LIKELIHOOD RATIO BASED MULTI-ATTRIBUTE CONTROL CHART

2005 ◽  
Vol 12 (02) ◽  
pp. 149-166 ◽  
Author(s):  
M. P. GADRE ◽  
R. N. RATTIHALLI
Keyword(s):  
Quality Control ◽  
Production Process ◽  
Likelihood Ratio ◽  
Control Chart ◽  
Joint Distribution ◽  
Multivariate Quality Control ◽  
Lr Test

In a production process, when quality of the product depends on more than one characteristic, 'Multivariate Quality Control' (MQC) techniques are efficiently used. Many MQC techniques have been developed to control the multivariate variable processes, but no much work has been reported to control the multivariate attribute processes. In this article, to detect a change in the vector of fraction non-conforming, we develop 'Likelihood Ratio based Multi-Attribute Control Chart' (LR-MACC) using the exact joint distribution and the LR-test under multinomial setup. It is verified that, in some situations, LR-MACC is superior to the MNP chart proposed by Lu et al.7 When MACC gives a signal, the attributes responsible are not readily identifiable. Therefore, a procedure to detect the responsible attributes is also developed.

A Research on Remanufacturing Products Quality Control

2011 ◽  
Vol 314-316 ◽  
pp. 2162-2167
Author(s):  
Yun Liu ◽  
Bin Shi Xu ◽  
Pei Jing Shi ◽  
Bo Hai Liu
Keyword(s):  
Quality Control ◽  
Process Control ◽  
Production Process ◽  
Control Chart ◽  
Product Certification ◽  
Low Volume ◽  
Posterior Analysis

The quality of remanufacturing products, which is always restricting the development of remanufacturing industry, is one of sixty-four-dollar questions. By detecting the cores, process control in remanufacturing production and certificating remanufacturing products, quality control of remanufacturing products is studied. Because of cores different in original states, remanufacturing is in low-volume on the whole. Based on Bayesian posterior analysis, the paper improves the control chart and uses the previous data to monitor the production process. Finally, some advances are given to remanufacturing product certification.

scholarly journals PENERAPAN IMPROVED GENERALIZED VARIANCE PADA PENGENDALIAN KUALITAS PAVING BLOCK SEGIENAM

2020 ◽  
Vol 9 (1) ◽  
pp. 87-97
Author(s):  
Nathasa Erdya Kristy ◽  
Mustafid Mustafid ◽  
Sudarno Sudarno
Keyword(s):  
Quality Control ◽  
Production Process ◽  
Control Chart ◽  
Process Capability ◽  
Quality Characteristics ◽  
Quality Characteristic ◽  
Generalized Variance ◽  
Process Capability Analysis ◽  
Capability Analysis

In quality assurance of hexagonal paving block products, quality control is needed so the products that produced are in accordance with the specified standards. Quality control carried out involves two interconnected quality characteristics, that is thickness and weight of hexagonal paving blocks, so multivariate control chart is used. Improved Generalized Variance control chart is a tool used to control process variability in multivariate manner. Variability needs to be controlled because of in a production process, sometimes there are variabilities that caused by engine problems, operator errors, and deffect in raw materials that affect the process. The purpose of this study is to apply Improved Generalized Variance control chart in controlling the quality of hexagonal paving block products and calculating the capability of production process to meet the standards. Based on the assumption of multivariate normal distribution test, it can be seen that the data of quality characteristics of hexagonal paving blocks have multivariate distribution. While based on the correlation test between variables it can be concluded that the characteristics of the quality of thickness and weight correlate with each other. The result of the control using these control chart shows that the process is statistically in control. The results of process capability analysis show that the production process has been running according to the standard because the process capability index value is generated using a weighting of 0.5 for each quality characteristic that is 1.01517. Keywords: Paving Block, Quality Control, Variability, Improved Generalized Variance, Process Capability Analysis

scholarly journals Pengendalian Mutu Pada Proses Produksi Di Tiga Usaha Kecil Menengah Tahu Kabupaten Bogor

2016 ◽  
Vol 4 (2) ◽  
pp. 112
Author(s):  
Devi Sonalia ◽  
Musa Hubeis
Keyword(s):  
Quality Control ◽  
Production Process ◽  
Control Chart ◽  
Secondary Data ◽  
Influential Factor ◽  
Analysis Tool ◽  
Pareto Chart ◽  
Cause And Effect ◽  
Cause And Effect Diagram

<p><em>Today the growth of Small and Medium Enterprises (SMEs) is increasing significantly along with the rise in competitiveness in this field. Accordingly entrepreneurs who want to get into the competition and do not want to be left behind by other SMEs in the business field have to pay attention to the quality of their product. The purpose of this study are: (1) to analyze the quality control (QC) on the production process in SMEs of Tofu (soybean cake) as Tahu  Bambu, Tahu Bandung Ashor and Tahu Bandung; (2) to  identify the factors which cause damage of Tofu as Tahu Bambu, Tahu Bandung Ashor and Tahu Bandung; (3) to identify the most influential factor affecting  the quality  of Tofu as Tahu Bambu, Tahu Bandung Ashor and Tahu Bandung; and (4) to assess the QC on the production process in the above three unit. The data used in this study were primary and secondary data. Primary data were obtained through direct observation and interviews with the SMEs, while the secondary data were taken from the internet and references such as books, journals and theses. Analysis tool used were Pareto Diagram, Cause and Effect Diagram and Control Chart. It is from Cause-Effect diagram that the factors affecting damage in three SMEs of Tahu were revealed, i.e human, raw materials, machines and tools, methods and environment with the main cause of most influence through analysis Pareto diagram is one piece. Quality control of the SMEs Tahu Bambu and SMEs Tahu Bandung  analyzed using by p Control Charts indicated that they were controlled.</em><strong><em></em></strong></p><p><em>Keywords: </em><em>Quality controls, Cause and effect diagram, Pareto chart, Control chart</em><strong></strong></p>

Statistical Management of Food Production Processes

2020 ◽  
pp. 30-35
Author(s):  
N.A. Jurk ◽  
Keyword(s):  
Production Process ◽  
Control Chart ◽  
Food Production ◽  
Time Interval ◽  
Bakery Products ◽  
Shewhart Control ◽  
Manufactured Products ◽  
Mnemonic Technique ◽  
The Stability

The article presents scientific research in the field of statistical controllability of the food production process using the example of bakery products for a certain time interval using statistical methods of quality management. During quality control of finished products, defects in bakery products were identified, while the initial data were recorded in the developed form of a checklist for registering defects. It has been established that the most common defect is packaging leakage. For the subsequent statistical assessment of the stability of the production process and further analysis of the causes of the identified defect, a Shewhart control chart (p-card by an alternative feature) was used, which allows you to control the quality of manufactured products by the number of defects detected. Analyzing the control chart, it was concluded that studied process is conditionally stable, and the emerging defects are random. At the last stage of the research, the Ishikawa causal diagram was used, developed using the 6M mnemonic technique, in order to identify the most significant causes that affect the occurrence of the considered defect in bakery products. A more detailed study will allow the enterprise to produce food products that meet the established requirements.

scholarly journals KAPABILITAS PROSES DENGAN ESTIMASI FUNGSI DENSITAS KERNEL PADA PRODUKSI DENIM DI PT APAC INTI CORPORA

2018 ◽  
Vol 7 (3) ◽  
pp. 326-336
Author(s):  
Puput Ramadhani ◽  
Dwi Ispriyanti ◽  
Diah Safitri
Keyword(s):  
Quality Control ◽  
Production Process ◽  
Density Function ◽  
Control Chart ◽  
Cross Validation ◽  
Kernel Density ◽  
Process Capability ◽  
Conformity Index ◽  
Denim Fabric ◽  
Kernel Density Function

The quality of production becomes one of the basic factors of consumer decisions in choosing a product. Quality control is needed to control the production process. Control chart is a tool used in performing statistical quality control. One of the alternatives used when the data obtained is not known distribution is analyzed by nonparametric approach based on estimation of kernel density function. The most important thing in estimating kernel density function is optimal bandwidth selection (h) which minimizes Cross Validation (CV) value. Some of the kernel functions used in this research are Rectangular, Epanechnikov, Triangular, Biweight, and Gaussian. If the process control chart is statistically controlled, a process capability analysis can be calculated using the process conformity index to determine the nature of the process capability. In this research, the kernel control chart and process conformity index were used to analyze the slope shift of Akira-F style fabric and Corvus-SI style on the production of denim fabric at PT Apac Inti Corpora. The results of the analysis show that the production process for Akira-F style is statistically controlled, but Ypk > Yp is 0.889823 > 0,508059 indicating that the process is still not in accordance with the specified limits set by the company, while for Corvus- SI is statistically controlled and Ypk < Yp is 0.637742 < 0.638776 which indicates that the process is in accordance with the specification limits specified by the company. Keywords:     kernel density function estimation, Cross Validation, kernel control chart, denim fabric, process capability

scholarly journals Quality of Water Production Process Using Mixed Multivariate EWMA-CUSUM (MEC) Control Chart

2021 ◽  
Vol 1863 (1) ◽  
pp. 012037
Author(s):  
N H D Asmara ◽  
Wibawati ◽  
M Ahsan ◽  
M Mashuri ◽  
H Khusna
Keyword(s):  
Production Process ◽  
Control Chart ◽  
Water Production ◽  
Quality Of Water

scholarly journals Quality control of aluminium melt in production process

2016 ◽  
Vol 61 (Special Issue) ◽  
pp. S43-S47 ◽  
Author(s):  
M. Kotus ◽  
E. Jankajová ◽  
M. Petrík
Keyword(s):  
Quality Control ◽  
Chemical Composition ◽  
Production Process ◽  
Aluminium Alloy ◽  
Technological Process ◽  
Casting Alloy

The quality of aluminium alloy in the production process on the chemical composition basis was evaluated. The quality of casting alloy depends on the chemical composition of melt and on the technological process of production process. The basic elements such as Si, Cu, Fe, Mg and Al in melting were evaluated. The obtained data were compared with the guide data referred to in the standard for aluminium alloy.

scholarly journals ANALISIS SISTEM PENGAWASAN KUALITAS PRODUK PADA PT INDUSTRI SANDANG NUSANTARA UNIT PATAL SECANG DI MAGELANG JAWA TENGAH

2014 ◽  
Vol 5 (2) ◽  
Author(s):  
Listiani Listiani
Keyword(s):  
Quality Control ◽  
Control System ◽  
Production Process ◽  
Raw Materials ◽  
Employee Performance ◽  
Fish Bone ◽  
Quality Control System ◽  
Observation Data ◽  
And Control

This research is aimed to determine the quality control system of production process in PT Industri Sandang Nusantara unit Patal Secang, measure the efectivity of quality control system by using control P-Chart and determine factors that cause defect product. This research is explorative descriptive by case study method. Data used in this research is the procedure of production process and the number of defect product. Product used in this company is  thread R30/1 UW and R 40/1 UW PT Industri Sandang Nusantara Unit Patal Secang in 24 periods of production between April – Mei 2006. Data is collected by interview, documentation, and observation. Data is analyzed by control p-chart and fish bone diagram. The conclusion of this research are: (1) The quality control system which is consists of controlling raw materials, production process and final product is appropriate with the company’s standard; (2) the number of defect product R 30/1 UW is 26.956 bale with the average 0.0167; Control P Chart shows that there are three periods which are out of control. They are in April 30, Mei 5 and 21, 2006. (3) The number of final product R 40/1 UW is 2159 bale with the average 0.0214; control p-chart shows that there are tw periods which are out of control. They are ini Mei 6 and Mei 12, 2006. (4) Factors that cause defect product are obsolete machines, employee performance, control system, and raw materials. Based on that condition, management should impove the controlling of machines, improve motivation and commitment of the employee, improve the method of inspection and control the quality of raw materials.

scholarly journals PENERAPAN METODE SIX SIGMA DALAM ANALISIS KUALITAS PRODUK (Studi Kasus Produk Batik Handprint Pada PT XYZ di Bali)

2017 ◽  
Vol 6 (2) ◽  
pp. 124
Author(s):  
TRI ALIT TRESNA PUTRA ◽  
I KOMANG GDE SUKARSA ◽  
I GUSTI AYU MADE SRINADI
Keyword(s):  
Quality Control ◽  
Production Process ◽  
Six Sigma ◽  
Production Quality ◽  
Improve Production ◽  
Defect Rate ◽  
Improve Production Quality

The aim of this study was to demonstrate the application of Statistics Quality Control in fierce industries. By observing Batik production process at PT XYZ as a case in this work, we applied Six Sigma Method to analyze defective product and their cause while also measure overall quality goodness. Six Sigma is a method to improve a process and reduce defects in productions into 3.4 defects per million productions. We use handprint batik productions at PT XYZ as a case in this study. The method is involving Define, Measure and Analyze (DMA) phases. By using Six Sigma, it was obtained that the quality of handprint batik are quite good with sigma of 3.105 and defect rate of 54.269 million production (DPMO). There are four defect causes of handprint batik namely: ripped fabric, shallowness, perforation, and mispattern which contribute 41,7%, 35,8%, 15%, 7,5% respectively from overall defects. The main cause of defects is the carelessness of workers in production process. Therefore we need to reduce the carelessness to  improve production quality.

Sign in / Sign up

Export Citation Format

Share Document