scholarly journals Stochastic Model For Setpoint of a Rolling Mill: An Application In The Soybean Oil Production

2021 ◽  
Author(s):  
Magna Paulina de Souza Ferreira ◽  
Márcio da Silva Arantes ◽  
Jesimar da Silva Arantes ◽  
Renan Bonnard ◽  
Claudio Fabiano Motta Toledo
Keyword(s):  
Stochastic Model ◽  
Soybean Oil ◽  
Production Process ◽  
Industrial Production ◽  
Rolling Mill ◽  
Oil Extraction ◽  
Operating Range ◽  
Production Processes ◽  
Scientific Challenge ◽  
Specific Part

Abstract A scientific challenge on industrial production is to mathematically represent a production process, and this challenge increases when describing production processes with stochastic behavior. The present paper will be approaching a specific part of the production process of soybean oil, where the main objective is to maximize the oil extraction by keeping the thicknesses of the soybean flakes within an operating range. We propose a method, based on a mathematical stochastic model, to obtain pressure setpoints that produce flakes as ideal as possible for oil extraction. The results reported are achieved by applying the proposed method in the industry with improvements within the process in terms of time and quality.

Improving Efficiency of Rolling Production by Predicting Negative Technological Events

2021 ◽  
Vol 410 ◽  
pp. 96-101
Author(s):  
Sergey M. Belskiy ◽  
Ivan I. Shopin ◽  
Andrey A. Safronov
Keyword(s):  
Statistical Analysis ◽  
Cold Rolling ◽  
Production Process ◽  
Rolling Mill ◽  
Production Efficiency ◽  
Cold Rolling Mill ◽  
Digital Service ◽  
Production Processes ◽  
Rolling Production ◽  
Basic Technology

Improving the production efficiency is the task with the increasing difficulty. Therefore, it is important to constantly expand the set of tools and perfect the methodology for improving the processes. Some of the losses associated with the negative technological events (breaks, drifting, etc.) are difficult to eliminate completely due to the complexity of making changes to the basic technology. But if you know in advance that the event will occur, you can significantly reduce the probability and consequences, thereby significantly improve the efficiency of the production process. Therefore, it is important to develop and introduce the applied approaches to forecasting the negative technological events in the production processes. This paper presents the method of the forecast-event statistical analysis of the cause-and-effect relationships. The technique was tested on the events of strip’s breakage during rolling at the cold rolling mill 1400 and strip’s drifting in the input storage of the continuous etching unit (CEU). Based on the presented methodology, the specialized digital service was developed and introduced in the production processes of the dynamo steels shop.

scholarly journals Análisis del sistema de medición en una fábrica ensambladora de electrónicos

2020 ◽  
pp. 18-26
Author(s):  
Mauricio López-Acosta ◽  
Andrea Montoya-Castro ◽  
Allán Chacara-Montes ◽  
José Manuel Velarde-Cantú
Keyword(s):  
Production Process ◽  
Measurement System ◽  
Industrial Production ◽  
Production Line ◽  
Measurement Method ◽  
Present Problem ◽  
Statistical Tools ◽  
Production Processes ◽  
Reproducibility Study ◽  
Repeatability And Reproducibility

The importance of developing statistical tools in the manufacturing labor field starts from the daily struggle of industrial production processes against variability. The analysis of the measurement system aims to assess the variability associated with the measurement method used in the production process. Considering the instrument (Gage) and the operator that performs the measurement, in order to identify if it can be considered as acceptable. The objective of the research is to evaluate the reliability of the measurement system used in the production line of electronic locks through a Gage R&R study, to reduce the number of defective parts. The production line under evaluation is dedicated to the assembly and manufacture of electronic padlocks, has three inspection stations in which a repeatability and reproducibility study is carried out to obtain as a result the percentage of accuracy associated with the performance of the machine in the measurement system and personnel. The methodology or procedure to be followed for the development of the repeatability and reproducibility study will be carried out as mentioned by Pulido (2009), in the described steps of a short and long R&R study, from which the most relevant and applicable steps were taken. according to the characteristics of the present problem. The contribution of the study is the development of an analysis of the measurement system offers the company the outline of the current situation in a quantitative and qualitative way and allows it to provide a solid basis for the recognition of improvement opportunities that can help to decrease reported defects.

Efficient and fast monitoring and disruption management for a pressure diecast system

2018 ◽  
Vol 60 (3) ◽  
pp. 165-171
Author(s):  
Yvonne Hegenbarth ◽  
Thomas Bartsch ◽  
Gerald H. Ristow
Keyword(s):  
Big Data ◽  
Production Process ◽  
Real Time ◽  
Industrial Production ◽  
Disruption Management ◽  
Funded Research ◽  
Production Processes ◽  
Data Platform ◽  
The Government ◽  
Funded Research Project

Abstract An increasing amount of information is collected in industrial production processes. In many cases, this data is only accessible to the vendor of the machines involved in the production process. In the government-funded research project BigPro, we propose a flexible and fast Big Data platform that allows detection and reaction to incidents and anomalies in the production process in near real-time.

scholarly journals The Role of Green Attributes in Production Processes as Well as Their Impact on Operational, Commercial, and Economic Benefits

2019 ◽  
Vol 11 (5) ◽  
pp. 1294 ◽  
Author(s):  
José Mendoza-Fong ◽  
Jorge García-Alcaraz ◽  
José Díaz-Reza ◽  
Emilio Jiménez-Macías ◽  
Julio Blanco-Fernández
Keyword(s):  
Production Process ◽  
Structural Equation Model ◽  
Industrial Production ◽  
Structural Equation ◽  
Economic Benefits ◽  
Equation Model ◽  
Production Processes ◽  
Before And After ◽  
Positive Effect

This paper reports a second-order structural equation model composed of four variables: the green attributes before and after an industrial production process, the operating benefits, the commercial benefits, and the economic benefits. The variables are related by means of five hypotheses and are validated statistically with information obtained from 559 responses to a questionnaire applied to the Mexican maquila industry. The model is evaluated using the technique of partial least squares and the results obtained indicate that the green attributes before and after the production process have a direct and positive effect on the obtained benefits, mostly on the operational ones. It is concluded that companies that are focused on increasing their greenness level must monitor and evaluate the existence of green attributes in their production process to guarantee benefits and make fast decisions if required due to deviations.

scholarly journals A 3D MODEL FOR FIBER LAY-DOWN IN NONWOVEN PRODUCTION PROCESSES

2012 ◽  
Vol 22 (09) ◽  
pp. 1250020 ◽  
Author(s):  
AXEL KLAR ◽  
JOHANNES MARINGER ◽  
RAIMUND WEGENER
Keyword(s):  
Differential Equations ◽  
Stochastic Model ◽  
Production Process ◽  
Stochastic Differential Equations ◽  
Surrogate Model ◽  
3D Model ◽  
Three Dimensional ◽  
Conveyor Belt ◽  
Production Processes ◽  
Nonwoven Materials

In this paper a three-dimensional stochastic model for the lay-down of fibers on a moving conveyor belt in the production process of nonwoven materials is derived. The model is based on stochastic differential equations describing the resulting position of the fiber on the belt under the influence of turbulent air flows. The model presented here is an extension of an existing surrogate model, see Refs. 6 and 3.

scholarly journals Application of the Deep CNN-Based Method in Industrial System for Wire Marking Identification

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3659
Author(s):  
Andrzej Szajna ◽  
Mariusz Kostrzewski ◽  
Krzysztof Ciebiera ◽  
Roman Stryjski ◽  
Waldemar Woźniak
Keyword(s):  
Production Process ◽  
Process Development ◽  
Process Time ◽  
Industrial System ◽  
Assembly Process ◽  
Production Environment ◽  
Deep Convolutional Neural Networks ◽  
Control Cabinet ◽  
Production Processes ◽  
The Wire

Industry 4.0, a term invented by Wolfgang Wahlster in Germany, is celebrating its 10th anniversary in 2021. Still, the digitalization of the production environment is one of the hottest topics in the computer science departments at universities and companies. Optimization of production processes or redefinition of the production concepts is meaningful in light of the current industrial and research agendas. Both the mentioned optimization and redefinition are considered in numerous subtopics and technologies. One of the most significant topics in these areas is the newest findings and applications of artificial intelligence (AI)—machine learning (ML) and deep convolutional neural networks (DCNNs). The authors invented a method and device that supports the wiring assembly in the control cabinet production process, namely, the Wire Label Reader (WLR) industrial system. The implementation of this device was a big technical challenge. It required very advanced IT technologies, ML, image recognition, and DCNN as well. This paper focuses on an in-depth description of the underlying methodology of this device, its construction, and foremostly, the assembly industrial processes, through which this device is implemented. It was significant for the authors to validate the usability of the device within mentioned production processes and to express both advantages and challenges connected to such assembly process development. The authors noted that in-depth studies connected to the effects of AI applications in the presented area are sparse. Further, the idea of the WLR device is presented while also including results of DCNN training (with recognition results of 99.7% although challenging conditions), the device implementation in the wire assembly production process, and its users’ opinions. The authors have analyzed how the WLR affects assembly process time and energy consumption, and accordingly, the advantages and challenges of the device. Among the most impressive results of the WLR implementation in the assembly process one can be mentioned—the device ensures significant process time reduction regardless of the number of characters printed on a wire.

Microworld Development

2008 ◽  
Vol 40 (1) ◽  
pp. 84-97 ◽  
Author(s):  
Mathias M. Fischer ◽  
Federico Barnabè
Keyword(s):  
Production Process ◽  
Model Building ◽  
Calcium Carbide ◽  
Group Model ◽  
Interactive Learning Environment ◽  
Industrial Firms ◽  
Chemical Company ◽  
Production Processes ◽  
Computer Based ◽  
Building Project

The article presents the outcomes of a group model-building project at a chemical company that produces calcium carbide. The project led not only to the creation of a system dynamics model describing the production process but also to a microworld, a computer-based interactive learning environment meant to reproduce most of the features of the operating and controlling software actually used in the company. The process of organizational learning, the gaining of a better common understanding of the production process, and the development of the different mental models of the plant operators were some of the project's main goals. Moreover, the method followed during the project can be considered as general and can be used mainly in a variety of production processes in most manufacturing industrial firms both for the modeling of production processes and for teaching and training the operators who manage such systems.

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