scholarly journals Industry 4.0: «Digital Counterpart» as means for effectiveness increase of production system

2019 ◽  
Vol 2018 (2) ◽  
pp. 42-48 ◽  
Author(s):  
Евгений Фролов ◽  
Evgeniy Frolov ◽  
Ирина Паршина ◽  
Irina Parshina ◽  
Александр Зайцев ◽  
...  
Keyword(s):  
Real Time ◽  
Production System ◽  
Industry 4.0 ◽  
External Environment ◽  
Digital Production ◽  
Manufacturing Procedure ◽  
Product Manufacturing ◽  
Production Organization ◽  
Digital Enterprise ◽  
And Control

A digital enterprise is a part of the (Industry 4.0) Concept which allows considering the production organization and control of product manufacturing procedure at a new level during the whole product life. It is a completely automated digital production which is controlled in real-time by intelligence systems in constant interaction with external environment.

Additive and hybrid technologies for products manufacturing using powders of metals, their alloys and ceramics

2020 ◽  
Vol 2 (102) ◽  
pp. 59-85
Author(s):  
L.A. Dobrzański ◽  
L.B. Dobrzański ◽  
A.D. Dobrzańska-Danikiewicz
Keyword(s):  
Industry 4.0 ◽  
Design Methodology ◽  
Knowledge Engineering ◽  
Extensive Literature ◽  
Processing Technologies ◽  
Methods Development ◽  
Digital Production ◽  
Product Manufacturing ◽  
Hybrid Technologies ◽  
Manufacturing Technologies

Purpose: The paper is a comprehensive review of the literature on additive and hybrid technologies for products manufacturing using powders of metals, their alloys and ceramics. Design/methodology/approach: Extensive literature studies on conventional powder engineering technologies have been carried out. By using knowledge engineering methods, development perspectives of individual technologies were indicated. Findings: The additive and hybrid technologies for products manufacturing using powders of metals, their alloys and ceramics as the advanced digital production (ADP) technologies are located in the two-quarters of the dendrological matrix of technologies "wide-stretching oak" and "rooted dwarf mountain pine" respectively. It proves their highest possible potential and attractiveness, as well as their fully exploited attractiveness or substantial development opportunities in this respect. Originality/value: According to augmented holistic Industry 4.0 model, many materials processing technologies and among them additive and hybrid technologies for products manufacturing using powders of metals, their alloys and ceramics are becoming very important among product manufacturing technologies. They are an essential part not only of powder engineering but also of the manufacturing development according to the concept of Industry 4.0.

scholarly journals Smart search for optimal technological processes in cyber-physical systems

2018 ◽  
Vol 224 ◽  
pp. 02110
Author(s):  
Vasiliy Golovin
Keyword(s):  
Technological Process ◽  
Production System ◽  
Physical System ◽  
Industry 4.0 ◽  
Cyber Physical Systems ◽  
Additive Technologies ◽  
Cyber Physical System ◽  
Physical Systems ◽  
Technological Processes ◽  
Digital Production

Digital production dictates new approaches to the organization of technological processes, including the development of cyber-physical systems within the framework of Industry 4.0. The development of these systems involves the use of not only classical methods, but also additive technologies in production. The article deals with the concept of a smart production system to find the optimal technological process, which is based on the user defined constraints and expert data of the cloud cyber-physical system.

Impact of Industry 4.0 Concept on the Levers of Lean Manufacturing Approach in Manufacturing Industries

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
M Ghouat ◽  
A. Haddout ◽  
M. Benhadou
Keyword(s):  
Real Time ◽  
Production System ◽  
Lean Manufacturing ◽  
Industry 4.0 ◽  
Production Costs ◽  
Production Performance ◽  
Time Data ◽  
Industrial Companies ◽  
Real Time Analysis ◽  
Real Time Data

Industrial companies looking for permanent performance are facing challenges of reducing production costs, reducing customer delivery delays and improving their quality products, this lead them to improve their responsiveness and flexibility to meet the varying needs of customers. To cope with these constraints, several industrial companies have adopted the Lean Manufacturing (LM)  concept, based on the Toyota production system, to reduce wastage according to a methodical and structured approach that has given this proof for several years, this approach currently finds its limits, since it is based on static data, while a dynamic approach, with real-time data on customer needs and production performance, will readjust the levers of Lean Manufacturing to improve its efficiency. This paper has been aimed to show that the concept Industry 4.0 incarnates the lean Manufacturing approach by feeding it by real-time data and a real-time analysis of Big Data in a Cyber Physical Production System (CPPS), in order to improve decision-making and readjust in real time the levers of the Lean Manufacturing approach

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.

Microstructural investigation of surface roughness in MBE-grown AlAs

1995 ◽  
Vol 53 ◽  
pp. 454-455
Author(s):  
R. Rajesh ◽  
R. Droopad ◽  
C. H. Kuo ◽  
R. W. Carpenter ◽  
G. N. Maracas
Keyword(s):  
Thin Film ◽  
Real Time ◽  
Growth Control ◽  
Native Oxide ◽  
Effusion Cell ◽  
Surface Oxide Layer ◽  
Microstructural Investigation ◽  
Mbe Growth ◽  
Film Substrate ◽  
And Control

Knowledge of material pseudodielectric functions at MBE growth temperatures is essential for achieving in-situ, real time growth control. This allows us to accurately monitor and control thicknesses of the layers during growth. Undesired effusion cell temperature fluctuations during growth can thus be compensated for in real-time by spectroscopic ellipsometry. The accuracy in determining pseudodielectric functions is increased if one does not require applying a structure model to correct for the presence of an unknown surface layer such as a native oxide. Performing these measurements in an MBE reactor on as-grown material gives us this advantage. Thus, a simple three phase model (vacuum/thin film/substrate) can be used to obtain thin film data without uncertainties arising from a surface oxide layer of unknown composition and temperature dependence.In this study, we obtain the pseudodielectric functions of MBE-grown AlAs from growth temperature (650°C) to room temperature (30°C). The profile of the wavelength-dependent function from the ellipsometry data indicated a rough surface after growth of 0.5 μm of AlAs at a substrate temperature of 600°C, which is typical for MBE-growth of GaAs.

Adaptive Signal Analysis and Interpretation for Real-time Intelligent Patient Monitoring

1994 ◽  
Vol 33 (01) ◽  
pp. 60-63 ◽  
Author(s):  
E. J. Manders ◽  
D. P. Lindstrom ◽  
B. M. Dawant
Keyword(s):  
Computer Architecture ◽  
Real Time ◽  
Data Abstraction ◽  
Monitoring Strategy ◽  
Intelligent Monitoring ◽  
Patient Status ◽  
On Line ◽  
Main Components ◽  
And Control ◽  
Adaptive Signal

Abstract:On-line intelligent monitoring, diagnosis, and control of dynamic systems such as patients in intensive care units necessitates the context-dependent acquisition, processing, analysis, and interpretation of large amounts of possibly noisy and incomplete data. The dynamic nature of the process also requires a continuous evaluation and adaptation of the monitoring strategy to respond to changes both in the monitored patient and in the monitoring equipment. Moreover, real-time constraints may imply data losses, the importance of which has to be minimized. This paper presents a computer architecture designed to accomplish these tasks. Its main components are a model and a data abstraction module. The model provides the system with a monitoring context related to the patient status. The data abstraction module relies on that information to adapt the monitoring strategy and provide the model with the necessary information. This paper focuses on the data abstraction module and its interaction with the model.

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