Reliable job execution with process failure recovery in computational grid

Latchoumy, P.; Khader, P. Sheik Abdul

doi:10.1504/ijict.2015.072042

Cited by 1 publication

(1 citation statement)

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“…One can identify critical procedure by taking correlation degree, quality level, and influence degree as influencing factors among procedure [19]. Latchoumy P et al calculated the process faults in the grid through the reliability execution model to determine the critical procedure [20]. Yuan et al used the improved random matrix to establish the association between the manufacturing process and product features.…”

Section: Introductionmentioning

confidence: 99%

Critical Procedure Identification Method Considering the Key Quality Characteristics of the Product Manufacturing Process

Gao

Zhou

et al. 2022

Processes

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The product’s manufacturing process has an evident influence on product quality. In order to control the quality and identify the critical procedure of the product manufacturing process reasonably and effectively, a method combining genetic back-propagation (BP) neural network algorithm and grey relational analysis is proposed. Firstly, the genetic BP neural network algorithm is used to obtain the key quality characteristics (KQCs) in the product manufacturing process. At the same time, considering the three factors that have an essential impact on the quality of the procedures, the grey correlation analysis method is used to establish the correlation scoring matrix between the procedure and the KQCs to calculate the criticality of each procedure. Finally, taking the manufacturing process of the evaporator as a case, the application process of this method is introduced, and four critical procedures are identified. It provides a reference for the procedure quality control and improvement of enterprise in the future.

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Section: Introductionmentioning

confidence: 99%