• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.8
• /
• pp.29-37
• /
• 2019

Textile quality management targets the physical properties of fabrics and the subjective discriminations of color and fitting. Color is the most representative quality factor that consumers can use to evaluate quality levels without any instruments. For this reason, quantification using a color discrimination device has been used for statistical quality management in the textile industry. However, small and medium-sized domestic textile manufacturers use only visual inspection for color discrimination. As a result, color discrimination is different based on the inspectors' individual tendencies and work procedures. In this research, we want to develop a textile industry-friendly quality management method, evaluating the possibility of rapid color discrimination using a digital imaging device, which is one of the office-automation instruments. The results show that an imaging process-based color discrimination method is highly correlated with conventional color discrimination instruments ($R^2=0.969$), and is also applicable to field discrimination of the manufacturing process, or for different lots. Moreover, it is possible to recognize quality management factors by analyzing color components, ${\Delta}L$, ${\Delta}a$, ${\Delta}b$. We hope that our rapid discrimination method will be a substitute technique for conventional color discrimination instruments via elaboration and optimization.

• Journal of the Korean Data and Information Science Society
• /
• v.26 no.3
• /
• pp.639-652
• /
• 2015

In today's manufacturing environment, the process data can be easily measured and transferred to a computer for analysis in a real-time mode. As a result, it is possible to monitor several correlated quality variables simultaneously. Various multivariate statistical process control (MSPC) procedures have been presented to detect an out-of-control event. Although the classical MSPC procedures give the out-of-control signal, it is difficult to determine which variable has caused the signal. In order to solve this problem, data mining and machine learning techniques can be considered. In this paper, we applied the technique of decision tree learning to the MSPC, and we did simulation for MSPC procedures to monitor the bivariate normal process means. The results of simulation show that the overall performance of the MSPC procedure using decision tree learning technique is similar for several values of correlation coefficient, and the accurate classification rates for out-of-control are different depending on the values of correlation coefficient and the shift magnitude. The introduced procedure has the advantage that it provides the information about assignable causes, which can be required by practitioners.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.33 no.4
• /
• pp.245-258
• /
• 2015

This study aimed to conduct the standardization of various specifications for determining the proper construction and operation of domestic CORS (Continuously Operating Reference Station). To achieve the plan, the standardization was proposed for various compositions of CORS, such as the data quality, structure, and equipment. Also, we have studied the method for empirically determining the reference values of QC (Quality Check) of CORS data. Those large amounts of samples for each QC index values were built to approach in empirical and statistical methods. In fact, those general and recommended reference values were determined from analyzing the sample distributions, using the empirical and statistical approaches. The result is expected to be utilized for a variety of research fields for standardization, accurate data acquisitions and service operations for the domestic CORS

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.10
• /
• pp.531-538
• /
• 2017

In the case of hydraulic pressure type fuse, we accept or reject certain product lots by considering the number of defective products in the operating pressure test. Generally, this procedure, known as 'The inspection by attributes', has been most commonly used in the field of quality assurance of products. However, the method of inspection by attributes suffers because it tests more samples than inspection by variables. Even though the quality of the products has remained stable in the process condition, the same number of samples is required for every lot, which wastes time and money. This paper suggests that the lot acceptance procedure is changed from inspection by attributes to inspection by variables. We can calculate the statistical tolerance percent of defectives and compare this to the Acceptable Quality Level (AQL) in order to save money and time. It is also easier to monitor and control the quality of products by using the process capability index and x-bar charts. In conclusion, the procedure delivers mutual benefit to both the customer and the producer by securing high quality products and reference data.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.8 no.5
• /
• pp.345-353
• /
• 2015

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do parameter inference for software reliability models based on finite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision to market software, the conditional failure rate is an important variables. In this case, finite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outlier, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical process control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, proposed a control mechanism based on NHPP using mean value function of polynomial hazard function.

• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.6
• /
• pp.255-266
• /
• 2022

The quality control of coarse aggregate among aggregates, which are the main ingredients of concrete, is currently carried out by SPC(Statistical Process Control) method through sampling. We construct a smart factory for manufacturing innovation by changing the quality control of coarse aggregates to inspect the coarse aggregates based on this image by acquired images through the camera instead of the current sieve analysis. First, obtained images were preprocessed, and HED(Hollistically-nested Edge Detection) which is the filter learned by deep learning segment each object. After analyzing each aggregate by image processing the segmentation result, fineness modulus and the aggregate shape rate are determined by analyzing result. The quality of aggregate obtained through the video was examined by calculate fineness modulus and aggregate shape rate and the accuracy of the algorithm was more than 90% accurate compared to that of aggregates through the sieve analysis. Furthermore, the aggregate shape rate could not be examined by conventional methods, but the content of this paper also allowed the measurement of the aggregate shape rate. For the aggregate shape rate, it was verified with the length of models, which showed a difference of ±4.5%. In the case of measuring the length of the aggregate, the algorithm result and actual length of the aggregate showed a ±6% difference. Analyzing the actual three-dimensional data in a two-dimensional video made a difference from the actual data, which requires further research.

• Journal of Applied Biological Chemistry
• /
• v.61 no.1
• /
• pp.25-31
• /
• 2018

This study investigated the effect of different $O_2$ transmission rate (OTR) of films on surface temperature, weight loss, pH, $O_2$, $CO_2$ and sensory characteristics, microbial quality, total phenolic contents and 1,1-diphenyl-2-picryl hydrazyl radical scavenging activity of fresh-cut lettuce during storage at $10^{\circ}C$ for 7 days. $80{\pm}5g$ of fresh-cut lettuce were packaged with oriented polypropylene films respectively. The OTR of packaging materials was 5,000, 8,000 and $10,000cc/m^2{\cdot}day{\cdot}atm$. Quality characteristics showed significant differences during storage. The surface temperature was averaged 13 and lower in higher OTR of films. The weight loss of lettuce ranged from 2.8 to 5.4% and the highest loss showed in $5,000cc/m^2{\cdot}day{\cdot}atm$ of film. pH was increased during storage and the highest pH was found in $5,000cc/m^2{\cdot}day{\cdot}atm$. The $O_2$ content in the packaging was decreased with increasing $CO_2$ content during storage. The lowest $CO_2$ was found in $10,000cc/m^2{\cdot}day{\cdot}atm$. As OTR was decreased, antioxidant profile of lettuce was decreased. Total aerobic bacteria showed from 5.48 to 6.59 log CFU/g. From the result of the overall sensory test, the marketability of fresh-cut lettuce stored at $10^{\circ}C$ seemed to be maintained effectively over 5 days.

• Journal of the Korean Data and Information Science Society
• /
• v.22 no.4
• /
• pp.679-690
• /
• 2011

Two widely used approaches for improving the quality of the output of a process are statistical process control (SPC) and automatic process control (APC). In recent hybrid processes that combine aspects of the process and parts industries, process variations due to both the inherent wandering and special causes occur commonly, and thus simultaneous application of APC and SPC schemes is needed to effectively keep such processes close to target. The simultaneous implementation of APC and SPC schemes is called integrated process control (IPC). In the IPC procedure, the output variables are monitored during the process where adjustments are repeatedly done by its controller. For monitoring the APC-controlled process, control charts can be generally applied to the output variable. However, as an alternative, some authors suggested that monitoring the input variable may improve the chance of detection. In this paper, we evaluate the performance of several monitoring statistics, such as the output variable, the input variable, and the difference variable, for efficiently monitoring the APC-controlled process when we assume IMA(1,1) noise model with a minimum mean squared error adjustment policy.

• The Korean Journal of Applied Statistics
• /
• v.28 no.6
• /
• pp.1257-1273
• /
• 2015

The development process of Embedded Software (SW) is gathering interest due to the increased importance of SW in mobile products. According to tough competition and the growing size of the Embedded SW, there is a demand for a new effective way to improve the SW development process, based on customer and market quality aspects, rather than focusing on defect removals in individual SW modules. We review 103 SW improvement projects from the area of mobile phones in order to check the effectiveness of Six Sigma which is the standard for the process improvement statistical tools and methods.

• Journal of the Microelectronics and Packaging Society
• /
• v.28 no.4
• /
• pp.19-23
• /
• 2021

A statistical approach to inspection of the 3-D shape of micro solder balls is proposed, where an optical method with spatially arranged LED and specular reflection is used. The reflected image captured by a vision system was analyzed to calculate the relative displacements of LED's in the image. Also, the statistics of displacements for the solder balls contained in a captured image are used to detect existing defects, and the usefulness of the proposed method is shown via experiments.