PUMA publications for /tag/Processing%20processing%20data%20engineeringThu Jan 11 11:54:20 CET 2024Journal of Computational Design and Engineering41460-1478Data processing, analysis, and evaluation methods for co-design of coreless filament-wound building systems1020232023 analysis balangé bischoff building co-design coreless data engineering evaluation faserverbund filament-wound forster gil gresser guo hügle itke kannenberg knippers menges methods middendorf mindermann processing schwieger systems zechmeister The linear design workflow for structural systems, involving a multitude of iterative loops and specialists, obstructs disruptive innovations. During design iterations, vast amounts of data in different reference systems, origins, and significance are generated. This data is often not directly comparable or is not collected at all, which implies a great unused potential for advancements in the process. In this paper, a novel workflow to process and analyze the data sets in a unified reference frame is proposed. From this, differently sophisticated iteration loops can be derived. The developed methods are presented within a case study using coreless filament winding as an exemplary fabrication process within an architectural context. This additive manufacturing process, using fiber-reinforced plastics, exhibits great potential for efficient structures when its intrinsic parameter variations can be minimized. The presented method aims to make data sets comparable by identifying the steps each data set needs to undergo (acquisition, pre-processing, mapping, post-processing, analysis, and evaluation). These processes are imperative to provide the means to find domain interrelations, which in the future can provide quantitative results that will help to inform the design process, making it more reliable, and allowing for the reduction of safety factors. The results of the case study demonstrate the data set processes, proving the necessity of these methods for the comprehensive inter-domain data comparison.Thu Jan 11 11:54:20 CET 2024Journal of Computational Design and Engineering41460-1478Data processing, analysis, and evaluation methods for co-design of coreless filament-wound building systems102023faserverbund hügle 2023 knippers engineering analysis forster itke processing menges guo filament-wound co-design coreless methods data gil mindermann zechmeister building gresser middendorf kannenberg systems balangé evaluation schwieger bischoff The linear design workflow for structural systems, involving a multitude of iterative loops and specialists, obstructs disruptive innovations. During design iterations, vast amounts of data in different reference systems, origins, and significance are generated. This data is often not directly comparable or is not collected at all, which implies a great unused potential for advancements in the process. In this paper, a novel workflow to process and analyze the data sets in a unified reference frame is proposed. From this, differently sophisticated iteration loops can be derived. The developed methods are presented within a case study using coreless filament winding as an exemplary fabrication process within an architectural context. This additive manufacturing process, using fiber-reinforced plastics, exhibits great potential for efficient structures when its intrinsic parameter variations can be minimized. The presented method aims to make data sets comparable by identifying the steps each data set needs to undergo (acquisition, pre-processing, mapping, post-processing, analysis, and evaluation). These processes are imperative to provide the means to find domain interrelations, which in the future can provide quantitative results that will help to inform the design process, making it more reliable, and allowing for the reduction of safety factors. The results of the case study demonstrate the data set processes, proving the necessity of these methods for the comprehensive inter-domain data comparison.Processing processing data engineeringCommunity for tag(s) Processing processing data engineering