A new type of fiber reinforced filament materials for Fused Deposition Modeling applications has been developed. Polylactic acid (PLA), compounded with two types of plasticizer, is reinforced with bamboo and flax fibers. The fiber fractions are characterized by measuring their length (l) over diameter (d) before and after compounding so that the effect of the l/d on the final filament properties can be systematically studied. The pre‐processing and processing activities, to produce filaments with a diameter of 3 mm, are described. The porosities and the orientation of the fibers in the filament are assessed to predict the theoretical stiffness of the filament via short fiber mechanics which is compared to the experimental results. Reinforcing the PLA filament with short bamboo fibers (l/d = 4–5) increases the modulus with 91–230%, whereas the dust‐like fractions only show an increase up till 39%. The glass transition temperature of the produced filaments is also determined to investigate the suitability of the filaments and finally a demonstrator part was printed. POLYM. COMPOS., 40:1951–1963, 2019. © 2018 Society of Plastics Engineers

Recently, a novel two-component injection molding process has been developed for combining thermoplastics with thermoset rubbers. This process is of interest for example when thermoplastic parts include seals which are usually produced out of thermoset rubber. The present study evaluates the influence of different process parameters on the bond strength by means of a half factorial experimental design. The considered process parameters are the mold temperature at the interface, the injection temperature, the injection speed, the holding pressure, and the initial roughness of the thermoplastic part at the later interface. The study indicates a large influence of the mold temperature at the interface. Furthermore, the holding pressure only affects the adhesion strength when it is set too low or when the holding time is too short. The other process parameters have no significant effect on the adhesion strength.

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Multicomponent injection molding often combines a stiff thermoplastic material with a thermoplastic elastomer or thermoplastic vulcanite. Recently, for high‐demanding applications, a novel process has been developed to replace these thermoplastic elastomers or vulcanite with a thermoset rubber, for example, NBR or EPDM. One of the most important properties of a two component product is an adequate adhesion between both components. This paper describes a method, which combines experiments and numerical simulations to predict the adhesion strength between a thermoplastic, semicrystalline HDPE, and an EPDM thermoset rubber. This method uses numerical simulations of the interfacial temperature and the local degree of cure. The local interface temperature is combined with the results of DSC measurements to predict the degree of melting, subsequently linked to the ability to develop adhesive strength. The degree of cure is used to determine the local rubber strength. The combination of the given data will be used to predict interfacial strength. The results obtained by proposed numerical strategy have been successfully validated with experimental data on a simple plate product. POLYM. ENG. SCI., 59:1489–1498 2019. © 2019 Society of Plastics Engineers

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Within polymer processing, nowadays, one has to deal with higher variations in material properties, for sure if one deals with recycled thermoplastic materials. Those waste streams typically can be of the same polymer type, but different products and or applications. To end up with a as homogeneous as possible material, typically solid mixing of the different batches is performed at large scale. Depending of the application and origin of the material, there is still a possibility to cope with larger variation within material properties. The most important material property for standard polymer processing as injection moulding or extrusion is the shear viscosity behavior in a large range. Within this investigation, at first, a strategy is developed to identify this variation in an industrial way. Next, a strategy is developed to use this characterized material data within a 1d approach valid for several types of the extrusion process. To end up with a physical reliable numerical tool coping with stochastics within data, there is a need to identify a correlation as function of time within the characterization of the shear viscosity. Within the process simulation, this correlation time is also used to implement stochastic information in a physically relevant way. This investigation can also be seen as a multiscale approach, as material characterization is done at meso scale; on processing scale (macro scale), local stochastic changes are compensated within the processing. In this investigation, the comparison is made between the processing of virgin material with the processing of recycled material. Finally, the potential of this approach is shown in a conceptual way.