Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : Predictive modeling


Predictive Modeling of Multilayer Graphene Growth by Chemical Vapour Deposition on Co-Ni/Al2O3 Substrate using Artificial Neural Network

May A. Muslim; Zainab Yousif; Mohamed A. Abdel Ghany

Engineering and Technology Journal, 2019, Volume 37, Issue 1C, Pages 113-119
DOI: 10.30684/etj.37.1C.18

The uniqueness of multilayer graphene as extremely high carrier mobility, tune-able band gap and high elasticity has made it be considered as a high prospect engineering material that can be employed for several applications such as solar cells, field effect transistors, super-capacitors, batteries and sensors. In this study, the application of Artificial Neural Networks (ANN) for the predictive modeling of multilayer graphene (MLG) growth by chemical vapor deposition (CVD) on Co-Ni/Al2O3 substrate was investigated. Data comprises temperature, catalyst compositions, ethanol flowrates were generated using central composite experimental design and employed to obtain the MLG yield as the response. The data were subsequently used for predictive modeling using ANN. The findings show that the predictive values of the MLG yields were in good agreement with those obtained from the experimental runs having a coefficient of determination (R2 ) of 0.988.

Predictive Modeling of Surface Roughness Of Centered And Un-Centered Workpiece Lengths In Turning Operation

Abdullah H. Singal; Farhad M. Kushnaw; Ali Abbar Khleif

Engineering and Technology Journal, 2010, Volume 28, Issue 1, Pages 65-71

The attempt of the present study has addressed an area that has been relatively
neglected in the past researches. This area focuses on studying and analysis the effect
of different centered and un-centered workpiece lengths, using turning machine
tailstock, on the products surface roughness, and then collecting data to generate an
experimental charts and equations for the prediction modeling of surface roughness
and increasing productivity for many turned products. These charts and equations
could be serving as a quick indication for manufacturers to avoid pre-chatter conditions
and the trial and error methods, and consequently reduce the required experience in
this field. So, the applicable range of workpiece lengths can be safely extended from
10 mm to 60 mm bars with 10 mm in diameter, and from 10 to 75 mm bars with 20
mm in diameter. This range could be increasing as bar diameter increasing and vise
versa.