Prediction of tool wear using regression and ANN models in end-milling operation

Palanisamy, P.; Rajendran, I.; Shanmugasundaram, S.

doi:10.1007/s00170-007-0948-5

Cited by 148 publications

(55 citation statements)

References 12 publications

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“…Given this fact, it would be interesting to analyze the ideal levels of the factors for the size of each almond (18,21,23,25 and 28 mm) in order to determine with more specificity the most adequate adjustment for this factor. In this work, only the analysis for the size of 21 mm (table 04) will be presented.…”

Section: Discussion Of the Resultsmentioning

confidence: 99%

“…In this sense the author [7] affirms that the Design of Experiments is a scientific approach of planning e accomplishment of experiments to generate, analyze and interpret the datas in a way that conclusions can be used to design a process more efficient and economic. [8] adds that the DOE involves a set of carefully programmed testes where the operational parameters of the experimental test are personalized, in a way to reduce the time and cost of the experimentation.…”

Section: Design Of Experimentsmentioning

confidence: 96%

“…The statistical Northeastern Brazil analysis of the method are useful in the identification and control of the critical variables, in other words, those that possesses a greater influence on the process, if adjusted inadequately, can cause deviations that affect the quality and efficiency of the product/process [7].…”

Section: Design Of Experimentsmentioning

confidence: 99%

“…Examples of works applied in the food industries can be quoted like in the works of [13,16,17,18]; works applied in the pharmaceutical industry and biotechnology like it was demonstrated in the works of [19,20,21]; and works in mechanical, metallurgical and chemical processes such as those presented by [22,23,24,25,26,27,28,29,30,31,32,33].…”

Section: Design Of Experimentsmentioning

confidence: 99%

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The Design of Experiment Application (DOE) in the Beneficiation of Cashew Chestnut in Northeastern Brazil

Rocha¹

2015

AJTAS

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Abstract:Brazil is one of the world´s leaders in the production and processing of cashew chestnut and 100% of these cashew chestnut processing industries are located in the northeastern region of the country. For the maintenance and enlargement of the cashew chestnut market it is necessary to have a guarantee of the product quality by means of controlling the productive process. In this case, the application of DOE (Design of Experiments) is suggested in the beneficiation process of the cashew chestnut, notably in the stage of decortication, where the chestnuts are being cut in bands, by a mechanical means. For this process, a fractionated factorial experiment planning was used and evaluated response variable in the experiment was the quality of the almond in the final stage of production, measured by the percentage of whole almonds after the separation from the barks. The chosen process factors were the almonds size, the humidification of the environment, the temperature of the environment before the decorticator and the velocity of the decorticator. At the end of the experiment, it was observed that DOE showed to be an applicable tool that indicates which factors showed to be more influential, as well as, their levels of adjustment. It was observed that the variables related to the size of the almonds, the velocity in decortication are the influential factors of production in this process, apart from a strong noise being identified in this process, observed by the strong variance in the experiment data, especially that of the response variable.

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Section: Discussion Of the Resultsmentioning

confidence: 99%

Section: Design Of Experimentsmentioning

confidence: 96%

Section: Design Of Experimentsmentioning

confidence: 99%

Section: Design Of Experimentsmentioning

confidence: 99%

See 2 more Smart Citations

The Design of Experiment Application (DOE) in the Beneficiation of Cashew Chestnut in Northeastern Brazil

Rocha¹

2015

AJTAS

View full text Add to dashboard Cite

show abstract

“…In this case, the regression model was slightly superior. Palanisamy, Rajendran and Shanmugasundaram (2008) compared the performance of regression and ANN models for predicting tool wear in ending milling operation, with ANNs presenting better results. Karnik, Gaitonde and Davim (2007) applied neural networks and RSM models to predict the burr size for a drilling process.…”

Section: Rbf's Applied To Surface Roughness Predictionmentioning

confidence: 99%