News Update on Manufacturing Engineering : Nov 2020

Advanced manufacturing engineering

In this paper reported are some of the activities of the Laboratory of Manufacturing Technology of the NTUA in manufacturing engineering, focusing onto some recent trends and developments in advanced manufacturing of advanced materials, mainly emphasizing my long-standing Greek–Ukrainian–Russian–Hungarian scientific cooperation, also with international involvement worldwide, in the principal research and very important engineering topics nowadays, from industrial, research and academic point of view: ultraprecision engineering and nanotechnology and net-shape manufacturing of high-temperature ceramic superconductors. [1]

Globalization and the Undergraduate Manufacturing Engineering Curriculum

At an ASME panel on manufacturing engineering education, industry representatives emphasized preparation for globalization. The concept has not yet had widespread impact on undergraduate engineering curricula. In this paper the industry updates are summarized, especially as they pertain to undergraduate engineering education for a globalized economy, and synthesized with the literature on the subject. Objectives for manufacturing engineering education are derived and possible ways of introducing the subject into an undergraduate curriculum without lengthening the program are suggested. The findings should be applicable to manufacturing, mechanical, and industrial engineering. [2]

Virtual reality simulations and animations in a web-based interactive manufacturing engineering module

This paper presents a web-based interactive teaching package that provides a comprehensive and conducive yet dynamic and interactive environment for a module on automated machine tools in the Manufacturing Division at the National University of Singapore. The use of Internet technologies in this teaching tool makes it possible to conjure visualisations that cannot be achieved using traditional teaching materials such as transparencies. Virtual reality simulations and animations were developed and appropriately placed in the teaching materials to enhance the student understanding of complex concepts. This is especially useful in teaching automated machine tools, which deals primarily with the numerical control (NC) of the motions of automated machine tools. These virtual reality simulations and animations provide the capability of training students in NC programming and operations without the need to work on actual NC machines in the laboratory. The simulations are suitably placed in the package to engage the students and enhance their concentration, while at the same time generate interactions. Customised question types were also designed and implemented with a tutorial monitoring application. [3]

Application of House of Quality Matrix to Material Selection for Engineering Designs

Aims: The paper developed a strategy that apply the house of quality (HOQ) matrix for selecting appropriate engineering materials for use in engineering designs. The HOQ matrix provides a means for translating customer needs into appropriate technical requirements for effective product planning.

Study Design: Development of strategy for material selection and comparison using HOQ Computer Assisted Materials Selection (HCAMS) Software.

Place and Duration of Study: Department of Mechanical Engineering, Federal University of Technology, Akure, Ondo State, Nigeria, between January 2014 and May 2015.

Methodology: The HOQ concept was used for determining and selecting the best material available that is suitable and which can adequately be used to manufacture a designed component. It was employed for screening and ranking of materials in a quantitative manner, within the strategy developed prior to selection. The strategy was then  implemented through a software that was  developed using Visual Basic programming language nested with Python. The software was developed to run on microsoft windows operating platform and to be interractive and user-friendly. It processed specific informations supplied by the users in respect of a designed product into standard requirements useful in quantitatively determining the materials that are best fitted for the manufacture of the product.

Results: Recommendation of materials best suited for the manufacturing of the designed product was provided by the material selector software developed. The software was validated and evaluated using practical examples from past engineering design work. Also, a comparison of the time it takes to finish the process of material selection using manual approach to the one when HCAMS is used revealed that the software is two hundred and three times faster.

Conclusion:  Materials recommendations for design by the software in respect of the case studies are the same with the ones recommended from manually conducted material selection exercise using the developed strategy. [4]

Overview of Neurogenesis Growth and Glia Cell to Cloudle Architecture in Cloud Manufacturing

By realizing on future view of manufacturing, demand intelligent became a challenge for any manufacturers. Many manufacturing concepts emphasize rapid responses to demand change or fluctuation demand in the current market. Cloud manufacturing offers better service between a supplier to manufacturer and user to a manufacturer. In cloud manufacturing, all manufacturing process is linked together in cloud pool and this lead to time reduction in data processing. However, this concept will be successful if cloudle as agent-based searching engine able to implement brain emulation in the cloud manufacturing system. Brain emulation is emphasizing the neurogenesis phenomenon in the system by supporting with glia cells concept to expedite the searching process. [5]


[1] Mamalis, A.G., 2005. Advanced manufacturing engineering. Journal of Materials Processing Technology, 161(1-2), pp.1-9.

[2] Swearengen, J.C., Barnes, S., Coe, S., Reinhardt, C. and Subramanian, K., 2002. Globalization and the undergraduate manufacturing engineering curriculum. Journal of Engineering Education, 91(2), pp.255-261.

[3] Ong, S.K. and Mannan, M.A., 2004. Virtual reality simulations and animations in a web-based interactive manufacturing engineering module. Computers & Education, 43(4), pp.361-382.

[4] Isaac, O., Olumide, O. and Rasaki, O. (2015) “Application of House of Quality Matrix to Material Selection for Engineering Designs”, Current Journal of Applied Science and Technology, 10(4), pp. 1-11. doi: 10.9734/BJAST/2015/19105.

[5] Norazlin, N., Hashim, A. Y. and Fauadi, M. H. F. M. (2014) “Overview of Neurogenesis Growth and Glia Cell to Cloudle Architecture in Cloud Manufacturing”, Journal of Scientific Research and Reports, 3(24), pp. 3126-3135. doi: 10.9734/JSRR/2014/9828.

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