An approach for process optimisation of the Automated Fibre Placement (AFP) based thermoplastic composites manufacturing using Machine Learning, photonic sensing and thermo-mechanics modelling
“…This design was subsequently validated through the tensile testing of 3D-printed samples. A mixed method that combines machine learning algorithms, virtual sample generation, physics-based simulations, and experimental data can be used to improve automated fiber placement (AFP) in the production of thermoplastic composites [ 265 ]. Chiu et al utilized a genetic algorithm (GA) and conditionally variable automatic encoder (CVAEs) to analyze a binary composite system with edge cracks and a lattice-like structure [ 266 ].…”
Section: Challenges and Future Directionsmentioning
Regenerative medicine aims to address substantial defects by amplifying the body’s natural regenerative abilities and preserving the health of tissues and organs. To achieve these goals, materials that can provide the spatial and biological support for cell proliferation and differentiation, as well as the micro-environment essential for the intended tissue, are needed. Scaffolds such as polymers and metallic materials provide three-dimensional structures for cells to attach to and grow in defects. These materials have limitations in terms of mechanical properties or biocompatibility. In contrast, biominerals are formed by living organisms through biomineralization, which also includes minerals created by replicating this process. Incorporating biominerals into conventional materials allows for enhanced strength, durability, and biocompatibility. Specifically, biominerals can improve the bond between the implant and tissue by mimicking the micro-environment. This enhances cell differentiation and tissue regeneration. Furthermore, biomineral composites have wound healing and antimicrobial properties, which can aid in wound repair. Additionally, biominerals can be engineered as drug carriers, which can efficiently deliver drugs to their intended targets, minimizing side effects and increasing therapeutic efficacy. This article examines the role of biominerals and their composite materials in regenerative medicine applications and discusses their properties, synthesis methods, and potential uses.
“…This design was subsequently validated through the tensile testing of 3D-printed samples. A mixed method that combines machine learning algorithms, virtual sample generation, physics-based simulations, and experimental data can be used to improve automated fiber placement (AFP) in the production of thermoplastic composites [ 265 ]. Chiu et al utilized a genetic algorithm (GA) and conditionally variable automatic encoder (CVAEs) to analyze a binary composite system with edge cracks and a lattice-like structure [ 266 ].…”
Section: Challenges and Future Directionsmentioning
Regenerative medicine aims to address substantial defects by amplifying the body’s natural regenerative abilities and preserving the health of tissues and organs. To achieve these goals, materials that can provide the spatial and biological support for cell proliferation and differentiation, as well as the micro-environment essential for the intended tissue, are needed. Scaffolds such as polymers and metallic materials provide three-dimensional structures for cells to attach to and grow in defects. These materials have limitations in terms of mechanical properties or biocompatibility. In contrast, biominerals are formed by living organisms through biomineralization, which also includes minerals created by replicating this process. Incorporating biominerals into conventional materials allows for enhanced strength, durability, and biocompatibility. Specifically, biominerals can improve the bond between the implant and tissue by mimicking the micro-environment. This enhances cell differentiation and tissue regeneration. Furthermore, biomineral composites have wound healing and antimicrobial properties, which can aid in wound repair. Additionally, biominerals can be engineered as drug carriers, which can efficiently deliver drugs to their intended targets, minimizing side effects and increasing therapeutic efficacy. This article examines the role of biominerals and their composite materials in regenerative medicine applications and discusses their properties, synthesis methods, and potential uses.
“…The pressure is applied to the substrate by a compaction roller and the tapes are consolidated upon deposition through which any entrapped air gets compressed out of the composite structure. 14,15 Limitations of the current modelling perspectives Many numerical models of the AFP manufacturing process have been developed to overcome the trial-and-error approaches for estimating suitable process windows of manufacturing parameters. Most models simplify the problem into one or two dimensions by making assumptions about planar effects.…”
Section: Automated Fibre Placement (Afp) Process Overviewmentioning
confidence: 99%
“…The pressure is applied to the substrate by a compaction roller and the tapes are consolidated upon deposition through which any entrapped air gets compressed out of the composite structure. 14,15 Figure 1.Schematic layout of the tape placement system (left) and the AFP machine (right).…”
Many numerical models of the Automated Fibre Placement (AFP) manufacturing process have been developed to assist in the design process of composite components and structures. Although the tape placement process, in general is a 3-D transient process, limited models considering the 3-D nature of the process exist. This paper describes the development of a 3-D Finite Element (FE) model incorporating the effect of non-concentrated input heat flux distribution on adjacent paths. The model can predict an accurate thermal history of a thermoplastic composite laminate for a complete AFP deposition process. Composite laminates having plies made up of both a single tow and multiple tows have been simulated to study their thermal behaviour during the manufacturing process. Simulations have been conducted both with and without considering the input heat effect on adjacent tows for comparison. Temperatures were measured by embedding two different configurations of optical fibre Bragg grating (FBGs) sensors within the laminate during the lay-up process. This served a dual purpose of validating the model as well as the experimental methodology.
“…The bonding model can be incorporated in thermal pro le prediction applications to directly predict the ILSS of composites. Ultimately a graphical user interface (GUI) based tool on the hybrid approach as proposed by Islam et a [27], combining the advantages of ML algorithms, virtual sample generation (VSG) techniques, nite element simulations of the AFP process and experimental data to improve the AFP process can also be developed. Such optimization tools could be embedded in the DT of the AFP process to enhance the AFP process optimization and control for manufacturing better quality composites.…”
Automated fibre placement (AFP) is an advanced robotic manufacturing technique which can overcome the challenges of traditional composite manufacturing. The interlaminar strength of AFP-manufactured composites depends on the in-situ thermal history during manufacturing. The thermal history is controlled by the choice of processing conditions and improper interfacial temperatures may result in insufficient bonding. Being able to better predict such maintenance issues in real-time is an important focus of smart manufacturing and Industry 4.0 to improve manufacturing operations. This study focuses on developing a digital tool for process monitoring which integrates the physical and digital space of the AFP process. The digital tool constitutes a machine learning model to predict the in-situ thermal history during AFP manufacturing. The predicted thermal history can be compared with the real-time in-situ temperatures during manufacturing to predict the quality of the layup. A GUI application is developed to provide benchmarking data for comparison with real-time temperatures during manufacturing enabling monitoring and predictive maintenance of the AFP process paving way for the development of a digital twin of the AFP composites manufacturing process.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
