Investigating Process Parameters and Microhardness Predictive Modeling Approaches for Single Bead 420 Stainless Steel Laser Cladding

2017 ◽  
Author(s):  
Mohammad K. Alam ◽  
Navid Nazemi ◽  
Ruth Jill Urbanic ◽  
Syed Saqib ◽  
Afsaneh Edrisy
Keyword(s):  
Stainless Steel ◽  
Laser Cladding ◽  
Predictive Modeling ◽  
Process Parameters ◽  
Modeling Approaches ◽  
Single Bead

scholarly journals Analysis of the Process Parameter Influence in Laser Cladding of 316L Stainless Steel

2018 ◽  
Vol 2 (3) ◽  
pp. 55 ◽  
Author(s):  
Piera Alvarez ◽  
M. Montealegre ◽  
Jose Pulido-Jiménez ◽  
Jon Arrizubieta
Keyword(s):  
Stainless Steel ◽  
Laser Cladding ◽  
Process Parameters ◽  
Cross Sections ◽  
316L Stainless Steel ◽  
Deposition Process ◽  
Process Parameter ◽  
Optimum Process ◽  
Processing Times ◽  
Manufacturing Technologies

Laser Cladding is one of the leading processes within Additive Manufacturing technologies, which has concentrated a considerable amount of effort on its development. In regard to the latter, the current study aims to summarize the influence of the most relevant process parameters in the laser cladding processing of single and compound volumes (solid forms) made from AISI 316L stainless steel powders and using a coaxial nozzle for their deposition. Process speed, applied laser power and powder flow are considered to be the main variables affecting the laser cladding in single clads, whereas overlap percentage and overlapping strategy also become relevant when dealing with multiple clads. By setting appropriate values for each process parameter, the main goal of this paper is to develop a processing window in which a good metallurgical bond between the delivered powder and the substrate is obtained, trying simultaneously to maintain processing times at their lowest value possible. Conventional metallography techniques were performed on the cross sections of the laser tracks to measure the effective dimensions of clads, height and width, as well as the resulting dilution value. Besides the influence of the overlap between contiguous clads and layers, physical defects such as porosity and cracks were also evaluated. Optimum process parameters to maximize productivity were defined as 13 mm/s, 2500 W, 30% of overlap and a 25 g/min powder feed rate.

Using Predictive Modeling and Classification Methods for Single and Overlapping Bead Laser Cladding to Understand Bead Geometry to Process Parameter Relationships

2016 ◽  
Vol 138 (5) ◽  
Author(s):  
R. J. Urbanic ◽  
S. M. Saqib ◽  
K. Aggarwal
Keyword(s):  
Laser Cladding ◽  
Predictive Modeling ◽  
Predictive Models ◽  
Goodness Of Fit ◽  
Process Parameter ◽  
Bead Geometry ◽  
Process Characteristics ◽  
Single Bead ◽  
Reduced Gradient ◽  
Generalized Reduced Gradient

Developing a bead shape to process parameter model is challenging due to the multiparameter, nonlinear, and dynamic nature of the laser cladding (LC) environment. This introduces unique predictive modeling challenges for both single bead and overlapping bead configurations. It is essential to develop predictive models for both as the boundary conditions for overlapping beads are different from a single bead configuration. A single bead model provides insight with respect to the process characteristics. An overlapping model is relevant for process planning and travel path generation for surface cladding operations. Complementing the modeling challenges is the development of a framework and methodologies to minimize experimental data collection while maximizing the goodness of fit for the predictive models for additional experimentation and modeling. To facilitate this, it is important to understand the key process parameters, the predictive model methodologies, and data structures. Two modeling methods are employed to develop predictive models: analysis of variance (ANOVA), and a generalized reduced gradient (GRG) approach. To assist with process parameter solutions and to provide an initial value for nonlinear model seeding, data clustering is performed to identify characteristic bead shape families. This research illustrates good predictive models can be generated using multiple approaches.

scholarly journals Parameters Optimization of Auxiliary Gas Process for Double-Wire SS316L Stainless Steel Arc Additive Manufacturing

Metals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 190
Author(s):  
Wei Wu ◽  
Jiaxiang Xue ◽  
Wei Xu ◽  
Hongyan Lin ◽  
Heqing Tang ◽  
...  
Keyword(s):  
Stainless Steel ◽  
Additive Manufacturing ◽  
Process Parameters ◽  
Evaluation System ◽  
Gas Flow ◽  
Interactive Effect ◽  
Parameters Optimization ◽  
Heat Accumulation ◽  
Auxiliary Process ◽  
Strength And Stiffness

Serious heat accumulation limits the further efficiency and application in additive manufacturing (AM). This study accordingly proposed a double-wire SS316L stainless steel arc AM with a two-direction auxiliary gas process to research the effect of three parameters, such as auxiliary gas nozzle angle, auxiliary gas flow rate and nozzle-to-substrate distance on depositions, then based on the Box–Behnken Design response surface, a regression equation between three parameters and the total score were established to optimized parameters by an evaluation system. The results showed that samples with nozzle angle of 30° had poor morphology but good properties, and increasing gas flow or decreasing distance would enhance the airflow strength and stiffness, then strongly stir the molten pool and resist the interference. Then a diverse combination of auxiliary process parameters had different influences on the morphology and properties, and an interactive effect on the comprehensive score. Ultimately the optimal auxiliary gas process parameters were 17.4°, 25 L/min and 10.44 mm, which not only bettered the morphology, but refined the grains and improved the properties due to the stirring and cooling effect of the auxiliary gas, which provides a feasible way for quality and efficiency improvements in arc additive manufacturing.

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