scholarly journals Sensors performance in laser-based manufacturing process quality assessment: a conceptual framework

Procedia CIRP ◽  
2019 ◽  
Vol 79 ◽  
pp. 490-494
Author(s):  
Alexios Papacharalampopoulos ◽  
John Stavridis ◽  
Panagiotis Stavropoulos
Keyword(s):  
Quality Assessment ◽  
Conceptual Framework ◽  
Manufacturing Process ◽  
Process Quality

Geometric recognition methodology of honeycomb structure based on dynamic window

2020 ◽  
pp. 109963622091172
Author(s):  
Wei Zhou ◽  
Wanhui Wei ◽  
Zhonggang Wang ◽  
Can Cui
Keyword(s):  
Quality Assessment ◽  
Manufacturing Process ◽  
Sandwich Structure ◽  
High Standard ◽  
Honeycomb Structure ◽  
Maximum Average Degree ◽  
Honeycomb Cell ◽  
Degree Deviation ◽  
Relationship Of

Defect determination is important for guaranteeing the quality of sandwich structure. The present study, a geometric recognition methodology based on dynamic window was constructed for honeycomb structure, by identifying the vertices from given images captured in the manufacturing process. The combination of traversing window, annihilation window, and tracking window was developed to reconstruct the contoured maximums, locate the vertices positions, and determine the cell–node relationships, respectively. Moore boundary tracking was practically used to deal with the problem caused by the edge effect. Based on these, all relevant vertices as well as their relationship of each honeycomb cell can be determined. Afterward, quality assessment of the honeycomb product was carried out in terms of the maximum, the average, and the maximum average degree deviation. Illustrations validate the present methodology well. All these achievements shed a light on design of the consistency, reliability, and homogeneity of high-standard sandwich structure.

scholarly journals A method of coding for aerospace product quality DNA

2018 ◽  
Vol 151 ◽  
pp. 05006
Author(s):  
Yao Jiayu
Keyword(s):  
Quality Assessment ◽  
Product Quality ◽  
Manufacturing Process ◽  
Feedback Mechanism ◽  
Quality Monitoring ◽  
The Core ◽  
Coding Method ◽  
Wall Panels ◽  
Variation Characteristics ◽  
Coding Rules

Aiming at the problem that the manufacturing process of our aerospace products is relatively discrete and the lack of appropriate quality monitoring and feedback mechanism, a method of coding for aerospace product quality DNA was proposed. Based on the structure of biological DNA and the theory of quality assessment, equipment diagnosis and quality traceability, the biological DNA structure was transformed into the structure of aerospace product quality DNA, and the concept of aerospace product quality DNA was defined, including the genetic and variation characteristics of aerospace product quality DNA. The coding rules of aerospace product quality DNA were designed, and the designed encoding rules are applied to the case of welding of wall panels in the manufacturing process of aerospace products. The results show that the coding method can monitor and feedback the core information related to quality in the manufacturing process of aerospace products.

scholarly journals New Business and Operating Models. Optimization of a Blast Furnace in the Steel Industry. Machine Learning as a Process Optimization

2021 ◽  
Author(s):  
Andrés Redchuk ◽  
Federico Walas Mateo
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Blast Furnace ◽  
Conceptual Framework ◽  
Manufacturing Process ◽  
Smart Manufacturing ◽  
Key Factors ◽  
Steel Company ◽  
Steel Manufacturing ◽  
New Business

The article takes the case of the adoption of machine learning in a steel manufacturing process through a platform provided by a novel Canadian startup, Canvass Analytics. This way the steel company could optimize the process in a blast furnace. The content of the paper includes a conceptual framework on key factors around steel manufacturing and machine learning. Method: The article takes the case of the adoption of machine learning in a steel manufacturing process through a platform provided by a novel Canadian startup, Canvass Analytics. This way the steel company could optimize the process in a blast furnace. The content of the paper includes a conceptual framework on key factors around steel manufacturing and machine learning. Results: This case is relevant for the authors by the way the business model proposed by the startup attempts to democratize Artificial Intelligence and Machine Learning in industrial environments. This way the startup delivers value to facilitate traditional industries to obtain better operational results, and contribute to a better use of resources. Conclusion: This work is focused on opportunities that arise around Artificial Intelligence as a driver for new business and operating models. Besides the paper looks into the framework of the adoption of Artificial Intelligence and Machine Learning in a traditional industrial environment towards a smart manufacturing approach.

scholarly journals Accreditation is not a One-time Process: Quality Assessment of Intensive Care Unit during Post-NABH Accreditation Period in a Tertiary Care Hospital

2017 ◽  
Vol 5 (1) ◽  
pp. 29-41
Author(s):  
Suneeta Dubey ◽  
VK Tadia ◽  
Monalisa LNU
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Quality Assessment ◽  
Health Care Providers ◽  
Tertiary Care Hospital ◽  
Tertiary Care ◽  
Process Quality ◽  
Care Hospital ◽  
Time Process ◽  
Care Providers

ABSTRACT Accreditation is an integral part of quality and it is not a onetime process. This study was done to know the extent to which hospitals maintain the standards after obtaining accreditation. This study tries to find out the gaps in standards during the postaccreditation period. The objective of the study was to assess the policies of the intensive care unit (ICU) with reference to standard protocols of the National Accreditation Board for Hospital and Health Care Providers (NABH) and measures taken by the management to maintain the standards. Data was collected from a 285-bedded NABH-accredited hospital that had five ICUs and four recovery rooms by means of nonparticipant observation, semistructured interviews. Data on indicators was collected by using the hospital management information system; the questionnaire on satisfaction was filled by 30 patients/relatives who were admitted in the ICU for more than a week. Quality team was interviewed to know the perception of the management toward quality and accreditation. To know the compliance of the staff to the NABH standards, a surprise check was done in three ICUs of the hospital. Data analysis showed that the organization was not able to maintain the standards, as it had done at the time of accreditation. The quality team strongly accepted that accreditation helps in maintaining and improving quality, whereas the data from ICUs showed a wide variation in compliance. Three ICUs from the same hospital were having different compliance rates for standards, which shows that staff was not aware about the standard protocol to be followed. The patient-satisfaction questionnaire also showed that the patients were not satisfied with the services given. How to cite this article Tadia VK, Monalisa, Dubey S. Accreditation is not a One-time Process: Quality Assessment of Intensive Care Unit during Post-NABH Accreditation Period in a Tertiary Care Hospital. Int J Res Foundation Hosp Healthc Adm 2017;5(1):29-41.

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