Accelerated life tests at higher usage rates: a case study

2006 ◽  
Author(s):  
Guangbin Yang ◽  
Z. Zaghati
Keyword(s):  
Accelerated Life Tests ◽  
Accelerated Life ◽  
Life Tests ◽  
Usage Rates

scholarly journals Accelerated life tests for new product qualification: a case study in the household appliance

2013 ◽  
Vol 46 (7) ◽  
pp. 269-274 ◽  
Author(s):  
Orlando Borgia ◽  
Filippo De Carlo ◽  
Nelson Fanciullacci ◽  
Mario Tucci
Keyword(s):  
New Product ◽  
Household Appliance ◽  
Accelerated Life Tests ◽  
Accelerated Life ◽  
Life Tests

Design for Reliability of Refrigerator Components Subject to Repetitive Loads in Use

2010 ◽  
Author(s):  
Seong-woo Woo ◽  
Dennis L. O’Neal ◽  
Michael Pecht ◽  
Hyoung-Eui Kim
Keyword(s):  
Corrective Action ◽  
Action Plans ◽  
Original Design ◽  
Reliability Design ◽  
Frozen Food ◽  
Accelerated Life Tests ◽  
Accelerated Life ◽  
Life Tests ◽  
General Method

A general method for reliability design of a mechanical system is proposed. A case study is presented for a frozen food drawer and handle system used in a residential refrigerator. The system had been failing when subjected to repetitive loads under normal consumer usage in the field. The mode and mechanism of the failure was fracturing which originated in a design flaw. Data from failed products in the field, accelerated life tests, and corrective action plans were used to identify the key control parameters for the drawer and handle system. The missing or improper design parameter in the original design was the system’s inability to endure the normal repetitive stresses in the field. After a tailored series of accelerated life tests with corrective action plans, the B1 life of the new drawer and handle system is now guaranteed to be over ten years with a yearly failure rate of 0.1 percent.

scholarly journals Leveraging Label Information in a Knowledge-Driven Approach for Rolling-Element Bearings Remaining Useful Life Prediction

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2163
Author(s):  
Tarek Berghout ◽  
Mohamed Benbouzid ◽  
Leïla-Hayet Mouss
Keyword(s):  
Transfer Learning ◽  
Short Term Memory ◽  
Remaining Useful Life ◽  
Accelerated Life Tests ◽  
Learning Path ◽  
Accelerated Life ◽  
Unseen Data ◽  
Label Information ◽  
Life Tests ◽  
Ill Posed

Since bearing deterioration patterns are difficult to collect from real, long lifetime scenarios, data-driven research has been directed towards recovering them by imposing accelerated life tests. Consequently, insufficiently recovered features due to rapid damage propagation seem more likely to lead to poorly generalized learning machines. Knowledge-driven learning comes as a solution by providing prior assumptions from transfer learning. Likewise, the absence of true labels was able to create inconsistency related problems between samples, and teacher-given label behaviors led to more ill-posed predictors. Therefore, in an attempt to overcome the incomplete, unlabeled data drawbacks, a new autoencoder has been designed as an additional source that could correlate inputs and labels by exploiting label information in a completely unsupervised learning scheme. Additionally, its stacked denoising version seems to more robustly be able to recover them for new unseen data. Due to the non-stationary and sequentially driven nature of samples, recovered representations have been fed into a transfer learning, convolutional, long–short-term memory neural network for further meaningful learning representations. The assessment procedures were benchmarked against recent methods under different training datasets. The obtained results led to more efficiency confirming the strength of the new learning path.

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