Modular Construction of Industrial Buildings and Lean Thinking—Identifying the Role of Daylight through a Case Study
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Published:2023-09-06
Issue:18
Volume:15
Page:13354
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ISSN:2071-1050
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Container-title:Sustainability
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language:en
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Short-container-title:Sustainability
Author:
Mavridou Theodora1, Nanos Nikolaos2, Doulos Lambros3ORCID
Affiliation:
1. School of Mechanical and Design Engineering, University of Portsmouth, Portsmouth PO1 3DJ, UK 2. School of Civil Engineering and Surveying, University of Portsmouth, Portsmouth PO1 3AH, UK 3. School of Applied Arts and Sustainable Design, Hellenic Open University, 26335 Patra, Greece
Abstract
This research looks at the optimisation of industrial buildings through the application of the principles of lean thinking and philosophy, with an emphasis on daylighting in the design of industrial buildings. With the use of multiparametric analysis tools, we provide a solution for the optimized design of a roof system for the provision of daylight, whilst maximising the benefits and minimising the cost during its lifetime, in different geographic and climatic regions in Greece. An optimisation algorithm has been proposed that improves the selection of the optimal roof opening type and geometry for industrial buildings in different geographical locations. The investigation of a roof system model was based on the maximum performance of daylighting, while reducing unnecessary energy use and cost. To reach our solution, we investigated the sawtooth roofing system in terms of energy cost (cooling, heating, and lighting), geography (orientation, location), and building variables (the opening dimensions and number). This has been achieved through the use of multi-parametric design, computational simulations, genetic algorithms, and the post-processing of results through statistical analysis. The use of natural lighting proved to be an effective sustainability strategy, providing energy savings of up to 20–30%, and offering economic advantages, hence presenting a comprehensive approach that benefits stakeholders and end-users by reducing the thermal loads, cooling requirements, initial HVAC costs, and overall waste. The developed algorithm has identified the optimal opening size and distance as ranging between 10 and 11 m for the conditions examined.
Subject
Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction
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