Evaluation of operational system structures based on reliability data

Author(s):  
Alan M. Polansky ◽  
Duchwan Ryu
2018 ◽  
Vol 3 (1) ◽  
pp. 67-78
Author(s):  
Moonjun Kim ◽  
Taekgeun Kim
Keyword(s):  

Encyclopedia ◽  
2021 ◽  
Vol 1 (2) ◽  
pp. 401-408
Author(s):  
Renata Puppin Zandonadi ◽  
Raquel Braz Assunção Botelho ◽  
Dayanne da Costa Maynard ◽  
Rita de Cassia Coelho de Almeida Akutsu

During the SARS-CoV-2 pandemic, the self-service restaurant sector, as well as other types of food services, are facing an unprecedented crisis needing to adapt their service to avoid closing their doors. With varied and quick meals, the self-service buffet is one of the most important types of outside services. However, the type of service where the clients follow a line on the buffet and serve their meals has impaired traditional restaurant operation during the SARS-CoV-2 pandemic and, perhaps, after it. In this sense, this study presents an overview of the self-service buffet restaurant operational system in the context of the SARS-CoV-2 pandemic.


Author(s):  
Abbas Barabadi

The development of offshore energy resources involves highly complex and extensive technological processes. Reliability evaluation of offshore production facilities provides essential information in the design and operation phase. Historical reliability data play an important role in reliability analysis, and as such data reflect the effect of influencing factors that production facilities have experienced during their life cycle. Due to there being less offshore activity in the Arctic region compared with other areas, there is a lack of data and little experience available regarding operational equipment. In contrast to the Arctic region, oil and gas companies have a lot of experience and information related to the design and operation of offshore production facilities in the other parts of the world. Using this type of data and information, collected from similar systems but under different operational conditions, in design processes for the Arctic region may lead to incorrect design. This may increase health, safety, and environmental (HSE) risk or operating and maintenance costs. This paper develops a methodology for the application of the accelerated failure time model (AFT) to predict the reliability of equipment to be used in the Arctic region based on the available data. In the methodology used here, the available data is assumed to reflect the behavior of the equipment under low stress conditions, and using the AFT models the reliability of equipment in the Arctic environment, which represents high stress, is predicted. An illustrative example is used to demonstrate how the methodology can be applied in a real case.


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