scholarly journals Introduction to Scheduling in Industry 4.0 and Cloud Manufacturing Systems

2020 ◽  
pp. 1-9
Author(s):  
Dmitry Ivanov ◽  
Boris Sokolov ◽  
Alexandre Dolgui
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Cloud Manufacturing

scholarly journals Formal Tools for Management of Manufacturing Systems: A Multi Agents System Approach

2019 ◽  
Vol 13 (5) ◽  
pp. 691-699
Author(s):  
Doriana M. D’Addona ◽  
Alessandro A. Bruzzone ◽  
◽  
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Manufacturing Industry ◽  
Cloud Manufacturing ◽  
Technological Innovations ◽  
Real Sector ◽  
Multi Agent System ◽  
Industrial Internet ◽  
Multi Agent ◽  
Multi Agents

To overcome the consequences of the 2008 crisis on the real sector, especially manufacturing, Industry 4.0 gives guidelines to drive production by emphasizing technological innovations, such as industrial internet, cloud manufacturing, etc. The proposed paper focuses on cognitive manufacturing within the framework of the emergent synthesis paradigm. Specifically, the structuring process by which the manufacturing assets are organized to provide the finished goods is analyzed. The study is carried out by considering the analogies between manufacturing and other inventive processes supported by formal tools such as formal languages, semantic webs, and multi agent system.

scholarly journals Open Source Control Device for Industry 4.0 Based on RAMI 4.0

Electronics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 869
Author(s):  
Pablo F. S. Melo ◽  
Eduardo P. Godoy ◽  
Paolo Ferrari ◽  
Emiliano Sisinni
Keyword(s):  
Open Source ◽  
Industry 4.0 ◽  
Product Life Cycle ◽  
Manufacturing Systems ◽  
Industrial Revolution ◽  
Control Device ◽  
Source Control ◽  
Reference Architecture ◽  
Architecture Model ◽  
Complex Relationships

The technical innovation of the fourth industrial revolution (Industry 4.0—I4.0) is based on the following respective conditions: horizontal and vertical integration of manufacturing systems, decentralization of computing resources and continuous digital engineering throughout the product life cycle. The reference architecture model for Industry 4.0 (RAMI 4.0) is a common model for systematizing, structuring and mapping the complex relationships and functionalities required in I4.0 applications. Despite its adoption in I4.0 projects, RAMI 4.0 is an abstract model, not an implementation guide, which hinders its current adoption and full deployment. As a result, many papers have recently studied the interactions required among the elements distributed along the three axes of RAMI 4.0 to develop a solution compatible with the model. This paper investigates RAMI 4.0 and describes our proposal for the development of an open-source control device for I4.0 applications. The control device is one of the elements in the hierarchy-level axis of RAMI 4.0. Its main contribution is the integration of open-source solutions of hardware, software, communication and programming, covering the relationships among three layers of RAMI 4.0 (assets, integration and communication). The implementation of a proof of concept of the control device is discussed. Experiments in an I4.0 scenario were used to validate the operation of the control device and demonstrated its effectiveness and robustness without interruption, failure or communication problems during the experiments.

scholarly journals Digital Twins Collaboration for Automatic Erratic Operational Data Detection in Industry 4.0

2021 ◽  
Vol 11 (7) ◽  
pp. 3186
Author(s):  
Radhya Sahal ◽  
Saeed H. Alsamhi ◽  
John G. Breslin ◽  
Kenneth N. Brown ◽  
Muhammad Intizar Ali
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Interaction Mechanism ◽  
Semantic Knowledge ◽  
Smart Manufacturing ◽  
Data Detection ◽  
Workflow Model ◽  
Digital Twins ◽  
Potential Failure ◽  
Operational Data

Digital twin (DT) plays a pivotal role in the vision of Industry 4.0. The idea is that the real product and its virtual counterpart are twins that travel a parallel journey from design and development to production and service life. The intelligence that comes from DTs’ operational data supports the interactions between the DTs to pave the way for the cyber-physical integration of smart manufacturing. This paper presents a conceptual framework for digital twins collaboration to provide an auto-detection of erratic operational data by utilizing operational data intelligence in the manufacturing systems. The proposed framework provide an interaction mechanism to understand the DT status, interact with other DTs, learn from each other DTs, and share common semantic knowledge. In addition, it can detect the anomalies and understand the overall picture and conditions of the operational environments. Furthermore, the proposed framework is described in the workflow model, which breaks down into four phases: information extraction, change detection, synchronization, and notification. A use case of Energy 4.0 fault diagnosis for wind turbines is described to present the use of the proposed framework and DTs collaboration to identify and diagnose the potential failure, e.g., malfunctioning nodes within the energy industry.

Modulare Fertigungslinien für die individualisierte Produktion/Modular manufacturing systems for individualized production - Improving flexibility through business process modelling

2016 ◽  
Vol 106 (04) ◽  
pp. 204-210
Author(s):  
S. Wrede ◽  
M. Wojtynek ◽  
J. Prof. Steil ◽  
O. Beyer ◽  
C. Frobieter ◽  
...  
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Leading Edge ◽  
Industrie 4.0 ◽  
Process Models ◽  
Modular System ◽  
Lot Size ◽  
Business Process Modelling ◽  
Individualized Production ◽  
Modular Production

Der Beitrag beschreibt ein Hard- und Softwarekonzept für vernetzte Fertigungsmodule. Eine modulare Systemarchitektur sowie die dezentrale Steuerung durch Prozessmodelle auf Basis von BPMN2 erlauben eine kundenspezifische Produktion bis hin zu Losgröße eins. Anhand eines vertikal in die Unternehmens-IT integrierten Demonstrators wurden die Vorteile als Showcase für Industrie 4.0 auf verschiedenen Fachmessen erlebbar. Der innovative Ansatz wurde im Verbundprojekt itsowl-FlexiMon im Rahmen des BMBF Spitzenclusters „Intelligente Technische Systeme OstWestfalenLippe“ (it’s OWL) entwickelt.   This contribution describes a distributed modular production system for individualized production. A modular system architecture and semi-autonomous cell control based on executable process models with BPMN2 are used to realize a customer specific production down to lot size one. The advantages have become tangible through a vertically integrated demonstrator that has been exhibited at different fares and showcases the progress towards Industry 4.0. The overall approach was developed in the project itsowl-FlexiMon in the framework of the BMBF leading edge cluster „Intelligent Technical Systems OWL“ (it’s OWL).

Interoperability in Cloud Manufacturing and Practice on Private Cloud Structure for SMEs

2017 ◽  
Author(s):  
Xi Vincent Wang ◽  
Lihui Wang
Keyword(s):  
Manufacturing Systems ◽  
Manufacturing System ◽  
Research Work ◽  
Cloud Manufacturing ◽  
Cloud Services ◽  
Security Requirements ◽  
Research Trend ◽  
Safety Regulations ◽  
Multiple Challenges ◽  
New Research

In recent years, Cloud manufacturing has become a new research trend in manufacturing systems leading to the next generation of production paradigm. However, the interoperability issue still requires more research due to the heterogeneous environment caused by multiple Cloud services and applications developed in different platforms and languages. Therefore, this research aims to combat the interoperability issue in Cloud Manufacturing System. During implementation, the industrial users, especially Small- and Medium-sized Enterprises (SMEs), are normally short of budget for hardware and software investment due to financial stresses, but they are facing multiple challenges required by customers at the same time including security requirements, safety regulations. Therefore in this research work, the proposed Cloud manufacturing system is specifically tailored for SMEs.

scholarly journals Dynamic Pricing in Cloud Manufacturing Systems under Combined Effects of Consumer Structure, Negotiation, and Demand

2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Wei Peng ◽  
Wei Guo ◽  
Lei Wang ◽  
Ruo-Yu Liang
Keyword(s):  
Dynamic Pricing ◽  
Manufacturing Systems ◽  
Wholesale Price ◽  
Cloud Manufacturing ◽  
High Ratio ◽  
Reservation Price ◽  
Combined Effects ◽  
Constant Elasticity ◽  
Price Increases ◽  
Linear Demand

In this study, we proposed a game-theory based framework to model the dynamic pricing process in the cloud manufacturing (CMfg) system. We considered a service provider (SP), a broker agent (BA), and a dynamic service demander (SD) population that is composed of price takers and bargainers in this study. The pricing processes under linear demand and constant elasticity demand were modeled, respectively. The combined effects of SD population structure, negotiation, and demand forms on the SP’s and the BA’s equilibrium prices and expected revenues were examined. We found that the SP’s optimal wholesale price, the BA’s optimal reservation price, and posted price all increase with the proportion of price takers under linear demand but decrease with it under constant elasticity demand. We also found that the BA’s optimal reservation price increases with bargainers’ power no matter under what kind of demand. Through analyzing the participants’ revenues, we showed that a dynamic SD population with a high ratio of price takers would benefit the SP and the BA.

scholarly journals Middleware Application, Suitable to Build an Automated and Connected Smart Manufacturing Environment

2021 ◽  
Author(s):  
Muzaffar Rao ◽  
Thomas Newe
Keyword(s):  
Mobile Robots ◽  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Smart Manufacturing ◽  
Manufacturing Execution System ◽  
Manufacturing Environment ◽  
Industrial Internet ◽  
A Cell ◽  
Smart Industry ◽  
Manufacturing Execution

The current manufacturing transformation is represented by using different terms like; Industry 4.0, smart manufacturing, Industrial Internet of Things (IIoTs), and the Model-Based enterprise. This transformation involves integrated and collaborative manufacturing systems. These manufacturing systems should meet the demands changing in real-time in the smart factory environment. Here, this manufacturing transformation is represented by the term ‘Smart Manufacturing’. Smart manufacturing can optimize the manufacturing process using different technologies like IoT, Analytics, Manufacturing Intelligence, Cloud, Supplier Platforms, and Manufacturing Execution System (MES). In the cell-based manufacturing environment of the smart industry, the best way to transfer the goods between cells is through automation (mobile robots). That is why automation is the core of the smart industry i.e. industry 4.0. In a smart industrial environment, mobile-robots can safely operate with repeatability; also can take decisions based on detailed production sequences defined by Manufacturing Execution System (MES). This work focuses on the development of a middleware application using LabVIEW for mobile-robots, in a cell-based manufacturing environment. This application works as middleware to connect mobile robots with the MES system.

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