Sustainable Value Creation Networks, Digitized Mass Production, and Networked Information-driven Technologies in Industry 4.0-based Manufacturing Systems

2020 ◽  
Vol 15 (2) ◽  
pp. 37
Keyword(s):  
Value Creation ◽  
Mass Production ◽  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Sustainable Value

scholarly journals Development of a Smart Cyber-Physical Manufacturing System in the Industry 4.0 Context

2019 ◽  
Vol 9 (16) ◽  
pp. 3325 ◽  
Author(s):  
Tran ◽  
Park ◽  
Nguyen ◽  
Hoang
Keyword(s):  
Radio Frequency Identification ◽  
Mass Production ◽  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Shop Floor ◽  
Self Healing ◽  
Manufacturing Environment ◽  
Information And Communication ◽  
Ict Infrastructure

The complexity and dynamic of the manufacturing environment are growing due to the changes of manufacturing demand from mass production to mass customization that require variable product types, small lot sizes, and a short lead-time to market. Currently, the automatic manufacturing systems are suitable for mass production. To cope with the changes of the manufacturing environment, the paper proposes the model and technologies for developing a smart cyber-physical manufacturing system (Smart-CPMS). The transformation of the actual manufacturing systems to the Smart-CPMS is considered as the next generation of manufacturing development in Industry 4.0. The Smart-CPMS has advanced characteristics inspired from biology such as self-organization, self-diagnosis, and self-healing. These characteristics ensure that the Smart-CPMS is able to adapt with continuously changing manufacturing requirements. The model of Smart-CPMS is inherited from the organization of living systems in biology and nature. Consequently, in the Smart-CPMS, each resource on the shop floor such as machines, robots, transporters, and so on, is an autonomous entity, namely a cyber-physical system (CPS) which is equipped with cognitive capabilities such as perception, reasoning, learning, and cooperation. The Smart-CPMS adapts to the changes of manufacturing environment by the interaction among CPSs without external intervention. The CPS implementation uses the cognitive agent technology. Internet of things (IoT) with wireless networks, radio frequency identification (RFID), and sensor networks are used as information and communication technology (ICT) infrastructure for carrying out the Smart-CPMS.

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).

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