Author Archives: Zinnia Ramirez

Kick off summer with the June 2021 edition of the Aurora Newsletter, featuring the latest insights into intelligent planning and scheduling. This issue explores how dynamic resource allocation can improve project management outcomes, highlights how leading aerospace organizations optimize production and maintenance operations, and examines the powerful integration of Siemens’ IPP&E software with Aurora’s advanced scheduling capabilities. Read the newsletter to discover how intelligent scheduling technologies help organizations solve increasingly complex operational challenges.

New Alliance with Collinear Group Will Drive Production Optimization

Stottler Henke has entered into a sales partnership with Collinear Group to expand the deployment and implementation of its Aurora™ intelligent planning and scheduling software. Through this collaboration, Collinear Group will support Aurora™ sales, configuration, and customer deployment efforts, helping organizations successfully implement advanced scheduling solutions.

Collinear Group brings extensive expertise in project management, aerospace systems engineering, software development, program management, and applied analytics. By combining Stottler Henke’s proven AI-based scheduling technology with Collinear Group’s implementation experience, the partnership is positioned to deliver greater value to customers tackling complex planning and scheduling challenges.

Together, Stottler Henke and Collinear Group are committed to helping organizations improve operational planning, optimize resources, and achieve more effective project execution with Aurora™, one of the industry’s leading intelligent scheduling solutions. Read the full press release.

Explore the July 2020 edition of the Aurora Intelligent Project Management Newsletter, featuring recent applications, integrations, and technical developments. This issue highlights Aurora’s role in supporting planning and scheduling initiatives at one of America’s national laboratories, its integration with Siemens’ IPP&E program management software, and insights from a paper and presentation presented at the 2020 IEEE Aerospace Conference. Read the newsletter to learn how Aurora continues to address complex planning and scheduling challenges across a wide range of industries.

Artificial Intelligence and Critical Chain Project Management Combine to Schedule Large, Complex Operations Efficiently

Stottler Henke has been awarded a U.S. Navy contract to develop an advanced ship maintenance scheduling solution built on its Aurora intelligent scheduling platform with Critical Chain Project Management (CCPM) capabilities. The system is designed to optimize complex maintenance activities by balancing resource constraints, improving schedule quality, and helping planners make more informed decisions for mission-critical naval operations. Read the full press release on the Stottler Henke website to learn more about the project and Aurora’s intelligent scheduling capabilities.

Aurora has been featured:

• Aerospace Tech Review
• Global Defence Technology

Stottler Henke presents “Leveraging PHM with Intelligent Scheduling to Improve Manufacturing Resilience,” at the 2020 IEEE Aerospace Conference.

This presentation examines how integrating Prognostics and Health Management (PHM) with intelligent scheduling can strengthen manufacturing operations in the face of changing conditions. It explains how predictive equipment health information can be combined with advanced scheduling techniques to make more informed maintenance and production decisions. Rather than reacting to unexpected equipment failures, organizations can proactively adjust schedules to reduce disruptions and better utilize available resources. The presentation also highlights how this integrated approach supports greater operational flexibility, improved asset utilization, and more resilient manufacturing processes. Together, PHM and intelligent scheduling provide a practical framework for helping manufacturers maintain productivity while responding more effectively to uncertainty.