ArticlePolymers2023
Weld Line Strength of Polyamide Fiberglass Composite at Different Processing Parameters in Injection Molding Technique.
Article in Polymers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Injection Molding and Special Injection Molding Technologies of Polymer and Polymer Composites.Polymers · 2025Article
- Prediction of Mechanical Properties of Injection-Molded Weld Lines of Glass Fiber-Reinforced Composites.Polymers · 2025Article
- Study on Cooling Layer and Thin Insert Thickness Between Coolant and Cavity for Injection Mold with Bridge-Type Composite Product.Polymers · 2025Article
- A Review on Injection Molding: Conformal Cooling Channels, Modelling, Surrogate Models and Multi-Objective Optimization.Polymers · 2025Review
- Micro-Injection Molding of Carbon-Fiber-Reinforced Plastic (CFRP)/Polymethyl Methacrylate (PMMA) Composite Components.Polymers · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
This study examines the impact of injection parameters on the weld line strength of the polyamide 6 and 30% fiberglass (PA6 + 30% FG) composite samples. The effects of filling time, packing time, packing pressure, melt temperature, and mold temperature on the ultimate tensile strength (UTS) and the elongation value of the weld line are investigated. The results reveal that the filling time factor has the lowest influence rate. On the contrary, the packing pressure has the most considerable value of UTS standard deviation, indicating that this factor has a high impact rate. The melt temperature factor has the highest elongation standard deviation, pointing out the strong impact of melt temperature on the elongation value. In reverse, the filling time factor has the lowest elongation standard deviation, showing the low impact of this factor on the elongation value. Increasing the mold temperature enhances the elongation value greatly because a higher temperature generates a better connection in the weld line area. Although the UTS value improves modestly when the mold temperature control system is used, the elongation result from the mold temperature parameter is better than expected. The UTS result from all parameters presents a minor deviation; therefore, it is lower than expected. The optimal strength result from artificial neural networks with genetic algorithm optimization is 85.1 MPa, which is higher than the best experiment result of 76.8 MPa. Scanning electron microscopy (SEM) results show that the interface between the fiberglass and the PA matrix has high adherence. The fracture surface is smooth, indicating that the PA6 + 30% FG composite sample has a high fragility level. The findings could help to increase the injection sample's weld line strength by optimizing the injection molding conditions.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.