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The cooling-slope (CS) casting technique is one of the simple semi-solid processing (SSP) processes a foundryman uses to produce the feedstock. This study attempts to develop mathematical regression models and optimise the CS parameters process for predicting optimal feedstock performance, which utilises tensile strength and impact strength to reduce the number of experimental runs and material wastage. This study considers several parameters, including pouring temperature, pouring distance, and slanting angles for producing quality feedstock. Hence, multi-objective optimisation (MOO) techniques using computational approaches utilised alongside the caster while deciding to design are applied to help produce faster and more accurate output. The experiment was performed based on the full factorial design (FFD). Then, mathematical regression models were developed from the data obtained and implemented as an objective function equation in the MOO optimisation process. In this study, MOO named multi-objective Jaya (MOJaya) was improved in terms of hybrid MOJaya and inertia weight with archive K-Nearest Neighbor (MOiJaya-aKNN) algorithm. The proposed algorithm was improved in terms of the search process and archive selection to achieve a better feedstock performance through the CS. The study's findings showed that the values of tensile and impact strengths from MOiJaya_aKNN are close to the experiment values. The results show that the hybrid MOJaya has improved the prediction of feedstock using optimal CS parameters. [ABSTRACT FROM AUTHOR]

TRIZ is a methodology and a collection of problem solving tools and strategies that has been used in many other fields. Therefore, this paper proposes TRIZ method for improving the productivity in a textile industry. It focuses at the packing department in a textile company situated in Malaysia. The process was monitored and the problem was observed. TRIZ method is applied in this problem using Functional Analysis and trimming method. A comparison between before and after implementation is done in order to evaluate the productivity effectiveness.

The objective of this study was to compare the performance of Engineering Technology (ET) students’ in a Pre and Post Mathematics Competency Test during their first year of study at the Faculty of Engineering Technology (FTK), Universiti Teknikal Malaysia Melaka (UTeM). This article also aims to examine the student’s understanding in the area of Mathematics, particularly in Algebra, Trigonometry and Functions. A total of 176 first year students from the Department of Mechanical Engineering Technology (JTKM) were chosen to answer the Mathematics Competency Test. The pre-test was held in the first week of the semester, while the post-test was held during the second semester. The results showed that the students’ performance in post-test was better compared to that pre-test. However, statistical analysis on students’ performance by each question showed that most of the students did not understand the basic concepts in Algebra, Trigonometry and Functions.

In this paper, it is being proposed on the development of the product that consists of thermoelectric generator (TEG) with integrating IoT system. The product is mainly concerned to harvest the heat energy using biomass sources to generate electricity, DC and AC electricity for community need. Besides that, analytical graphs have been produced based on the data collected and these data can be viewed into a different dimension such as gadget based or web view based as the data will be called-off from each time the burning process happens. [ABSTRACT FROM AUTHOR]