Author Archive for Peter Reynolds

Managing Operational Risk Needs Data in Context – on Any Device

Due to the complex, energy-intensive, and potentially hazardous and environmentally sensitive nature of most downstream petroleum refining, petrochemical, and chemical manufacturing processes and facilities, these sectors have traditionally relied upon automation and other operational technology (OT).  In recent decades, much of this investment has shifted to operational risk management software applications that reside above the […]

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Cybersecurity Implications for an Industry in Transition

Cybersecurity is a critical topic for many world regions, and indeed, for the middle east countries, this has become a natural defense and embedded in the industrial culture.  Cyber-warfare is a relatively new phenomenon for the GCC, and since high-level attacks struck in 2012, these companies have made industrial cyber security awareness as a top priority.  To help […]

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Predictive Maintenance or Predictive Operations?

When embarking on digital transformation, digitalization or significant changes to work process and re-engineering, it is often the maintenance organization and practices that are first considered. An essential ingredient for transformation is the application of machine learning and predictive analytics. These technologies have promised to remove unnecessary maintenance costs and shift industrial organizations to use […]

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Condition Based Maintenance is Still Reactive: Operations Need Advanced Analytics

I recently attended the Asian Downstream Week conference and exhibition, which took place in Singapore, October 26-27, is an anchor event of Singapore International Energy Week (SIEW). At the event, I had the privilege to hear from Martin Hawkins, chief operating officer from HMEL. HMEL is a joint venture between Hindustan Petroleum and Mittal Energy that has built […]

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Cloud-Based Process Simulation Platforms: Agile Cost Effective Engineering

Oil price volatility tied to over capacities has squeezed margins across the oil & gas industry, significantly reducing capital spend on major expansion projects, increasing the need to optimize existing assets, debottleneck plants, and take out cost across the board.   To support these objectives, process and plant engineers need improved, easier to use process simulation […]

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