This technical summary is based on the academic paper “Effect of water flow rate, casting speed, alloying elements and pull distance on tensile strength, elongation percentage and microstructure of continuous cast copper alloys” published by Bagherian, E-R., Fan, Y., Cooper, M., Frame, B., & Abdolvand, A. in Metallurgical Research and Technology (2016). It was analyzed
This technical summary is based on the academic paper “Quality Assurance Testing for Screening Defective Aluminum Die-cast Rotors of Squirrel Cage Induction Machines” published by Jeong, M., Yun, J., Park, Y., Lee, S.B. and Gyftakis, K. in IEEE (2017). It was analyzed and summarized for HPDC experts by CASTMAN with the support of AI. Keywords
This technical summary is based on the academic paper “An investigation on effect of rotary degassing-ultrasonic method on high pressure die casting products” published in La Metallurgia Italiana (2022). It was analyzed and summarized for HPDC experts by CASTMAN experts with the help of LLM AI such as Gemini, ChatGPT, and Grok. Keywords Executive Summary
This technical brief is based on the academic paper “A STATISTICAL ANALYSIS OF JOINT STRENGTH OF DISSIMILAR ALUMINIUM ALLOYS FORMED BY FRICTION STIR WELDING USING TAGUCHI DESIGN APPROACH, ANOVA FOR THE OPTIMIZATION OF PROCESS PARAMETERS” by Mohammed Yunus & Mohammad S. Alsoufi, published in [IMPACT: International Journal of Research in Engineering & Technology (IMPACT: IJRET)]
How New EZAC® and HF Alloys Are Overcoming Traditional Temperature and Weight Limitations in Die Casting This technical brief is based on the academic paper “Recent Zinc Die Casting Developments” by R. Winter and F. E. Goodwin, Sc.D., published by the North American Die Casting Association (2013). It is summarized and analyzed for HPDC professionals
From Root Cause Analysis to Predictive Quality: A Dual AI Approach to Slash Die Casting Scrap Rates This technical brief is based on the academic paper “TOWARDS AN AI-Driven Smart Manufacturing of Diecastings” by F. Liu, S. Wang, X. Liu, T. Zhang, B. Yang, Q. Han, D. Yang, and Corey Vian, published in NADCA Transactions
Using Machine Learning to Predict and Reduce Porosity Defects in Die-Casting This technical brief is based on the academic paper “Factors Analysis and Prediction in Die-casting Process for Defects Reduction” by Pavee Siriruk and Titiwetaya Yaikratok, published in the Proceedings of the International Conference on Industrial Engineering and Operations Management (2022). It is summarized and
A Phased, Data-Driven Approach to Eliminating the 5 Major Wastes in Die Casting Operations This technical brief is based on the academic paper “Elimination of Wastes In Die Casting Industry By Lean Manufacturing: A Case Study” by Sumit Kumar Singh, Deepak Kumar, and Tarun Gupta, published in the IOSR Journal of Engineering (IOSRJEN) (2014). It
Boosting Durability of SKD61 Die-Casting Steel: A Data-Driven Look at Ti/Cr vs. Ti/Mo PVD Coatings This technical brief is based on the academic paper “Comparative Analysis on the Surface Property of SKD 61 Die-casting Steel Using Multilayer PVD Coating” by Seung Wook Kim, published in the Journal of the Semiconductor & Display Technology (2021). It
A Practical Guide to Boosting Productivity and Quality in Die Casting Using Proven Lean Principles This technical brief is based on the academic paper “Case study of lean manufacturing application in a die casting manufacturing company” by Ng Tan Ching, Clarence Chan Kok Hoe, Tang Sai Hong, Morteza Ghobakhloo, and Chen Kah Pin, published in
