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Understanding the behaviors of heat transfer and fluid flow in weld pool and their effects on the solidification microstructure are significant for performance improvement of laser welds. This paper develops a three-dimensional numerical model to understand the multi-physical processes such as heat transfer, melt convection and solidification behavior in full-penetration laser welding of thin 5083 aluminum sheet. Solidification parameters including temperature gradient G and solidification rate R, and their combined forms are evaluated to interpret solidification microstructure. The predicted weld dimensions and the microstructure morphology and scale agree well with experiments. Results indicate that heat conduction is the dominant mechanism of heat transfer in weld pool, and melt convection plays a critical role in microstructure scale. The mushy zone shape/size and solidification parameters can be modulated by changing process parameters. Dendritic structures form because of the low G/R value. The scale of dendritic structures can be reduced by increasing GR via decreasing heat input. The columnar to equiaxed transition is predicted quantitatively via the process related G3/R. These findings illustrate how heat transfer and fluid flow affect the solidification parameters and hence the microstructure, and show how to improve microstructure by optimizing the process.

Bayesian optimization is a metamodel-based global optimization approach that can balance between exploration and exploitation. It has been widely used to solve single-objective optimization problems. In engineering design, making trade-offs between multiple conflicting objectives is common. In this work, a multi-objective Bayesian optimization approach is proposed to obtain the Pareto solutions. A novel acquisition function is proposed to determine the next sample point, which helps improve the diversity and convergence of the Pareto solutions. The proposed approach is compared with some state-of-the-art metamodel-based multi-objective optimization approaches with four numerical examples and one engineering case. The results show that the proposed approach can obtain satisfactory Pareto solutions with significantly reduced computational cost.

In order to extend fatigue life of structures, traditional methods involving controlled creation of boundaries and local microstructure discontinuities are used to obstruct dislocation motion and change the crack propagation path during fatigue service. However, such strategies inevitably sacrifice ductility due to the reduced ability to accommodate dislocations. Herein, an external magnetic field is used to assist laser-MIG hybrid welding for 316L austenitic stainless steel. Fatigue crack propagation rate is decreased by 33% at f = 0.1 Hz and 12% at f = 1 Hz in air. The external magnetic field optimizes fatigue resistance of 316L welds from two aspects: diverse orientation distributions of ferrite and non-K-S orientation relationship (OR) between ferrite (δ) and austenite (γ). Diverse orientation distributions of δ induced by magnetic field activate different slip systems, promoting crack deflection in γ grain interior during cyclic deformation. Semi-coherent interface between δ-γ with non- Kurdjumov-Sachs (K-S) OR not only impedes transmission of the dislocation slip but also accommodates a considerable amount of plastic strain by continual loss of coherency. Thus, external magnetic field assisted welding of 316L extends fatigue life by increasing strength and ductility, and promoting crack deflection in grain interior.

Based on two-dimensional phase-field simulations, we demonstrated the possible reasons why Al-Mg alloys can have better resistance to solidification cracking than Al-Cu alloys despite their wide freezing temperature range. Using Al-4.0 wt% Cu and Al-4.0 wt% Mg alloy as examples, we found that back-diffusion is negligible due to the relatively high cooling rate, and extensive coalescence occurs at earlier solidification stage in Al-4.0 wt% Mg alloy compared with Al-4.0 wt% Cu alloy. With considering coalescence predicted by phase-field simulations, the calculated solidification cracking index of Al-Mg alloy is reasonably lower than Al-Cu alloy.

Laser cladding has been widely applied in surface modification and repairing. In this study, laser cladding was employed to fabricate Inconel 625 composite coatings reinforced by TiC particles using a 4000W fiber laser. The morphologies of bead samples, particle distributions, mechanisms of microstructure evolution, mechanical property and corrosion performance of the individual molten pool which was produced in laser cladding composites were investigated. The results showed that homogeneous distributed TiC particles, along with refined microstructures were obtained in TiC reinforced Inconel 625 composite coatings under appropriate cladding process parameters. During laser cladding, almost no transformation of Fe or Ni was occurred around the TiC particle but Laves phases were precipitated at the boundary. Compared with the pure Inconel 625 coatings, significantly improvement of microhardness and tensile strength were observed in TiC reinforced Inconel 625 coatings. The TiC reinforced Inconel 625 coatings also exhibited good corrosion resistance, proving a further surface improvement of ASIS 316L stainless steel substrate.

The microstructure of dissimilar joint between galvanized steel and 6061 aluminum alloy was studied by experiments and numerical simulation. Three types of experiments including full factor experiments to establish processing window, four chosen parameters to analyze macro profile of weld joints, and two parameters closing to upper and lower limits of processing window were carried out in this study. Besides two common intermetallic compounds (lamellar IMC and acicular IMC) which were reported before, other two new intermetallic compounds (IMC), namely stellate IMC and skeleton IMC were found at the joint under high linear energy density (LED). The chemical compositions and possible phase types of different IMCs observed were determined according to energy dispersive spectroscopy (EDS) results. The temperature histories during welding were simulated based on a finite volume model to further investigate the influence of LED on diffusion process which was thought to be the decisive factor for IMC growing. The growth orientation and phase morphology were determined by temperature histories, local iron atom fraction and constitutional supercooling. The increasing linear energy affected both macro morphology and microstructure of weld joints. It could be concluded that the increasing linear energy was harmful for mechanical properties because it increased thickness of lamellar IMC and brought some new brittle phases which led to some microcracks.

Numerical simulations of laser welding could provide unprecedented insight into the physical details of the welding process; however, it remains a central challenge to understand laser welding with a high-efficiency and high-resolution method. This paper reports an octree-based adaptive mesh refinement method for efficient process modeling of laser welding in three dimensions. Based on multiresolution analysis algorithm, we also propose a hybrid adaptive mesh refinement strategy depending on local temperature, fluid velocity, and volume of fluid (VOF) value of weld pool of laser welding. Using the proposed method, the predicted heat transfer, and fluid flow behaviors of weld pool are consistent with experimental and previous theoretical results. Spatter formation at the beginning stage of laser welding is observed with a grid resolution in tens of microns. Under certain circumstances, the liquid jet can be produced when the fluid speed near the top surface of the weld pool is 1 m/s. The time for breakup of a liquid jet into spatters is about 0.065 ms. Furthermore, using the method, we just need 7 hours to complete a simulation of a 40-ms real laser welding process on a small workstation (2.60 GHz CPU, 16 cores), comparing with 120 hours needed using uniform grids. In a word, this method shows great potential for efficient computer simulation-based process optimization of laser material processing.

In this study, fatigue crack growth rates in weld center and Heat Affected Zone (HAZ) of laser-MIG hybrid welded joint are compared using standard compact tension (CT) specimens. Electron backscatter diffraction (EBSD) is applied to analyze crack tip transformation zone by characterizing phases, plastic strains and crystallographic orientations. This study provides interesting insights into the growth of fatigue cracks in austenite steel welded joint at micro-scale. Analysis of the plastic strain and Schmid factor indicates that mechanical energy provided by external load transforms into internal crystal energy firstly, which is stored within grains in the form of strain energy, then partly relieves to provide mechanical driving force for martensite transformation. With plastic strain accumulating within individual grain, dislocations begin to glide on slip system resulting in formation of persistent slip bands (PSB), then metastable austenite grains transform into martensite. Thus, strain-induced martensite transformation increases resistance to crack growth by dissipating energy and crack closure effect. Different crack growth rate in weld center and HAZ is attributed to variant volume of strain-induced martensite. Shielding effect produced by neighboring harder ferrite decreases martensite in weld center, as confirmed by nanoidentation and Atomic Force Microscope (AFM). Additionally, martensite phase is found to have a Kurdjumov-Sachs (K-S) orientation relationship with austenite phase according to Inverse Pole Figure (IPF) and Pole Figures (PF) derived by EBSD.

Laser cladding has been widely applied in surface modification and repairing. In this study, single bead and multiple beads Inconel 625 coatings were fabricated on the surface of 316L stainless steel by laser cladding. This investigation was conducted using an optical microscopy, scanning electron microscope (SEM), X-ray diffraction (XRD) and other methodologies. A three-dimensional (3D) finite element (FE) model was applied to predict the temperature evolution in the laser cladding process. The results indicated that the defect-free Inconel 625 coating presented an obvious microstructure transformation while the bonding interface can be divided into three different areas. An unmixed area was observed near the bonding interface with precipitated ferrite of different formations. A decrease of the hardness (H) and reduced elastic modulus (Er) profile was detected in this area. Cladded area and bonding area exhibited superior tensile properties at both room temperature and high temperature than substrate. The corrosion performance of coating area was also close to bonding area and superior to substrate in different solutions, indicating an excellent protecting effect of Inconel 625 coating.

Laser metal deposition (LMD) with a filler has been demonstrated to be an effective method for additive manufacturing because of its high material deposition efficiency, improved surface quality, reduced material wastage, and cleaner process environment without metal dust pollution. In this study, single beads and samples with ten layers were successfully deposited on a 316 L stainless steel surface under optimized conditions using a 4000 W continuous wave fibre laser and an arc welding machine. The results showed that satisfactory layered samples with a large deposition height and smooth side surface could be achieved under appropriate parameters. The uniform structures had fine cellular and network austenite grains with good metallurgical bonding between layers, showing an austenite solidification mode. Precipitated ferrite at the grain boundaries showed a subgrain structure with fine uniform grain size. A higher microhardness (205–226 HV) was detected in the middle of the deposition area, while the tensile strength of the 50 layer sample reached 669 MPa. In addition, ductile fracturing was proven by the emergence of obvious dimples at the fracture surface.

The weld geometry characteristics are highly related to the mechanical properties and performance of the joints. The top surface of the weld is often assumed as the flat surface during calculating the fluid flow in the molten pool and hence weld reinforcement is ignored among the geometric parameters. In this paper, a three-dimensional numerical simulation model is developed to investigate the characteristics of the weld generated in the fiber laser keyhole welding. The gas layer above the molten pool has been considered to simulate the top surface of the weld in the simulation model and the free surface shape of the keyhole is calculated by the volume of fluid method. The hybrid heat source model is determined by the analysis of weld bead characteristics. Based on the numerical simulation results, the evolution of the weld profile characteristics have been demonstrated and the results are adopted to estimate the shape and sizes of the generated weld bead. From the comparison, the simulated results of the weld bead agree well with that of experiments. Furthermore, weld beads formed under different process conditions are calculated and the errors between the simulated and experimental results are analyzed in details.

The existence of thermoelectric currents (TECs) in workpieces during the laser welding of metals has been common knowledge for more than 15 years. However, the time-dependent evolutions of TECs in laser welding remain unclear. The present study developed a novel three-dimensional theoretical model of thermoelectric phenomena in the fiber laser welding of austenite stainless steel and used it to observe the time-dependent evolutions of TECs for the first time. Our model includes the complex physical effects of thermal, electromagnetic, fluid and phase transformation dynamics occurring at the millimeter laser ablated zone, which allowed us to simulate the TEC, self-induced magnetic field, Lorentz force, keyhole and weld pool behaviors varying with the welding time for different parameters. We found that TECs are truly three-dimensional, time-dependent, and uneven with a maximum current density of around 10 7 A/m 2 located at the liquid-solid (L/S) interface near the front or bottom part of the keyhole at a laser power of 1.5 kW and a welding speed of 3 m/min. The TEC formed three-dimensional circulations moving from the melting front to solidification front in the solid part of workpiece, after which the contrary direction was followed in the liquid part. High frequency oscillation characteristics (2.2–8.5 kHz) were demonstrated in the TEC, which coincides with that of the keyhole instability (2.0–5.0 kHz). The magnitude of the self-induced magnetic field and Lorentz force can reach 0.1 mT and 1 kN/m 3 , respectively, which are both consistent with literature data. The predicted results of the weld dimensions by the proposed model agree well with the experimental results. Our findings could enhance the fundamental understanding of thermoelectric phenomena in laser welding.

The quality of the welded joints is greatly affected by the appearance and geometry of the weld bead. Understanding the formation mechanism of whole weld bead has great theoretical significance and engineering value. This paper proposes a novel three-dimensional model considering the heat transfer, keyhole free surface, surface tension and recoil pressure for simulating the formation process of the weld bead and predicting its full sizes in the fiber laser keyhole welding. To improve the simulation accuracy, the relationship between the weld geometry and welding process parameters is established and taken into consideration in the numerical modeling. Based on the model, the keyhole phenomena and weld bead formation process have been revealed. During the numerical simulation, the weld shape including the width, reinforcement and penetration are all calculated, as well as the corresponding size. The validity of the proposed model is confirmed by experiments, and the simulated results show good agreement with the experimental values. Additionally, the changing tendency of the weld geometry affected by the welding process parameters is analyzed by simulation and the results are found to be consistent with the theoretical and experimental data. Therefore, the proposed method is very effective for improving the weld shape and welded joints quality.

In this paper, the dynamic stability of the fluid-conveying in the periodically composite pipeline (FCPCP) is researched, and the FCPCP system is divided into two parts: pipeline with partial viscoelastic composite part and the conveying-fluid part. The in-plane variables of the first part are calculated by the Zig-Zag laminated shell theory, and the equilibrium equations are obtained by Hamilton's principle. Meanwhile, the equilibrium equations of the fluid part are mainly obtained by Newton's Second law. The govern equations of the FCPCP system can be determined by combining the equations obtained of the two parts, and considering the boundary conditions, and the instability of the current structure can be obtained by solve the govern equation system. The factors (Such as the thickness ratio of the pipeline, the thickness of viscoelastic damping layer and the viscoelastic composite fraction, etc.) which affected the instability of FCPCP is thoroughly examined, and validate is performed finally.

In this study, a method combining magnetic, MIG, and laser was applied to weld the 304 stainless steel with a thickness of 4 mm. The effect of magnetic field on the weld microstructures and mechanical properties was investigated. The weld geometry and microstructure were characterized by optical microscope (OM) and scanning electric microscopy. Electron back scattered diffraction (EBSD) was used to determine the grain sizes and crystallographic orientations. Residual stress and tensile stress of welds were measured and compared with the laser-arc hybrid welds without an external magnetic field. The results showed that with an appropriate magnetic field intensity, an optimal joint was obtained with tensile strength enhanced by nearly 12% and tensile residual stresses reduced. In addition, the grain refining and promotion of the phase transformation with the magnetic field were analyzed.

Dissimilar materials welded joints provide many advantages in power, automotive, chemical, and spacecraft industries. The weld bead integrity which is determined by process parameters plays a significant role in the welding quality during the fiber laser welding (FLW) of dissimilar materials. In this paper, an optimization method by taking the integrity of the weld bead and weld area into consideration is proposed for FLW of dissimilar materials, the low carbon steel and stainless steel. The relationships between the weld bead integrity and process parameters are developed by the genetic algorithm optimized back propagation neural network (GA-BPNN). The particle swarm optimization (PSO) algorithm is taken for optimizing the predicted outputs from GA-BPNN for the objective. Through the optimization process, the desired weld bead with good integrity and minimum weld area are obtained and the corresponding microstructure and microhardness are excellent. The mechanical properties of the optimized joints are greatly improved compared with that of the un-optimized welded joints. Moreover, the effects of significant factors are analyzed based on the statistical approach and the laser power (LP) is identified as the most significant factor on the weld bead integrity and weld area. The results indicate that the proposed method is effective for improving the reliability and stability of welded joints in the practical production.

The structural dynamic property of periodically and orthogonally stiffened composite laminar (POSCL) embedded within viscoelastic damping material (VDM) is studied with the asymptotic homogenization analysis method (AHAM) in this paper. A representative unit-cell (RUC) that includes the periodical property of POSCL is extracted from the structure. With the in-plane variables obtained by zigzag laminated theory (ZZLT), the energy equilibrium equation is established based on Hamilton's principle. The equilibrium equations of shear deformation are built by considering the inner shear and initial deformation between the stiffener and the face layers. By introducing the ‘rapid’ asymptotic factor, the equilibrium equations are expanded by AHAM, and then, the frequency- and temperature-dependent coefficients for all variables are obtained. Finally, the structural loss factor (SLF) of POSCL is determined. In this stage, the factors that affect the POSCL's SLF are thoroughly studied at different temperatures. Validation and comparison are presented at the end of this paper, and the results show that there are advantages to current structures in engineering application.

It is of great significance to select appropriate welding process parameters for obtaining optimal weld geometry in hybrid laser-arc welding. An integrated optimization approach by combining Kriging model and GA is proposed to optimize process parameters. A four-factor, five-level experiment using Taguchi L 25 is conducted considering laser power (P), welding current (A), distance between laser and arc (D) and traveling speed (V). Kriging model is adopted to approximate the relationship between process parameters and weld geometry, namely depth of penetration (DP), bead width (BW) and bead reinforcement (BR). The constructed Kriging model was used for parameters optimization by GA to maximize DP, minimize BW and ensure BR at a desired value. The effects of process parameters on weld geometry are analyzed. Microstructure and micro-hardness are also discussed. Verification experiments demonstrate that the obtained optimum values are in good agreement with experimental results.

Multi-objective laser welding process parameters optimization approach is proposed.The effects of process parameters on bead profile in light of Kriging are analyzed.Experiment results show the efficiency of the proposed approach. Laser welding process parameters have significant effects on the welding bead profile and quality of the welding joint. This paper proposes an integration method of process parameters optimization using finite element method (FEM), Kriging metamodels and nondominated sorting genetic algorithm II (NSGA-II) in laser welding for stainless steel 316L. The process parameters in this study are laser power (LP), welding speed (WS) and laser focal position (LF). Firstly, a three-dimensional thermal finite element model is developed to obtain the simulated results of bead width (BW) and depth of penetration (DP). Then, Kriging metamodels are constructed to reflect the relationship between input process parameters and output responses. Finally, NSGA-II is used to search for multi-objective Pareto optimal solutions. In addition, the main effects and contribution rates of multiple process parameters on welding bead profile are analyzed. The results of verification experiments indicate that the optimal process parameters are effective and reliable for producing expected welding bead profile.

The integration of process planning and scheduling is a very important problem because it proposes a new idea for improving the performance of a manufacturing system. At present, most existing studies on this problem are static, which assumes that all the jobs to be processed are available in the beginning. However, the practical processing situation is dynamic, such as new job arrivals. Since dynamic production situations are different with static cases, it is important to study the characteristics of actual production situations. In this article, the characteristics of dynamic integrated process planning and scheduling problem with job arrivals are studied. A novel mixed integer linear programming model is established to accommodate new job arrivals, and three criteria (makespan, stability, and tardiness) are considered. New periodic and event-driven rescheduling strategies are presented. In the proposed strategy, newly added jobs together with uncompleted jobs will be rescheduled by non-dominated sorting genetic algorithm-II to obtain the optimal Pareto front when the rescheduling procedure is triggered. The entropy-based weight assigning method together with the Technique for Order of Preference by Similarity to Ideal Solution method is adopted to determine an appropriate schedule among the resultant non-dominated solutions. A set of well-known benchmark instances is employed to investigate the characteristics of the dynamic integrated process planning and scheduling problem with random job arrivals. Experimental results show that the length of a scheduling interval, the number of newly added jobs, and the shop utilization have an important influence on the efficiency of a manufacturing system.

In order to better understand the local evaporation phenomena of keyhole wall, vapor plume swing above the keyhole and ambient gas entrapment into the porosity defects, the 3D time-dependent dynamics of the metallic vapor plume in a transient keyhole during fiber laser welding is numerically investigated. The vapor dynamical parameters, including the velocity and pressure, are successfully predicted and obtain good agreements with the experimental and literature data. It is found that the vapor plume flow inside the keyhole has complex multiple directions, and this various directions characteristic of the vapor plume is resulted from the dynamic evaporation phenomena with variable locations and orientations on the keyhole wall. The results also demonstrate that because of this dynamic local evaporation, the ejected vapor plume from the keyhole opening is usually in high frequency swinging. The results further indicate that the oscillation frequency of the plume swing angle is around 2.0–8.0 kHz, which is of the same order of magnitude with that of the keyhole depth (2.0–5.0 kHz). This consistency clearly shows that the swing of the ejected vapor plume is closely associated with the keyhole instability during laser welding. Furthermore, it is learned that there is usually a negative pressure region (several hundred Pa lower than the atmospheric pressure) of the vapor flow around the keyhole opening. This pressure could lead to a strong vortex flow near the rear keyhole wall, especially when the velocity of the ejected metallic vapor from the keyhole opening is high. Under the effect of this flow, the ambient gas is involved into the keyhole, and could finally be entrapped into the bubbles within a very short time (

A novel functional structure which can generate large structural loss factor (LF) in low frequency is designed in this research. The free flexural dynamic characteristics of composite laminated plate (CLP) cored with viscoelastic damping material (VDM) are studied by considering its frequency- and temperature-dependent properties. The heavy-density-material-rods (HDMRs) are periodically embedded into CLP. CLP's in-plane variables are obtained by classic laminated plate theory (CLPT) first, and then substituted it into the equilibrium equations which are derived from the Hamilton's principle, the flexural and shearing deformation compatible equations according to the mechanism of a primitive cell. The analytical deformation equation of the CLP is solved by the second order “rapid” asymptotic method, and LF is obtained, subsequently. The parameters that affect the LF are thoroughly analyzed. The validity of the research is verified by FEM. The research show the advantages of the presented CLP which could be applied in engineering under low frequency zone, especially in 1–200 Hz.

Laser-MIG hybrid welding of 316L stainless steel was carried out to investigate influence of welding process parameters, i.e., laser power (P), welding current (I), distance between laser and arc (D), and welding speed (V) on arc characteristics, droplet transfer, and weld quality. Arc characteristics and droplet transfer behavior were investigated using high-speed imaging technology. Microstructures of the joint were observed by optical microscope, and microhardness was measured by microhardness tester. The results showed that the maximum deviation angle of the arc from the wire axis decreases with the increasing laser power. Welding current played a dominant role in arc length and droplet transfer mode. Optimal weld with no spatters and humps was obtained when P = 3 kW, I = 140 A, D = 3 mm, and V = 1.2 m/min. Microstructures in the weld zone mainly consist of columnar and equiaxed dendrites. Microhardness decreased toward the center of the weld zone, increased toward the WZ boundary, and decreased sharply at the heat-affected zone (HAZ).

Laser arc hybrid welding became a useful method to weld thick plates. But a sound weld is not so easy to obtain because of the uncontrollability of droplet transfer state, especially in ultra-narrow gap welding process. In this study, V-like ultra-narrow gap welds were carried out using 80 % Ar + 20 % CO2 blend as shielding gas. A high-speed video system was used to observe the droplet transfer behaviors. The results showed that the transfer mode did not change with the same welding current. The transfer mode changed from the short circuiting transfer to the mixture of the short circuiting and the globular transfer and then to spray transfer as the welding current increased. The relationship between the droplet transfer process and the welded defects was studied to obtain high-quality weld joint with a stable transfer process. The optimal parameter window between welding current and groove size was found. Only when the welding current was 200 to 270 A and groove gap was 2 to 3 mm, can a good welded joint be got. Finally, 30-mm-thick plate with 5.49-mm maximum groove gap was welded well by one pass laser autogenous welding and seven passes laser arc hybrid welding process.

Hybrid laser–arc welding (LAW) provides an effective way to overcome problems commonly encountered during either laser or arc welding such as brittle phase formation, cracking, and porosity. The process parameters of LAW have significant effects on the bead profile and hence the quality of joint. This paper proposes an optimization methodology by combining non-dominated sorting genetic algorithm (NSGA-II) and ensemble of metamodels (EMs) to address multi-objective process parameter optimization in LAW onto 316L. Firstly, Taguchi experimental design is adopted to generate the experimental samples. Secondly, the relationships between process parameters (i.e., laser power (P), welding current (A), distance between laser and arc (D), and welding speed (V)) and the bead geometries are fitted using EMs. The comparative results show that the EMs can take advantage of the prediction ability of each stand-alone metamodel and thus decrease the risk of adopting inappropriate metamodels. Then, the NSGA-II is used to facilitate design space exploration. Besides, the main effects and contribution rates of process parameters on bead profile are analyzed. Eventually, the verification experiments of the obtained optima are carried out and compared with the un-optimized weld seam for bead geometries, weld appearances, and welding defects. Results illustrate that the proposed hybrid approach exhibits great capability of improving welding quality in LAW.

This paper presents a comprehensive review of the various research methods and theory calculation models that are employed in engineering to study the static and dynamic vibration characteristics of viscoelastic damping material (VDM) formed structures. The review classifies of traditional VDMs by their physical properties, application fields and calculation methods. A thorough description and comparison is performed between conventional and improved methods and, their applicability, and the advantages and disadvantages of each calculation theory in engineering structures that contain VDM are sequentially illustrated. VDM mathematical models in previous studies are then described and compared. Finally, the future development of VDM and its composites are discussed. The main objective of this paper is to serve the interests of researchers and engineers involved in the analysis and design of structures whose vibration must be reduced by VDM.

Laser brazing (LB) provides a promising way to join the galvanized steels in automotive industry. The process parameters of LB have significant effects on the bead profile and hence the quality of joint. Since the relationships between the process parameters and bead profiles cannot be expressed explicitly, it is impractical to determine the optimal process parameters intuitively. This paper proposes an optimization methodology by combining Kriging surrogate and particle swarm optimization (PSO) to address the process parameters optimization of the bead profiles in LB with crimping butt of 0.8-mm-thick galvanized steel. Firstly, an experiment using Taguchi L 25 orthogonal array is conducted where welding speed (WS), wire speed rate (WF), and gap (GAP) are taken into consideration as the input parameters, while the bead profiles are the output responses. Secondly, the relationships between the inputs and outputs are established using the Kriging model. Thirdly, the effects of the input parameters on the bead profiles are analyzed, and the global process parameters are obtained by the presented Kriging-PSO approach. At last, the verification experiments were conducted to verify the effectiveness of the optimal values. On the whole, the proposed hybrid method, Kriging-PSO, shows great promise for improving the effectiveness and stability of LB welding process.

The integration of process planning and scheduling is important for an efficient utilization of manufacturing resources. However, the focus of existing works is mainly on deterministic constraints of jobs. This article proposes a novel memetic algorithm for the integrated process planning and scheduling problem with processing time uncertainty based on processing time scenarios. First, a mathematical model for the stochastic integrated process planning and scheduling problem based on the network graph is established. Due to the nonlinearity in the model and the complexity of the problem, a memetic algorithm is then suggested for this problem. A novel local search (variable neighborhood search) algorithm is incorporated into the memetic algorithm. Two effective neighborhood structures are employed in the variable neighborhood search algorithm to improve the overall performance of the population. Furthermore, for the uncertainty in processing times, a set of scenarios have been generated to evaluate each individual. Finally, two performance measures—the expected performance measure and the worst-case deviation measure—are introduced and compared. In the experimental studies, the proposed memetic algorithm is tested on typical benchmark instances. Computational results show that the expected makespan measure performs better than the worst-case deviation measure and the proposed method exhibits high performance especially for large-scale instances. In addition, the results obtained by the proposed memetic algorithm are more satisfactory than those obtained by the algorithm that considers deterministic processing times only.

Laser brazing (LB) provides a promising way to join the galvanized steel in automotive industry for its significant advantages including high speed, small heat-affected zone, and high welding seam quality. The process parameters of LB have significant effects on the bead profile and hence the quality of joint. Since the relationships between the process parameters and bead profile cannot be expressed explicitly, it is impractical to determine the optimal process parameters intuitively. This paper proposes an optimization methodology by combining genetic algorithm (GA) and ensemble of metamodels (EMs) to address the process parameters optimization of the bead profile in LB with crimping butt. Firstly, Taguchi experimental design is adopted to generate the experimental points. Secondly, the relationships between process parameters (i.e., welding speed, wire feed rate, gap) and the bead geometries are fitted using EMs based on the experimental data. The comparative results show that the EMs can take advantage of the prediction ability of each stand-alone metamodel and thus decrease the risk of adopting inappropriate metamodels. Then, the GA is used to facilitate design space exploration and global optimum search. Besides, the main effects and contribution rates of multiple process parameters on bead profile are analyzed. Eventually, the verification experiments are carried out to demonstrate the effectiveness and reliability of the obtained optimal parameters. Overall, the proposed hybrid approach, GA–EMs, exhibits great capability of guiding the actual LB processing and improving welding quality.

Laser butt welding (LBW) of dissimilar materials has received great attention in automotive, power, chemical, nuclear and aerospace industries. The quality of welded joints is significantly affected by the generated defects in the dissimilar materials welding process. This paper proposes a defect-reducing optimization method that considers the geometric features of weld bead as evaluation indexes of welding defects and process parameters effect on the responses. The former aims to reduce welding defects for welding operations, and the latter seeks to identify the extent of contribution of actual process parameters on welding defects. The particle swarm optimization and back propagation neural network (PSO-BPNN), which has proved to be good modeling for no-linear problems, are utilized to establish the mathematical model and the defects reduction objective is combined with weld area. The genetic algorithm (GA) is adopted to solve the model. The effect of significant factors on the responses is identified based on the calculation of signal to noise (S/N) ratio and analysis of variance (ANOVA). The proposed method is evaluated by macro weld profile, microstructure and mechanical properties in confirmation tests. The results show that the proposed method is effective at reducing weld defects for dissimilar materials welding in practical production. Keywords: Laser butt welding, Welding defects reducing, BPNN, PSO, GA

LMPP is developed to enhance the accuracy and efficiency of Kriging-based RBDO.LMPP locates samples mainly in a local region around the current MPP.Feasibility of probabilistic constraint at the current design is checked in LMPP.LEFF criterion is proposed to determine the sequential samples in local region.IS using MPP as sampling center is used to perform reliability analysis. Kriging approximation has been widely used in reliability-based design optimization (RBDO) to replace the complex black-box performance functions. In this paper, a new local approximation method using the most probable point (LMPP) is proposed to improve the accuracy and efficiency of RBDO methods using Kriging model. In the LMPP, the concept of local sampling region is used and the most probable point (MPP) is chosen as the sampling center. The size of the local region is determined by target reliability and the linearity of probability constraint around MPP. Rather than fitting the Kriging model for all the probabilistic constraints, the new method uses the MPP to find feasible constraints, and only these feasible constraints are accurately approximated, which can significantly improve the optimization efficiency. Importance Sampling method using the MPP obtained above as sampling center is utilized to perform reliability analysis and reliability sensitivity calculation. A numerical example, a honeycomb material design problem and a box girder design application are used to demonstrate the computational capability of the LMPP method. The comparison results demonstrate that RBDO using the proposed method is very effective.

The angular distortion is a typical out-of-plane distortion, and it has negative effects on the performance of welded structures. However, the researches on angular distortion of welded structures using intelligent algorithm and mathematical analysis are comparatively less. In this article, the influence from the bead profile on the angular distortion is analyzed, and the angular distortion of tungsten inert gas arc welding with no gap would be predicted by back propagation neural network and the novel inherent strain considering the actual bead geometry model, and the prediction accuracy is also evaluated through comparative analysis of the results with each other. The average relative error of the model built using inherent strain considering the actual bead geometry model method is only 1.289 % and better than that predicted by back propagation neural network algorithm (4.772 %). Meanwhile, the inherent strain considering the actual bead geometry model prediction stability that is estimated using standard deviation is also clearly better than that of back propagation neural network. Actually, the prediction methods by back propagation neural network algorithm and inherent strain considering the actual bead geometry model are proved to be correct and stable. Therefore, the proposed methods can be used to predict the angular distortion of the welded structures with no gap butt joint and guide the actual welding process to decrease the welding deformation.

Process planning and scheduling are two crucial components in a manufacturing system. The integration of the two functions has an important significance on improving the performance of the manufacturing system. However, integrated process planning and scheduling is an intractable non-deterministic polynomial-time (NP)-hard problem, and the multiple objectives requirement widely exists in real-world production situations. In this paper, a multi-objective mathematical model of integrated process planning and scheduling is set up with three different objectives: the overall finishing time (makespan), the maximum machine workload (MMW), and the total workload of machines (TWM). A multi-objective memetic algorithm (MOMA) is proposed to solve this problem. In MOMA, all the possible schedules are improved by a problem-specific multi-objective local search method, which combines a variable neighborhood search (VNS) procedure and an effective objective-specific intensification search method. Moreover, we adopt the TOPSIS method to select a satisfactory schedule scheme from the optimal Pareto front. The proposed MOMA is tested on typical benchmark instances and the experimental results are compared with those obtained by the well-known NSGA-II. Computational results show that MOMA is a promising and very effective method for the multi-objective IPPS problem.

The physical process of deep penetration laser welding involves complex, self-consistent multiphase keyhole, metallic vapor plume, and weld pool dynamics. Currently, efforts are still needed to understand these multiphase dynamics. In this paper, a novel 3D transient multiphase model capable of describing a self-consistent keyhole, metallic vapor plume in the keyhole, and weld pool dynamics in deep penetration fiber laser welding is proposed. Major physical factors of the welding process, such as recoil pressure, surface tension, Marangoni shear stress, Fresnel absorptions mechanisms, heat transfer, and fluid flow in weld pool, keyhole free surface evolutions and solid–liquid–vapor three phase transformations are coupling considered. The effect of ambient pressure in laser welding is rigorously treated using an improved recoil pressure model. The predicated weld bead dimensions, transient keyhole instability, weld pool dynamics, and vapor plume dynamics are compared with experimental and literature results, and good agreements are obtained. The predicted results are investigated by not considering the effects of the ambient pressure. It is found that by not considering the effects of ambient pressure, the average keyhole wall temperature is underestimated about 500 K; besides, the average speed of metallic vapor will be significantly overestimated. The ambient pressure is an essential physical factor for a comprehensive understanding the dynamics of deep penetration laser welding.

Flexural vibration characteristics of a periodically stiffened-thin-plate filled with viscoelastic damping material (VDM) are researched originally based on a simplified-super-element-method (SSEM) according to Floquet–Bloch׳s theorem and super-element-method (SEM). The density, damping ratio (the parameters of the VDM), and the lattice constant of the structure, which impact the frequency characteristics of periodically stiffened-thin-plate, are thoroughly analyzed. The SSEM developed in this research ensured the accuracy and simplified calculation work. It can be used in designing a periodic or quasi-periodic thin plate and shell structures for improving the mechanical property. The advantages of this method are verified by comparing the structures that is and is not filled with VDM.

The welded joints of dissimilar materials have been widely used in automotive, ship and space industries. The joint quality is often evaluated by weld seam geometry, microstructures and mechanical properties. To obtain the desired weld seam geometry and improve the quality of welded joints, this paper proposes a process modeling and parameter optimization method to obtain the weld seam with minimum width and desired depth of penetration for laser butt welding of dissimilar materials. During the process, Taguchi experiments are conducted on the laser welding of the low carbon steel (Q235) and stainless steel (SUS301L-HT). The experimental results are used to develop the radial basis function neural network model, and the process parameters are optimized by genetic algorithm. The proposed method is validated by a confirmation experiment. Simultaneously, the microstructures and mechanical properties of the weld seam generated from optimal process parameters are further studied by optical microscopy and tensile strength test. Compared with the unoptimized weld seam, the welding defects are eliminated in the optimized weld seam and the mechanical properties are improved. The results show that the proposed method is effective and reliable for improving the quality of welded joints in practical production.

In the present paper, the application of laser cleaning technology in thick plate ultra-narrow gap multi-pass multi-layer laser non-autogenous welding process was described. The comparison between weld cross sections and the amount of oxide on the weld surface before and after welding tested by environmental scanning electron microscopy (ESEM) proved the laser cleaning method does play an important role in cleaning the weld. The influence rule of some cleaning parameters to welded joints, including groove angle, laser power, defocusing amount, and cleaning speed, was studied, and the welding defects decreased obviously with the optimal cleaning parameters. Combining this cleaning technology and the laser non-autogenous welding system comprised of the laser autogenous welding, laser wire filling welding, and the laser arc hybrid welding, a 40-mm-thick plate was welded well using a 4-kW fiber laser.

Process planning and scheduling are two of the most important functions of a manufacturing system. Traditionally, these two functions are executed separately. Since they are interrelated, conducting process planning and scheduling simultaneously will provide more advantages. In this paper, according to the characteristics of the integrated process planning and scheduling (IPPS) problem, a hybrid honey bee mating optimization (HBMO) algorithm, which combines the HBMO algorithm and variable neighborhood search (VNS), is proposed to settle the problem with makespan criterion. Different with conventional HBMO, we utilize VNS with two effective and efficient neighborhood structures in the algorithm to simulate the workers’ brood caring action to avoid premature convergence and to find more excellent broods. In addition, a novel individual initialization method is developed in the algorithm. The proposed algorithm is tested on typical benchmark instances taken from related literature, and the computational results are compared with those of other algorithms. Experimental results show the effectiveness and efficiency of the hybrid HBMO algorithm. New upper bounds have been captured for 16 instances, and most instances have been improved within reasonable CPU times.

The laser brazing (LB) is widely used in the automotive industry due to the advantages of high speed, small heat affected zone, high quality of welding seam, and low heat input. Welding parameters play a significant role in determining the bead geometry and hence quality of the weld joint. This paper addresses the optimization of the seam shape in LB process with welding crimping butt of 0.8 mm thickness using back propagation neural network (BPNN) and genetic algorithm (GA). A 3-factor, 5-level welding experiment is conducted by Taguchi L25 orthogonal array through the statistical design method. Then, the input parameters are considered here including welding speed, wire speed rate, and gap with 5 levels. The output results are efficient connection length of left side and right side, top width (WT) and bottom width (WB) of the weld bead. The experiment results are embed into the BPNN network to establish relationship between the input and output variables. The predicted results of the BPNN are fed to GA algorithm that optimizes the process parameters subjected to the objectives. Then, the effects of welding speed (WS), wire feed rate (WF), and gap (GAP) on the sum values of bead geometry is discussed. Eventually, the confirmation experiments are carried out to demonstrate the optimal values were effective and reliable. On the whole, the proposed hybrid method, BPNN-GA, can be used to guide the actual work and improve the efficiency and stability of LB process.

Parametric interpolation for Non-Uniform Rational B-Spline (NURBS) curve has become more important than ever before in the control of CNC machine tools. An effective NURBS interpolator not only can obtain accurate contour trajectories, but also have smooth dynamics performance. This paper proposes a numerically efficient NURBS interpolation scheme which consists of two stages namely preprocessing and interpolating. In the stage of pre-processing, the parameter interval is split into several blocks at breakpoints and an iterative numerical quadrature method is applied for each block. By means of the iterative quadrature method, the initial parameter intervals of each block are divided into several subintervals according to the arc length approximation error. Meanwhile, the curvature of each knot and the cubic polynomial coefficients of each subinterval are obtained. Then the critical points with large curvature of each block are found from the candidate points and the tolerated speed of each critical point is calculated according to the constraints of chord error and centripetal acceleration. Hence, the feedrate scheduling based on the S-shaped acceleration profile for each block can be preplanned via the approximate arc length of each subinterval, the tolerated speed of each critical point and kinematics characteristics such as acceleration/deceleration and jerk limits of the machine tools. In the stage of interpolating, the parameter of the next interpolation point can be calculated directly using the cumulative arc length and the cubic polynomial coefficients of each subinterval. Finally, a series of numerical simulations and real machining experiments are conducted, and the simulation and experimental results have showed the good performance of the proposed NURBS interpolator both in efficiency and accuracy.

This paper presents a periodic concept in stiffened-thin-plates by applying Bloch׳s theorem. Through the established dynamic equation for periodically stiffened-thin-plate (PSTP), the band gap of PSTP is calculated with the help of center-finite-difference-method (CFDM). CFDM simplifies the calculation in plate vibration differential equation. Instead of dealing with complex high-level differential equation, CFDM solves only algebraic equation. In this paper, the band gap׳s frequency property of PSTP has also been analyzed. The parameters of structure that influence the band gap׳s frequency have been fully discussed as well. Finally, the theory presented in this paper is verified by numerical simulations and the results reveal that there is consistency between two methods.

Surface roughness is a technical requirement for machined products and one of the main product quality specifications. In order to avoid the costly trial-and-error process in machining parameters determination, the Gaussian process regression (GPR) was proposed for modeling and predicting the surface roughness in end face milling. Cutting experiments on C45E4 steel were conducted and the results were used for training and verifying the GPR model. Three parameters, spindle speed, feed rate, and depth of cut were considered; the experiment results showed that depth of cut is the main factor affecting the surface roughness and regression results showed that the GPR model has a good precision in predicting the surface roughness in different cutting conditions. The prediction accuracy was nearly about 84.3 %. Based on the GPR prediction model, 3D-maps of surface roughness under various cutting parameters could be obtained. It is very concise and useful to select the appropriate cutting parameters according to the maps. As experimental results did not conform to the empirical knowledge, frequency spectrums of the tool were analyzed according to the 3D-maps, it was found that tool vibration is also a crucial factor affecting the machined surface quality.

This article proposes a novel artificial ecological niche optimization algorithm for car sequencing problem considering energy consumption to satisfy the requirements of the paint shop and the assembly line. Energy consumption, which is an important issue, is often neglected during the production process. In this article, the mathematical model of car sequencing problem with energy consumption is established. A new artificial ecological niche optimization algorithm that imitates natural ecosystem is proposed to solve this problem. The car sequence is considered as an ecosystem. Ecological niche theory, niche overlap and niche differentiation principles are applied in this algorithm, which leads the ecosystem to adapt itself to a more ecological balance condition accompanying less violence appear in the car sequence. Energy consumption in the scheduling process of ring sorting buffer was considered as biogenic migration in the algorithm. The proposed algorithm is verified on a set of instances provided by the French car manufacturer Renault. The computation results indicate the effectiveness of the proposed algorithm.

This paper describes a study on laser butt welding of 4 and 2 mm SUS301L stainless steel and a detailed analysis of welding joints. The gap tolerance of butt joint was also studied with optimized process parameters. The electrolytic etching in 10 % oxalate solution was used to test the intergranular corrosion of the 4 mm SUS301L welded joint. Fatigue property of the 2 mm SUS301L welded joint was tested under the conditional cycle times of 1 × 107. Using optical microscopy, the changes of metallurgical microstructure in the weld zone of 4 mm SUS301L were also studied. It has been found that laser butt welding of 4 mm SUS301L is able to achieve sound metallurgical morphology and high strength weld joint when the butt gap is within certain tolerance. The weld joint also has good resistance to intergranular corrosion and has a fatigue limit of 310 MPa.

Reliability prediction is of great importance to improve the operational safety of machinery and decreasing their maintenance costs. In this paper, a new method combining double-Wiener process model with Monte Carlo algorithm is proposed to solve the problem of degradation modeling and reliability prediction of machinery with multiple degradation characteristics. Unlike other Wiener process-based prediction methods that only the mean is modelled, this method considers the degradation of both mean and variance, making degradation modelling more accurate. Meanwhile, the proposed method estimates reliability level of the machinery based on its entire monitoring information to date through an expectation maximization algorithm and a Monte Carlo algorithm, which does not require historical degradation data of other machines in a population. A numerical degradation case and a bearing degradation case with a set of degradation data are studied to validate the proposed method. The results demonstrate the effectiveness of the proposed method compared with other existing methods.

Optimization for the surface grinding process is a problem with high complexity and nonlinearity. Hence, evolutionary algorithms are needed to apply to get the optimum solution of the problem instead of the traditional optimization algorithms. In this work, a hybrid particle swarm optimization (HPSO) algorithm which combines the dynamic neighborhood particle swarm optimization (DN-PSO) algorithm with the strategy of mutation considering constraints is presented to handle multi-objective optimization for surface grinding process. Such four process parameters as wheel speed, workpiece speed, depth of dressing, and lead of dressing are considered as the variables for optimization, and the following three objectives such as production cost, production rate, and surface roughness are used in a multi-objective function model with a weighted approach. Meanwhile, the constraints of thermal damage, wheel wear, and machine tool stiffness are considered. Computational experiments are conducted on cases of both rough grinding and finish grinding, and comparison results with the previously published results obtained by using other optimization techniques shows the efficiency of the proposed algorithm.

This paper discusses how to improve the position precision of a semi-closed loop servo system. A support vector regression algorithm is chosen to model and predict position error. The predicted error is then fed back to the input entry to compensate the error. Fuzzy PID control is introduced to adjust the controlling rule of the PID controller in the semi-closed loop servo system so as to improve the dynamic response characteristics of the servo system and reach a high degree of position precision. A case study is implemented. The simulation and experimental results show that combining the improved fuzzy control with predicted position error feedback ensures a high degree of position precision and a high degree of dynamic response characteristics.

In the medium-speed wire electrical discharge machining (MS-WEDM) process, the extremely high temperature and massive electrical discharges in a fraction of 1 s result in the poor surface quality such as high tensile residual stresses, high surface roughness, white layers, and micro cracks. In this paper, an experimental plan for central composite design (CCD) of processing the tool steel (SKD11) has been conducted according to response surface methodology (RSM). The aim is to develop the mathematical model that can correlate the main process parameters of MS-WEDM with machining performance and to seek the optimal parameters on material removal rate (MRR) and 3D surface quality (Sq) by integrated RSM and Non-dominated Sorting Genetic Algorithm-II (NSGA-II). Then, a set of pareto-optimal solutions is obtained. Moreover, from the confirmation experiment, it has been proved that the optimal process-parameter combinations are suitable on the MRR and the 3D surface texture. Eventually, it has also demonstrated that the method of integrated RSM and NSGA-II is an effective way for multi-objective optimization.

The core loss of the grain-oriented silicon steel influences the energy loss of transformer. Pulse energy, point spacing, and scribing spacing are the three key parameters of laser scribing process, which determine the core loss of silicon steel. In this study, the relationship between the three key parameters and core loss reduction was investigated and analyzed. Experiments of laser scribing on 30Q130 silicon steel with different parameter combinations were implemented. The results showed that there was no obvious silicon coating burns in the surface of the steel after laser scribing and that the core loss reduction rate (reduction rate) significantly increased with the increasing laser energy density. However, when the energy density exceeded a certain range, the reduction rate decreased and gradually tended to a stable level. Hence, the parameters had significant influence on the reduction rate of core loss, and the two-factor interaction effects of reduction rate of core loss were prominent when parameters of high pulse energy, small point spacing, and small scribing spacing were selected. The optimization combination values of the three key parameters of laser scribing process on 30Q130 silicon steel was acquired by genetic algorithm–enhanced artificial neural network algorithm. For achieving high reduction of core loss, the optimized combination of pulse energy of 2.52 mJ, small point spacing of 0.22 mm, and small scribing spacing of 3.03 mm were selected, and the reduction rate of 13.12 % was verified through experiment.

For assemble-to-order enterprises, both order scheduling and mixed-model sequencing need to be taken into consideration in the formulation of order-oriented assembly plan. First, determining production priority for the received orders, and then conducting assembly sequence to the mixed-model products in each order. Order scheduling is aimed to ensure order delivery with the optimization goal of minimal total overdue time, while product sequencing is aimed to minimize the makespan so as to meet the requirement on completion time of the order. In the end, the paper establishes a mixed integer programming model based on an industrial case, and makes programming calculation with Xpress-MP to accomplish an order-oriented assembly plan conforming to actual production.