150,000 SF Greenfield Fab Design
Semiconductor Client
Looking to maximize utilized space on an already crowded campus, a major semiconductor manufacturer asked SSOE to design a new fab on a plot originally planned as a loading dock. SSOE designed the 150,000 SF facility to support 50,000 SF of cleanroom manufacturing space with minimum impact to adjacent fabs during construction and operation.
This project presented several challenges which were resolved with creative design solutions:
Flexibility for Next-Gen Fab Equipment
The client requested maximum flexibility to support current and next-generation chip manufacturing tools. This impacted the structural and vibration design of the building, as well as, the routing of process material and waste removal feeds within the structure to support flexible tool layouts from day one.
No Support Buildings
The team was asked to maximize production space and find alternatives to using dedicated support buildings, like a Central Utility Building (CUB) or bulk gas yard. The client and design team collaborated on a utility gap analysis to determine capacity shortfalls. Upgrades were made to existing systems that were required to support the new manufacturing space. As a result, the team designed and implemented basebuild-style upgrades to several systems on adjacent fab infrastructure to support the new fab.
Meeting Egress Code Requirements
With barely the minimum seismic gap between the new fab and existing structures, difficulties in meeting code requirements for egress routing became a constraint for the project. A deep knowledge of the applicable regulations, combined with strong AHJ coordination, allowed SSOE to develop and implement a safe and code-compliant solution.
Utility and Waste Routing
In addition to feeding the new fab from upgraded, existing utilities serving an adjacent fab, some utilities needed under-slab routing, which required a custom sleeve to accommodate differential settlement between the two facility foundations. Likewise, process waste was routed through the subfab area of an adjacent building to reach existing tie-ins capable of supporting the flows to existing collection points for on-site treatment and off-site removal of waste streams.
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SSOE is actively piloting AI Chat large language models (LLMs) or copilots that use Natural Language Processing (NLP) to streamline both design and development tasks, transforming how our teams interact with software and each other.
By integrating chat LLM engines into platforms like Revit, we’re enabling users to prompt complex actions using simple, conversational commands. In Revit, this means automating tasks such as modeling elements, cleaning up parameter data, managing annotations and dimensions, and organizing sheets—without writing scripts. These automations and quality prompts can be shared across project teams, accelerating workflows and reducing manual effort.
Similarly, our internal Software Development Community is leveraging GitHub Copilot to expedite coding tasks. Developers can generate and refine code using NLP prompts, tapping into GitHub’s extensive Repo to move faster from concept to implementation.
Together, these tools represent a shift from traditional, expert-driven scripting to intuitive, AI-assisted automation, unlocking new levels of efficiency and scalability across our projects.
SSOE is utilizing Microsoft Copilot Edge and M365 to significantly enhance work efficiency and accuracy across various departments. Copilot is accessible to all staff after training. Key areas of application include using it as a writing assistant, for idea generation, document summarization and generation, research assistant, excel assistant, programming code assistant, language translations, product comparison and data analysis. Use of Copilot has become part of the everyday life of SSOE employees who have identified key ways it can help them become more efficient with their daily tasks as well as more accurate in their deliverables.
Today, 100% of SSOE employees have taken the voluntary training and have access to Copilot Edge, achieving early our October 1, 2025 goal.
We found ourselves in need of a more robust tool to enhance resource forecasting and staff assignment capabilities. Instead of waiting for the perfect tool, we’re building it. SSOE’s in-house technology team has developed and piloted a tool that aims to forecast optimal staff mix and duration for new projects against existing workload to better understand capacity and manage resources efficiently. Additionally, the tool will allow teams to identify gaps to optimal staff mix.
SSOE has developed a proof-of-concept to use an AI Agent to act as a Master Engineer and Architect trained in SSOE’s processes, best-known-methods, and trainings. Our data structure is being remodeled to enable better use of our proprietary knowledge to train the agent on the ‘SSOE way’.
We helped our client visualize and optimize façade design for occupant comfort—long before breaking ground through the use of the Autodesk Forma tool. It allows the designer to rapidly experiment with the building’s geometry and façade design to promote sustainability, prioritizing quality of spaces and comfort for end uses, especially in extreme climates (daylighting and microclimate analysis tools) at the project’s exact geographic location, using location-specific environmental data.
Discover how SSOE is using Autodesk Forma to improve sustainability outcomes for industrial projects: SSOE Group: Improving sustainability outcomes for industrial projects with Autodesk Forma.
Autodesk Construction Cloud (ACC) is SSOE’s enterprise-wide project delivery platform. We partner with the Autodesk Product team and have research access. Use of the AI Assistant allows our design teams, owners, and general contractors the ability to query the project specifications for quality, answers, and more rapid responses to RFIs, submittals, or issues.