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Contributor
HARNESSING AI FOR ENHANCED FACILITY DESIGN AND BUILDING MANAGEMENT IN PHARMACEUTICAL PLANTS
By Ryan Rennie , from the Spada-Rennie Group
In this article I explore the impact of artificial intelligence ( AI ) on Building Management Systems ( BMS ) in pharmaceutical plants , with a special focus on fully integrated smart building systems .
Supplied by Ryan Rennie
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' ll discuss the comprehensive benefits these systems offer , from optimised energy usage , integration of renewable energy , water conservation , to improved air quality and climate adaptability . Additionally , I ' ll explore the potential risks , such as job displacement , privacy concerns , and cybersecurity threats , and discuss effective mitigation strategies . I will uncover how AI and smart technologies are reshaping pharmaceutical BMS , enhancing operational efficiency , sustainability , and market access across the continent .
1 . Benefits of AI in facility design & BMS a . Optimised system design Generative design The design of a facility has only one constant : change . It is therefore important to have a signed-off first revision Good Manufacturing Practice ( GMP ) architectural layout and confirmation of the User Requirements Specifications ( URS ) early in the design phase . All the design work related to services like HVAC , electrical and utilities then have a baseline . Before the first services design is complete a first change will inevitably come into play . For instance , the client will change a process equipment supplier , and they need more space ; the client will want to introduce another manufacturing line or process and omit another , etc . Then all that work - and specifically from an HVAC perspective - will need to be redone . Remember that the whole HVAC design is based on a pressure cascade with carefully considered air volumes . Change one
Ryan Rennie , from the Spada- Rennie Group . room and the design has to change . The impact of these changes on b . the overall project timeline is massive . The redesign is a highly time-consuming process that can be sped up dramatically with an integrated AI design system .
Current tools such as Autodesk ’ s Revit allow engineers to create optimised building designs that AI will be able to evaluate to find the most efficient options . AI can further assist in creating multiple design options , optimising for energy consumption , airflow , temperature control , and system cost . It can help engineers choose designs that balance performance with cost-efficiency .
Predictive modelling AI enables more accurate predictive modelling by empowering architects and engineers to optimise cGMP manufacturing facility designs during the design phase by analysing large datasets such as historical weather data . It helps design HVAC systems that are more energy-efficient , cost-effective , and tailored to specific environments , factoring in aspects like occupancy patterns , local climate , and building usage . AI identifies potential bottlenecks , minimises risks , and maximises operational efficiency , ultimately reducing construction timelines and costs . Additionally , AI-driven design assists in resource allocation , layout optimisation , and energy efficiency , aligning facilities with sustainable and cost-effective practices .
Other AI tools that architects and engineers might utilise include text to image for idea generation , photo to sketch , image to video , augmented reality and process simulation . Energy management It is disturbing to see how often we go back to these sites after handover and find that the client has turned the BMS computer off and shut the door . The amount of information available on these systems ; the need for one of two full time BMS operators to maintain the system ; the requirement
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RACA Journal I November 2024 www . refrigerationandaircon . co . za