https://repositori.mypolycc.edu.my/jspui/handle/123456789/4 Mon, 27 Apr 2026 01:13:21 GMT 2026-04-27T01:13:21Z https://repositori.mypolycc.edu.my/jspui/handle/123456789/9794 Title: DJM20042 ELECTRONIC SYSTEM Authors: Lim Tian Pau; Nurul Adillah Ariffin; Muhammad Abdul Jalil Abstract: The electronic system e-book covers knowledge on basic concepts of semiconductor materials, electronic devices and DC power supply. The course emphasizes on the electrical characteristics and properties of semiconductor materials, linear DC power supplies system, amplifier circuits and sinusoidal wave oscillator circuits. The contents in this e-book are relevant to the syllabus for Diploma in Mechatronics Engineering student. There are the note, diagrams, example of problem solution and tutorial of the topic to ease for student to refer to. This ebook is very helpful for polytechnic students as a reference in their studies. Mon, 01 Aug 2022 00:00:00 GMT https://repositori.mypolycc.edu.my/jspui/handle/123456789/9794 2022-08-01T00:00:00Z https://repositori.mypolycc.edu.my/jspui/handle/123456789/9788 Title: MACHINE LEARNING FOR FLUID THERMODYNAMICS: STATE OF THE ART AND OPEN CHALLENGES Authors: Succetti, Federico; Panella, Massimo; Giannitrapani, Paolo; Rigo, Jean-Christophe; Colonnese, Stefania Abstract: This paper presents a critical survey on adopting machine learning in solving complex real fluid thermodynamics problems. After reviewing the primary computational machine learning frameworks employed in thermodynamic modelling, we have analysed current research with a particular emphasis on properly estimating gas and liquid properties, vapour-liquid equilibrium, and supercritical fluids, focusing on pure gases. While ML offers a powerful paradigm for augmenting or even replacing traditional methods, its application faces significant open challenges. Key issues include the persistent trade-off between model accuracy and computational efficiency, the difficulty in capturing highly non-linear behaviour, especially near critical points or under extreme conditions, and the pervasive problem of data scarcity. We conclude the paper by introducing the main datasets available for thermodynamic property computation, such as the results of the GERG2008 project, and others relevant to turbomachinery applications. This survey provides a unified perspective on machine learning architectures used in thermodynamics and identifies open challenges and potential future advancements for enhancing predictive accuracy and efficiency while reducing execution time. Mon, 01 Jan 2024 00:00:00 GMT https://repositori.mypolycc.edu.my/jspui/handle/123456789/9788 2024-01-01T00:00:00Z https://repositori.mypolycc.edu.my/jspui/handle/123456789/9787 Title: JUST-IN-TIME (JIT) IMPLEMENTATION IN FOUNDRY DIVISION USING MIX MODEL MANUFACTURING AND INVENTORY HANDLING SYSTEM Authors: Pratheesh Kumar S.; Naveen Anthuvan R.; Dharshini P. U.; Jayasadha S.; Shanmugam S. Abstract: In this study, a foundry division which is producing a variety of products like pump parts, gears, cams, lathe beds, and engine housing is taken. But the foundry cannot able to meet the customer’s demand for a variety of the same product. The main problem is the layout of the foundry is randomly arranged and the inventory holding of the finished goods is also not optimized. To overcome these problems lean tools like mix model manufacturing, value stream mapping, and inventory handling system are used. Just-in-Time (JIT) is also implemented to reduce the manufacturing time of the products. The result that is obtained by implementing the lean tools is the inventory holding cost is reduced drastically, the layout change reduces the work-in- progress inventory. These methods are most suitable for a foundry division that is unable to produce a variety of the same products in the same manufacturing line. Wed, 01 Jan 2025 00:00:00 GMT https://repositori.mypolycc.edu.my/jspui/handle/123456789/9787 2025-01-01T00:00:00Z https://repositori.mypolycc.edu.my/jspui/handle/123456789/9786 Title: KINEMATIC COMPENSATION ALGORITHM FOR REDUCING ERRORS IN A CLOSED-LOOP MANUFACTURING SYSTEM Authors: Jaimes, Cristhian I. R.; Álvares, Alberto J.; Peña, Cesar A. Abstract: During the manufacturing process of a piece, different factors influence the process so that errors of a systematic and random nature are added, affecting both the dimensions and the final geometry. The strategy presented in this research seeks to identify, monitor, and computationally control the errors arising from the arrangement of the actuators that can be derived from errors in assembly, wear of the components, and thermal deformations. This article proposes an algorithm to prevent and correct geometric and dimensional errors in manufacturing parts as a compensation strategy. The algorithm obtains the references of the manufacturing process and estimates the process’s deviation, calculating the manufactured part’s error concerning the projected piece. Error compensation is performed through reference points that alter the location of the target points in the opposite direction to the resulting error to nullify it kinematically. The validation of the strategy is carried out through the computational implementation of kinematic algorithms of a machine tool with a Cartesian structure of two degrees of freedom on which position and orientation errors are induced. The presented results allow for verifying the proposed algorithm’s effectiveness against tests with significant errors. The compensation strategy presented allows projecting this algorithm as an online software calibration method, reducing the number of stops due to mechanical maintenance of the CNC machine and making closed-loop manufacturing possible with real time compensation. Fri, 05 Jul 2024 00:00:00 GMT https://repositori.mypolycc.edu.my/jspui/handle/123456789/9786 2024-07-05T00:00:00Z