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"Rotating Machinery, Optical Methods & Scanning LDV Methods, Volume 6: Proceedings of the 37th IMAC, A Conference and Exposition on Structural Dynamics, 2019, the sixth volume of eight from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Structural Health Monitoring, including papers on:- Novel Techniques- Optical Methods,- Scanning LDV Methods- Photogrammetry & DIC- Rotating Machinery"

"Rotating Machinery, Vibro-Acoustics & Laser Vibrometry, Volume 7: Proceedings of the 36th IMAC, A Conference and Exposition on Structural Dynamics, 2018, the seveth volume of nine from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Rotating Machinery, Hybrid Testing, Vibro-Acoustics & Laser Vibrometry, including papers on; Rotating Machinery, Vibro-Acoustics, Experimental Techniques, and Scanning Laser Doppler Vibrometry Methods."

"This book highlights recent findings in industrial, manufacturing and mechanical engineering, and provides an overview of the state of the art in these fields, mainly in Russia and Eastern Europe. A broad range of topics and issues in modern engineering are discussed, including the dynamics of machines and working processes, friction, wear and lubrication in machines, surface transport and technological machines, manufacturing engineering of industrial facilities, materials engineering, metallurgy, control systems and their industrial applications, industrial mechatronics, automation and robotics. The book gathers selected papers presented at the 4th International Conference on Industrial Engineering (ICIE), held in Moscow, Russia in May 2018. The authors are experts in various fields of engineering, and all papers have been carefully reviewed. Given its scope, the book will be of interest to a wide readership, including mechanical and production engineers, lecturers in engineering disciplines, and engineering graduates."

"Rotating machinery dalam industri minyak dan gas merupakan aset kritis yang beroperasi dalam medan kerja yang berat, sehingga beberapa bagian umum rentan mengalami fault. Fault merupakan anomali yang menunjukkan penyimpangan dari kondisi operasi normal pada suatu sistem, sehingga perlu dideteksi lebih dini, secara akurat, dan terotomasi. Salah satu metode yang dapat digunakan adalah dengan machine learning. Data yang digunakan dalam penelitian ini adalah sensor condition monitoring aset rotating machinery yang diperoleh dari sebuah perusahaan minyak dan gas di Indonesia. Data sensor yang diperoleh mencakup 3 operation parameters yakni kecepatan, suhu, dan vibrasi. Algoritme klasifikasi pada penelitian ini menggunakan supervised learning yakni Support Vector Machine (SVM), Random Forest (RF), dan K-Nearest Neighbors (KNN). Kinerja model machine learning dievaluasi menggunakan metrik accuracy, precision, F1 score, dan matthews correlation coefficient (MCC). Hasil model klasifikasi random forest menunjukkan hasil yang sangat baik dengan akurasi 98,5%, presisi 98,6%, f1-score 98,5%, dan MCC sebesar 97,2%. Analisis SHAP Explainer secara global mampu menjelaskan feature importance dan secara lokal yang memperlihatkan kontribusi variabel-variabel operating parameter yang berkontribusi paling besar pada kelas normal, alert, dan fault.

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Rotating machinery in the oil and gas industry is a critical asset that operates in a tough work environment, where some of the common parts are prone to faults. Fault is an anomaly that indicates a deviation from the normal operating conditions of a system, so it needs to be detected early, accurately, and automated. The data used in this study is obtained from a condition monitoring sensor of rotating machinery in an oil and gas company in Indonesia. The acquired sensor data includes 3 operating parameters: speed, temperature, and vibration. The classification algorithms used in this research are supervised learning methods, namely Support Vector Machine (SVM), Random Forest (RF), and K-Nearest Neighbors (KNN). The performance of the machine learning models is evaluated using metrics such as accuracy, precision, F1 score, and Matthews correlation coefficient (MCC). The results of the random forest classification model show very good results with an accuracy of 98.5%, a precision of 98.6%, an f1-score of 98.5%, and an MCC of 97.2%. SHAP Explainer in global explanation is able to explain the feature importance and also locally which shows the contribution of operating parameter variables that contribute the most to the normal, alert, and fault classes."

"Industri asuransi rangka kapal (H&M) memperoleh profitabilitas rendah yang berdampak pada keberlanjutan industri asuransi, salah satunya terjadi pada bisnis fakultatif di reasuransi PT. ABC. Penelitian ini bertujuan untuk (1) menganalisis proses bisnis asuransi H&M yang dijalankan saat ini, (2) mengidentifikasi permasalahan yang menyebabkan ketidakefektifan proses bisnis, (3) mengevaluasi parameter underwriting, dan (4) merancang bisnis proses baru di reasuransi PT. ABC. Penelitian ini menggunakan metode analisis kualitatif. Metode delphi dilakukan terhadap tujuh expertise di industri asuransi H&M yang dipilih melalui metode purposive sampling untuk mendukung pengumpulan data. Business process digambarkan menggunakan Business Process Model and Notation (BPMN). Analisis proses bisnis diselesaikan menggunakan root-cause analysis, value added analysis, waste analysis, dan direct weighting analysis digunakan untuk menentukan tingkat relevansi parameter underwriting. Transformasi business process dilakukan dengan (1) menambahkan parameter risiko yang penting diperhatikan dalam proses underwriting,(2) menghapus aktivitas waste dan non value added,(3) meningkatkan aktivitas analisis risiko yang memberikan business value added terhadap proses akseptasi bisnis (underwriting),(4) memperbaiki manajemen data dengan mengoptimalkan adminsitrasi sebagai agen bank data dan sistem, dan (5) pengaplikasian pricing rate untuk menjaga tarif dan kecukupan premi. Analisis statistik yang menunjang penilaian tingkat risiko dan pricing rate untuk menjaga kecukupan premi sangat diperlukan untuk penelitian selanjutnya.

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Hull and Machinery (H&M) insurance industry suffered low profitability which impacted the sustainability of insurance industry, one of which occurs in reinsurance company PT. ABC. This study aim to (1) analyze current business process of H&M insurance,(2) identify problem of business process uneffectiveness,(3) evaluate underwriting parameters, and (4) propose new business process in PT. ABC. This study use qualitative method. Delphi method is carried out to seven expertises in H&M insurance who are choosen by purposive sampling to support data collection. Business processes are described by Business Process Model and Notation (BPMN). Business process analysis is completed by using root-cause analysis, value added analysis, waste analysis, and direct weighting analysis specifically used to determine underwriting parameters relevancy degree. Business process transformation is carried out by (1) completing underwriting parameters,(2) eliminating waste and non-value added activities,(3) increasing risk analysis activities that provide business value added to the underwriting process,(4) improving data management by optimizing administration as a data bank agent and system, and (5) applying pricing rates to maintain tariff and premium adequacy. Statistical analysis that supports the assessment of the risk level and pricing rate that maintain premium adequacy are urgently needed for proceeding observation."

"Polis Asuransi Hull & Machinery merupakan salah satu bentuk polis yang kerap digunakan sebagai perlindungan untuk kapal-kapal yang ada di Indonesia hingga saat ini. Dalam Produk polis ini sendiri terdapat klausa baku yang mengatur mengenai pertanggungjawaban umum atau yang dikenal sebagai General Average yaitu prinsip kontribusi dari para pihak terhadap suatu kejadian yang terdapat beberapa kepentingan di dalamnya, terutama yang sering terjadi pada saat dilakukannya penyelamatan terhadap suatu kapal (Salvage). Dalam Skripsi ini akan membahas mengenai penerapan Asas General Average terhadap tindakan Penyelamatan Kapal antara PT Alatas Marine dan PT Tugu Asuransi Indonesia, yang kemudian menyebabkan tertundanya klaim atas Polis Asuransi Hull & Machinery. Metode Penelitian yang digunakan adalah penelitian hukum normatif yang menggunakan metode penelitian deskriptif analitis. Dalam penelitian ini ditemukan bahwa Pengaturan mengenai General Average pada prinsipnya telah diatur dalam KUHD namun mengenai limitasi dan tanggungjawab para pihak terkhususnya perihal penyelamatan kapal lebih khusus diatur dalam Marine Insurance Act 1906.Akan tetapi, pertimbangan hukum dari hakim pada Pengadilan Negeri tidak sesuai, dikarenakan dalam putusannya telah menghukum dan mewajibkan penanggung untuk membayarkan klaim yang tidak sesuai dengan nilai yang seharusnya dibayarkan secara kontribusi menurut Asas.

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Hull & Machinery Insurance Policy  is a form of policy that is often used as protection for ships in Indonesia until now. In this policy product itself there is a standard clause that regulates general liability or what is known as General Average, which is the principle of contribution from the parties to an event that has some interest in it, especially those that often occur during the rescue of a ship (Salvage). In this thesis will discuss the application of the General Average Principle to ship rescue actions between PT Alatas Marine and PT Tugu Asuransi Indonesia, which then causes delays in claims on the Hull & Machinery Insurance Policy. The research method used is normative legal research that uses analytical descriptive research methods. In this study, it was found that the Regulation on General Average has in principle been regulated in the KUHD but regarding the limitations and responsibilities of the parties, especially regarding the rescue of ships, it is more specifically regulated in the Marine Insurance Act 1906.However, the legal considerations of the judges in the District Court are not appropriate, because in their decisions they have punished and obliged the insurer to pay claims that are not in accordance with the value that should be  paid on a contribution basis according to the General Average Principle."

"This book provides readers with a timely snapshot of the potential offered by and challenges posed by signal processing methods in the field of machine diagnostics and condition monitoring. It gathers contributions to the first Workshop on Signal Processing Applied to Rotating Machinery Diagnostics, held in Setif, Algeria, on April 9-10, 2017, and organized by the Applied Precision Mechanics Laboratory (LMPA) at the Institute of Precision Mechanics, University of Setif, Algeria and the Laboratory of Mechanics, Modeling and Manufacturing (LA2MP) at the National School of Engineers of Sfax. The respective chapters highlight research conducted by the two laboratories on the following main topics: noise and vibration in machines; condition monitoring in non-stationary operations; vibro-acoustic diagnosis of machinery; signal processing and pattern recognition methods; monitoring and diagnostic systems; and dynamic modeling and fault detection."

"IFToMM conferences have a history of success due to the various advances achieved in the field of rotor dynamics over the past three decades. These meetings have since become a leading global event, bringing together specialists from industry and academia to promote the exchange of knowledge, ideas, and information on the latest developments in the dynamics of rotating machinery. The scope of the conference is broad, including e.g. active components and vibration control, balancing, bearings, condition monitoring, dynamic analysis and stability, wind turbines and generators, electromechanical interactions in rotor dynamics and turbochargers. The proceedings are divided into four volumes. This fourth volume covers the following main topics: aero-engines; turbochargers; eolian (wind) generators; automotive rotating systems; and hydro power plants. "

"IFToMM conferences have a history of success due to the various advances achieved in the field of rotor dynamics over the past three decades. These meetings have since become a leading global event, bringing together specialists from industry and academia to promote the exchange of knowledge, ideas, and information on the latest developments in the dynamics of rotating machinery. The scope of the conference is broad, including e.g. active components and vibration control, balancing, bearings, condition monitoring, dynamic analysis and stability, wind turbines and generators, electromechanical interactions in rotor dynamics and turbochargers. The proceedings are divided into four volumes. This third volume covers the following main topics: dynamic analysis and stability; electromechanical interactions in rotordynamics; nonlinear phenomena in rotordynamics; rotordynamics of micro, nano and cryogenic machines; and fluid structure interactions in rotordynamics. "