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.

Design multivariate statistical process control procedure in the case of Ethio cement

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Daniel Ashagrie Tegegne ◽  
Daniel Kitaw Azene ◽  
Eshetie Berhan Atanaw
Keyword(s):  
Neural Network ◽  
Production Process ◽  
Control Chart ◽  
Cement Industry ◽  
Time Interval ◽  
Control Procedure ◽  
Sufficient Information ◽  
Content Type ◽  
Multivariate Control Chart ◽  
Multivariate Control

PurposeThis study aims to design a multivariate control chart that improves the applicability of the traditional Hotelling T2 chart. This new type of multivariate control chart displays sufficient information about the states and relationships of the variables in the production process. It is used to make better quality control decisions during the production process.Design/methodology/approachMultivariate data are collected at an equal time interval and are represented by nodes of the graph. The edges connecting the nodes represent the sequence of operation. Each node is plotted on the control chart based on their Hotelling T2 statistical distance. The changing behavior of each pair of input and output nodes is studied by the neural network. A case study from the cement industry is conducted to validate the control chart.FindingsThe finding of this paper is that the points and lines in the classic Hotelling T2 chart are effectively substituted by nodes and edges of the graph respectively. Nodes and edges have dimension and color and represent several attributes. As a result, this control chart displays much more information than the traditional Hotelling T2 control chart. The pattern of the plot represents whether the process is normal or not. The effect of the sequence of operation is visible in the control chart. The frequency of the happening of nodes is recognized by the size of nodes. The decision to change the product feature is assisted by finding the shortest path between nodes. Moreover, consecutive nodes have different behaviors, and that behavior change is recognized by neural network.Originality/valueModifying the classical Hotelling T2 control chart by integrating with the concept of graph theory and neural network is new of its kind.

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

Improving Benchmarking Student Learning Outcomes Using Repetitive Sampling Control Chart

2016 ◽  
Vol 13 (10) ◽  
pp. 7036-7039
Author(s):  
Nawal G Alghamdi ◽  
Muhammad Aslam
Keyword(s):  
Control Chart ◽  
Control Charts ◽  
Assessment Tool ◽  
Educational Programs ◽  
Management Program ◽  
Pass Rate ◽  
Shewhart Control Charts ◽  
Process Understanding ◽  
Shewhart Control

In recent years research on the application of Shewhart control charts in evaluating the performance of educational programs have gain sufficient grounds. These control charts aid in process understanding and identify changes that indicate either improvement or deterioration in quality of the program. Current research proposes control charts using repetitive sampling on the data taken from Weber State University’s construction management program, which uses the Associate Constructor Level 1 exam as an assessment tool. A code was developed to run the proposed control charts. Both the traditional and proposed charts were plotted using R software. The results indicate that the proposed control charts are comparatively more efficient than the traditional control charts in assessment of educational programs and minimizing false positives. At the end comparison of the benchmark—pass rate and traditional control chart with the proposed control chart has also been elucidated so that the proposed control charts may be readily employed in evaluating any educational program by academic counsellors.

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 Monitoring the quality of production process using CUSUM control chart

Skola biznisa ◽  
2016 ◽  
pp. 127-139
Author(s):  
Nataša Papić-Blagojević ◽  
Zbigniew Paszek ◽  
Sanja Lončar
Keyword(s):  
Production Process ◽  
Control Chart ◽  
Cusum Control Chart

scholarly journals Statitstical Analysis of Correctness of Seaming Canned Food in Food Production with the Use of Standard Control Chart

2019 ◽  
Vol 23 (4) ◽  
pp. 31-39
Author(s):  
Michał Michałowski ◽  
Sylwia Mierzejewska ◽  
Krzysztof Kukiełka ◽  
Aldona Bać ◽  
Joanna Piepiórka-Stepuk
Keyword(s):  
Statistical Analysis ◽  
Control Chart ◽  
Control Charts ◽  
Food Production ◽  
Canned Food ◽  
Canned Fish ◽  
The Stability ◽  
Made In

AbstractThe paper presents a study on the control of the canned fish seaming with the so-called double seam and statistical analysis of correctness of seaming. The use of standard control charts enabled observation and intervention in case irrelevant parameters occur to keep the stability of the process. Based on the analysis made in Statistica program, a moment could have been captured when a machine had to be regulated in case the value of parameters of the double seam decreased and it had to be concluded unanimously when the most important seaming tools (rolls) should be replaced. A problem that had been solved consists mainly in ensuring the stability of the process during constant monitoring of the seaming process of the canned food.

scholarly journals The Quality Management of the Products Produced by the Enterprises for the Production of Metal Structures

2021 ◽  
Vol 12 (4) ◽  
Author(s):  
Nikolay Anikienko ◽  
Inna Savchenko
Keyword(s):  
Quality Management ◽  
Management System ◽  
Quality Management System ◽  
Metal Structures ◽  
Technical Control ◽  
Manufactured Products ◽  
Mnemonic Technique ◽  
Control Department ◽  
Quality Of Products

Currently, it is necessary to build a product quality management system that ensures the smooth operation of the organization, the competitiveness of products, the development and maintenance of the organization's quality goals. The article discusses the theoretical foundations of quality management of manufactured products at the enterprise. The necessity of quality management of the enterprise's products as the basis of the competitiveness of the enterprise is substantiated. The concept of quality management is considered. The stages of development of the quality management system are given. The threats of defective goods and their impact on the economic condition of the enterprise are considered. At the research stage, the Ishikawa causal diagram was used, developed using the 6M mnemonic technique. The quality control system of metal structures is analyzed. Losses from defects in the manufacture of metal structures were revealed. A Pareto diagram of the defected goods distribution is constructed, the data of which indicate that more than 55 % of the defects is caused by locksmiths, 17 % — undercuts, 13 % — displacement of holes and other reasons. The main reason was the insufficient level of qualification of locksmiths. In order to improve the quality of products, measures have been proposed concerning the retraining of workers, updating equipment. It is recommended at operational meetings to develop preventive and corrective measures to reduce defects, reduce the workload of engineers of the technical control department. The suggested measures will reduce the number of defective products, increase the competitiveness of the company's products.

scholarly journals Fusarium Mycotoxins Stability during the Malting and Brewing Processes

Toxins ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 257 ◽  
Author(s):  
Karim C. Piacentini ◽  
Sylvie Běláková ◽  
Karolína Benešová ◽  
Marek Pernica ◽  
Geovana D. Savi ◽  
...  
Keyword(s):  
Dietary Intake ◽  
Production Process ◽  
Decisive Role ◽  
Raw Material ◽  
Research Groups ◽  
Fusarium Mycotoxins ◽  
Spent Grains ◽  
The Creation ◽  
The Stability

Mycotoxins are widely studied by many research groups in all aspects, but the stability of these compounds needs further research for clarification. The objective of this study is to evaluate deoxynivalenol and zearalenone stability during all steps of the malting and brewing processes. The levels of these compounds decreased significantly during the production process (barley to beer). During the malting process, the DON levels decreased significantly in the steeping, germination, and malting steps (62%, 51.5%, and 68%, respectively). Considering ZEN, when the levels were compared between barley and the last step of the process, a significant decrease was observed. Most of the mycotoxins produced were transferred to the rootlets and spent grains, which is advantageous considering the final product. Furthermore, the mycotoxin dietary intake estimation was included in this study. The results proved that if the concentrations of target mycotoxins in raw material are under the limits established by the regulations, the levels decrease during the malting and brewing processes and make the beer secure for consumers. The quality of the five commodities involved in the beer process plays a decisive role in the creation of a safe final product.

Decision Rules and Risk Analysis

2014 ◽  
Vol 625 ◽  
pp. 26-33 ◽  
Author(s):  
Michael Krystek
Keyword(s):  
Measurement Uncertainty ◽  
Decision Rules ◽  
Uncertainty Budget ◽  
Economic Consequences ◽  
Manufactured Products ◽  
Acceptance Limits ◽  
The Stability ◽  
The Relationship ◽  
Product Specification

Measurement uncertainty has important economic consequences for calibration and inspection activities and is often taken as an indication of the quality of a test laboratory. Smaller uncertainty values are generally of higher value. In industry decision rules employed in accepting and rejecting products are based on the measurement uncertainty budget of the related characteristics of the products. Conformity assessment based on the product specification and the measurement evaluation is an important part of the industrial quality assurance of manufactured products and for the stability of production processes. The aim of this paper is to describe the relationship between the conformance zone and the acceptance zone and to address the problem of determining acceptance limits that define the boundaries of the acceptance zone.

scholarly journals DIAGRAM KONTROL MULTIVARIAT np DAN DIAGRAM KONTROL JARAK CHI-SQUARE DALAM PENGENDALIAN KUALITAS PRODUK KAIN DENIM (Studi Kasus di PT Apac Inti Corpora)

2018 ◽  
Vol 7 (4) ◽  
pp. 385-396
Author(s):  
Dwi Harti Pujiana ◽  
Mustafid Mustafid ◽  
Di Asih I Maruddani
Keyword(s):  
Production Process ◽  
Control Chart ◽  
Control Charts ◽  
Process Capability ◽  
Chi Square ◽  
Multivariate Control Charts ◽  
Distance Control ◽  
Denim Fabric ◽  
Multivariate Control

Denim fabric sort number 78032 is one type of fabric in the last 4 years almost every month produced by PT Apac Inti Corpora. In the continuity of denim fabric production process, there are data defects (non-conformity) that causes the quality of denim fabric decreases. To maintain the consistency of the quality of products produced in accordance with the specified specifications, it is necessary to control the quality of the production process that has been running for this. Multivariate control charts attributes used are multivariate control charts np using the number of samples and the proportion of disability data with correlation between variables while the chi-square distance control charts use squared distances with uncorrelated data between variables. The results showed that in the multivariate control chart np there were 2 out-of-control observations in the phase II data using control limits from phase I data already controlled by the value of BKA of 636321.4. While in the chi-square distance control chart showed all observations are in in-control condition with BKA value of 0.06536. Controlled production process obtained multivariate process capability value  for multivariate control np diagram of 0.625142 <1 which means the process is not capable, while the value of process capability in the chi-square distance control chart is 1.1329> 1 which means the process is capable. Keywords: denim fabric, multivariate np control chart, chi-square distance control chart, multivariate process capability

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