Part B is a diagnostic study of the current process control (a seven-step product assessment process) that results in determining the adequacy of the current control strategy. ... The protocol-driven product assessment closely dissects the manufacturing process to determine the current state of control, to comprehend and …

Symmetry 2019, 11, 685 3 of 40 1.2. Research Framework A novel quality defects diagnosis method based on product gene theory and knowledge base was developed to address the problems of the quality ...

Early fault detection and quick diagnosis of faulty wafer are important to ensure controlling process operations and reduce yield losses in semiconductor manufacturing (Hsu et al. 2020).Advanced in sensing and information technology have enabled the automatic collection and recording of the massive data generated by the …

of process monitoring techniques reported for metal etching process, which is a batch operation carried out in semiconductor manufacturing industry. V arious machine learning

A deep-belief-network-based intelligent method is proposed for monitoring and diagnosing manufacturing process profiles. •. The proposed method is more sensitive …

Definition: In vitro diagnostic products are those reagents, instruments, and systems intended for use in diagnosis of disease or other conditions, including a determination of the state of health ...

niques to manufacturing process diagnosis. This review covers papers published from 2007 to 2017 that utilized machine learning techniques for manufacturing fault diagno-sis. This review covers 20 articles. The keywords used in the search are "machine learn-ing application in manufacturing process diagnosis". The search was filtered to focus

In five of these studies, visual object detection, surface defect detection, machine production scheduling application, fault diagnosis and prediction, and monitoring of the manufacturing process ...

In this paper, we propose a diagnostic scheme for condition monitoring of mechanical components. The proposed scheme combines anomaly detection algorithms, …

The aim of this paper is to review the recent application of machine learning tech-niques to manufacturing process diagnosis. This review covers papers published from 2007 to …

The RT-PCR method is the 'gold standard' test and widely used worldwide. It involves RNA extraction from the patient swab solution followed by reverse transcription of the RNA and then PCR expansion of the cDNA. The whole process can be automated and high-throughput testing can be performed, which makes it ideal for central test laboratories.

For the diagnosis of faulty processes, in this study, they modeled the sequential flow features of data patterns, that is, spatiotemporal patterns in times and …

Description. Objective - Develop and deploy measurement science to promote the implementation, verification, and validation of advanced monitoring, diagnostic, and prognostic technologies to minimize unplanned downtime and optimize …

The process followed is a combination of discussion with functional head, presentations, company visit and feedback sessions. Also study the relevant data on the company's Key Performance characteristics. Review of Strategic goals, customer complaints and COPQ data. Based on this, laundry list of potential projects will be prepared.

DOI: 10.1016/J.MEASUREMENT.2018.12.067 Corpus ID: 115285597; Experimental study of the process failure diagnosis in additive manufacturing based on acoustic emission @article{Wu2019ExperimentalSO, title={Experimental study of the process failure diagnosis in additive manufacturing based on acoustic emission}, author={Haixi Wu …

One of the key technologies to realize the quality control and continuous improvement of the complex product manufacturing process is to deeply study the forming principle of quality characteristic deviation and carry out the fault diagnosis of the complex product's multi-source and multi-level manufacturing process.

This study aims to construct a system for predicting and diagnosing defects in casting products and their causes to improve the productivity of the casting process in the die casting industry. Three data analysis algorithms are proposed to predict defects and diagnose the causes of the defects. First, diagnosing the pre-heating state, which ...

A comprehensive guide to the future of process fault diagnosis Automation has revolutionized every aspect of industrial production, from the accumulation of raw materials to quality control inspections. Even process analysis itself has become subject to automated efficiencies, in the form of process fault analyzers, computer programs …

Self-healing refers to the ability of a manufacturing process to detect system abnormalities and make the necessary adjustments to return to normal operation without …

Machine learning-based techniques for fault diagnosis in the semiconductor manufacturing process: a comparative study Published: 06 August …

It has been tested as a case study approach using real data from two complete years of the balanced scorecard of a leading manufacturing company. The results provided a new understanding of how the quality management system works that was used to make systemic and strategic decisions to improve the long-term …

In the process of laser additive manufacturing, the transmission efficiency of laser energy and the forming quality are influenced by the plasma which plays a fundamental role in coupling the incident radiation to the material. The aim of this work is to present an effective spectral diagnosis method for quality research in laser additive …

The Diagnostic Process. Every member of the clinical team, including patients and family, has a role to play in ensuring that diagnoses are accurate, timely and communicated to the patient. The Diagnostic Process Map is a resource developed by the National Academies of Sciences, Engineering, and Medicine (National Academies) and offered by the ...

S S symmetry Article A Novel Quality Defects Diagnosis Method for the Manufacturing Process of Large Equipment Based on Product Gene Theory Wenxiang Xu 1,2, Chen Guo 3,*, Shunsheng Guo 1,2 and Xixing Li 4 1 School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China; xuwenxiang910327@126 …

A review of diagnostic and prognostic capabilities and best practices for manufacturing. Gregory W. Vogl1 Brian A. Weiss1 Moneer Helu1. ·. Received: 29 October 2015 / …

Fig. 1. Feature transfer for machine fault diagnosis. 2.2. Transferability. Proper and effective model/feature transfer depends on data transferability. For model transfer, the transferability is evaluated by examining whether the network can effectively characterize data in both the source and target domains.

In the current scenario, industries need to have continuous improvement in their manufacturing processes. Digital twin (DT), a virtual representation of a physical entity, serves this purpose. It aims to bridge the prevailing gap between the design and manufacturing stages of a product by effective flow of information. This article aims to …

In this study, a two-stage attention-based variational long short-term memory (LSTM) that allows fault detection and diagnosis in electrolytic copper manufacturing processes is proposed. As the surface quality of electrolytic copper determines the yield and quality of the product, an automated surface inspection (ASI) …

The two main components that make up the pharma-ceutical manufacturing process are those of drug substance and drug product manufacturing. Drug substance is an active ingredient that is intended to furnish pharmacolog-ical activity, directly impact the diagnosis, cure, mitigation, treatment, or prevention of disease, or to affect the structure ...

This study aims to propose a multiple time-series convolutional neural network (MTS-CNN) model for fault detection and diagnosis in semiconductor manufacturing. This study incorporates data ...