Abstract
In the present work, genetic algorithms and fuzzy logic were combined to model and optimise the shear strength of hybrid composite-polymer joints obtained by two step laser joining process. The first step of the process consists of a surface treatment (cleaning) of the carbon fibre-reinforced polymer (CFRP) laminate, by way of a 30 W nanosecond laser. This phase allows removing the first matrix layer from the CFRP and was performed under fixed process parameters condition. In the second step, a diode laser was adopted to join the CFRP to polycarbonate (PC) sheet by laser-assisted direct joining (LADJ). The experimentation was performed adopting an experimental plan developed according to the design of experiment (DOE) methodology, changing the laser power and the laser energy. In order to verify the cleaning effect, untreated laminated were also joined and tested adopting the same process conditions. Analysis of variance (ANOVA) was adopted to detect the statistical influence of the process parameters. Results showed that both the laser treatment and the process parameters strongly influence the joint performances. Then, an uncertain model based on the combination of fuzzy logic and genetic algorithms was developed and adopted to find the best process parameters’ set able to give the maximum joint strength against the lowest uncertainty level. This type of approach is especially useful to provide information about how much the precision of the model and the process varies by changing the process parameters.
Highlights
During the last decade, traditional manufacturing processes have dealt with an increasing demand from the modern industry in terms of processing of new materials and complexity of final products.This is giving rise to new technological frontiers, which can only be overcome with new and advanced production technologies and systems.The main reason of this revolution must be sought in the request of more and more reduced environmental impact, with low fuel consumption, CO2 emissions and at the same time, improved performances for commercial, industrial and military applications [1,2]
(UTS) as as response results consist of a of table containing the degrees of freedom the (DoF), sequential responsevariable
The results consist a table containing the degrees of (DoF), freedom the sums of squares (Seq.SS), contribution percentagepercentage (Π%) the adjusted of squares sequential sums of squaresthe (Seq.SS), the contribution (Π%) the sum adjusted sum of(Adj.SS), squares the adjusted squares the F-value and the p-value of p-value each parameter parameter (Adj.SS), the mean adjusted mean(Adj.MS), squares (Adj.MS), the
Summary
Traditional manufacturing processes have dealt with an increasing demand from the modern industry in terms of processing of new materials and complexity of final products.This is giving rise to new technological frontiers, which can only be overcome with new and advanced production technologies and systems.The main reason of this revolution must be sought in the request of more and more reduced environmental impact, with low fuel consumption, CO2 emissions and at the same time, improved performances for commercial, industrial and military applications [1,2]. Traditional manufacturing processes have dealt with an increasing demand from the modern industry in terms of processing of new materials and complexity of final products. This is giving rise to new technological frontiers, which can only be overcome with new and advanced production technologies and systems. Materials 2020, 13, 283 in offering different opportunities that are not achievable if the materials are used individually [3,4], e.g., obtaining components characterized by high strength and toughness, with the presence of transparent areas for inspection or aesthetical reasons. Carbon fibre-reinforced polymers are very well suited for reducing the overall weight of the structure and improving fuel efficiency [5]. The only available solution is to join smaller components with, in most cases, supports made by different materials, i.e., metals as well as polymers
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