Nayef Bou Chaaya, Vice President, Middle East, Turkey & Central Asia, AVEVA.

    Nayef Bou Chaaya explains how connected industrial data, predictive analytics and digital twins can help energy and marine companies improve reliability, optimise operations and advance decarbonisation.
    Industrial digital transformation depends on more than deploying new technology. Connecting engineering, operations and maintenance data gives organisations a clearer understanding of their assets, helping teams make informed decisions and measure the business value of their investments.

    Nayef Bou Chaaya, Vice President, Middle East, Turkey & Central Asia at AVEVA, spoke to Tahawultech on why trusted, contextualised data provides the foundation for improving industrial performance. With three decades of experience in industrial technology, including senior roles at Schneider Electric and Invensys, Nayef leads AVEVA’s regional strategy, sales and customer engagement across energy, infrastructure and manufacturing.

    Speaking to Sandhya D’Mello, Technology Editor, CPI Media Group, ahead of ADIPEC 2026, Nayef discusses AVEVA’s approach to connecting the asset lifecycle, the opportunities for predictive analytics and optimisation, and the role of digital technology in supporting more efficient energy production and marine decarbonisation.

    Interview excerpts

    What will AVEVA showcase at ADIPEC 2026, and which energy-sector challenges will take priority?
    AVEVA will showcase CONNECT, its industrial intelligence platform linking asset design, construction, operations, maintenance and optimisation. Demonstrations will cover enterprise visualisation, industrial AI assistance, advanced analytics and contextualised data sharing across organisations, ecosystems and platforms including Databricks, Snowflake and Microsoft Fabric. Unified engineering and digital twins will connect project delivery with operations, alongside predictive analytics, process and energy optimisation, and unified supply chain capabilities. Planned Model Context Protocol (MCP) server integration with AVEVA PI System will enable AI applications and large language models to access operational data.

    “Customer priorities include energy security, operational resilience, and supply chain performance across the lifecycle.”

    How can connecting engineering and operational data help energy companies overcome fragmented information and make faster decisions?
    Connecting engineering, operations, maintenance and business data gives teams a shared foundation for decisions. CONNECT and AVEVA PI System bring operational technology, engineering and IT information into one governed environment, establishing a trusted source across the asset lifecycle. A digital twin develops from design and construction, incorporating operational and maintenance data throughout its life. Engineers can assess modifications against actual operating conditions, while operators understand the asset’s original design, intended performance and constraints. Shared context improves collaboration, reduces conflicting decisions and supports faster responses.

    Teams can work more efficiently while understanding the implications of their decisions for asset performance and safety.

    Where are real-time visibility, predictive analytics and optimisation delivering the greatest measurable improvements in asset performance?
    Operations, maintenance and value chain optimisation offer the strongest opportunities. Near-real-time visibility, supported by consolidated, contextualised data, helps teams identify issues earlier and strengthens awareness from control rooms to business leadership. Predictive analytics uses AI and machine learning, trained on historical data and informed by incoming operational information, to anticipate equipment failures, reduce unplanned shutdowns and protect production. Our use cases indicate energy savings of 5–20% and operational efficiency improvements of 3–10%, depending on application and operating conditions. Combined, these capabilities improve reliability, availability and decisions while reducing operating costs and emissions, supporting sustainability objectives and keeping safety the overriding priority.

    Which digital investments should energy companies prioritise today to strengthen long-term competitiveness and sustainable production?
    Energy companies should prioritise trusted industrial data, predictive maintenance, and process and energy optimisation. Reliable, contextualised information and secure sharing underpin every subsequent application. Predictive maintenance protects production, reduces maintenance costs and extends asset life by preventing unplanned equipment shutdowns. Optimisation combines advanced process control, AI and models based on physical principles to improve production and energy efficiency. Savings can fund further digital transformation while supporting emissions reduction. Cybersecurity remains essential throughout. Investment decisions should begin with defined business outcomes and clear measurement criteria, ensuring technology delivers demonstrable returns through safer, more efficient and sustainable production that strengthens long-term market competitiveness.

    How can AVEVA help the marine industry translate decarbonisation goals into measurable progress while supporting the UAE’s net-zero ambitions?
    AVEVA connects vessel, fleet and port data to improve energy visibility, emissions monitoring and operational decisions. AVEVA PI System consolidates and contextualises information to support fuel efficiency, vessel performance and transparent carbon reporting. Predictive maintenance strengthens equipment reliability and reduces unplanned downtime, while marine design and engineering capabilities support efficient vessels and less rework from inception. CSL Group reports a 29% carbon-intensity reduction across 40 vessels and 8,000 tonnes of CO₂ avoided using AVEVA PI System. Zamil Marine unifies data across 73 offshore vessels. Such capabilities help translate the UAE’s net-zero ambitions into measurable operational improvements, underpinned by trusted industrial data.


    Source: Tahawul Tech

    Comments are closed.