Composites manufacturing is characterized by many degrees of freedom. Different materials, geometries and thermo-dynamical conditions contribute to a behavior that is difficult to predict. Monitoring the running process (in-line monitoring) eliminates the need for prediction; real time data provided by appropriate sensing systems can be used in the direction of process optimization, quality upgrade or material characterization. The aim of the review at hand is to record and discuss the latest progress in the field of in-line composites monitoring with a focus on Fiber Reinforced Polymericbased (FRP) composite structures. Summaries of each sensor’s principles of operation, appropriate association with polymer/composite properties detection, brief descriptions of representative studies, a critical overview of implementation aspects and discussion on the upcoming trends, contribute in constructing a complete picture

The curing behavior of a fiber-reinforced polymer composite part is interesting for both the industrial and scientific community, for it is related to process optimization, quality upgrade, and material characterization. The study at hand focuses on the potential of temperature measurements as a means to monitor curing; kinetic analysis which conventionally is being done for small neat resin samples in a thermally stable environment (laboratory instruments), is in this study implemented for actual scale composite samples in an environment with significant thermal gradients (manufacturing). To ensure the success of this transition, live temperature data and kinetic parameters derived from DSC of composite samples were used as input to the kinetic equations. Process monitoring with thermocouples that was compared with dielectric constant monitoring and conventional kinetic analysis confirmed the validity of the method. An application with infrared thermography determined the impact of heat insulators within the composite (e.g. delaminations) on the superficial curing degree.

Liquid composite molding (LCM) suffers from multiple factors that contribute to pronounced uncertainty of process characteristics. This results in compromised reproducibility which is associated to high scrap or the unpredictable behavior of approved parts. However, LCM is still attractive for Fiber-reinforced polymeric composites (FRPC) production due to its economic advantage (i.e. in relation to Autoclave), the capability of some of its variants to produce high performance parts and its potential for process optimization. This review analyzes each uncertainty with respect to its origins and its impact in part or process, based on a combination of past literature and original numerical results. The possible methods to counteract uncertainties are critically discussed, with an eye on both the scientific and feasibility (technical/economical) aspects. The overall aim is to provide to future LCM implementations a roadmap of the most critical challenges and solutions regarding the establishment of a reproducible process. Graphical abstract

Research concerning the measurement of the permeability of fabrics for polymer matrix composites has been ongoing since several decades, but remains in the focus of applied research for liquid composite molding. Today, several systems and technologies for the measurement of in- and out-of-plane permeability are available, but still no approach has gained acceptance as a common standard. A main requirement for reliable permeability measurement technology is the reproducibility of results when comparing different characterization systems. In this context, benchmark studies are an appropriate method to evaluate the reproducibility of a technology. This study presents a benchmark on unsaturated out-of-plane permeability measurement systems based on flow front monitoring via ultrasonic sensors. Two corresponding systems are compared in the study comprising carbon and glass wovens as well as non-crimp fabrics. The out-of-plane permeability was measured with both systems at three different levels of fiber volume content and three repetitive measurements. The results gained with the systems showed good compliance with relative deviation of the permeability values mostly below 50%. Textile-induced inhomogeneities and varying measurement parameters, e.g. injection pressure, were found to be main reasons for the deviations.

Filling is a critical stage in resin transfer molding (RTM) manufacturing; it is associated to the formation of impregnation imperfections which can lead to defects. Simulations are typically employed to predict the flow behavior, which however need the preform permeability as an input. Significant work has been done in the past in in-plane permeability identification. This study focuses on the determination of the permeability of unidirectional curvatures typically encountered in RTM parts. A model for analytical calculation and a numerical optimization approach for inverse determination have been developed and applied in an omega-shaped RTM part where material-embedded flow sensors were employed for the essential flow measurements. The differences found between the experimentally derived permeability of the curvature and theoretical predictions were discussed critically and associated to flow time disagreements between simulations and reality.