DOE Based Statistical Approaches in Modeling of Laser Processing – Review & Suggestion
نویسندگان
چکیده
Design of Experiment commonly referred to as DOE is one of the extensively used methods for experimental study of many processes in engineering. It is a statistical approach in which a mathematical model is developed through experimental runs. DOE provides us the opportunity to optimize and predict possible output based on the parameters setting. In this study, a review is done on DOE techniques that have been employed for laser beam process optimization by other researches. This study predominantly focuses on the usage of response surface methodology, Taguchi’s method and factorial design in laser beam machining. A deduction is made to illustrate the significance of machining parameters
منابع مشابه
Combined application of computational fluid dynamics (CFD) and design of experiments (DOE) to hydrodynamic simulation of a coal classifier
Combining the computational fluid dynamics (CFD) and the design of experiments (DOE) methods, as a mixed approach in modeling was proposed so that to simultaneously benefit from the advantages of both modeling methods. The presented method was validated using a coal hydraulic classifier in an industrial scale. Effects of operating parameters including feed flow rate, solid content and baffle le...
متن کاملDetermination of settlement trough width and optimization of soil behavior parameters based on the design of experiment method (DOE)
The expansion of the settlement trough is an important factor in the risk assessment of the tunneling induced settlement. The increase of settlement trough requires buildings to be included in the impact zone, which causes damages. This paper conducts estimation of the settlement trough width (STW) using empirical approaches, field measurement data and numerical solutions. The credibility of th...
متن کاملAccuracy evaluation of different statistical and geostatistical censored data imputation approaches (Case study: Sari Gunay gold deposit)
Most of the geochemical datasets include missing data with different portions and this may cause a significant problem in geostatistical modeling or multivariate analysis of the data. Therefore, it is common to impute the missing data in most of geochemical studies. In this study, three approaches called half detection (HD), multiple imputation (MI), and the cosimulation based on Markov model 2...
متن کاملMachine learning algorithms in air quality modeling
Modern studies in the field of environment science and engineering show that deterministic models struggle to capture the relationship between the concentration of atmospheric pollutants and their emission sources. The recent advances in statistical modeling based on machine learning approaches have emerged as solution to tackle these issues. It is a fact that, input variable type largely affec...
متن کاملLand use impacts on surface water quality by statistical approaches
Surface waters are the most important economic resource for humans which provide water for agricultural, industrial and anthropogenic activities. Surface water quality plays vital role in protecting aquatic ecosystems. Unplanned urbanization, intense agricultural activities and deforestation are positively associated with carbon, nitrogen and phosphorous related water quality parameters. Multip...
متن کامل