Graduation Intelligent Manufacturing System (GiMS): an Industry 4.0 paradigm for production and operations management

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Daqiang Guo ◽  
Mingxing Li ◽  
Ray Zhong ◽  
G.Q. Huang
Keyword(s):  
Real Time ◽  
Production Planning ◽  
Operations Management ◽  
Industry 4.0 ◽  
Production Management ◽  
Manufacturing System ◽  
Intelligent Manufacturing ◽  
Content Type ◽  
Intelligent Manufacturing System ◽  
And Control

PurposeThe purpose of this paper is to develop an intelligent manufacturing system for transforming production management and operations to an Industry 4.0 manufacturing paradigm.Design/methodology/approachA manufacturing mode-Graduation Manufacturing System is designed for organizing and controlling production operations. An Industrial Internet of Things (IIoT) and digital twin-enabled Graduation Intelligent Manufacturing System (GiMS) with real-time task allocation and execution mechanisms is proposed to achieve real-time information sharing and production planning, scheduling, execution and control with reduced complexity and uncertainty.FindingsThe implementation of GiMS in an industrial company illustrates the potential advantages for real-time production planning, scheduling, execution and control with reduced complexity and uncertainty. For production managers and onsite operators, effective tools, such as cloud services integrates effective production and operations management strategies are needed to facilitate their decision-making and daily operations at the operational level.Originality/valueThis paper presents an Industry 4.0 paradigm-GiMS, which aims to explore Industry 4.0 technologies opportunities on operations and production management, especially on production planning, scheduling, execution and control.

Augmented Technology for Safety and Maintenance in Industry 4.0

2021 ◽  
pp. 495-502
Author(s):  
Vikas Kukshal ◽  
Amar Patnaik ◽  
Sarbjeet Singh
Keyword(s):  
Industry 4.0 ◽  
Manufacturing System ◽  
Industrial Revolution ◽  
Intelligent Manufacturing ◽  
Skilled Workers ◽  
New Era ◽  
Intelligent Manufacturing System ◽  
Traditional Manufacturing ◽  
Area Of Concern ◽  
Rapid Transformation

The traditional manufacturing system is going through a rapid transformation and has brought a revolution in the industries. Industry 4.0 is considered to be a new era of the industrial revolution in which all the processes are integrated with a product to achieve higher efficiency. Digitization and automation have changed the nature of work resulting in an intelligent manufacturing system. The benefits of Industry 4.0 include higher productivity and increased flexibility. However, the implementation of the new processes and methods comes along with a lot of challenges. Industry 4.0. requires more skilled workers to handle the operations of the digitalized manufacturing system. The fourth industrial revolution or Industry 4.0 has become the absolute reality and will undoubtedly have an impact on safety and maintenance. Hence, to tackle the issues arising due to digitization is an area of concern and has to be dealt with using the innovative technologies in the manufacturing industries.

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.

Augmented Technology for Safety and Maintenance in Industry 4.0

2020 ◽  
pp. 134-141
Author(s):  
Vikas Kukshal ◽  
Amar Patnaik ◽  
Sarbjeet Singh
Keyword(s):  
Industry 4.0 ◽  
Manufacturing System ◽  
Industrial Revolution ◽  
Intelligent Manufacturing ◽  
Skilled Workers ◽  
New Era ◽  
Intelligent Manufacturing System ◽  
Traditional Manufacturing ◽  
Area Of Concern ◽  
Rapid Transformation

The traditional manufacturing system is going through a rapid transformation and has brought a revolution in the industries. Industry 4.0 is considered to be a new era of the industrial revolution in which all the processes are integrated with a product to achieve higher efficiency. Digitization and automation have changed the nature of work resulting in an intelligent manufacturing system. The benefits of Industry 4.0 include higher productivity and increased flexibility. However, the implementation of the new processes and methods comes along with a lot of challenges. Industry 4.0. requires more skilled workers to handle the operations of the digitalized manufacturing system. The fourth industrial revolution or Industry 4.0 has become the absolute reality and will undoubtedly have an impact on safety and maintenance. Hence, to tackle the issues arising due to digitization is an area of concern and has to be dealt with using the innovative technologies in the manufacturing industries.

scholarly journals A Construction Method of Intelligent Manufacturing System under Industry 4.0 Model

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yue Xiao ◽  
Zhiqing Zeng
Keyword(s):  
Neural Network ◽  
Industrial Production ◽  
Industry 4.0 ◽  
Manufacturing System ◽  
Intelligent Manufacturing ◽  
Parameter Measurement ◽  
Current Status ◽  
Smart Manufacturing ◽  
Intelligent Manufacturing System ◽  
Algorithm Comparison

Starting from the current problems facing Industry 4.0, this article analyzes the changes in the macro and industrial environment that Industry 4.0 faces and explains the problems, opportunities, and strategies for the manufacturing industry in the external environment. First, the reference system of the intelligent manufacturing system, the current status, and the existing problems of industrial production management are analyzed through the investigation of the status quo of industrial production and management. This puts forward the detailed requirements of the industrial intelligent manufacturing system in the data acquisition layer, data storage layer, and analysis and decision support layer and then designs the hierarchical structure of the industrial intelligent manufacturing system. Subsequently, it adopts design methods and lists product manufacturing costs, pointing out that Industry 4.0 requires industrial transformation, and finally proposes the strategic direction of smart manufacturing in combination with the Industry 4.0 network strategy. At the same time, in view of the problems of long parameter measurement time and untimely system feedback in the existing koji-making process, an online parameter measurement method based on network optimization is proposed. On the basis of the neural network, an industrial neural network with double hidden layers and self-feedback of the output layer is proposed. Through algorithm comparison experiments, the proposed parameter prediction model based on industrial neural network has better prediction results and higher accuracy. Finally, a comparison of cost, quality, delivery time, etc., before and after the implementation of Industry 4.0 intelligent manufacturing is carried out. An intelligent solution is proposed, the implementation goal is formulated, and the implementation is gradually implemented in stages, and finally an intelligent upgrade and transformation are realized. It is shown in many aspects that intelligent manufacturing provides a powerful means for enterprises to achieve agility, virtualization, lean, integration, and collaboration, and it can bring efficiency, reliability, and safety to the manufacturing process of enterprises.

An EDM Multi-Agent Collaborative Manufacturing System Based on Petri Net

2012 ◽  
Vol 457-458 ◽  
pp. 921-926
Author(s):  
Jin Zhi Zhao ◽  
Yuan Tao Liu ◽  
Hui Ying Zhao
Keyword(s):  
Petri Net ◽  
Manufacturing System ◽  
Intelligent Manufacturing ◽  
Agent Technology ◽  
Manufacturing Processes ◽  
Intelligent Manufacturing System ◽  
Collaborative Manufacturing ◽  
Model Based ◽  
Support Organizations ◽  
Multi Agent

A framework for building EDM collaborative manufacturing system using multi-agent technology to support organizations characterized by physically distributed, enterprise-wide, heterogeneous intelligent manufacturing system over Internet is proposed. According to the characteristics of agile EDM collaborative manufacturing system(AEDMCMS), the agent technology is combined with Petri net in order to analyze the model. Based on the basic Petri Net, the definition is extended and the Agent-oriented Petri net (APN) is proposed. AEDMCM is turned into the model of Petri Net which is suitable to the analysis and optimization of manufacturing processes.

Die synchrone Produktion*/Synchronous manufacturing - An approach for semi-autonomous production planning and control and human-based decision support

2015 ◽  
Vol 105 (04) ◽  
pp. 204-208
Author(s):  
D. Kreimeier ◽  
E. Müller ◽  
F. Morlock ◽  
D. Jentsch ◽  
H. Unger ◽  
...  
Keyword(s):  
Decision Support ◽  
Real Time ◽  
Production Planning ◽  
Data Exchange ◽  
Production Control ◽  
Production Planning And Control ◽  
Planning And Control ◽  
Manufacturing Execution Systems ◽  
And Control ◽  
Manufacturing Execution

Kurzfristige sowie ungeplante Änderungen – wie Auftragsschwankungen, Maschinenausfälle oder Krankheitstage der Mitarbeiter – beeinflussen die Produktionsplanung und -steuerung (PPS) von Industriefirmen. Trends wie Globalisierung und erhöhter Marktdruck verstärken diese Probleme. Zur Komplexitätsbewältigung bei der Entscheidungsfindung zur Fertigungssteuerung kommen in der Produktion Werkzeuge der „Digitalen Fabrik“, beispielsweise Simulationsprogramme, oder IT (Informationstechnologie)-Lösungen, wie Manufacturing Execution Systems (MES), zum Einsatz. Eine Verknüpfung dieser Bereiche würde einen echtzeitfähigen Datenaustausch erlauben, der wiederum eine echtzeitfähige Entscheidungsunterstützung bietet. Der Fachbeitrag stellt hierfür einen Lösungsansatz vor.   Sudden and unsystematic changes, such as fluctuations in order flow, machine failures, or employee sick days affect the Production Planning and Control (PPC) activities of industrial companies. Trends like globalization and increased market pressure intensify these problems. To master the complexity of decision-making in production control, tools of the digital factory (e.g. simulation systems) or IT systems (e.g. Manufacturing Execution Systems (MES)) are applied in manufacturing. Combining these areas would enable real-time capable data exchange which, in turn, provides real-time capable decision support. This article presents an approach for solving this problem.

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