Results 241 to 250 of about 3,956,939 (297)

Real-time PEM fuel cell fault classification in smart manufacturing plant by using uncertainty aware federated deep learning. [PDF]

Sci Rep
Aurangzeb M, Shusheng X, Iqbal S, Shafiullah M, Qazi HS, Dafalla AM, Fuguang Z, Zhuoyu L, Xinwei L, Nazir S.   +9 more
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Occupational injuries caused by exposure to hydrogen sulfide generated by microbial activity. [PDF]

Environ Occup Health Pract
Vranová M, Štěpánková L, Kushkevych I, Vítěz T, Trávníček P.   +4 more
europepmc   +1 more source

Maintenance for Industrial Systems

, 2010
New, global and extended markets are forcing companies to process and manage increasingly different products with shorter life cycles, low volumes and reduced customer delivery times. In today’s global marketplace production systems need to deliver products on time, maintain market credibility, and introduce new products and services faster than ...
MANZINI, RICCARDO, REGATTIERI, ALBERTO, PHAM H., FERRARI, EMILIO   +3 more
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Software maintenance—an industrial experience

Journal of Software Maintenance: Research and Practice, 1995
AbstractThis paper gives an overview of the software maintenance process of Hitachi Software Engineering (HSK) Co., Ltd in Japan‐including its success and failure cases. It discusses HSK's software processes, issues, use of specific tools and techniques such as IMOZU diagrams, and approaches in solving problems.
Akira K. Onoma, Wei-Tek Tsai, Fumihiro Tsunoda, Hiroshi Suganuma, Satish Subramanian   +4 more
openaire   +2 more sources

Wearable Solution for Industrial Maintenance

Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems, 2015
Wearable technology, such as Google Glass, offers potential benefits to engineers in industrial settings. We designed and developed a wearable solution for industrial maintenance, which 1) provides workflow guidance to the user, 2) supports hands-free operation, 3) allows the users to focus on their work, and 4) enables an efficient way for ...
Xianjun Sam Zheng, Patrik Matos da Silva, Cédric Foucault, Siddharth Dasari, Meng Yuan, Stuart Goose   +5 more
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Predictive Maintenance Analysis for Industries

2024 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom)
In this paper, we are focused on deriving conclusions from sensor parameter data that would enable the detection of potential faults and the prediction of failures. We used Random Forest, Decision Tree, Naive Bayes, Logistic Regression, Support Vector Machine, and Long Short-Term Memory models to predict faults for sensor data.
Sunetcioglu, Selin, Arsan, Taner, Arsan, Taner   +2 more
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