scholarly journals Sensors and Process Control in Copper Smelters: A Review of Current Systems and Some Opportunities

Minerals ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 1
Author(s):  
Luis Arias ◽  
Eduardo Balladares ◽  
Roberto Parra ◽  
Daniel Sbarbaro ◽  
Sergio Torres
Keyword(s):  
Process Control ◽  
Primary Production ◽  
Hyperspectral Imaging ◽  
Industry 4.0 ◽  
Production Control ◽  
Iron Sulfides ◽  
Advanced Level ◽  
Entire Process ◽  
Current Systems ◽  
Equivalent Conditions

Despite the widespread and extended use of sensor systems in different industries, there is an important gap to reach equivalent conditions in pyrometallurgical processes for primary production. In the specific case of copper pyrometallurgy, the situation is particularly challenging to incorporate the Industry 4.0 concept for the optimization of their operations. Currently, only two instruments can be identified at the commercial level: the Noranda pyrometer and the Online Production Control (OPC) system. The iron-making and steelmaking industries, however, present an advanced level of control based on monitoring and sensing networks throughout the entire process. This reality has served as a basis for developing a series of solutions based on radiometric sensors for copper pyrometallurgy. We present two types of sensing concept. The first one is applied to smelting and converting reactors based on the measurements of the radiation of the oxidation of different copper and iron sulfides. The second one considers hyperspectral imaging of molten phases flow during operations. The idea of this proposal is to transfer some commercial sensing technologies already in use in the steelmaking industry. In this article, the fundamentals of the sensor design, proofs of concept, and the initial industrial validations are reviewed. Finally, a discussion on the contribution of this knowledge and development opportunities within the framework of Industry 4.0 are addressed.

scholarly journals Multi-Layer Quality Inspection System Framework for Industry 4.0

2021 ◽  
Vol 15 (5) ◽  
pp. 641-650
Author(s):  
Victor Azamfirei ◽  
◽  
Anna Granlund ◽  
Yvonne Lagrosen
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Industry ◽  
Production Control ◽  
Measurement Instrument ◽  
Future Research ◽  
Inspection System ◽  
Work Piece ◽  
Quality Inspection ◽  
Industrial Case Study ◽  
Key Factor

In the era of market globalisation, the quality of products has become a key factor for success in the manufacturing industry. The growing demand for customised products requires a corresponding adjustment of processes, leading to frequent and necessary changes in production control. Quality inspection has been historically used by the manufacturing industry to detect defects before customer delivery of the end product. However, traditional quality methods, such as quality inspection, suffer from large limitations in highly customised small batch production. Frameworks for quality inspection have been proposed in the current literature. Nevertheless, full exploitation of the Industry 4.0 context for quality inspection purpose remains an open field. Vice-versa, for quality inspection to be suitable for Industry 4.0, it needs to become fast, accurate, reliable, flexible, and holistic. This paper addresses these challenges by developing a multi-layer quality inspection framework built on previous research on quality inspection in the realm of Industry 4.0. In the proposed framework, the quality inspection system consists of (a) the work-piece to be inspected, (b) the measurement instrument, (c) the actuator that manipulates the measurement instrument and possibly the work-piece, (d) an intelligent control system, and (e) a cloud-connected database to the previous resources; that interact with each other in five different layers, i.e., resources, actions, and data in both the cyber and physical world. The framework is built on the assumption that data (used and collected) need to be validated, holistic and on-line, i.e., when needed, for the system to effectively decide upon conformity to surpass the presented challenges. Future research will focus on implementing and validating the proposed framework in an industrial case study.

scholarly journals Simulation von Cyber-Physischen Produktionssystemen in einer Forschungsinfrastruktur

2020 ◽  
Author(s):  
Iris Gräßler
Keyword(s):  
Communication Technology ◽  
Information Acquisition ◽  
Industry 4.0 ◽  
Production Control ◽  
Production Systems ◽  
General Concept ◽  
Radio Network ◽  
Systems Research ◽  
Digital Twins ◽  
Cyber Physical Production Systems

The article describes the setup of an experimentation and validation environment by extending a production laboratory: All relevant elements of the production laboratory were equipped with computer systems, so-called "industry 4.0 boxes", and interconnected via a peer-to-peer radio network. The "industry 4.0 boxes" are used to upgrade dedicated sensors for recording machine behaviour and communication technology to be integrated into decentralized production control. In addition, digital twins were implemented to map machine and user behaviour, enable control and support information acquisition and processing. Thereby, a research infrastructure is created for research on potentials of cyber-physical production systems. Research outcomes will be used as a decision basis for companies and for validation of production optimizations. This paper describes the concept and implementation of industry 4.0 functionalities and derives a general concept of simulation platforms for CPPS.

scholarly journals INFORMATION SYSTEM AND PRODUCTION PROCESS CONTROL

2019 ◽  
Author(s):  
Angelo Zanella ◽  
Egidio Cascini
Keyword(s):  
Information System ◽  
Quality Control ◽  
Process Control ◽  
Production Control ◽  
Reference Conditions ◽  
Specific Reference ◽  
Theoretic Model ◽  
Perishable Goods ◽  
Control Production ◽  
Accounting Control

We start with the definition of experimental data. First place we consider the controllable variables, whose levels are established by technical production experts with regard to a theoretic “model” defining the production components, their connections and working rules in sight of the envisaged achievements. Then, the responses or results of production activities, which typically show random variability. The controllable variables are used to regulate the means of their distributions and aspects of variability (Taguchi approach). An information system represents a data collection, which is directed to specific purposes like: financial control, accounting control, personnel control, business control, production control, framed around production programs, control of production lines and related maintenance, quality control, framed around control of nonconformities regarding some specification limits and ensuring product good quality over time. Qualitative guidelines for choosing the data for a quality control information system are that it must be as near as possible to a sufficient system which means that it is capable of explaining any nonconformity in a product characteristic, as well as being complete, that is, such that it is also capable of suggesting how to remove them. In a natural way quality control implies a dynamic approach based on a systematic improvement of production activities, starting from specific reference conditions. We consider two examples appropriated to explain the fundamentals of a methodology useful to cope with this complex subject. The first example refers to a real industrial application regarding the process control of polyvinyl chloride production, found in literature [9]. The second example concerns the distribution process of perishable goods, which is considered to be an innovation. In this case we suppose that there is a finite set of operating situations (points of sale) and that we can define an indicator Q=Q1 /c = Quality of a reference product/a corresponding economic quantity (cost or earning). In the case considered, by means of the ordering of the ratios total cost/total earning, we come to the most profitable situation.

scholarly journals Industry 4.0 and basic principles of a new architecture for control of power plants processes

2018 ◽  
Vol 44 ◽  
pp. 00008
Author(s):  
Nikolay Amosov ◽  
Alexander Andryushin ◽  
Edik Arakelyan ◽  
Anatoliy Kosoy
Keyword(s):  
Process Control ◽  
Industry 4.0 ◽  
Power Plants ◽  
Thermal Power ◽  
Economic Effect ◽  
Basic Principles ◽  
Level Of Automation ◽  
Software And Hardware ◽  
Plant Level ◽  
Level Analysis

The results of the level analysis of intellectuality and efficiency of up-to-date automated process control systems (APCS) based on software and hardware systems (SHS) are presented. It was demonstrated that, despite the widespread implementation of modern software and hardware systems during the construction of new APCS and upgrading the existing ones for thermal power plants (TPP), improvement of the process control quality, optimization of their modes and parameters take place generally at the equipment and power unit level and to a far lesser extent – at the power plant level and as a result – insufficient level of automation and low technical and economic efficiency. Another conclusion from the performed analysis – when implementing control algorithms in the APCS based on the up-to-date SHS, their wide data and software capabilities are not fully used. The main ways of further APCS improvement for the purpose of further increasing of their efficiency and the level of intelligence of SHS based APCS of power plants are presented. The possibility of their implementation is considered with application of the basic principles laid in the concept Industry 4.0. The possible economic effect from the implementation of the proposed solutions for increasing the intelligence and efficiency of the SHS based APCS was assessed. A brief description of the configuration of the proposed SHS based control system is given.

A semi-heterarchical production control architecture for industry 4.0-based manufacturing systems

2020 ◽  
Vol 24 ◽  
pp. 43-46 ◽  
Author(s):  
Andrea Grassi ◽  
Guido Guizzi ◽  
Liberatina Carmela Santillo ◽  
Silvestro Vespoli
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Production Control ◽  
Control Architecture

scholarly journals The concept of operation and production control

2021 ◽  
Vol 27 (2) ◽  
pp. 100-107
Author(s):  
Radosław Wolniak
Keyword(s):  
Artificial Intelligence ◽  
Production Planning ◽  
Industry 4.0 ◽  
Production Management ◽  
Production Control ◽  
Main Function ◽  
Production Planning And Control ◽  
Factors Affecting ◽  
Planning And Control ◽  
And Control

Abstract The theoretical aim of the paper is to analyses the main function and concept of production control in operation management. The empirical aim of the paper is to investigate polish production firm opinion about factors affecting production planning and control and also functions of production planning and control. Production control is very important in every factory, and every aspect of operation and production management especially in times of Industry 4.0 conditions. In the paper we presented all classical seven task of production management control. Also there is in the paper an analysis of main factors affecting production control in industrial organization. In the paper we analysed the problems connected with production control. Nowadays in the conditions of Industry 4.0 this is very important concept because the increasing level of digitalization of all industrial processes leads to possibility of detailed analysis of all processes and better level of control. Operation managers should have good level of knowledge about production control and especially quality control. They can use in this many new information tools like statistical methods and artificial intelligence. Especially we think that in the future many function of production control would be assisted by artificial intelligence. We also in the paper give results of research conducted on example of 30 polish production organizations located in Silesia region.

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