Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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Masrol, Shaiful Rizal

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (7/7 displayed)

  • 2020The Mechanical Performance of Tile Based on Plastic Waste (PW) Mixed Wood Waste (MWW)4citations
  • 2019A study of reflection phase of reflectarray antennas with high loss organic substrates1citations
  • 2019Multiple Responses Optimisation in Injection Moulding Parameter for Polypropylene-Nanoclay-Gigantochloa Scortechinii via Taguchi Method.5citations
  • 2018Loss Quantization of Reflectarray Antenna Based on Organic Substrate Materialscitations
  • 2015Green Strength Optimization in Metal Injection Molding applicable with a Taguchi Method L9 (3) 44citations
  • 2013Mechanical and physical behaviour of short and randomly oriented banana pseudo-stem fiber reinforced epoxy compositecitations
  • 2013Sound absorption characteristics of palm oil male flower spikes fiber reinforced compositecitations

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Chart of shared publication
Mahmood, Salwa
1 / 2 shared
Marsi, Noraini
1 / 16 shared
Rashid, Azrin Hani Abdul
1 / 3 shared
Rus, Anika Zafiah Muhd
1 / 1 shared
Lecthumanan, Thineshnaidu
1 / 1 shared
Fodzi, Muhammad Haikal Mohd
1 / 3 shared
Huzaisham, Nur Athirah
1 / 4 shared
Rupashinii, A.
1 / 1 shared
Singam, P. Thana
1 / 1 shared
Adnan, Sharmiza
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Ismail, Muhammad Yusof
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Malik, H. I.
2 / 2 shared
Shaari, Muhammad Farid
1 / 6 shared
Hasan, Sulaiman
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Salim, Sabiha
1 / 2 shared
Main, Nor Mazlana
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Othman, Mohd Hilmi
1 / 1 shared
Amin, Azriszul Mohd
1 / 12 shared
Mustafa, N.
1 / 10 shared
Asmawi, Rosli
1 / 16 shared
Ibrahim, Mohd Halim Irwan
2 / 14 shared
Sudin, S. A.
1 / 1 shared
Ibrahim, Mohd Norihan
1 / 2 shared
Rosdin, M. K. R.
1 / 1 shared
Chart of publication period
2020
2019
2018
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Co-Authors (by relevance)

  • Mahmood, Salwa
  • Marsi, Noraini
  • Rashid, Azrin Hani Abdul
  • Rus, Anika Zafiah Muhd
  • Lecthumanan, Thineshnaidu
  • Fodzi, Muhammad Haikal Mohd
  • Huzaisham, Nur Athirah
  • Rupashinii, A.
  • Singam, P. Thana
  • Adnan, Sharmiza
  • Ismail, Muhammad Yusof
  • Malik, H. I.
  • Shaari, Muhammad Farid
  • Hasan, Sulaiman
  • Salim, Sabiha
  • Main, Nor Mazlana
  • Othman, Mohd Hilmi
  • Amin, Azriszul Mohd
  • Mustafa, N.
  • Asmawi, Rosli
  • Ibrahim, Mohd Halim Irwan
  • Sudin, S. A.
  • Ibrahim, Mohd Norihan
  • Rosdin, M. K. R.
OrganizationsLocationPeople

article

Green Strength Optimization in Metal Injection Molding applicable with a Taguchi Method L9 (3) 4

  • Amin, Azriszul Mohd
  • Mustafa, N.
  • Masrol, Shaiful Rizal
  • Asmawi, Rosli
  • Ibrahim, Mohd Halim Irwan
Abstract

Recently Metal injection molding is selected as a vital process in producing large amount of small part with complex geometry and intricate shape. This process is lead to solve cost effective issue in manufacturing fields. Feedstock composition behavior categorized as one of impact factor in determines the victories in metal injection molding process. Thus this paper is focused on optimizing the strength of green part by applied Taguchi Method L9 (34) as optimization tools during injection process. The composition of feedstock is 55% powder loading (PL) were injected by injection molding machine .Several injection parameter were optimized such as injection temperature (A), barrel temperature (B), injection pressure (C) and Speed (D) The results analyzed by using Signal to Noise Ratio (S/N ratio) terms. The highest green strength is A2, B2, C2, and D2

Topics
  • impedance spectroscopy
  • strength
  • injection molding