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Journal : International Journal of Advanced Technology in Mechanical, Mechatronics and Material (IJATEC)

Design and Analysis of Ejector Pin in The Oil Seal Mould to Improve Its Mechanical Properties Haris Wahyudi; Swandya Eka Pratiwi; Irwan Firdaus
International Journal of Advanced Technology Vol 1, No 1 (2020)
Publisher : Institute for Research on Innovation and Industrial System (IRIS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (252.512 KB) | DOI: 10.37869/ijatec.v1i1.8

Abstract

Ejector pin in the mould is used to release (eject) the finished product, to vent gas out of the cavity and to expedite the material flow. It must have high strength, good hardness, good wear and corrosion resistance to withstand high pressure. Poor ejector pin may result in defect of finished product and delay the process due to additional time was required to release sticking product in the mould. The aim of this research is to select proper material for the ejector pin and analyse it not to experience plastic deformation. Three specimens’ steel was considered for making the pin, SUS 304, normal SKS 3 and heat treated SKS 3. Hardness and tensile test were used to examine the mechanical properties of specimens and impact was utilized to obtain impact energy using Charpy method. Static stress analysis was also used to simulate the working load using SolidWorks.  Rockwell hardness test recorded that SUS 304, normal SKS 3 and heat treated SKS have 23.2 HRC 9.6 HRC and 38.03 HRC, respectively. Tensile test produced yield strength of 452.9 MPa for SUS 304 and 432.6 MPa for SKS 3. Impact energy absorbed during Charpy test for SUS 304 equal to 0,804 J/ mm2 and specimen SKS 3 equal to 0,863 J/mm2. By taking the mechanical test result and SolidWorks simulation, it was concluded that the suitable material for ejector pin is SUS 304.
Development of a Smart Digital Advertisement Board Based on Face Recognition System Fahri Heltha; Sharandhass Radakrishnan; Haris Wahyudi; Aulia Rahman
International Journal of Advanced Technology Vol 4, No 1 (2023)
Publisher : Institute for Research on Innovation and Industrial System (IRIS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37869/ijatec.v4i1.100

Abstract

Abstract. We develop a smart digital advertisement board system which allows the system to display advertisements based on the majority of age and gender classifications of the consumers. The system captures the faces of the crowd and the face recognition techniques used to classify the majority gender and age of the crowd and then shows appropriate advertisement from the database to the advertisement board. A DNN model that is built, trained, and validated is used to recognize and predict the age and gender of the visible faces through image input or webcam using face photo dataset known as audience dataset. Several testing and analysis have been done onto the system in order to demonstrate the effectiveness and reliability of the system in displaying suitable advertisement for the public. The system can get gender accuracy of 77.82% and 86% for female and male respectively. And 68.78% accuracy for age recognition. The recognition speed is less than 1.3 second for up to 9 faces in an input image.