51Âþ»­

An academically and commercially astute researcher with a passion for the ideation, design and manufacture of products that make human systems much more easier. I find it more fulfilling impacting people with ideas and placing them on the the right path that is affiliated to their abilities in the learning curve. I am an innovative industrious talented Mechanical and Mechatronics Engineer with a proven track record in learning new skills since graduating from both engineering disciplines. A communicative, encouraging team player who presents ideas effectively and can assist others in the latest procedures with good tracking research acumen and quickly surpassed expectations in design as well as in end-to-end project management. 

I have continued to maintain an excellent academic record in the aspect of research, practical and learning. However, my dream is to attain a PhD degree in my present area of research in order to impact lives and contribute my quota in attaining the United nations sustainable development goals. 

I currently have about 12 research publications while 4 is under review in my field of interest and I have consistently proven throughout my previous studies and working experience that when presented with an opportunity I will strive as hard as I can to best represent myself and reward those who have granted me a chance to prove such. This is evident in my continuing relations with 51Âþ»­ in research publication and my professional deliveries within the faculty at 51Âþ»­. 

My eventual career goal is therefore to assume responsibility for the analysis and implementation of all skillset i have acquired over time and actively contribute to the overall success of any establishment I would feature in.

Institute of Engineering Sciences (IES)

• Sustainable development 
• MATLAB
• Neural Networks
• Dynamics and control
• Additive Manufacturing

• Dynamics and Control
• Thermofluid and Heat transfer
• Vibration

M.Sc Mechatronics
B.Eng Mechanical Engineering

Title

Real time Quality monitoring of 3D printed Scaffold

Abstract

This study describes a modified 3-D printer and a developed software-based algorithm which can be used to monitor layer-wise 3-D printing processes, identify certain common printing errors, and initiate appropriate feedback actions to the printer for adjustments of status settings in order to improve reliability and eliminate tendencies that might affect the mechanical property and general aesthetic quality of the final component under manufacture. The approach adopted here builds upon computer vision and multi-stage image classification, which allows monitoring by extracting features of the external shape of the object on the print bed and internal structure of its layers and compare it to the features of an originally designed model. To access the quality of parts, an integrated camera initiates the process by capturing pictures of the top and side layers at regular intervals defined by the feedback signals of an integrated microcontroller which monitors the extruder’s position. Extracted image data are inputted into the developed program in real time and analysed using mean error multi-template matching and iterative closest point algorithms and segmenting spatial anomalies by vector quantization through partitioning of the data space into Voronoi cells with K-means clustering algorithm. ABS and PLA parts were printed to demonstrate the viability of the framework and the experimentally verified runtime of the algorithm is estimated to about 25secs which can be considered a good trade off compared to the loss of material, loss of energy and money associated with a normal setting.

Dr Abolfazl Zahedi and Dr Seng Chong