Optimisation of laser welding of deep drawing steel for automotive applications by Machine Learning: A comparison of different techniques

Laser welding is particularly relevant in the industry thanks to its simplicity, flexibility and final quality. The industry 4.0 and sustainable manufacturing framework gives massive attention to in situ and non-destructive inspection methods to predict laser weld final quality. Literature often resorts to supervised Machine Learning approaches. However, selecting the ApTest method is non-trivial and often decision making relies on diverse and unclearly defined criteria. This work addresses this task by proposing a statistical comparison method based on nonparametric tests. The method is applied to the most relevant supervised Machine Learning approaches exploited in literature to predict laser weld quality, specifically, considering the optimisation of a new production line, hence focussing on supervised Machine Learning methods that do not require massive data set, that is, Generalized Linear Model (GLM), Gaussian Process Regression, Support Vector Machine, Classification and Regression Tree, and Genetic Algorithms. The statistical comparison is carried out to select the best-performing model, which is then exploited to optimise the production process. Additionally, an automatic process to optimise Machine Learning models and process parameters is resorted to, basing on Bayesian approaches, to reduce operator effect. This work provides quality and process engineers with a simple framework to compare Machine Learning approaches performances and select the most suitable process modelling technique

PERBEDAAN HASIL BELAJAR DASAR-DASAR KELISTRIKAN SISWA KELAS X MENGGUNAKAN METODE PEMBELAJARAN SNOWBALL THROWING DAN METODE PEMBELAJARAN BERPUSAT PADA GURU (Suatu Studi Eksperimen di SMK Negeri 2 Bogor)

Penelitian ini bertujuan untuk mengetahui perbedaan antara hasil belajar siswa menggunakan metode pembelajaran snowball throwing dan hasil belajar siswa dengan menggunakan metode pembelajaran berpusat pada guru pada mata pelajaran dasar-dasar kelistrikan kelas X di SMK Negeri 2 Bogor tahun pelajaran 2015/2016 serta untuk mengetahui hasil belajar mana yang lebih tinggi antara hasil belajar menggunakan metode pembelajaran snowball throwing dengan hasil belajar menggunakan metode pembelajaran berpusat pada guru. Hipotesisnya yaitu diduga terdapat perbedaan antara hasil belajar menggunakan metode pembelajaran snowball throwing dengan hasil belajar menggunakan metode pembelajaran berpusat pada guru dalam mata pelajaran dasar-dasar kelistrikan dimana hasil belajar menggunakan metode pembelajaran snowball throwing lebih tinggi dibandingkan dengan hasil belajar menggunakan metode pembelajaran berpusat pada guru. Dalam penelitian ini metode yang dipakai peneliti yaitu metode penelitian eksperimen yang melibatkan dua variabel yaitu variabel bebas adalah metode pembelajaran yang dibedakan atas metode pembelajaran snowball throwing dan metode pembelajaran berpusat pada guru (non-snowball throwing), dan variabel terikat adalah hasil belajar dasar-dasar kelistrikan. Teknik pengumpulan datanya menggunakan tes tertulis dan metode dokumentasi, sedangkan teknik analisis datanya menggunakan rumus uji-t. Berdasarkan analisis data menggunakan rumus uji-t diperoleh nilai 7,63 > 1,671, hal ini berarti terdapat perbedaan antara hasil belajar siswa menggunakan metode pembelajaran snowball throwing dengan hasil belajar siswa menggunakan metode pembelajaran berpusat pada guru (non-snowball throwing). Berdasarkan hasil perhitungan diperoleh nilai akhir yaitu siswa yang menggunakan metode pembelajaran snowball throwing mendapat nilai rata-rata 71,87, sedangkan siswa yang menggunakan metode pembelajaran berpusat pada guru (non-snowball throwing) mendapat nilai rata-rata 55,9, hal ini berarti hasil belajar siswa dengan menggunakan metode pembelajaran snowball throwing lebih tinggi dibandingkan dengan hasil belajar siswa menggunakan metode pembelajaran berpusat pada guru. Dari hasil penelitian ini dapat disimpulkan bahwa terdapat perbedaan antara hasil belajar siswa yang menggunakan metode pembelajaran snowball throwing dengan hasil belajar siswa yang menggunakan metode pembelajaran berpusat pada guru dalam mata pelajaran dasar-dasar kelistrikan, dimana hasil belajar siswa menggunakan metode pembelajaran snowball throwing lebih tinggi dibandingkan dengan hasil belajar siswa menggunakan metode pembelajaran berpusat pada guru

Non-Contact Articulated Robot-Integrated Gap and Flushness Measurement System for Automobile Assembly

The paper proposes and metrologically characterizes a gap and flushness optical measurement system based on machine vision. The system is developed for an operator-free application as a plug-and-play feature for articulated robotic arms. The system is designed for use in Stop-and-Go quality control point of vehicle assembly process. Non-contact measurement system that consists of an ultraviolet line laser with a sensitive camera and complemented with an advanced machine vision measurement algorithm is developed. The system is directly calibrated according to state-of-the-art literature and the measurement uncertainty within the laboratory conditions is derived according to Guide to the Expression of Uncertainty in Measurement. Measurements on the real vehicle body is done to elicit the difference. The expanded uncertainty achieved by the system is 0.221 mm and 0.177 mm for gap and flushness respectively, significantly smaller than the sole resolution of the most adopted manual feeler gauge verification method

Hydrogels for 3D neural tissue models: understanding cell-material interactions at a molecular level.

The development of 3D neural tissue analogs is of great interest to a range of biomedical engineering applications including tissue engineering of neural interfaces, treatment of neurodegenerative diseases and in vitro assessment of cell-material interactions. Despite continued efforts to develop synthetic or biosynthetic hydrogels which promote the development of complex neural networks in 3D, successful long-term 3D approaches have been restricted to the use of biologically derived constructs. In this study a poly (vinyl alcohol) biosynthetic hydrogel functionalized with gelatin and sericin (PVA-SG), was used to understand the interplay between cell-cell communication and cell-material interaction. This was used to probe critical short-term interactions that determine the success or failure of neural network growth and ultimately the development of a useful model. Complex primary ventral mesencephalic (VM) neural cells were encapsulated in PVA-SG hydrogels and critical molecular cues that demonstrate mechanosensory interaction were examined. Neuronal presence was constant over the 10 day culture, but the astrocyte population decreased in number. The lack of astrocytic support led to a reduction in neural process outgrowth from 24.0 ± 1.3 μm on Day 7 to 7.0 ± 0.1 μm on Day 10. Subsequently, purified astrocytes were studied in isolation to understand the reasons behind PVA-SG hydrogel inability to support neural network development. It was proposed that the spatially restrictive nature (or tight mesh size) of PVA-SG hydrogels limited the astrocytic actin polymerization together with a cytoplasmic-nuclear translocation of YAP over time, causing an alteration in their cell cycle. This was confirmed by the evaluation of p27/Kip1 gene that was found to be upregulated by a twofold increase in expression at both Days 7 and 10 compared to Day 3, indicating the quiescent stage of the astrocytes in PVA-SG hydrogel. Cell migration was further studied by the quantification of MMP-2 production that was negligible compared to 2D controls, ranging from 2.7 ± 2.3% on Day 3 to 5.3 ± 2.9% on Day 10. This study demonstrates the importance of understanding astrocyte-material interactions at the molecular level, with the need to address spatial constraints in the 3D hydrogel environment. These findings will inform the design of future hydrogel constructs with greater capacity for remodeling by the cell population to create space for cell migration and neural process extension

Pengaruh Celebrity Endorsement terhadap Purchase Intention: Telaah pada Instagram @SamsungIndonesia

Penggunaan intertnet mempunyai manfaat tersendiri bagi masyarakat karena dengan menggunakan internet masyarakat mampu mendapatkan ilmu pengetahuan yang tiada batas serta dapat untuk berkoneksi dengan orang-orang diluar sana. Per Januari 2023 sebanyak 77% dari populasi di Indonesia sudah terkoneksi dengan internet dimana hal tersebut didukung dengan adanya peran pemerintah di Indonesia dan didinkung dengan persebaran smartphone di Indonesia. Oppo, Sasmung, Vivo, Xiaomi, dan Realme menjadi top lima penguasa pangsa pasar smartphone di Indonesia saat ini. Samsung yang menjadi raja pangsa pasar smartphone di dunia tampaknya tidak mampu melakukan hal yang sama di Indonesia dimana Samsung harus dikalahkan dengan merek smartphone China dalam beberapa tahun terakhir. Salah satu strategi yang dimanfaatkan oleh Samsung untuk menarik minat beli konsumen di Indonesia adalah menggunakan strategi celebrity endorsement dengan bekerjasama dengan celebrity-celebrity ternama di Indonesia dengan harap mampu untuk mengalahahkan dominasi merek smartphone asal China Indonesia. Penelitian ini menggunakan variabel celebrity endorsement dengan tiga dimensi, brand loyalty, consumer perception of quality,dan purchase intention. Penelitian ini menggunaakan metode non probability sampling dengan data dari 137 responden yang kemudian diolah dengan menggunakan software Smart PLS 4. Temuan dari penelitian ini adalah celebrity endorsement tidak mempunyai pengaruh signifikan terhadap purchase intention, celebrity endorsement mempunyai penganh signifikan positif terbadap brand loyaity, celebrity endorsement mempunyai pengaruh signifikan positif terhadap consumer perception of quality, consumer perception of quality mempunyai pengarih signifikan positif terhadap brand loyalty, consumer perception of quality mempunyai penganubh signifikan positif terhadap purchase intention dan brand loyalty mempunyai pengaruh siginifikan positif teradap purchase intention

Accurate coil springs axial and transverse stiffness measurements with multicomponent testing machines

Accurate characterization of coil springs, typically in terms of axial and transverse stiffness, is crucial in many applications, in particular in automotive engineering, such as suspensions, vibration reduction, seating, exhaust valves, gear engagement controls, transmission hose, fuel panels, car trunks, and engine hoods. These measurements are usually performed in spring testing machines along the vertical axis in quasi-static conditions. However, when springs are stressed along the main vertical axis, side forces, bending and torsion moments are generated, thus have to be evaluated. For this reason, a hexapod-shaped multicomponent force and moment transducer has been recently devised, realized and integrated into standard spring testing machines capable to measure the displacement along the main and transverse axes. In this way, forces, moments and displacement components generated by the springs can be measured and axial and transverse stiffness derived. In this work, two multicomponent spring testing machines with the hexapod-shaped force and moment transducer are described and measurements on different large coil springs are presented

PEMBERDAYAAN MASYARAKAT MENGGALI POTENSI SUMBER DAYA LOKAL UNTUK MENINGKATKAN PEREKONOMIAN KELUARGA DI DESA PASAR IV NAMO TERASI KECAMATAN SEI BINGAI LANGKAT

Kabupaten Langkat terdiri dari 277 desa dan 23 kecamatan dengan jumlah penduduk 1.084.108 jiwa, dengan luas ± 6.140,04 km². Salah satu sasaran pengabdian adalah di Desa Namo Terasi, Kecamatan Sei Bingai yang merupakan bagian dari wilayah Kabupaten Langkat. Tujuan pengabdian adalah menggali kearifan lokal dan mengembangkannya menjadi tradisi kehidupan adat dalam melestarikan alam dan lingkungan dengan tujuan: a. Menjamin pemanfaatan Sumber Daya Alam dan Lingkungan Hidup dikelola dan; B. terpelihara dengan baik yang mendukung pembangunan berkelanjutan; C. Melestarikan dan melindungi Sumber Daya Alam dan Lingkungan Hidup dari kerusakan dan pencemaran serta eksploitasi Sumber Daya Alam yang tidak terkendali. Metode yang digunakan adalah Pembelajaran Aktif dan Partisipatif, dengan penekanan pada diskusi, praktik, dan demonstrasi. Pada kesempatan kali ini kearifan lokal yang digali adalah tentang menyadap Air Nira kelapa yang terletak di Dusun VIII Desa Namo Terasi. Luas perkebunan kelapa adalah 0,5 ha dengan produksi Air Nira 25 sampai 30 liter per hari. Hasil pengabdian ini adalah (1) Air Nira pohon kelapa umumnya banyak digunakan untuk membuat minuman segar dan juga dapat digunakan sebagai obat alami untuk menjaga kesehatan tubuh. (2) Selain sebagai bahan dasar pembuatan minuman segar, Air Nira juga digunakan sebagai bahan pembuatan gula merah. (3) Air Nira dari sumber daya lokal berpotensi meningkatkan pendapatan masyarakat dan juga bermanfaat bagi kesehatan

Microfluidic encapsulation method to produce stable liposomes containing iohexol

Since the discovery of X-rays in the late 1890s, several medical imaging techniques have been developed, such as Computed Tomography (CT), Magnetic Resonance Imaging (MRI) and Ultrasound Imaging, which are used daily to diagnose, monitor, or treat medical conditions. Some of these techniques include the use of contrast agents to enhance the contrast images, therefore, toxic effects must be considered. Among these, Contrast-Induced Nephropathy (CIN) is an acute renal failure resulting from the administration of iodinated contrast media (CM). To date, there is no definitive treatment for CIN and several prevention approaches have been evaluated. Nanoparticles (NPs) represent a promising strategy for treatment and prevention of CIN, due to their ability to deliver CM during diagnosis imaging. In this study, iohexol-containing liposomes were produced using microfluidic technique for first time. Several phosphocholine lipids (e.g. DMPC, DOPC, DPPC and DSPC) with cholesterol (2:1 ratio) were investigated and DLS, FTIR and in vitro release studies at 37 °C were performed, with stability studies conducted on the best formulation. The microfluidic method allowed to obtain a high encapsulation efficiency (over 70%), and release profiles showed an iohexol release around or less than 0.12 mg/ml after 2 h for the majority of the formulations, which is not toxic to the kidney cells

Analysis of residual plastic deformation of blanked sheets out of automotive aluminium alloys through hardness map

Reducing overall vehicle weight is essential to reduce fuel consumption and pollutant emission and to improve noise, vibration, and harshness (NVH) performances. The substitution with lighter alloys can involve the grand majority of vehicle components, depending on the market sector. In several applications, e.g., chassis, pulleys, and viscodampers, metal sheets are formed in several steps, each of whom work-hardens the material reducing the available residual plasticity. Typically, the process is designed via FEM, whose results are affected by the initial conditions, often neglected, and is performed on pre-processed materials from suppliers. In this regard, correctly simulating the first step of the process is critical. However, the related initial conditions, in terms of residual stress and strain induced by former preliminary operations, are often neglected. This work proposes a quick and economical experimental procedure based on a hardness map to estimate initial conditions and to validate FEM results. The procedure allows evaluating the material's residual plasticity, which is necessary to process engineers to design following manufacturing steps. The approach is demonstrated on an industrially relevant case study, i.e., the blanking of an AA 5754, in use for water pump pulleys

Minimization of defects generation in laser welding process of steel alloy for automotive application

Laser welding (LW) thanks to its flexibility, limited energy consumption and simple realization has a prominent role in several industrial sectors. LW process requires careful parameters' tuning to avoid generating internal defects in the microstructure or a poor weld depth, which reduce the joining mechanical strength and result in waste. This work exploits a supervised machine learning algorithm to optimize the process parameters to minimize the generated defects, while catering for design specifications and tolerances to predict defect generation probability. The work outputs a predictive quality control model to reduce non-destructive controls in the LW of aluminum for automotive applications