scholarly journals Human and Social Dimensions in CPS & IoT based Automated Production Systems

2021 ◽  
Author(s):  
Hind Bril El-Haouzi ◽  
Etienne Valette ◽  
Bettina-Johanna Krings ◽  
António Brandão Moniz
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Production Systems ◽  
Intelligent Manufacturing ◽  
Human Dimensions ◽  
Automated Production ◽  
Human In The Loop ◽  
Research Fields ◽  
Human Operators ◽  
Conceptual Evolution

Since the 1970s, the application of microprocessor in industrial machinery and the development of computer systems have transformed the manufacturing landscape. The rapid integration and automation of production systems have outpaced the development of suitable human design criteria, creating a deepening gap where human factor was seen as an important source of errors and disruptions. Today the situation seems different: the scientific and public debate about the concept of Industry 4.0 has raised the awareness about the central role humans have to play in manufacturing systems, to the design of which they must be considered from the very beginning. The future of industrial systems, as represented by Industry 4.0, will rely on the convergence of several research fields such as Intelligent Manufacturing Systems (IMS), Cyber-Physical Systems (CPS), Internet of things (IoT), but also socio-technical fields such as social approaches within technical systems. This article deals with different Human dimensions associated with CPS and IoT and focuses on their conceptual evolution of automatization to improve the sociability of such automated production systems and consequently puts again the human in the loop. Hereby, our aim is to take stock of current research trends, and to show the importance of integrating human operators as a part of a socio-technical system based autonomous and intelligent products or resources. As results, different models of sociability as way to integrate human into the broad sense and/or the development of future automated production systems, were identified from the literature and analysed.

scholarly journals Social Dimensions in CPS & IoT Based Automated Production Systems

Societies ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 98
Author(s):  
Hind Bril El-Haouzi ◽  
Etienne Valette ◽  
Bettina-Johanna Krings ◽  
António Brandão Moniz
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Production Systems ◽  
Intelligent Manufacturing ◽  
Social Dimensions ◽  
Industrial Systems ◽  
Automated Production ◽  
Research Fields ◽  
Human Operators ◽  
Conceptual Evolution

Since the 1970s, the application of microprocessor in industrial machinery and the development of computer systems have transformed the manufacturing landscape. The rapid integration and automation of production systems have outpaced the development of suitable human design criteria, creating a deepening gap between humans and systems in which human was seen as an important source of errors and disruptions. Today, the situation seems different: the scientific and public debate about the concept of Industry 4.0 has raised awareness about the central role humans have to play in manufacturing systems, the design of which must be considered from the very beginning. The future of industrial systems, as represented by Industry 4.0, will rely on the convergence of several research fields such as Intelligent Manufacturing Systems (IMS), Cyber-Physical Systems (CPS), Internet of Things (IoT), but also socio-technical fields such as social approaches within technical systems. This article deals with different human social dimensions associated with CPS and IoT and focuses on their conceptual evolution regarding automated production systems’ sociability, notably by bringing humans back in the loop. Hereby, this paper aims to take stock of current research trends to show the importance of integrating human operators as a part of a socio-technical system based autonomous and intelligent products or resources. Consequently, different models of sociability as a way to integrate humans in the broad sense and/or the develop future automated production systems have been identified from the literature and analysed.

scholarly journals Conditions for the Development of Industry 4.0 from the Human Capital Technological Competences Perspective

2019 ◽  
Vol 2 (4) ◽  
pp. 159-165
Author(s):  
Patricia Avitia-Carlos ◽  
Carlos Gerardo Morales-García ◽  
José Luis Rodríguez-Verduzco ◽  
Bernabe Rodríguez Tapia ◽  
Norma Candolfi Arballo
Keyword(s):  
Human Capital ◽  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Production Systems ◽  
Intelligent Manufacturing ◽  
Regional Economies ◽  
Industry Collaboration ◽  
Computer Based ◽  
Technological Competences ◽  
University Industry

The so-called Industry 4.0 supports its emergence and growth in the use of artificial intelligence techniques for the development of production systems whose capacity, efficiency and adaptability exceed the performance of current computer-based systems. Intelligent manufacturing corresponds to the digitization and interconnection of devices for the construction of production and supply chains that share a continuous flow of information. This revolution involves the development of technologies such as the Internet of Things, data analytics and cyber-systems aligned with machine learning, among others. The development and sustainability of these advanced manufacturing systems represent an area of opportunity for the growth of the technological competitiveness of regional economies. There are, however, training needs among engineering professionals for the development of specific updated technological competences; as well as a need of general conditions for the establishment of innovation networks between academia and the productive sector. This paper uses bibliographic techniques to examine existing literature and conducts a review on Industry 4.0. As a result, it presents an overview of the related technological trends and discuss the role of higher education institutions in the development of competitive human capital. There are also multiple areas of opportunity in the medium and long term to strength university-industry collaboration programs related to this adoption.

Intelligent Manufacturing Systems Driven by Artificial Intelligence in Industry 4.0

2022 ◽  
pp. 406-428
Author(s):  
Lejla Banjanović-Mehmedović ◽  
Fahrudin Mehmedović
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Industry 4.0 ◽  
Data Analytics ◽  
Manufacturing Systems ◽  
System Modeling ◽  
Big Data Analytics ◽  
Intelligent Manufacturing ◽  
Intelligent Manufacturing Systems ◽  
Intelligent Decision Making

Intelligent manufacturing plays an important role in Industry 4.0. Key technologies such as artificial intelligence (AI), big data analytics (BDA), the internet of things (IoT), cyber-physical systems (CPSs), and cloud computing enable intelligent manufacturing systems (IMS). Artificial intelligence (AI) plays an essential role in IMS by providing typical features such as learning, reasoning, acting, modeling, intelligent interconnecting, and intelligent decision making. Artificial intelligence's impact on manufacturing is involved in Industry 4.0 through big data analytics, predictive maintenance, data-driven system modeling, control and optimization, human-robot collaboration, and smart machine communication. The recent advances in machine and deep learning algorithms combined with powerful computational hardware have opened new possibilities for technological progress in manufacturing, which led to improving and optimizing any business model.

Proposal of an Architecture based on RAMI 4.0 Layers for Flexible Manufacturing in Industry 4.0

2020 ◽  
Author(s):  
José Z. Neto ◽  
Joel Ravelli Jr ◽  
Eduardo P. Godoy
Keyword(s):  
Flexible Manufacturing ◽  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Production Systems ◽  
Three Dimensional ◽  
Reference Architecture ◽  
Architecture Model ◽  
Industrial Internet ◽  
Integration Architecture ◽  
Rapid Changes

The Industry 4.0 (I4.0) together with the Industrial Internet of Things (IIoT) enable business productivity to be improved through rapid changes in production scope in an increasingly volatile market. This technology innovation is perceived by integrating manufacturing systems, managing business rules, and decentralizing computing resources, enabling rapid changes in production systems. The Reference Architecture Model for Industry 4.0 (RAMI 4.0) is a three-dimensional layer model to support I4.0 applications. One of the major challenges for adopting RAMI 4.0 is the development of solutions that support the functionality of each layer and the necessary interactions between the elements of each layer. This paper focuses on the proposal of architecture for flexible manufacturing in I4.0 using all the Information Technology (IT) Layers of the RAMI 4.0. In order to enable a standardized and interoperable communication, the architecture used the OPC-UA protocol to connect the low layers elements in the factory perspective and REST APIs to connect the high layers in the business perspective. The integration architecture creates an online interface to provide the client the ability to enter, view, and even modify an order based on their needs and priorities, enabling the industry to implement rapid changes to adapt to the marketplace.

Intelligent Manufacturing Systems Driven by Artificial Intelligence in Industry 4.0

2020 ◽  
pp. 31-52 ◽  
Author(s):  
Lejla Banjanović-Mehmedović ◽  
Fahrudin Mehmedović
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Industry 4.0 ◽  
Data Analytics ◽  
Manufacturing Systems ◽  
System Modeling ◽  
Big Data Analytics ◽  
Intelligent Manufacturing ◽  
Intelligent Manufacturing Systems ◽  
Intelligent Decision Making

Intelligent manufacturing plays an important role in Industry 4.0. Key technologies such as artificial intelligence (AI), big data analytics (BDA), the internet of things (IoT), cyber-physical systems (CPSs), and cloud computing enable intelligent manufacturing systems (IMS). Artificial intelligence (AI) plays an essential role in IMS by providing typical features such as learning, reasoning, acting, modeling, intelligent interconnecting, and intelligent decision making. Artificial intelligence's impact on manufacturing is involved in Industry 4.0 through big data analytics, predictive maintenance, data-driven system modeling, control and optimization, human-robot collaboration, and smart machine communication. The recent advances in machine and deep learning algorithms combined with powerful computational hardware have opened new possibilities for technological progress in manufacturing, which led to improving and optimizing any business model.

Effect of Failure Rate on the Availability Analysis of Nestle CERELAC Plant Using Markov Chain Method

2018 ◽  
pp. 121-127
Author(s):  
Gurbinder Singh ◽  
Rakesh Kumar
Keyword(s):  
Markov Chain ◽  
Manufacturing Systems ◽  
Production Systems ◽  
Research Work ◽  
Automated Production ◽  
Availability Analysis ◽  
Long Run ◽  
Machine Reliability ◽  
Markov Chain Method

In the performance analysis of production systems by using the traditional methods of engineering the knowledge of machine reliability factors is assumed to be precisely known. The current study entitled performance evaluation of food industry in India. To analyze and determine the availability of plant a case study has been undertaken from Moga Nestle food private limited industry in India. Various studies evaluating the performance of automated production systems with the help of modeling and simulation and analytical methods have always given priority to steady state performance as compared to transient performance. Production systems in which such kind of situations arises include systems with dysfunctional states and deadlocks, not stable queuing systems. This research work presents an approach for analyzing the performance of unreliable manufacturing systems that take care of uncertain machine factor estimates. The method that is being proposed is on the basis of Markov chain and probability density function discretization techniques for studying manufacture lines consist unreliable machines. To determine the performance of plant, important information has been collected from different systems and subsystems to find out long run availability of whole system.

Advanced Metrology and Intelligent Quality Automation for Industry 4.0-Based Precision Manufacturing Systems

2017 ◽  
Vol 261 ◽  
pp. 432-439 ◽  
Author(s):  
Numan M. Durakbasa ◽  
Jorge Bauer ◽  
Günther Poszvek
Keyword(s):  
Industry 4.0 ◽  
Data Exchange ◽  
Manufacturing Systems ◽  
Production Systems ◽  
Integrated Management ◽  
Essential Feature ◽  
Cost Effective ◽  
Scale Production ◽  
Precision Engineering ◽  
Technological Developments

Intelligence is an essential feature of future development and production systems, and intelligent production is a major component of future business. To meet market demands in present and future global industrial world, manufacturing enterprises of any kind and any size must be flexible and agile enough to respond quickly to product demand changes also according technological developments especially in the field of precision engineering at micro/nanoand pico scale production. With support of AI and modern IT it is possible to realise modern cost-effective customer-driven design and manufacturing taking into account the importance and basic role of modern Integrated Management Systems - IMS and intelligent advanced metrology.This new concept can be developed on the basis of intelligent production technologies and integrated systems as well as extensive use of the IT, AI, simulation, quality autonomation, robotics, advanced metrology and advanced engineering data exchange techniques. Moreover by utilizing advanced information analytics, networked intelligent machines and instruments will be able to perform more efficiently, collaboratively and sustainably, that makes possible an agile and optimal industrial production in any kind of industry and especially in up-to-date SMEs towards Industry 4.0.

scholarly journals Practical Use of Robot Manipulators as Intelligent Manufacturing Systems

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2877 ◽  
Author(s):  
Pablo Alhama Blanco ◽  
Fares Abu-Dakka ◽  
Mohamed Abderrahim
Keyword(s):  
Real Time ◽  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Robot Manipulators ◽  
Smart Cities ◽  
Industrial Robot ◽  
Online Communication ◽  
Intelligent Manufacturing ◽  
Communication Tool ◽  
Industrial Big Data

This paper presents features and advanced settings for a robot manipulator controller in a fully interconnected intelligent manufacturing system. Every system is made up of different agents. As also occurs in the Internet of Things and smart cities, the big issue here is to ensure not only that implementation is key, but also that there is better common understanding among the main players. The commitment of all agents is still required to translate that understanding into practice in Industry 4.0. Mutual interactions such as machine-to-machine and man-to-machine are solved in real time with cyber physical capabilities. This paper explores intelligent manufacturing through the context of industrial robot manipulators within a Smart Factory. An online communication algorithm with proven intelligent manufacturing abilities is proposed to solve real-time interactions. The algorithm is developed to manage and control all robot parameters in real-time. The proposed tool in conjunction with the intelligent manufacturing core incorporates data from the robot manipulators into the industrial big data to manage the factory. The novelty is a communication tool that implements the Industry 4.0 standards to allow communications among the required entities in the complete system. It is achieved by the developed tool and implemented in a real robot and simulation

scholarly journals Developing of Industry 4.0 Applications

2017 ◽  
Vol 13 (10) ◽  
pp. 30 ◽  
Author(s):  
Juan David Contreras ◽  
Jose Isidro Garcia ◽  
Juan David Diaz
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Industrial Revolution ◽  
Intelligent Manufacturing ◽  
Reference Architecture ◽  
Physical Systems ◽  
Architecture Model ◽  
Smart Factories ◽  
Correct Implementation

<p class="0papertitle">The fourth industrial revolution or industry 4.0 has become a trend topic nowadays, this standard-based strategy integrates Smart Factories, Cyber-physical systems, Internet of Things, and Internet of Service with the aim of extended the capacities of the manufacturing systems. Although several authors have presented the advantages of this approach, few papers refer to an architecture that allows the correct implementation of industry 4.0 applications using the guidelines of the reference architecture model (RAMI 4.0). In this way, this article exposes the essential characteristics that allow a manufacturing system to be retrofitting as a correct industry 4.0 application. Specifically, an intelligent manufacturing system under a holonic approach was developed and implemented using standards like FDI, AutomationML and OPC UA according to the RAMI 4.0</p>

A Comprehensive Approach of Advanced Error Troubleshooting in Intelligent Manufacturing Systems

2013 ◽  
Vol 404 ◽  
pp. 631-634 ◽  
Author(s):  
Lehel Csokmai ◽  
Ovidiu Moldovan ◽  
Ioan Constantin Tarca ◽  
Radu Tarca
Keyword(s):  
Flexible Manufacturing ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Flexible Manufacturing System ◽  
Production Systems ◽  
Error Recovery ◽  
Intelligent Manufacturing ◽  
Open Issue ◽  
New Type ◽  
Framework System

Production systems must be flexible and endowed with techniques and tools allowing an automatic recovery of errors. And so, the subject of error recovery in flexible manufacturing system is always an open issue. The objective of this work consists in proposing a new type of software framework for error troubleshooting in a flexible manufacturing system that is perceived as an Intelligent Space (iSpace). Our framework system is designed to solve the failures in the functioning of the FMS and to generate self-training from previous experience.

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