Refinery scheduling is more complex than ever. Volatile crude markets, shifting demand and constant operational changes can make it difficult to respond quickly while protecting margins.

Process simulation tools—such as steady-state and dynamic modeling platforms—provide value far beyond traditional design and analysis.

As industrial organizations seek to scale digital transformation initiatives, the ability to develop custom business applications fed by real-time operational data helps operational technology (OT) and data teams support enterprise and on-site use cases.

Operating one of the world’s largest methanol production facilities requires reliability teams to manage critical machinery and instrumentation in a fast-paced, complex manufacturing environment.

Manufacturers routinely lose margin due to the gap between what is planned, what is scheduled, and what actually happens on the plant floor.

OCP Ecuador operates a critical 485-kilometer heavy crude pipeline that transports approximately 30% of Ecuador’s oil production, making reliability essential to safe, efficient operations.

Developing projects in emerging industries often requires making critical decisions with limited information. Engineering teams must evaluate multiple design alternatives early in the project lifecycle to identify the optimal configuration that maximizes return on investment while minimizing risk.

In a world where supply chains, energy costs, feedstock availability and project economics can shift overnight, industrial leaders need the agility to act with confidence.

As industrial organizations accelerate AI, advanced analytics and digital transformation initiatives, traditional point-to-point data architectures are becoming a major barrier to innovation.

Electric utilities are under increasing pressure from regulators, customers and stakeholders to integrate renewable energy resources while maintaining reliability, power quality and operational flexibility.