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The purpose of this work is to explore predictive model approaches for selecting laser cladding process settings for a desired bead geometry/overlap strategy. Complementing the modelling challenges is the development of a framework and methodologies to minimize data collection while maximizing the goodness of fit for the predictive models. This is essential for developing a foundation for metallic additive manufacturing process planning solutions.

Using the coaxial powder flow laser cladding method, 420 steel cladding powder is deposited on low carbon structural steel plates. A design of experiments (DOE) approach is taken using the response surface methodology (RSM) to establish the experimental configuration. The five process parameters such as laser power, travel speed, etc. are varied to explore their impact on the bead geometry. A total of three replicate experiments are performed and the collected data are assessed using a variety of methods to determine the process trends and the best modelling approaches.

There exist unpredictable, non-linear relationships between the process parameters and the bead geometry. The best fit for a predictive model is achieved with the artificial neural network (ANN) approach. Using the RSM, the experimental set is reduced by an order of magnitude; however, a model with R2 = 0.96 is generated with ANN. The predictive model goodness of fit for a single bead is similar to that for the overlapping bead geometry using ANN.

Developing a bead shape to process parameters model is challenging due to the non-linear coupling between the process parameters and the bead geometry and the number of parameters to be considered. The experimental design and modelling approaches presented in this work illustrate how designed experiments can minimize the data collection and produce a robust predictive model. The output of this work will provide a solid foundation for process planning operations.

Traditional dynamic and flutter analysis demands a detailed finite element model of the aircraft in terms of its mass and stiffness distribution. However, in absence of these details, modal parameters obtained from experimental tests can be used to predict the flutter characteristics of an aircraft. The purpose of this paper is to develop an improved and reliable method to predict the flutter characteristics of an aircraft structure of unknown configuration under an anticipated aerodynamic loading using software such as MSC Nastran and experimental modal parameters (such as mode shapes, natural frequencies and damping) from ground vibration tests.

A finite element model with nodes representing the test points on the aircraft is created with appropriate boundary constraints. A direct matrix abstraction program has been written for NASTRAN software that carries out a normal modes analysis and replaces the mass normalized eigenvalues and vectors with the experimentally obtained modal parameters. The flutter analysis proceeds with the solution of the flutter equation in the flutter module of NASTRAN.

The method has been evaluated for a light composite aircraft and its results have been compared with flight flutter tests and the flutter speeds obtained from the finite element model with actual stiffness and mass distributions of the aircraft.

The methodology developed helps in the realistic prediction of flutter characteristics of a structure with known geometric configuration and does not need material properties, mass or stiffness distributions. However, experimental modal parameters of each configuration of the aircraft are required for flutter speed estimation.

The proposed methodology requires experimental modal parameters of each configuration of the aircraft for flutter speed estimation.

The paper shows that an effective method to predict flutter characteristics using modal parameters from ground vibration tests has been developed.

Lapping is a vital flattening process to improve the quality of processed semiconductor wafers such as single-crystal sapphire wafers. This study aims to optimise the lapping process of the fixed-abrasive lapping plate of sapphire wafers with good overall performance [i.e. high material removal rate (MRR), small surface roughness (Ra) of the wafers after lapping and small lapping plate wear ratio (η)].

The influence of process parameters such as lapping time, abrasive size, abrasive concentration, lapping pressure and lapping speed on MRR, Ra and η of lapping-processed sapphire wafers was studied, and the results were combined with experimental data to establish a regression model. The multi-evaluation index optimisation problem was transformed into a single-index optimisation problem via an entropy method and the grey relational analysis (GRA) to comprehensively evaluate the performance of each parameter.

The results revealed that lapping time, abrasive size, abrasive concentration, lapping pressure and lapping speed had different influence degrees on MRR, Ra and η. Among these parameters, lapping time, lapping speed and abrasive size had the most significant effects on MRR, Ra and η, and the established regression equations predicted the response values of MRR, Ra and η to be 99.56%, 99.51% and 93.88% and the relative errors between the predicted and actual measured values were <12%, respectively. With increased lapping time, MRR, Ra and η gradually decreased. With increased abrasive size, MRR increased nearly linearly, whereas Ra and η initially decreased but subsequently increased. With an increase in abrasive concentration, MRR, Ra and η initially increased but subsequently decreased. With increased lapping pressure, MRR and η increased nearly linearly and continuously, whereas Ra decreased nearly linearly and continuously. With increased lapping speed, Ra initially decreased sharply but subsequently increased gradually, whereas η initially increased sharply but subsequently decreased gradually; however, the change in MRR was not significant. Comparing the optimised results obtained via the analysis of influence law, the parameters optimised via the entropy method and GRA were used to obtain sapphire wafers lapping with an MRR of 4.26 µm/min, Ra of 0.141 µm and η of 25.08, and the lapping effect was significantly improved.

Therefore, GRA can provide new ideas for ultra-precision processing and process optimisation of semiconductor materials such as sapphire wafers.

The purpose of this study was to optimize the surface roughness (Ra), delamination damage at the hole entrance (FdT) and at the hole exit (FdB) and kerf angle (K) in the drilling of aramid fiber-reinforced polymer (AFRP) composite material using abrasive water jet (AWJ) machining.

The AFRP composite was produced by the vacuum infusion method. The drilling experiments were performed on an AWJ machine using a three-axis computerized numerical control system. Machine processing parameters were determined as water pressure (2,000, 3,000 and 4,000 bar), stand-off distance (2, 4 and 6 mm) and traverse feed rate (150, 250 and 350 mm/min). Optimization of processing parameters in the drilling experiments was carried out according to the Taguchi L27 (33) orthogonal array. In addition, gray relational analysis (GRA) was used to analyze the complex uncertainty affecting the results.

Results of the drilling operations demonstrated that water pressure (P) was the most effective parameter, with 65.3%, 65.2%, 49.8% and 52.1% contribution rates for Ra, FdT, FdB and K, respectively.

Reliable results have been obtained with Taguchi-based GRA while drilling AFRP composite material using AWJ. Significant results have been achieved to increase the hole quality in the drilling of AFRP composite material.

The new approach is to present more detailed analysis by using Taguchi method and multi-decision Taguchi-based gray relation analysis in AFRP composite material drilling using AWJ. Thus, time and experiment costs are saved.

This study aims to explore the impact of key parameters of brake pads on the dynamic characteristics of the braking system.

This study conducted experimental research based on a friction testing machine with a slider-disc structure. The experiment studied the impact of key parameters of brake pads (rotation speed, pressure, mass, braking radius, etc.) and the braking environment (dry friction, wetness, sand, etc.) on the stability of the braking system. At the same time, a dynamic model of the brake pad braking system was established and compared with experimental results using the mathematical tool of autocorrelation coefficient.

The key parameters of brake pads have a significant impact on the dynamic characteristics of the braking system; under different conditions of brake pad mass, tribological parameters, brake pad radius and braking environment, the chaotic characteristics of the braking friction force signal show a trend of expansion or contraction, which can be suppressed by adjusting the key parameters of brake pads.

This study can provide a reference for optimizing the braking strategy and reducing noise and vibration in brake pad systems.

The purpose of this study is to review the existing fatigue and vibration-based structural health monitoring techniques and highlight the advantages of combining both approaches.

Fatigue monitoring requires a fatigue model of the material, the stresses at specific points of the structure, a cycle counting technique and a fatigue damage criterion. Firstly, this paper reviews existing structural health monitoring (SHM) techniques, addresses their principal classifications and presents the main characteristics of each technique, with a particular emphasis on modal-based methodologies. Automated modal analysis, damage detection and localisation techniques are also reviewed. Fatigue monitoring is an SHM technique which evaluate the structural fatigue damage in real time. Stress estimation techniques and damage accumulation models based on the S-N field and the Miner rule are also reviewed in this paper.

A vast amount of research has been carried out in the field of SHM. The literature about fatigue calculation, fatigue testing, fatigue modelling and remaining fatigue life is also extensive. However, the number of publications related to monitor the fatigue process is scarce. A methodology to perform real-time structural fatigue monitoring, in both time and frequency domains, is presented.

Fatigue monitoring can be combined (applied simultaneously) with other vibration-based SHM techniques, which might significantly increase the reliability of the monitoring techniques.

This paper aims to investigate the curling behaviour of selective laser sintered polyamide/glass bead composites with changes in material compositions, part bed temperature, powder base thickness, laser power and layer cooling time.

The Taguchi parameter design method (design of experiments, DOE) and analysis of variance (ANOVA) technique were applied in the investigation to determine the optimal process parameter settings.

The results of statistical analysis and ANOVA provided evidence for the effectiveness of filler content and its surface treatment on reducing the amount of curling.

Warping and curling phenomena is one of several aspects of this work that can be pursued further. The present investigation could be expanded to explore other fillers and interface adhesion using other modifiers. Experiments could be conducted with other complicated geometries, various sizes, different positions and locations to widen the knowledge base of geometric accuracy of selective laser sintering process.

This experimental work is beneficial for materials development and accuracy characterisation in rapid manufacturing techniques. The experimental techniques adopted are readily transferable to virtually any material system used in rapid manufacturing.

Although many materials have been developed, there is still a need for research into new materials. This work demonstrates that it is possible to improve the geometric accuracy of selective laser sintered components from glass bead- filled polyamide 12 and achieve near-zero curling by adding rigid multiphase-coated particle to the material system.

The purpose of this paper is to optimize the frictional input parameters related to the yarn and woven fabric samples. Indeed, using metaheuristic techniques for optimization, it helps to attempt the best quality appearance of garment, by analysing their effects and relationships with the bagging behaviour of tested fabrics before and after bagging test. Using metaheuristic techniques allows us to select widely the minimal residual bagging properties and the optimized inputs to adjust them for this goal.

The metaheuristic methods were applied and discussed. Hence, the genetic algorithms (GA) and ant colony optimization (ACO) technique results are compared to select the best residual bagging behaviour and their correspondent parameters. The statistical analysis steps were implemented using Taguchi experimental design thanks to Minitab 14 software. The modelling methodology analysed in this paper deals with the linear regression method application and analysis to prepare to the optimization steps.

The regression results are essential for evaluate the effectiveness of the relationships founded between inputs and outputs parameters and for their optimizations in the design of interest.

This study is interesting for denim consumers and industrial applications during long and repetitive uses. Undoubtedly, the denim garments remained the largely used and consumed, hence, this particularity proves the necessity to study it in order to optimize the bagging phenomenon which occurs as function of number of uses. Although it is fashionable to have bagging, the denim fabric remains, in contrast with the worsted ones, the most popular fabric to produce garments. Moreover, regarding this characteristic, the large uses and the acceptable value of denim fabrics, their aesthetic appearance behaviour due to bagging phenomenon can be analysed and optimized accurately because compared to worsted fabrics, they have a high value and the repetitive tests to investigate widely bagged zones can fall the industrial. The paper has practical implications in the clothing appearance and other textile industry, especially in the weaving process when friction forms (yarn-to-yarn, yarn-to-metal frictions) and stresses are drastic. This can help to understand why residual bagging behaviour remained after garment uses due to the internal stress and excessive extensions.

Until now, there is no work dealing with the optimization of bagging behaviour using metaheuristic techniques. Indeed, all investigations are focused on the evaluation and theoretical modelling based on the multi linear regression analysis. It is notable that the metaheuristic techniques such as ACO and GA are used to optimize some difficult problems but not yet in the textile field excepting some studies using the GA. Besides, there is no sufficiently information to evaluate, predict and optimize the effect of the yarn-to-yarn friction as well as metal-to-yarn one on the residual bagging behaviour. Several and different denim fabrics within their different characteristics are investigated to widen the experimental analysis and thus to generalize the results in the experimental design of interest.

Stereolithography (SLA) is a broadly used technology in the field of rapid prototyping. One of the disadvantages of SLA is poor mechanical properties of its products. To approach the mechanical properties of original part, the mechanical properties of SLA part, such as tensile strength, should be optimized. In this process, there are many parameters that affect the tensile strength of parts. However, the “layer thickness”, “fabrication orientation” and “post curing time” are the most significant ones. Hence, the purpose of this study is to investigate the influence of these parameters on tensile strength of SLA parts.

According to the obtained results from experiments based on the “full factorial” method, an empirical equation was developed for the tensile strength in terms of the effective parameters by using regression analysis. Considering this empirical equation, the process parameters were optimized to maximize the tensile strength by using genetic algorithm. Finally, the tensile tests of the specimens were simulated via the general-purpose finite element package of ABAQUS.

The outputs of the numerical simulations were in good agreement with experimental results. Both experimental and numerical results show that the increase of layer thickness and the decrease in post curing time increase the tensile strength. Furthermore, the tensile strength of parts produced in vertical orientation is higher than that of parts produced in horizontal orientation.

This is a complete study about the tensile strength of the SLA parts from experimental and analytical viewpoints.

The advancement in modern manufacturing technology generated the need to develop new materials for better wear resistance. The purpose of this paper is to use the Taguchi optimization approach to examine which wear parameter significantly affects weight loss and coefficient of friction for RZ5-TiC composite. It is a simple and efficient method to find performance of wear parameter using minimum experimental runs.

RZ5-TiC composites were prepared using RZ5 as matrix, reinforced with TiC through self-propagating high-temperature synthesis technique. In the present work, an attempt has been made to study the influence of wear parameters like applied load (AL), sliding distance (SD) and Wt.% of TiC (WTC) on responses like weight loss and coefficient of friction of RZ5/TiCp composites. The pin-on-disc apparatus used to conduct abrasive wear test. The wear process parameters are optimized for minimum wear based on L27 Taguchi orthogonal design. The Taguchi technique using design of experiments (DOE) is used to obtain the data. The ANOVA and an orthogonal array are used to examine the influence of wear parameters on responses. The purpose is to examine parametric significances which affect responses.

It observed that wear parameters have the significant influence on responses of RZ5/TiCp composites. The interaction of sliding distance/Wt.% of TiC is observed and found significant influence on both responses. The optimum level of the significant wear parameters is achieved based on the maximum S/N ratio for RZ5/TiCp composites. The optimal interaction for weight loss and coefficient of friction is AL1-SD1-WTC3 and AL3-SD1-WTC3, respectively. Finally, the confirmation test is conducted and the results are obtained within the confidence interval.

The current manuscript provides an optimization of wear parameters using Taguchi approach. The extensive experimental data are used for this purpose and effects of wear parameters on responses are analyzed from the presented results. The results obtained are useful in improving the wear resistance of the RZ5-TiC composite.