Challenges for Predictive Quality in Multi-stage Manufacturing: Insights from Literature Review
Author:
Affiliation:
1. TU Darmstadt, Darmstadt, Germany
Funder
Bundesministerium für Wirtschaft und Klimaschutz
Publisher
ACM
Reference55 articles.
1. Data-Based Approach for Final Product Quality Inspection: Application to a Semiconductor Industry
2. Lucas Baier Fabian Jöhren and Stefan Seebacher. 2019. Challenges in the Deployment and Operation of Machine Learning in Practice. In ECIS. 1 https://www.researchgate.net/publication/332996647_CHALLENGES_IN_THE_DEPLOYMENT_AND_OPERATION_OF_MACHINE_LEARNING_IN_PRACTICE Lucas Baier Fabian Jöhren and Stefan Seebacher. 2019. Challenges in the Deployment and Operation of Machine Learning in Practice. In ECIS. 1 https://www.researchgate.net/publication/332996647_CHALLENGES_IN_THE_DEPLOYMENT_AND_OPERATION_OF_MACHINE_LEARNING_IN_PRACTICE
3. Methodologies for data quality assessment and improvement
4. Quality prediction in a smart factory: a real case study
5. The Core Industry Manufacturing Process of Electronics Assembly Based on Smart Manufacturing
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