In this session, we’ll explore how Woodside successfully reduced thousands of maintenance hours and banked over 7 figures in savings by optimising maintenance strategies.

We’ll dive into the innovative maintenance strategy review tool that was developed in-house, utilising diverse data sources and applying fundamental reliability techniques. This approach quickly pinpointed over, under and incorrectly maintained equipment, facilitating targeted reviews for data-driven decision making.

• Uniting reliability fundamentals and data science.
• The effectiveness of a minimum viable product (MVP) for quick wins.
• Deep dive into the strategy review tool & how we achieved rapid business integration and sustained value delivery.
• Future plans and application advancements.
• 7 figures in annualized savings by optimising maintenance using operational data and reliability principles.
• Saving thousands of maintenance hours.
• The direct benefits of a data-driven approach.
• Slowly changing culture around data collection and the benefits of good data collection.

Maintenance and reliability professionals are increasingly turning to data-driven approaches to enhance operational efficiency and asset longevity. This panel discussion delves into the two paramount challenges we're facing as we navigate the complexities of data utilization: data quality and integration, and the skill gap in data analytics.

Ensuring data quality and seamless integration still poses a significant hurdle. Maintenance and reliability operations generate vast amounts of data from diverse sources, including sensors, equipment logs, and maintenance records. However, inconsistencies, inaccuracies, and fragmentation in data can undermine decision-making processes. The panel will explore strategies for improving data quality, standardizing data formats, and integrating disparate data sources to create a cohesive and reliable data ecosystem.

The skills gap in data analytics also remains a critical issue. While advanced data analytics tools and techniques offer tremendous potential, the lack of personnel with the requisite expertise to leverage these tools effectively hinders progress. This discussion will address the need for upskilling existing staff, attracting new talent with data science proficiency, and fostering a culture of continuous learning within maintenance and reliability teams.

Join us as industry leaders share insights, experiences, and practical solutions to these pressing challenges, paving the way for a more data-savvy and resilient future in maintenance and reliability.