The International Journal of Advanced Manufacturing Technology

Doyle, Anthony; Nee, Andrew

doi: 10.1007/s00170-014-5892-6pmid: N/A

Pérez-Rodríguez, Ricardo; Jöns, S.; Hernández-Aguirre, Arturo; Alberto-Ochoa, Carlos

doi: 10.1007/s00170-014-5759-xpmid: N/A

The flexible jobshop scheduling problem permits the operation of each job to be processed by more than one machine. The idea is to assign the processing sequence of operations on the machines and the assignment of operations on machines such that the system objectives can be optimized. The assignment mentioned is a difficult task to implement on real manufacturing environments because there are many assumptions to satisfy, especially when the amount of work is not constant or sufficient to keep the manufacturing process busy for a long time, causing intermittent idle times. An estimation of distribution algorithm-based approach coupled with a simulation model is developed to solve the problem and implement the solution. Using the proposed approach, the shop performance can be noticeably improved when different machines are assigned to different schedules.

Gao, Xiangdong; Chen, Yuquan

doi: 10.1007/s00170-014-5811-xpmid: N/A

Accurate seam tracking plays a critical role in acquisition of good weld. During laser butt joint welding, the laser beam focus must be controlled to follow the weld trajectory. The key problem to be solved is the automatic identification of weld position. An approach to detect the micro gap weld (gap width is less than 0.05 mm) based on magneto-optical imaging (MOI) is proposed. The laser butt joint welding of carbon steel was carried out. A magnetic excitation device was used to magnetize the weldment, and it was found that magnetic field distribution at the weld was different from other regions. The magnetized weldment was detected by using a magneto-optical sensor, and magneto-optical images of the weld were captured. By analyzing and processing weld MO images with low contrast and strong magnetic field noises, the weld center position could be detected accurately. Weld MO images at different laser welding speeds were investigated to analyze the varieties of image characteristics. Experimental results indicated that the magneto-optical imaging technique could be applied to detect the micro gap weld accurately, which provides a novel approach for automatic identification and tracking of micro gap weld during laser welding.

Bordatchev, Evgueni; Hafiz, Abdullah; Tutunea-Fatan, O.

doi: 10.1007/s00170-014-5761-3pmid: N/A

Laser polishing is presently regarded as one of the enabling technologies hoped to eventually replace the need for time-consuming and error-prone manual polishing operations which are often required by metallic surfaces. During laser polishing, a thin layer of material is being melted as a result of laser irradiation. Since molten metal is characterized by increased relocation capabilities, laser polishing is generally accompanied by a more or less significant decrease in the surface roughness. The primary objective of this study is to present a comprehensive snapshot of the advancements made over more than one decade with respect to theoretical and experimental investigation of laser polishing technology. However, in addition to the usual review of the state-of-the-art in the field, the study places an increased emphasis on the finishing performance of the process, defined through the perspective of pre- and postpolishing surface roughness. The implementation of this metric with strong practical implications has revealed that under appropriate process parameters, certain classes of metallic materials can reduce their average surface roughness by more than 80 %, possibly to R a  = 5 nm. Nonetheless, a more rigorous and fundamental understanding of the intrinsic mechanisms underlying laser polishing remains one of the currently unfulfilled premises toward a wider industrial adoption of the process.

Alvarez, Jorge; Barrenetxea, David; Marquinez, Jose; Bediaga, Iñigo; Gallego, Ivan

doi: 10.1007/s00170-014-5771-1pmid: N/A

This paper presents a novel method for improving infeed grinding processes based on the application of continuous variable feed rate (CVFR). Nowadays, infeed cycle configuration is defined by selecting constant feed rates and stock removals for each consecutive stage, normally roughing, finishing, and a final spark-out, for the purpose of achieving required workpiece tolerances in a fixed time while avoiding process limitations and instabilities. CVFR leads to more efficient cycles without the difficulty of defining feed rate and stock removal values. To that end, CVFR has been implemented in a time-domain simulation of infeed grinding processes to analyze theoretically the influence of variation parameters in process forces, workpiece roughness, roundness and size tolerance, or dynamic behavior. Then, tests have been performed to validate the simulation approach, comparing CVFR cycles with equivalent conventional ones. Different types of downward variations for the feed rate have been applied, concluding that grinding processes can be improved with this method regarding productivity and workpiece geometrical and surface tolerances.

Li, Anhu; Lan, Qiangqiang; Dong, Dongsheng; Liu, Zhao; Li, Zhizhong; Bian, Yongming

doi: 10.1007/s00170-014-5785-8pmid: N/A

The flow channel structures of turbo-charged pipes used in vehicle engines should exhibit superior noise reduction and less pressure loss. A design model of nylon blow molding structure as a turbo-charged pipe is introduced in this paper. The integrated analysis of noise reduction and pressure drop over a flow channel inside a blow-molded pipe is carried out by the method of multiphysical field collaborative simulation. The coupling relation between noise reduction and pressure drop to access a combined optimization is innovatively established by defining the actual physical modes. Based on the design parameters, the blow molding for the design model is implemented in detail and, some valuable conclusions are drawn suggestive to the actual technology process. The experimental verification for the pipe sample indicates that the developed channel structure can meet the requirements of both noise reduction and pressure drop. This proposed design method can be referred for the development of blow-molded pipes.

Wang, Xiaojie; Wang, Hui-Ping; Lu, Fenggui; Carlson, Blair; Wu, Yixiong

doi: 10.1007/s00170-014-5810-ypmid: N/A

In this paper, an experimental study combined with a numerical model consideration of both thermal conduction and fluid flow in the molten pool were carried out, aiming to analyze solidification cracking susceptibility of dual-beam laser welding on Al alloys. The maximum accumulated transverse displacement in the mushy zone was calculated based on the strip expansion technique and employed to evaluate centerline solidification cracking susceptibility. Numerical calculations showed that increasing inter-beam spacing in side-by-side dual-beam laser welding of Al alloys could lead to increased accumulated transverse displacement in the weld, resulting in higher solidification cracking susceptibility, which agreed well with experimental observations. The analysis results also showed that increasing the laser power or reducing the welding velocity increased hot cracking susceptibility. The optimum cracking-free welding condition for dual-beam laser welding of Al can be determined with the help of numerical modeling, in which the hot cracking susceptibility can be evaluated and numerically reduced by adjusting welding process variables.

Peng, Anhua; Xiao, Xingming; Yue, Rui

doi: 10.1007/s00170-014-5796-5pmid: N/A

Fused deposition modeling (FDM) is gaining distinct advantages because of its ability to fabricate the 3D physical prototypes without the restrictions of geometric complexities, while when it comes to accuracy and efficiency, the advantages of FDM is not distinct, and so how to improve them is worthy of study. Focusing on process parameter optimization, such parameters as line width compensation, extrusion velocity, filling velocity, and layer thickness are selected as control factors, input variables, and dimensional error, warp deformation, and built time are selected as output responses, evaluation indexes. Experiment design is assigned according to uniform experiment design, and then the three output responses are converted with fuzzy inference system to a single comprehensive response. The relation between the comprehensive response and the four input variables is derived with second-order response surface methodology, the correctness of which is further validated with artificial neural network. Fitness function is created using penalty function and is solved with genetic algorithm toolbox in Matlab software. With confirmation test, the results are obtained preferring to the results of the experiment 1 with the best comprehensive response among the 17 experiment runs, which confirms that the proposed approach in this study can effectively improve accuracy and efficiency in the FDM process.

Hu, Zhanqi; Wang, Jialu; Chen, Dongdong

doi: 10.1007/s00170-014-5747-1pmid: N/A

In the high-speed milling process of large end milling cutter, the stress of cutter caused by centrifugal force accounts for a large proportion of the total stress of the cutter and has a great influence on the milling process. In this paper, an end milling cutter with a diameter of 2,800 mm used on large and high-speed aluminum blank milling machine tools is taken as a research object, and the equations of internal stress caused by centrifugal force have been derived by using analytic method. On this basis, the factors affecting the internal stress were analyzed. Furthermore, the analytic results and the finite element analysis results were compared in order to confirm their correctness. Finally, according to the results of stress analysis, structure topology optimization design for large end milling cutter was carried out in order to reduce the weight and centrifugal force of the cutter.

Garg, A.; Tai, K.; Vijayaraghavan, V.; Singru, Pravin

doi: 10.1007/s00170-014-5817-4pmid: N/A

Drilling is one of the important machining processes performed extensively in production industry. Literature emphasises that the output process parameters such as burr height, surface roughness, strength, etc. are related to and can be improved by the appropriate settings of the input process parameters. Recently, researchers have applied well-known computational intelligence methods such as regression analysis, artificial neural networks (ANNs), support vector regression (SVR), etc. in the prediction of performance characteristics of the drilling process. Alternatively, an evolutionary approach of multi-gene genetic programming (MGGP) that evolves the model structure and its coefficients automatically can be applied. Despite of being widely applied, MGGP has the limitation for producing models that over-fit on the testing data. One of the reasons attributed for this behaviour is the over-size of the evolved models. Therefore, a statistical-based MGGP (S-MGGP) approach is proposed and applied to the burr height data obtained from the drilling of AISI 316L stainless steel. In this proposed approach, Bayesian information criterion is embedded in its paradigm, which punishes the fitness of larger size models. The performance of S-MGGP and ANN models is found to be better than those of the standardised MGGP and SVR. Further, the parametric and sensitivity analysis conducted validates the robustness of our proposed model and is proved to capture the dynamics of the drilling phenomenon by unveiling dominant input process parameters and the hidden non-linear relationships.