A defect tracking tool framework for multi-process products
Procedia CIRP, ISSN: 2212-8271, Vol: 79, Page: 523-527
2019
- 7Citations
- 28Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
In production lines consisting of multi-process chains, defects are difficult to be detected, especially with a single-stage measurement. The framework presented in this paper concerns real-time defect tracking through modelling, leading to zero-defect manufacturing. The a priori knowledge of a mechanical system response is used. Examples of final products of gradually increasing complexity are studied in an attempt to detect the defect causes. The objective is to be able to manage highly complex products, such as the booster of brakes in automotive industry and potentially link the defect that has been detected to a preceding process that has generated it.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S2212827119302173; http://dx.doi.org/10.1016/j.procir.2019.02.100; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85065438461&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S2212827119302173; https://dx.doi.org/10.1016/j.procir.2019.02.100
Elsevier BV
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