves as the basis towards the improved implementation of PdM solutions and allows for a better understanding of the assets and control of a project. The new model has not been implemented in real life and might not be optimal if PdM is not the preferred maintenance technique. It was found that a PdM work process model will be more accurate if it can seamlessly match and adapt to the current work processes of the organization, and predictive maintenance solutions will be more effective if they are considered and evaluated during early project phases. The PdM concept is very complex, and the model still needs further exploration and enhancements. This will be a focus area in Aker Solutions internal PEM (Project Execution Model) improvement work in the coming years and closely connected to the O&G operators’ digitalization journey. These work processes offer a systematic approach for PdM engineering in the study phase, prioritizing cost-effective methods which can be adapted to satisfy different levels of deliverables.