bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluasi Penerapan Sistem Informasi Akademik Universitas Singaperbangsa Karawang Menggunakan Importance Performance Analysis
Authors: Jajuli Mohamad , Sulistiyowati Nina
Published: March 2024

Universitas Singaperbangsa Karawang telah memanfaatkan perkembangan teknologi informasi dengan menggunakan Sistem Informasi Akademik (SIAKAD). Namun untuk sekarang ini, penggunaan SIAKAD masih ada kekurangan. Dari kekurangan itu, diperlukan evaluasi agar dapat mengukur kinerja dan kepuasan dari pengguna akan fitur yang ada di SIAKAD. Ada beberapa metode yang dapat digunakan untuk mengevaluasi penerapan SIAKAD salah satunya adalah Importance Performance Analysis. Metode penelitian menggunakan deskriptif kuantitatif dengan populasinya adalah mahasiswa aktif fakultas Ilmu Komputer di Unsika angkatan 2015-2017 sebanyak 539 mahasiswa. Sampel yang diambil sebanyak 230 mahasiswa dengan teknik sampling yang digunakan adalah proportionate stratified random sampling. Pengumpulan data menggunakan kuesioner skala 1 sampai dengan 4. Kuesioner dalam penelitian ini terdiri dari 5 variabel yaitu performance, information and data, control and security, efficiency, dan service. Uji validitas dan reliabilitas kuisioner menggunakan Korelasi Product Moment dan Alpha Cronbach. Hasil uji validitas dan reliabilitas menunjukkan semua variabel valid dan reliabel. Berdasarkan hasil penelitian bahwa variabel yang harus menjadi prioritas utama adalah variabel performance karena dari pemetaan diagram Importance Performance Analysis berada pada kuadran I. Variabel yang menjadi prioritas kedua adalah control and security karena dari hasil analisis kesenjangan harapan dan kenyataan, variabel control and security mendapatkan nilai negatif terbesar.
Perancangan Aplikasi M-Discussion Berbasis Android Sebagai Wadah Diskusi Sekolah
Authors: Voutama Apriade
Published: March 2024

Pesatnya perkembangan Teknologi Informasi dan Komunikasi (Information and Communication Technology ICT) telah merambah berbagai bidang salah satunya adalah teknologi smartphone. Smartphone adalah media komunikasi yang sudah umum digunakan sekarang oleh pengguna sehingga banyaknya bermunculan berbagai macam aplikasi berbasis android dengan tujuan untuk mempermudah kebutuhan pengguna pada era digital ini. Melihat hal tersebut maka muncul sebuah ide menarik untuk di kembangkan di bidang pendidikan yaitu Aplikasi Forum Diskusi berbasis Android. Implementasi Aplikasi Forum Diskusi berbasis Android ini dirancang sebagai suatu media komunikasi antar siswa, guru, dan staf-staf yang terlibat di dalamnya sehingga dapat memebrikan kemudahan dengan memnafaatkan smartphone sebagai media seluler saat ini. sehingga dapat mempermudah pengguna yang terlibat dalam aplikasi M-Discussion ini memperoleh informasi, bertukar pikiran, berintekasi dengan mudah tanpa terhalang ruang dan waktu.
Vegetative propagation of Xylopia parviflora, a wild medicinal spice tree species in the tropics: insights for domestication
Authors: Gabriel Kanmegne , Delphine Ache Mbibong
Published: March 2024

Objective: Xylopia parviflora (A. Rich.) Benth. (commonly known as “striped African pepper”) is one of the most socio-economically high-valued tree species of the Central and Western African humid forests. Its propagation is hindered by poor seed germination. The present study aimed at examining its potential for vegetative propagation through the rooting of stem cuttings. Methodology and Results: In a split-plot experimental design, three leaf areas (0, 15 and 30 cm2) and six concentrations [(0, 0.25, 0.5, 1, 2 and 4% (w/w)] of indole-3-butyric acid (IBA) were tested for their effects on stem cutting parameters after five months in a non-mist propagator. Maximum rooting percentage (100%) was recorded with 15 cm2 x 4% IBA, 30 cm2 x 2% IBA and 30 cm2 x 4% IBA treatment combinations. The highest mean root count (9.1) was recorded with 30 cm2 x 4% IBA. The mortality rate of cutting was significantly affected by leaf area only. Leafless cuttings (0 cm2) resulted in 73.5% mortality, which was higher than 11.8% and 10.7% recorded with cuttings having 15 and 30 cm2 leaf areas respectively. Conclusion and application of findings: X. parviflora is amenable to vegetative propagation through rooting of leafy stem cutting within five months. For an efficient propagation of X. parviflora through stem cuttings, the use of cuttings with 30 cm2 leaf area and application of 4% (w/w) IBA are recommended. This is valuable insight into the domestication and in situ conservation of this species that is of direct relevance to the well-being of millions of people in sub-Saharan Africa. Propagation of X. parviflora using robust and low-cost procedure as described in this study would stand as an alternative to the sexual propagation which is hindered by poor seed germination. Keywords: auxin, leaf area, rooting, stem cuttings, striped African pepper.
ANALISIS BIOMASSA MANGROVE DAN INDEKS NILAI PENTING DI DESA RATATOTOK TIMUR KABUPATEN MINAHASA TENGGARA PROVINSI SULAWESI UTARA
Authors: Da Costa Cosme B. De C. , Rumengan Antonius P. , Angmalisang Ping A. , Manembu Indri S. , Lumuindong Frans , Losung Fitje
Published: March 2024

Mangrove forest is an ecosystem that lives in coastal areas and has muddy substrates and river mouths influenced by seawater and it is able to live in areas with high salinity ranges. Mangroves absorb CO2 during photosynthesis, then convert it into carbohydrates by storing it in biomass in, roots, and leaves. This study aimed to identify mangrove species, examine the structure of the mangrove community, analyze the importance value index, and determine the value of mangrove biomass in East Ratatotok Village, Southeast Minahasa Regency, North Sulawesi Province. The method used in this study is the quadrant line transect method which examines the importance value index and the amount of biomass in mangroves using a mangrove biomass determination algorithm. Based on the results of this study, four types of mangroves were found, namely Rhizophora mucronata, Rhizophora apiculate, Ceriops tagal, and Sonneratia alba. The type of R. mucronata dominates the mangrove species in East Ratatotok, Southeast Minahasa Regency. The analysis results of East Ratatotok mangrove biomass values are quite high, ranging from 113.15 to 239.03 tons/ha.Keywords: Mangrove, IVI, Biomass, East RatatotokABSTRAKHutan mangrove merupakan suatu ekosistem yang hidup di daerah pesisir pantai dan memiliki substrat berlumpur, muara sungai yang dipengaruhi oleh air laut serta dapat hidup di daerah dengan rentang salinitas yang tinggi. Mangrove menyerap CO2 pada saat proses fotosintesis, kemudian mengubahnya menjadi karbohidrat dengan menyimpannya dalam bentuk biomassa pada akar, batang, ranting, dan daun Tujuan dari penelitian ini, yaitu untuk mengidentifikasi jenis mangrove, mengkaji struktur komunitas mangrove dan menganalisis indeks nilai penting serta mengetahui nilai biomassa mangrove di Desa Ratatotok Timur, Kabupaten Minahasa Tenggara, Provinsi Sulawesi Utara. Metode yang digunakan dalam penelitian ini yaitu metode garis transek kuadrat yang meneliti indeks nilai penting dan jumlah biomassa pada mangrove menggunakan algoritma penentuan biomassa mangrove. Berdasarkan hasil penelitian ini, ditemukan 4 jenis mangrove yaitu Rhizophora mucronata, Rhizophora apiculata, Ceriops tagal, dan Sonneratia alba. Jenis R. mucronata mendominasi jenis-jenis mangrove yang di Ratatotok Timur Kabupaten Minahasa Tenggara. Hasil analisis nilai biomassa mangrove Ratatotok Timur cukup tinggi berkisar antara 113.15 hingga 239.03 ton/ha.Kata kunci: Mangrove, INP, Biomassa, Ratatotok Timur
STUDI MORFOMETRIK Thalassia hemprichii DAN Enhalus acoroides PERAIRAN SEKITAR DI DESA WORI KECAMATAN WORI KABUPATEN MINAHASA UTARA
Authors: Harum Christofel B. S. , Sondak Calvyn F.A. , Kaligis Erly Y. , Tilaar Sandra O. , Gerung Grevo S. , Rembet Unstain N.W.J.
Published: March 2024

Seagrass has roots, rhizomes, stems, and leaves like land plants (grasses) in general. Seagrass ecosystems are complex ecosystems and have important functions and benefits for coastal waters. Study aimed to describe the morphological characteristics of seagrass Thalassia hemprichiiand Enhalus acoroides and to compare the size of seagrass Thalassia hemprichii and Enhalus acoroides that lived in muddy-sand and sand-rubble substrates. Sampling was carried out using the cruising survey method and morphometric measurements using a digital caliper. The average length of the leaves in the muddy sand substrate was 9.1 cm and 9.3 cm in the crushed coral sand substrate.Independent T-test for Thalassia hemprichii and Enhalus acoroides showed no significant difference in their morphometrics, except for the length of the rhizome which showed a significant difference.Keywords: Seagrass, morphometric, Village WoriABSTRAKLamun memiliki akar, rhizoma, batang, dan daun seperti tumbuhan (rerumputan) darat pada umumnya. Ekosistem padang lamun adalah ekosistem yang kompleks dan mempunyai fungsi serta manfaat penting untuk wilayah perairan pesisir. Rumusan masalah penelitian ini yaitu bagaimana deskripsi karakteristik morfologi lamun Thalassia hemprichii dan Enhalus acoroides dan bagaimana membandingkan rata – rata ukuran lamun Thalassia hemprichii dan Enhalus acoroides. Tujuan penelitian ini yaitu mendeskripsikan karakteristik morfologi lamun Thalassia hemprichii dan Enhalus acoroides dan mengetahui membandingkan rata -rata ukuran lamun Thalassia hemprichii dan Enhalus acoroides. Pengambilan sampel dilakukan menggunakan metode survey jelajah dan pengukuran morfometrik menggunakan caliper. Hasil rata – rata ukuran panjang daun di substrat pasir berlumpur 9,1 cm dan di substrat pasir pecahan karang 9,3 cm. Uji T independen Thalassia hemprichii tidak menunjukkan ada perbedaan nyata dan Enhalus acoroides tidak menunjukkan ada perbedaan nyata, kecuali terhadap panjang rhizoma yang menunjukkan perbedaan nyata.Kata Kunci: Lamun, Morfometrik, Desa Wori
Near-infrared phosphorescent OLEDs exhibiting over 10% external quantum efficiency and extremely long lifetime using resonant energy transfer with a phosphorescent assist dopant
Authors: Hanayama Takanori , Sano Takeshi , Saito Yu , Nakamura Takeru , Okuyama Yutaka , Sasabe Hisahiro , Kido Junji
Published: March 2024

We have introduced a three-component light-emitting layer consisting of a host, a phosphorescent assist dopant, and a phosphorescent emitter to simultaneously realize high efficiency and long lifetime in NIR organic LEDs. An efficient energy transfer between the two phosphorescent materials was observed with 1 wt% doping ratio of the NIR emitter, significantly enhancing the external quantum efficiency reaching 10.5% with an emission peak at 769 nm. The device showed a low drive voltage and a long operational lifetime, with a luminance decay of less than 11% from the initial value after 4800 h under accelerated conditions of 100 mA cm−2.
Perancangan Sistem Informasi Rekam Medis Berbasis Web Pada Unit Kesehatan Sekolah IDN Boarding School Jonggol
Authors: Mulyana Dadang Iskandar , Ramadhan Gilang , Ardana Tegar Rizky , Aimar Muqorrobin , Saputra Mochammed Erryandra
Published: March 2024

In this modern era, many Islamic boarding schools have built their own Health Units. However, often these units only function as an effort to prevent and overcome student health problems in general. The more students there are in an Islamic boarding school, the more important it is for the Health Unit in the Islamic boarding school to innovate to improve the quality of its services. The concept of designing this information system refers to the activity of processing student medical record data that occurs in the Health Unit which is still manual, so a website-based medical record information system is needed at the IDN Jonggol Islamic boarding school which is computerized to solve this problem. This research aims to produce a software application that is expected to help the Health Unit in processing student data collection which can make it easier to search and make reports. To support this research, data collection methods are carried out using observation, interviewing, literature study, analysis, and design system, building the system, testing, and implementing the system. The implementation of the medical record information system at the IDN Jonggol Islamic boarding school has succeeded in increasing the efficiency, accuracy, and accessibility of student health data, providing convenience in making reports, and supporting improvements in the quality of health services
Implementasi Sistem Antrian Pasien Berbasis Website Pada Klinik Sehat Tamba Kelurahan Cilangkap
Authors: Poerwandono Edhy , Anwar Anggit Saepul , Mutia Selvi , Damayanti Yulia
Published: March 2024

Clinics are health facilities that provide basic medical services, diagnosis, treatment, and care to patients with minor or non-emergency medical conditions. The development of information technology has triggered the need for information systems in the medical field to improve health services. One important factor in increasing patient satisfaction is minimizing waiting time. Long queues can reduce clinic efficiency and affect patient satisfaction. This study aims to implement a website-based patient queue system at the Tamba Sehat Clinic, with the hope of increasing service efficiency and patient satisfaction. In implementing the website queuing system, researchers used qualitative methods to understand the effectiveness of health services and patient experiences. Data was collected through interviews, observations, and literature studies. The implementation of the Website-Based Patient Queuing System at the Tamba Sehat Clinic has had a significant impact. People can now easily get a queue number online via mobile phone or computer, eliminating the need to queue directly at the clinic location. Tamba Sehat Clinic, which was established in January 2023, has seen increased efficiency with this system. Patients can quickly and efficiently get a queue number, ensuring that their time is spent productively. Additionally, adopting this technology helps clinics improve the quality of service to prospective patients, creating a more comfortable and efficient experience for those in need of healthcare services. Thus, the implementation of a website-based patient queue system has brought real benefits to the community and clinics.
Azione revocatoria “a cascata”, inefficacia dell’atto istitutivo del trust e attività del trustee (App. Milano, 19 settembre 2023)
Authors: Giunchedi Diletta
Published: March 2024

Massima
Disposta la revoca ex art. 2901 cod. civ. del conferimento in trust, è revocabile la vendita di quote incluse nel fondo in trust intercorsa tra il trustee e i due beneficiari, in quanto costoro, pur aventi causa a titolo oneroso, erano in mala fede, come desumibile dal fatto che erano beneficiari, che il disponente era loro padre, che la duplice operazione di dismissione delle quote avveniva nell’arco di soli tre anni e che il prezzo di acquisto delle quote era molto modesto (nemmeno 2.000 Euro a fronte di ricavi, nell’anno precedente la vendita, per oltre 6 milioni).
Trust liquidatorio, soglie di fallibilità e cessazione dell’attività d’impresa (Cass., 18 luglio 2023, n. 20907)
Authors: Morotti Marco
Published: March 2024

Massima
In tema di dichiarazione di fallimento di una società, ai fini del rispetto del termine previsto dall’art. 10 L. Fall. l’iscrizione nel registro delle imprese del decreto con cui il giudice del registro, ai sensi dell’art. 2191 cod. civ., ordina la cancellazione della pregressa cancellazione della società già iscritta, fa presumere sino a prova contraria la continuazione dell’attività d’impresa, atteso che il rilievo di regola solo dichiarativo della pubblicità comporta che l’iscrizione del detto decreto rende opponibile ai terzi l’insussistenza delle condizioni che avevano dato luogo alla cancellazione della società alla data in cui questa era stata iscritta e determina altresì, con effetto retroattivo, il venir meno dell’estinzione della società per non essersi questa effettivamente verificata.
Opposizione di terzo complicata (App. Cagliari, 6 luglio 2023)
Authors: Napolitano Elena
Published: March 2024

Massima
Il beneficiario di un trust familiare, convenuto in giudizio per la revocatoria del conferimento in trust ex art. 2901 cod. civ., non può, nel costituirsi, proporre opposizione di terzo ex art. 404 cod. proc. civ. lamentando che il suo pregiudizio deriverebbe dall’accertamento – con pronuncia passata in giudicato – del credito vantato dall’istituto di credito-attore verso il fideiussore-disponente, in quanto detto beneficiario non vanta alcun diritto incompatibile con questo credito. Quanto agli effetti che si riverberano sul conferimento in trust a seguito dell’accoglimento dell’azione revocatoria ex art. 2901 cod. civ., essi riguardano solo indirettamente la posizione dei beneficiari.
Profili processuali relativi al difetto di legittimazione del trust e del trustee a seguito di declaratoria di nullità del trust (App. Napoli, 2 agosto 2023)
Authors: Napolitano Elena
Published: March 2024

Massima
Il trustee di un trust liquidatorio del quale sia stata dichiarata la nullità con sentenza passata in giudicato non è legittimato ad agire in giudizio per far valere contestazioni in ordine a un rapporto di conto corrente intrattenuto dalla società il cui patrimonio era confluito nel trust medesimo.
Sequestro di capitali e azienda nel blind trust (Cass., 6 giugno 2023, n. 24523)
Authors: Consoli Martha
Published: March 2024

Massima
Soltanto il trustee è legittimato a ricorrere avverso il sequestro preventivo disposto sul capitale sociale e sul complesso aziendale e patrimoniale di una s.r.l. conferiti in un blind trust (il sequestro era stato disposto per reati contestati a soggetti che, anteriormente all’istituzione del trust, gestivano di fatto tale società per condizionare illecitamente l’assegnazione di appalti pubblici).
Solving the ADAPT Benchmark Problem - A Student Project Study
Authors: Almqvist Erik , Eriksson Daniel , Lundberg Andreas , Nilsson Emil , Wahlstro ̈m Niklas , Frisk Erik , Krysander Mattias
Published: March 2024

This paper describes a solution to the Advanced Diagnosis and Prognostics testbed (ADAPT) diagnosis benchmark problem. One main objective was to study and discuss how engineering students, with no diagnosis research background, would solve a challenging diagnosis problem. The study was performed within the framework of a final year project course for control engineering students. A main contribution of the work is the discussion on the development process used by the students.
The solution is based on physical models of components and includes common techniques from control theory, like observers and parameter estimators, together with established algorithms for consistency based fault isolation. The system is fully implemented in C++ and evaluated, using the DXC software platform, with good diagnosis performance.
A Diagnosis Algorithm for Inconsistent Constraint Sets
Authors: Felfernig Alexander , Schubert Monika
Published: March 2024

Constraint sets can become inconsistent in different contexts. For example, during a configuration session the set of customer requirements can become inconsistent with the configuration knowledge base. Another example is the engineering phase of a configuration knowledge base where the underlying constraints can become inconsistent with a set of test cases. In such situations we are in the need of techniques that support the identification of minimal sets of constraints that have to be adapted or deleted in order to restore consistency. In this paper we introduce a divide-and-conquer based diagnosis algorithm (FastDiag) which identifies minimal sets of faulty constraints in an over-constrained problem. This algorithm is specifically applicable in scenarios where the efficient identification of leading (preferred) diagnoses is crucial. We compare the performance of FastDiag with the conflict-directed calculation of hitting sets and present an in-depth performance analysis that shows the advantages of our approach.
BAYESIAN SOFTWARE HEALTH MANAGEMENT FOR AIRCRAFT GUIDANCE, NAVIGATION, AND CONTROL
Authors: Schumann Johann , Mbaya Timmy , Mengshoel Ole
Published: March 2024

Modern aircraft—both piloted fly-by-wire commercial aircraft as well as UAVs—more and more depend on highly complex safety critical software systems with many sensors and computer-controlled actuators. Despite careful design and V&V of the software, severe incidents have happened due to malfunctioning software. In this paper, we discuss the use of Bayesian networks to monitor the health of the on-board software and sensor system, and to perform advanced on-board diagnostic reasoning. We focus on the development of reliable and robust health models for combined software and sensor systems, with application to guidance, navigation, and control (GN&C). Our Bayesian network-based approach is illustrated for a simplified GN&C system implemented using the open source real-time operating system OSEK/Trampoline. We show, using scenarios with injected faults, that our approach is able to detect and diagnose faults in software and sensor systems.
Online Estimation of Lithium-Ion Battery State-of-Charge and Capacity with a Multiscale Filtering Technique
Authors: Hu Chao , D. Youn Byeng , Kim Taejin , Chung Jaesik
Published: March 2024

Real-time prediction of state-of-charge (SOC), state-of-health (SOH) and state-of-life (SOL) plays an essential role in many battery energy storage applications, such as electric vehicle (EV), hybrid electric vehicle (HEV) and smart power grid. However, among these three quantities, only the SOC has been thoroughly studies while there is still lack of rigorous research efforts onthe other two quantities, SOH and SOL. Specially, real- time estimation of the SOH-relevant cell capacity by tracking readily available measurements (e.g., voltage,current and temperature) is still an open problem. Commonly used joint/dual extended Kalman filter(EKF) suffers from the lack of accuracy in the capacity estimation since (i) the cell voltage is the only measurable data for the SOC and capacity estimation and updates and (ii) the capacity is very weakly linked to the cell voltage. Furthermore, although the capacity is a slowly time-varying quantity that indicates cell state-of-health (SOH), the capacity estimation is generally performed on the same time-scale as the quickly time-varying SOC, resulting in high computational complexity. To resolve these difficulties, this paper proposes a multiscale framework with EKF for SOC and capacity estimation. The proposed framework comprises two ideas: (i) a multiscale framework to estimate SOC and capacity that exhibit time-scale separation and (ii) a state projection scheme for accurate and stable capacity estimation. Simulation and experimental results verify the effectiveness of our framework.
Performance Based Anomaly Detection Analysis of a Gas Turbine Engine by Artificial Neural Network Approach
Authors: Kumar Amar , Srivastava Alka , Banerjee Avisekh , Goel Alok
Published: March 2024

This present work follows our earlier research efforts on fault diagnosis and prognosis solutions considering statistical and physics based approaches. In-service performance analysis and detection of any malfunctioning in an operating small sized gas turbine engine using artificial neural network approach is the central theme of this work. The measured engine operating and performance parameters are used to train two neural network models, namely back propagation and generalized regression. Following the training and validation of the neural network model, simulation results for test data corresponding to various engine usage stages are found to be close by two models. The analysis identifies an anamoly in the simulated and measured data collected 17 months after the engine overhauling which may be attributed to deliberate adjustments in the operating parameters. A threshold for anomaly detection in terms of the probability levels for variation of the rated power capacity of the engine is also studied.
An Efficient Deterministic Approach to Model-based Prediction Uncertainty Estimation
Authors: Daigle Matthew , Saxena Abhinav , Goebel Kai
Published: March 2024

Prognostics deals with the prediction of the end of life (EOL) of a system. EOL is a random variable, due to the presence of process noise and uncertainty in the future inputs to the system. Prognostics algorithms must account for this inherent uncertainty. In addition, these algorithms never know exactly the state of the system at the desired time of prediction, or the exact model describing the future evolution of the system, accumulating additional uncertainty into the predicted EOL. Prediction algorithms that do not account for these sources of uncertainty are misrepresenting the EOL and can lead to poor decisions based on their results. In this paper, we explore the impact of uncertainty in the prediction problem. We develop a general model-based prediction algorithm that incorporates these sources of uncertainty and propose a novel approach to efficiently handle uncertainty in the future input trajectories of a system by using the unscented transform. Using this approach, we are not only able to reduce the computational load but also estimate the bounds of uncertainty in a deterministic manner, which can be useful to consider during decision-making. Using a lithium-ion battery as a case study, we perform several simulation-based experiments to explore these issues, and validate the overall approach using experimental data from a battery testbed.
A Distributed Approach to System-Level Prognostics
Authors: Daigle Matthew , Bregon Anibal , Roychoudhury Indranil
Published: March 2024

Prognostics, which deals with predicting remaining useful life of components, subsystems, and systems, is a key technology for systems health management that leads to improved safety and reliability with reduced costs. The prognostics problem is often approached from a component-centric view. However, in most cases, it is not specifically component life- times that are important, but, rather, the lifetimes of the systems in which these components reside. The system-level prognostics problem can be quite difficult due to the increased scale and scope of the prognostics problem and the relative lack of scalability and efficiency of typical prognostics approaches. In order to address these issues, we develop a distributed solution to the system-level prognostics problem, based on the concept of structural model decomposition. The system model is decomposed into independent submodels. Independent local prognostics subproblems are then formed based on these local submodels, resulting in a scalable, efficient, and flexible distributed approach to the system-level prognostics problem. We provide a formulation of the system-level prognostics problem and demonstrate the approach on a four-wheeled rover simulation testbed. The results show that the system-level prognostics problem can be accurately and efficiently solved in a distributed fashion.
Application of Inductive Monitoring System to Plug Load Anomaly Detection
Authors: Teubert Christopher , Poll Scott
Published: March 2024

NASA Ames Research Center’s Sustainability Base is a new 50,000 sq. ft. LEED Platinum office building. Plug loads are expected to account for a significant portion of the overall energy consumption. This is because building design choices have resulted in greatly reduced energy demand from Heating, Ventilation, and Air Conditioning (HVAC) and lighting systems, which are major contributors to energy consumption in traditional buildings. In anticipation of the importance of plug loads in Sustainability Base, a pilot study was conducted to collect data from a variety of plug loads. A number of cases of anomalous or unhealthy behavior were observed including schedule-based rule failures, time-to-standby errors, changed loads, and inter-channel anomalies. These issues prevent effective plug load management; therefore, they are important to promptly identify and correct. The Inductive Monitoring System (IMS) data mining algorithm was chosen to identify errors. This paper details how an automated data analysis program was created, tested and implemented using IMS. This program will be applied to Sustainability Base to maintain effective plug load management system performance, identify malfunctioning equipment, and reduce building energy consumption.
A Batch Detection Algorithm Installed on a Test Bench
Authors: Lacaille Jérôme , Gerez Valerio
Published: March 2024

Test benches are used to evaluate the performance of new turbofan engine parts during development phases. This can be especially risky for the bench itself because no one can predict in advance whether the component will behave properly. Moreover, a broken bench is often much more expensive than the deterioration of the component under test. Therefore, monitoring this environment is appropriate, but as the system is new, the algorithms must automatically adapt to the component and to the driver's behavior who wants to experience the system at the edge of its normal domain.
In this paper we present a novelty detection algorithm used in batch mode at the end of each cycle. During a test cycle, the pilot increases the shaft speed by successive steps then finally ends the cycle by an equivalent slow descent. The algorithm takes a summary of the cycle and works at a cycle frequency producing only one result at the end of each cycle. Its goal is to provide an indication to the pilot on the reliability of the bench's use for a next cycle.
Characterization of prognosis methods: an industrial approach
Authors: Gupta Jayant Sen , Trinquier Christian , Lorton Ariane , Feuillard Vincent
Published: March 2024

This article presents prognosis implementation from an industrial perspective. From the description of a use-case (available information, data, expertise, objective, expected performance indicators, etc.), an engineer should be able to select easily, among the large variety of prognosis methods, the ones that are compatible with his objectives and means. Many classifications of prognosis methods have already been published but they focus more on the techniques that are involved (physical model, statistical model, data-based model, ...) than on the necessary inputs to build/learn the model and/or run it and the expected outputs. This paper presents the different strategies of maintenance and the place of prognostics in these strategies. The life cycle of a prognosis function is described, which helps to define relevant, yet certainly not complete, characteristics of prognosis problems and methods. Depending on the maintenance strategy, the prognosis function will not be used at the same step and with different objectives. Two different steps of use are defined when using the prognosis function: evaluation of the current state and prediction of the prognosis output. This paper gives also some elements of classification that will help an engineer choose the appropriate class of methods to use to solve a prognosis problem.The paper also illustrates on one example the fact that, depending on the information at hand, the prognosis method chosen is different.
Lifetime models for remaining useful life estimation with randomly distributed failure thresholds
Authors: Nystad Bent Helge , Gola Giulio , Hulsund John Einar
Published: March 2024

In order to predict in advance and with the smallest possible uncertainty when a component needs to be fixed or replaced, lifetime models are developed based on the information of the component deterioration trend and its failure threshold to estimate the stochastic distribution of the hitting time (the first time the deterioration exceeds the failure threshold) and the remaining useful life. A primary issue is how to effectively handle the uncertainties related to the component deterioration trend and failure threshold. This problem is here investigated considering a non-stationary gamma process to model the component deterioration and a gamma-distributed failure threshold. Two lifetime models are proposed for comparison on an application concerning deterioration of choke valves used in offshore oil platforms.
Investigating Computational Geometry for Failure Prognostics in Presence of Imprecise Health Indicator: Results and Comparisons on C-MAPSS Datasets
Authors: Ramasso Emmanuel
Published: March 2024

Prognostics and Health Management (PHM) is a multidisciplinary field aiming at maintaining physical systems in their optimal functioning conditions. The system under study is assumed to be monitored by sensors from which are obtained measurements reflecting the system’s health state. A health index (HI) is estimated to feed a data-driven PHM solution developed to predict the remaining useful life (RUL). In this paper, the values taken by an HI are assumed imprecise (IHI). An IHI is interpreted as a planar figure called polygon and a case-based reasoning (CBR) approach is adapted to estimate the RUL. This adaptation makes use of computational geometry tools in order to estimate the nearest cases to a given testing instance. The proposed algorithm called RULCLIPPER is assessed and compared on datasets generated by the NASA’s turbofan simulator (C-MAPSS) including the four turbofan testing datasets and the two testing datasets of the PHM’08 data challenge. These datasets represent 1360 testing instances and cover different realistic and difficult cases considering operating conditions and fault modes with unknown characteristics. The problem of feature selection, health index estimation, RUL fusion and ensembles are also tackled. The proposed algorithm is shown to be efficient with few parameter tuning on all datasets.
Quantification of Signal Reconstruction Uncertainty in Fault Detection Systems
Authors: Al-Dahidi Sameer , Baraldi Piero , Maio Francesco Di , Zio Enrico
Published: March 2024

In Condition-Based Maintenance (CBM), Fault Detection (FD) systems monitor the health state of the components and aid the operator to decide whether a maintenance intervention is necessary. A FD system is a decision-aid tool typically based on i) a reconstruction model that estimates (reconstructs) the values of measurable signals in normal conditions, and ii) an analyzer of the differences (residuals) between the measured and reconstructed values: abnormal conditions are detected when residuals are statistically significant. The performance of the reconstruction model is influenced by several sources of uncertainty which can influence the operator decision: 1) measurement errors, 2) intrinsic stochasticity of the physical process, 3) uncertainty on the settings of the model parameters, and 4) uncertainty on the model output due to incompleteness of the training data. The objective of the present work is the quantification of the overall uncertainty affecting the model reconstructions. The proposed novel approach for uncertainty quantification relies on the estimation of Prediction Intervals (PIs) by using Order Statistics (OS) fora pre-defined confidence level. The proposed approach is verified with respect to an artificial case study; the obtained results show that the approach is able to guarantee the desired level of confidence on the correctness of the detection and provide the decision maker with the required information for establishing whether a maintenance intervention is necessary.
A Similarity-based Prognostics Approach for Remaining Useful Life Prediction
Authors: Eker O. F. , Camci F. , Jennions I. K.
Published: March 2024

Physics-based and data-driven models are the two major prognostic approaches in the literature with their own advantages and disadvantages. This paper presents a similarity-based data-driven prognostic methodology and efficiency analysis study on remaining useful life estimation results. A similarity-based prognostic model is modified to employ the most similar training samples for RUL estimations on each time instance. The presented model is tested on; Virkler’s fatigue crack growth dataset, a drilling process degradation dataset, and a sliding chair degradation of a turnout system dataset. Prediction performances are compared utilizing an evaluation metric. Efficiency analysis of optimization results show that the modified similarity-based model performs better than the original definition.
A Bayesian network based approach to improve the effectiveness of maintenance actions in Semiconductor Industry
Authors: BEN SAID Anis , SHAHZAD Muhammad Kashif , ZAMAI Eric , HUBAC Stéphane , TOLLENAERE Michel
Published: March 2024

The Semiconductor Industry (SI) is facing the challenge of high-mix low-volume production due to increasing diversity in customer demands. This has increased unscheduled equipment breakdowns followed by delays in diagnosis and ineffective maintenance actions that reduce the production capacities. At present, these challenges are addressed with mathematical approaches to optimize maintenance actions and their times of intervention. However, few studies take into account the ineffectiveness of maintenance actions, which is the key source for subsequent breakdowns. Hence, in this paper, we present a methodology to detect poorly executed maintenance actions and predict their consequences on the product quality and/or equipment as the feedback for technicians. It is based on the definition of maintenance objectives and criteria by experts to capture information on the extent to which the objective is fulfilled. Data collected from maintenance actions is then used to formulate Bayesian Network (BN) to model the causality between defined criteria and effectiveness of maintenance actions. This is further used in the respective FMECA defined for each equipment, to unify the maintenance knowledge. The key advantages from the proposed approach are (i) dynamic FMECA with unified and updated maintenance knowledge and (ii) real time feedback for technicians on poor maintenance actions.
Fault Diagnosis Methods for Wind Turbines Health Monitoring: a Review
Authors: Abichou Bouthaina , Flórez Diana , Sayed-Mouchaweh Moamar , Toubakh Houari , François Bruno , Girard Nicolas
Published: March 2024

Recently, the rapid expansion of wind energy activity has led to an increasing number of publications that deal with wind turbine health monitoring. In real practice, implementing a prognostics and health management (PHM) strategy for wind turbines is challenging. Indeed, wind turbines are complex electro-mechanical systems that often work under rapidly changing environment and operating load conditions. Although several review papers that address wind turbines fault diagnosis were published, they are mostly focused on a specific component or on a specific category of methods. Therefore, a larger snapshot on recent advances in wind turbine fault diagnosis is presented in this paper. Fault diagnosis approaches could be grouped in three major categories according to the available a priori knowledge about the system behavior: quantitative/qualitative model, signal analysis and artificial intelligence based approaches. Each of the proposed methods in the literature has its advantages and drawbacks. Therefore, a comparison between these methods according to some meaningful evaluation criteria is conducted.
A Real-time Data-driven Method for Battery Health Prognostics in Electric Vehicle Use
Authors: Barr´ Anthony , Suard Frédéric , Gérard Mathias , Riu Delphine
Published: March 2024

Online prognostics of the battery capacity is a major challenge as ageing process is a complex phenomenon, hardly directly measurable. This paper offers a new methodology for real-time estimating of the global battery performances for Electric Vehicle (EV) use. The presented data-driven framework build a model based on the modifications in battery signals behavior, according to the performance level. A first pattern extraction step consists in the selection of battery signals corresponding to specific acceleration profiles in real uses, allowing to highlight the battery behavior. These extracted voltage and current patterns are then considered to determine the battery behavior for each State of Health (SOH) feature. Studied patterns are compared using signal processing techniques, allowing the estimation of the battery performance, through statistical learning methods. The application of signal processing and Relevance Vector Machines (RVM) modelwith multiple kernels, provides a powerful tool to diagnose battery health online, only based on real signals. Furthermore, this methodology also allows the prediction of battery Remaining Useful Life (RUL) during real use. The proposed algorithm is validated using datasets from real EV uses. Presented diagnostics results on real data demonstrate the good accuracy of this new framework for battery SOH prognostics in real-time constraints, with uncontrolled conditions.
A Model-Based Approach for an Optimal Maintenance Strategy
Authors: Saha Bhaskar , Honda Tomonori , Matei Ion , Saund Eric , Kleer Johan de , Kurtoglu Tolga , Lattmann Zsolt
Published: March 2024

In this paper we introduce a novel model-based reliability analysis methodology to guide the best maintenance practices for the different components in complex engineered systems. We have developed a tool that allows the system designer to explore the consequences of different design choices, and to assess the effects of faults and wear on critical components as a result of usage or age. The tool uses pre-computed simulations of usage scenarios for which performance metrics can be computed as functions of system configurations and faulty/worn components. These simulations make use of damage maps, which estimate component degradation as a function of usage or age. This allows the designer to determine the components and their respective fault modes that are critical w.r.t. the performance requirements of the design. Given a design configuration, the tool is capable of providing a ranked list of critical fault modes and their individual contributions to the likelihood of failing the different performance requirements. From this initial analysis it is possible to determine the components that have little to no effect on the probabilityof the system meeting its performance requirements. These components are likely candidates for reactive maintenance. Other component faults may affect the performance over the short or long run. Given a limit for allowable failure risk, it is possible to compute the Mean Time Between Failure (MTBF) for each of those fault modes. These time intervals, grouped by component or Line Replaceable Units (LRUs), are aggregated to develop a preventive maintenance schedule. The most critical faults may be candidates for Condition-Based Maintenance (CBM). For these cases, the specific fault Bhaskar Saha et. al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. modes considered for CBM also guide sensor selection and placement.
Effect of parameters setting on performance of discrete component removal (DCR) methods for bearing faults detection
Authors: Kilundu Bovic , Ompusunggu Agusmian Partogi , Elasha Faris , Mba David
Published: March 2024

Separation between non-deterministic and deterministic components of gearbox vibration signals has been considered as important signal processing step for rolling-element bearing fault diagnostics. In this paper, the performance of bearing fault detection after applying various discrete components removal (DCR) methods is quantitatively compared. Three methods that have become widely used, namely (i) time synchronous average, (ii) self adaptive noise cancellation (SANC) and (iii) cepstrum editing, were considered. The three DCR methods with different parameter settings have been applied to vibration signals measured on two different gearboxes. In general, the experimental results show that cepstrum editing method outperforms the other two methods.
Methodology for Integrated Failure-Cause Diagnosis with Bayesian Approach: Application to Semiconductor Manufacturing Equipment
Authors: ABU SAMAH Asma , SHAHZAD Muhammad Kashif , ZAMAÏ Eric , HUBAC Stéphane
Published: March 2024

Semiconductor Industry (SI) is facing the challenge of short product life cycles due to increasing diversity in customer demands. As a result, it has transformed into a high-mix low -volume production line that requires sustainable production capacities. However, significant increase in the unscheduled equipment breakdowns, limits its success. It is observed that in a high-mix low-volume production, product commonality is inversely proportional to failure occurrences and number of corrective actions in each failure. This provides evidence of misdiagnosis for equipment failures and causes. Moreover, equipment is believed to be the only source for product quality drifts that increase the unscheduled breakdowns and result in unstable production capacities. In this paper, we propose two defense lines against increasing unscheduled equipment breakdowns due to misdiagnosis. We argue that product quality drift can be traced to product itself, process and maintenance events, besides equipment. The Bayesian Belief Network (BBN) is proposed using symptoms, collected across drift sources, that improves equipment breakdown decisions by accurately identifying the source of product quality drift. The misdiagnosis of equipment failures and causes, if equipment is found as a source of drift, is another significant factor for increasing unscheduled equipment breakdowns. Existing failures and causes diagnosis approaches, in the SI, model equipment as a single unit and use fault detection and classification (FDC) sensor data. We also argue that these are the key reasons for the misdiagnosis because of neglected facts that production equipment is composed of multiple modules and FDC sensors undergo reliability issues in a high-mix low-volume production line. Therefore, to improve these misdiagnosis, another BBN is proposed that uses statistical information, collected from the equipment database, at the module level. These BBN models are evaluated in a thermal treatment (TT) workshop at the world reputed semiconductor manufacturer. The BBN model for the identification of the source of product quality drift (failure mode) demonstrates 97.8% prediction accuracy; whereas, module level BBNs for equipment failures and causes diagnosis are found 45.7% more accurate than equipment level BBN.
Towards the Industrial Application of PHM: Challenges and Methodological Approach
Authors: López Antonio J Guillén , Márquez Adolfo Crespo , Fernández Juan Fco. Gómez , Bolaños Alejandro Guerrero
Published: March 2024

The diagnosis and prognosis capabilities are the key points of PHM (Prognosis Health Management) research. Most of the endeavor and investment are being oriented to get and improve these capabilities: new sensors, measurement techniques, communication/data solutions, detection algorithms, decision algorithms and reliability calculate tools. Nowadays it is actually possible take advantage of these capabilities to improve systems operation and maintenance. In spite of this, massive industrial application is still far away. Many of industrial sectors barely have heard about of PHM and its potential, or only have introduced classical CBM (Condition Based Maintenance) tools -vibration analysis, ultrasound, thermography- to specific and local maintenance applications.In this paper a comprehensive understanding of the problem of transferring PHM into industrial environments and its relevance is introduced. It's also argued the need of develop a methodological approach as a key point for getting a broad applying of PHM-based solutions. To do this, the main challenges to be addressed are listed and analyzed..