An economic off-line quality control approach for unstable production processes

2017 ◽  
Vol 29 (4) ◽  
pp. 623-642 ◽  
Author(s):  
Zhenlu Chen ◽  
Rong Pan ◽  
Lirong Cui
Keyword(s):  
Quality Control ◽  
Control Approach ◽  
Production Processes

scholarly journals Quality Control in Production Processes

2016 ◽  
Vol 19 (3) ◽  
pp. 77-83 ◽  
Author(s):  
Miroslav Prístavka ◽  
Martina Kotorová ◽  
Radovan Savov
Keyword(s):  
Quality Control ◽  
Quality Improvement ◽  
Quality Management ◽  
Statistical Methods ◽  
Developed Countries ◽  
Basic Knowledge ◽  
Root Cause ◽  
Production Processes ◽  
Basic Quality ◽  
Quality Tools

AbstractThe tools for quality management are used for quality improvement throughout the whole Europe and developed countries. Simple statistics are considered one of the most basic methods. The goal was to apply the simple statistical methods to practice and to solve problems by using them. Selected methods are used for processing the list of internal discrepancies within the organization, and for identification of the root cause of the problem and its appropriate solution. Seven basic quality tools are simple graphical tools, but very effective in solving problems related to quality. They are called essential because they are suitable for people with at least basic knowledge in statistics; therefore, they can be used to solve the vast majority of problems.

scholarly journals A Framework of Cloud Model Similarity-Based Quality Control Method in Data-Driven Production Process

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Sheng Hu ◽  
Shuanjun Song ◽  
Wenhui Liu
Keyword(s):  
Quality Control ◽  
Production Process ◽  
Control Method ◽  
Cloud Model ◽  
Data Driven ◽  
Monitoring Method ◽  
Control Approach ◽  
Acceptable Method ◽  
And Performance ◽  
Model Similarity

Considering the problem that the process quality state is difficult to analyze and monitor under manufacturing big data, this paper proposed a data cloud model similarity-based quality fluctuation monitoring method in data-driven production process. Firstly, the randomness of state fluctuation is characterized by entropy and hyperentropy features. Then, the cloud pool drive model between quality fluctuation monitoring parameters is built. On this basis, cloud model similarity degree from the perspective of maximum fluctuation border is defined and calculated to realize the process state analysis and monitoring. Finally, the experiment is conducted to verify the adaptability and performance of the cloud model similarity-based quality control approach, and the results indicate that the proposed approach is a feasible and acceptable method to solve the process fluctuation monitoring and quality stability analysis in the production process.

Online determination of chemical and physical properties of poly(ethylene vinyl acetate) pellets using a novel method of near-infrared spectroscopy combined with angle transformation

2019 ◽  
Vol 11 (18) ◽  
pp. 2435-2442 ◽  
Author(s):  
Jinchun Xie ◽  
Hongfu Yuan ◽  
Chunfeng Song ◽  
Xiangjun Yan ◽  
Hao Yan ◽  
...  
Keyword(s):  
Quality Control ◽  
Infrared Spectroscopy ◽  
Vinyl Acetate ◽  
Near Infrared ◽  
Ethylene Vinyl Acetate ◽  
Melt Flow Rate ◽  
Production Processes ◽  
Novel Method ◽  
Poly Ethylene

Melt flow rate (MFR) and vinyl acetate content (VAC) are the target parameters for quality control of poly(ethylene vinyl acetate) (EVA) pellets in production processes.

scholarly journals Quality assessment concept of the World Data Center for Climate and its application to CMIP5 data

2012 ◽  
Vol 5 (4) ◽  
pp. 1023-1032 ◽  
Author(s):  
M. Stockhause ◽  
H. Höck ◽  
F. Toussaint ◽  
M. Lautenschlager
Keyword(s):  
Quality Control ◽  
Quality Assessment ◽  
Data Center ◽  
Climate Model ◽  
Assessment Procedure ◽  
Data Repositories ◽  
Data Infrastructure ◽  
World Data ◽  
Control Approach ◽  
The World

Abstract. The preservation of data in a high state of quality which is suitable for interdisciplinary use is one of the most pressing and challenging current issues in long-term archiving. For high volume data such as climate model data, the data and data replica are no longer stored centrally but distributed over several local data repositories, e.g. the data of the Climate Model Intercomparison Project Phase 5 (CMIP5). The most important part of the data is to be archived, assigned a DOI, and published according to the World Data Center for Climate's (WDCC) application of the DataCite regulations. The integrated part of WDCC's data publication process, the data quality assessment, was adapted to the requirements of a federated data infrastructure. A concept of a distributed and federated quality assessment procedure was developed, in which the workload and responsibility for quality control is shared between the three primary CMIP5 data centers: Program for Climate Model Diagnosis and Intercomparison (PCMDI), British Atmospheric Data Centre (BADC), and WDCC. This distributed quality control concept, its pilot implementation for CMIP5, and first experiences are presented. The distributed quality control approach is capable of identifying data inconsistencies and to make quality results immediately available for data creators, data users and data infrastructure managers. Continuous publication of new data versions and slow data replication prevents the quality control from check completion. This together with ongoing developments of the data and metadata infrastructure requires adaptations in code and concept of the distributed quality control approach.

scholarly journals Control charts based on quantiles: New approaches

2020 ◽  
Vol 12 (2) ◽  
pp. 99-104
Author(s):  
Vesna Jevremovć ◽  
Atif Avdović
Keyword(s):  
Quality Control ◽  
Control Charts ◽  
Empirical Distribution Function ◽  
Empirical Distribution ◽  
Statistical Quality Control ◽  
P Value ◽  
Applied Statistics ◽  
Production Processes ◽  
New Ideas ◽  
Contemporary Development

Contemporary development of Statistical quality control includes researches on different control charts, which could be easily implemented in production processes due to facilities offered by computers. New control charts give more information about production processes than the conventional ones, that's why there is a lot of investigation in this area of applied statistics. In this paper, we shall explain some new ideas concerning the construction of control charts based on quantiles, empirical distribution function and p-value.

scholarly journals Development of Quality Control Methods for Dispersibility and Stability of Single-Wall Carbon Nanotubes in an Aqueous Medium

Nanomaterials ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 2618
Author(s):  
Moran Ben Basat ◽  
Noa Lachman
Keyword(s):  
Carbon Nanotubes ◽  
Quality Control ◽  
Single Wall Carbon Nanotubes ◽  
Characterization Methods ◽  
Single Wall Carbon ◽  
Control Approach ◽  
Advanced Composite Materials ◽  
Vis Spectroscopy ◽  
The Stability ◽  
Dispersion Quality

The attractive properties of single-wall carbon nanotubes (SWCNT) such as mechanical strength and high electrical and thermal conductivity are often undercut by their agglomeration and re-agglomeration tendencies. As a result, the application of SWCNT as additives in advanced composite materials remain far from their potential, with proper dispersion being the major inhibitor. This work presents a dispersion quality control approach for water-based SWCNT dispersions (dispersed by a unique combination of physical and chemical methods), using complementary and easily scalable, characterization methods. UV-Vis spectroscopy, rheological measurements, and precipitant sheet resistance were used to understand the properties of the initial solution through processing and application. From an industrial perspective, these methods are fast and easy to measure while giving a repetitive and quick indication of dispersion quality and stability. The methods were correlated with microscopy and Raman spectroscopy to validate dispersion and SWCNT quality under various dispersing energies. The protocol was then applied to estimate the stability of SWCNT solutions, as well as the effectiveness of different surfactants in aiding dispersion. The simple, fast, and scalable combination of different characterizations provides good SWCNT dispersion and can be used as a quality control system for industrial production and usage.

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