MANFAAT METODE INQUIRY TERHADAP PENGAMATAN HASIL PRAKTIKUM LAS LISTRIK DI LABORATORIUM MANUFAKTUR POLITEKNIK META INDUSTRI CIKARANG

ABSTRACTThe purpose of this study was to determine student achievement in the manufacturing process subject before giving treatment, to determine student achievement in the manufacturing process course after treatment, to determine whether there was an effect of the inquiry method on student achievement in the manufacturing process course and to find out whether there is a difference in learning achievement after treatment on the use of the inquiry method and the demonstration method. The type of research conducted by the researcher is Quasi Experiment. The research design used is Non Equivalent Control Group Design. The subjects of this study were third semester students (Industrial Engineering) at the Cikarang Industrial META Polytechnic. Data collection techniques were carried out through objective tests, observations of the welding process and assessment of welding results with performance. The results showed that the learning achievement of electric arc welding subjects before being given treatment in the control group and the experimental group had the same initial ability and the data results showed that there were still many students who had not finished. Learning achievement after being given treatment increased in both the control group and the experimental group. After learning with the inquiry method there is an influence on student learning achievement. Besides the effect, there are also differences in learning achievement after being given treatment, namely by comparing the results of the pretest and post-test, after the application of the demonstration method the test results have a significant percentage difference. Keywords: Inquiry Method, Learning Achievement, Electric Arc Welding ABSTRAKTujuan dari penelitian ini adalah untuk mengetahui prestasi belajar mahasiswa pada mata kuliah proses manufaktur sebelum pemberian perlakuan, mengetahui prestasi belajar mahasiswa pada mata kuliah proses manufaktur setelah pemberian perlakuan, mengetahui ada tidaknya pengaruh metode inquiry terhadap prestasi belajar mahasiswa pada mata mata kulaih proses manufaktur dan mengetahui ada tidaknya perbedaan prestasi belajar setelah perlakuan pada penggunaan metode inquiry dan metode demonstrasi. Jenis penelitian yang dilakukan oleh peneliti adalah Quasi Eksperimen. Desain penelitian yang digunakan adalah Non Equivalent Control Group Design. Subjek penelitian ini adalah mahasiswa semester III (Teknik Industri) di Politeknik META Industri Cikarang. Teknik pengumpulan data dilakukan melalui tes objektif, observasi terhadap proses pengelasan dan penilaian hasil las dengan unjuk kerja. Hasil penelitian menunjukkan bahwa prestasi belajar mata pelajaran las busur listrik sebelum diberikan perlakuan pada kelompok kontrol dan kelompok eksperimen memiliki kemampuan awal yang setara dan hasil data menunjukkan masih banyak mahasiswa yang belum tuntas. Prestasi belajar setelah diberikan perlakuan mengalami kenaikan baik pada kelompok kontrol maupun kelompok eksperimen. Setelah pembelajaran dengan metode inquiry terdapat pengaruh pada prestasi belajar mahasiswa. Selain pengaruh terdapat juga perbedaan prestasi belajar setelah diberikan perlakuan yaitu dengan membandingkan hasil pretest dan post-test, setelah penerapan metode demonstrasi hasil tes memiliki persentase perbedaan yang cukup berarti .Kata kunci: Metode Inquiry, Prestasi Belajar, Las Busur Listrik

Statistical process monitoring for e-waste based on beta regression and particle swarm optimization

PurposeE-waste management can reduce relevant impact of the business activity without affecting reliability, quality or performance. Statistical process monitoring is an effective way for managing reliability and quality to devices in manufacturing processes. This paper proposes an approach for monitoring the proportion of e-waste devices based on Beta regression model and particle swarm optimization. A statistical process monitoring scheme integrating residual useful life techniques for efficient monitoring of e-waste components or equipment was developed.Design/methodology/approachAn approach integrating regression method and particle swarm optimization algorithm was developed for increasing the accuracy of regression model estimates. The control chart tools were used for monitoring the proportion of e-waste devices from fault detection of electronic devices in manufacturing process.FindingsThe results showed that the proposed statistical process monitoring was an excellent reliability and quality scheme for monitoring the proportion of e-waste devices in toner manufacturing process. The optimized regression model estimates showed a significant influence of the process variables for both individually injection rate and toner treads and the interactions between injection rate, toner treads, viscosity and density.Originality/valueThis research is different from others by providing an approach for modeling and monitoring the proportion of e-waste devices. Statistical process monitoring can be used to monitor waste product in manufacturing. Besides, the key contribution in this study is to develop different models for fault detection and identify any change point in the manufacturing process. The optimized model used can be replicated to other Electronic Industry and allows support of a satisfactory e-waste management.

On Enhanced GLM-Based Monitoring: An Application to Additive Manufacturing Process

Innovations in technology assist the manufacturing processes in producing high-quality products and, hence, become a greater challenge for quality engineers. Control charts are frequently used to examine production operations and maintain product quality. The traditional charting structures rely on a response variable and do not incorporate any auxiliary data. To resolve this issue, one popular approach is to design charts based on a linear regression model, usually when the response variable shows a symmetric pattern (i.e., normality). The present work intends to propose new generalized linear model (GLM)-based homogeneously weighted moving average (HWMA) and double homogeneously weighted moving average (DHWMA) charting schemes to monitor count processes employing the deviance residuals (DRs) and standardized residuals (SRs) of the Poisson regression model. The symmetric limits of HWMA and DHWMA structures are derived, as SR and DR statistics showed a symmetric pattern. The performance of proposed and established methods (i.e., EWMA charts) is assessed by using run-length characteristics. The results revealed that SR-based schemes have relatively better performance as compared to DR-based schemes. In particular, the proposed SR-DHWMA chart outperforms the other two, namely SR-EWMA and SR-HWMA charts, in detecting shifts. To illustrate the practical features of the study’s proposal, a real application connected to the additive manufacturing process is offered.

Sustainable Manufacturing of Ultra-Fine Aluminium Alloy 6101 Wires Using Controlled High Levels of Mechanical Strain And Finite Element Modeling

The evolution of grain size and component mechanical behaviour are fundamental aspects to analyse and control when manufacturing processes are considered. In this context, severe plastic deformation (SPD) processes, in which a high shear strain is imposed on the material, are recognized as the main techniques to achieve microstructural changes and material strengthening by the recrystallization, attracting both academic and industrial investigation activities. At the same time, nowadays, sustainable manufacturing design is one of the main responsibilities of the researchers looking at UN2030 agenda and the modern industrial paradigms. In this paper a new severe SPD process is proposed with the aim to steer manufacturing to fourth industrial revolution using some of Industry 4.0 pillars. In particular, additive manufacturing (AM) and numerical simulations were setup as controlling and monitoring techniques in manufacturing process of wires.Strengthening effect (yield and ultimate tensile strength, plasticity and hardness) and microstructural evolution (continuous dynamic recrystallization -CDRX-) due to severe plastic deformation were experimentally analysed and numerically investigated by an innovative finite element (FE) model able to validate the effectiveness of a properly modified process for ultra-fine aluminium alloy AA6101 wires production designed with the aim to avoid any post manufacturing costly thermal treatment.The study provides an accurate experimental study and numerical prediction of the thermo-mechanical and microstructural phenomena that occur during an advanced large plastic deformation process; it shows how the combination of smart manufacturing and simulations control represents the key to renew the traditional manufacturing methods in the perspective of the Industry 4.0, connecting and integrating the manufacturing process for the industrial evolution in production.