• Title/Summary/Keyword: statistical quality control

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A Case Study on Quality Improvement of Employee Foodservice in Hospital, Seoul - Focused on Cost Control by the Quantity of Non-Offered Meal - (서울 지역 종합병원 직원 급식서비스의 질 향상 사례 연구 -잔식량 분석에 의한 원가 관리 중심으로 -)

  • Lee, Seung-Lim
    • The Korean Journal of Food And Nutrition
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    • v.23 no.3
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    • pp.411-418
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    • 2010
  • The objective of this study was to analyze the effects of non-offered meal on waste reduction in foodservice. To this end, the quantity of non-offered meal before and after Quality Improvement(QI) activity was analyzed, and employee satisfaction with foodservice was investigated. Statistical data analyses can be summarized as follows: The daily quantity of non-offered meal decreased significantly after QI(p<0.001)($27.80{\pm}3.14\;kg$ before QI and $7.22{\pm}4.17\;kg$ after QI). Among 7 items related to employee satisfaction, kindness of meal service staffs improved significantly after QI(p<0.05)($4.05{\pm}0.74$ before QI and $4.21{\pm}0.17$ after QI). No significant difference was found in the variety of menus, or cooking/seasoning of food, and there seemed to be greater satisfaction with taste of food after QI.

Multivariate SPC Charts for On-line Monitoring the Batch Processes (배치 공정의 온라인 모니터링을 위한 다변량 관리도)

  • Lee Bae Jin;Kang Chang Wook
    • Proceedings of the Society of Korea Industrial and System Engineering Conference
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    • 2002.05a
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    • pp.387-396
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    • 2002
  • Batch processes are a significant class of processes in the process industry and play an important role in the production of high quality speciality materials. Examples include the production of semiconductors, chemicals, pharmaceuticals, and biochemicals. With on-line sensors connected to most batch processes, massive amounts of data are being collected routinely during the batch on easily measured process variables such as temperatures, pressures, and flowrates. In this paper, multivariate SPC charts for on-line monitoring of the progress of new batches are developed which utilize the information in the on-line measurements in real-time. We propose the formation of statistical model which describes the normal operation of a batch at each time interval during the batch operation. An on-line monitoring scheme based on the proposed method can handle both cross-correlation among process variables at any one time and auto-correlation over time. And the control limits for the monitoring charts are established from sound statistical framework unlike previous researches which use the external reference distribution. The proposed charts perform real-time, on-line monitoring to ensure that the batch is progressing in a manner that will lead to a high-quality product or to detect and indicate faults that can be corrected prior to completion of the batch. This approach is capable of tracking the progress of new batch runs, identifying the time periods in which the fault occurred and detecting underlying cause.

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Price Determinant Factors of Artworks and Prediction Model Based on Machine Learning (작품 가격 추정을 위한 기계 학습 기법의 응용 및 가격 결정 요인 분석)

  • Jang, Dongryul;Park, Minjae
    • Journal of Korean Society for Quality Management
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    • v.47 no.4
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    • pp.687-700
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    • 2019
  • Purpose: The purpose of this study is to investigate the interaction effects between price determinants of artworks. We expand the methodology in art market by applying machine learning techniques to estimate the price of artworks and compare linear regression and machine learning in terms of prediction accuracy. Methods: Moderated regression analysis was performed to verify the interaction effects of artistic characteristics on price. The moderating effects were studied by confirming the significance level of the interaction terms of the derived regression equation. In order to derive price estimation model, we use multiple linear regression analysis, which is a parametric statistical technique, and k-nearest neighbor (kNN) regression, which is a nonparametric statistical technique in machine learning methods. Results: Mostly, the influences of the price determinants of art are different according to the auction types and the artist 's reputation. However, the auction type did not control the influence of the genre of the work on the price. As a result of the analysis, the kNN regression was superior to the linear regression analysis based on the prediction accuracy. Conclusion: It provides a theoretical basis for the complexity that exists between pricing determinant factors of artworks. In addition, the nonparametric models and machine learning techniques as well as existing parameter models are implemented to estimate the artworks' price.

The Method of Automathic Operation of Coagulant Dosage by the quality of water (수질에 따른 응집제 주입 자동운영 방안)

  • Jun, Uk-Pyo
    • 유체기계공업학회:학술대회논문집
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    • 2005.12a
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    • pp.278-283
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    • 2005
  • Generally Jar-Test is available to determine the coagulant dosage rate. Disadventages associated with Jar-Test are that regular samples have to be taken requiring manual intervention and the limitation to feedback control. To deal with this difficulty, determined optimized dosage rates of coagulant to investigates the union operation method of the statistical equation which uses the multi-regression method and the SCD.

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A study on the development of quality control algorithm for internet of things (IoT) urban weather observed data based on machine learning (머신러닝기반의 사물인터넷 도시기상 관측자료 품질검사 알고리즘 개발에 관한 연구)

  • Lee, Seung Woon;Jung, Seung Kwon
    • Journal of Korea Water Resources Association
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    • v.54 no.spc1
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    • pp.1071-1081
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    • 2021
  • In addition to the current quality control procedures for the weather observation performed by the Korea Meteorological Administration (KMA), this study proposes quality inspection standards for Internet of Things (IoT) urban weather observed data based on machine learning that can be used in smart cities of the future. To this end, in order to confirm whether the standards currently set based on ASOS (Automated Synoptic Observing System) and AWS (Automatic Weather System) are suitable for urban weather, usability was verified based on SKT AWS data installed in Seoul, and a machine learning-based quality control algorithm was finally proposed in consideration of the IoT's own data's features. As for the quality control algorithm, missing value test, value pattern test, sufficient data test, statistical range abnormality test, time value abnormality test, spatial value abnormality test were performed first. After that, physical limit test, stage test, climate range test, and internal consistency test, which are QC for suggested by the KMA, were performed. To verify the proposed algorithm, it was applied to the actual IoT urban weather observed data to the weather station located in Songdo, Incheon. Through this, it is possible to identify defects that IoT devices can have that could not be identified by the existing KMA's QC and a quality control algorithm for IoT weather observation devices to be installed in smart cities of future is proposed.

Comparison of monitoring the output variable and the input variable in the integrated process control (통합공정관리에서 출력변수와 입력변수를 탐지하는 절차의 비교)

  • Lee, Jae-Heon
    • Journal of the Korean Data and Information Science Society
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    • v.22 no.4
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    • pp.679-690
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    • 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.

Design of Real-Time Monitoring System for Recycling Agricultural Resourcing Based on USN

  • Ji, Geun-Seok;Min, Byoung-Won;Oh, Yong-Sun;Mishima, Nobuo
    • International Journal of Contents
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    • v.9 no.4
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    • pp.22-29
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    • 2013
  • In this paper, we propose a integrated real-time monitoring system for recycling agriculture resourcing based on USN. We design and implement the monitoring system so that we can integrate the quality control of farmyard and liquid manures, barn environment monitoring, and positioning information control into a total management system performing recycling of excrement and manure. Selection of sensors and sensor-node construction and requirements, structure of wire/wireless communication networks, and design of monitoring program are also presented. As a result of operating our system, we can get over various drawbacks of conventional separated system and promote the proper circulation of excrement up to the farmyard. We confirm that these advanced effects arise from the effective management of the total system integrating quality control of farmyard/liquid manure, barn/farmhouse information, and vehicle moving monitoring information etc. Moreover, this monitoring system is able to exchange real-time information throughout communication networks so that we can construct a convenient information environment for agricultural community by converging IT technology with farm and stockbreeding industries. Finally we present some results of processing using our monitoring system. Sensing data and their graphs are processed in real-time, positioning information on the v-world map offers various moving paths of vehicles, and statistical analysis shows all the procedure from excrement occurrence to recycling and resourcing.

An application of datamining approach to CQI using the discharge summary (퇴원요약 데이터베이스를 이용한 데이터마이닝 기법의 CQI 활동에의 황용 방안)

  • 선미옥;채영문;이해종;이선희;강성홍;호승희
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2000.11a
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    • pp.289-299
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    • 2000
  • This study provides an application of datamining approach to CQI(Continuous Quality Improvement) using the discharge summary. First, we found a process variation in hospital infection rate by SPC (Statistical Process Control) technique. Second, importance of factors influencing hospital infection was inferred through the decision tree analysis which is a classification method in data-mining approach. The most important factor was surgery followed by comorbidity and length of operation. Comorbidity was further divided into age and principal diagnosis and the length of operation was further divided into age and chief complaint. 24 rules of hospital infection were generated by the decision tree analysis. Of these, 9 rules with predictive prover greater than 50% were suggested as guidelines for hospital infection control. The optimum range of target group in hospital infection control were Identified through the information gain summary. Association rule, which is another kind of datamining method, was performed to analyze the relationship between principal diagnosis and comorbidity. The confidence score, which measures the decree of association, between urinary tract infection and causal bacillus was the highest, followed by the score between postoperative wound disruption find postoperative wound infection. This study demonstrated how datamining approach could be used to provide information to support prospective surveillance of hospital infection. The datamining technique can also be applied to various areas fur CQI using other hospital databases.

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Effects of Indirect Wastewater Reuse on Water Quality and Soil Environment in Paddy Fields (간접하수재이용에 따른 논에서의 수질 및 토양환경 영향 분석)

  • Jeong, Han Seok;Park, Ji Hoon;Seong, Choung Hyun;Jang, Tae Il;Kang, Moon Seong;Park, Seung Woo
    • Journal of The Korean Society of Agricultural Engineers
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    • v.55 no.3
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    • pp.91-104
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    • 2013
  • The objectives of this study were to monitor and assess the environmental impacts of indirect wastewater reuse on water quality and soil in paddy fields. Yongin monitoring site (YI) irrigated from agricultural reservoir and Osan monitoring site (OS) irrigated with treated wastewater diluted with stream water were selected as control and treatment, respectively. Monitoring results for irrigation water quality showed a significant statistical difference in salinity, exchangeable cation and nutrients. Pond water quality showed a similar tendency with irrigation water except for the decreased difference in nutrients due to the fertilization impact. Soil chemical properties mainly influenced by fertilization activity such as T-N, T-P, and $P_2O_5$ were changed similarly in soil profiles of both monitoring sites, while the properties, EC, Ca, Mg, and Na, mainly effected by irrigation water quality showed a considerable change with time and soil depth in treatment plots. Heavy metal contents in paddy soil of both control and treatment did not exceed the soil contamination warning standards. This study could contribute to suggest the irrigation water quality standards and proper agricultural practices including fertilization for indirect wastewater reuse, although long-term monitoring is needed to get more scientific results.

Alternation to the Randomized Block Design for Agricultural Experiments in Korea (농업실험에서 임의화블록설계에 대한 대안 - 농촌진흥청 사례들을 중심으로 -)

  • 허명회;한원식;신한풍
    • The Korean Journal of Applied Statistics
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    • v.10 no.1
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    • pp.15-27
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    • 1997
  • Randomized block design (RBD) with three replication is very frequently adopted in agricultural experiments of the Rural Development Administration of Korea. Even though it works well in field trials of traditional crops, it may not accomodate trial site conditions and/or experimental environment. In this research report, we deal with two such cases. The first case is for a crop experiment in green houses. In house conditions, RBD may not be appropriate since it cannot reflect two directions of the yield gradient. So, a Latin square design is suggested as an alternative. The second case is for local field experiments of the newly-inbred rice. RBD with three replications is used without doubt for decades, even though the site layout is not appropriately shaped for the design. In this case, we suggest the RBD in two blocks with multiple replicates for control varieties as an alternative. To improve the quality of statistical experimental designs in over one-thousand agricultural trials performed annually in the Rural Development Administration, we need to re-train agricultural researchers on the design and analysis of experiments and call for concerns of Korean statisticians.

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