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.

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.

A Standards and Technology Roadmap for Scalable Distributed Manufacturing Systems

2018 ◽  
Author(s):  
Thomas Hedberg ◽  
Moneer Helu ◽  
Timothy Sprock
Keyword(s):  
Manufacturing Systems ◽  
Dynamic Decision Making ◽  
Smart Manufacturing ◽  
Distributed Manufacturing ◽  
Physical Systems ◽  
Technology Roadmap ◽  
Industrial Internet ◽  
Manufacturing Resources ◽  
Industrial Standards ◽  
Distributed Manufacturing Systems

The increasing decentralization of manufacturing has contributed to the growing interest in scalable distributed manufacturing systems (DMSs). The emerging body of work from smart manufacturing, Industrie 4.0, Industrial Internet of Things (IIoT), and cyber-physical systems can enable the continued development of scalable DMS, particularly through the digital thread. However, significant challenges exist in understanding how to apply the digital thread most appropriately for scalable DMS. This paper describes these major challenges and provides a standards and technology roadmap developed from the digital thread viewpoint and consensus-built industrial standards to realize scalable DMS. The goal of this roadmap is to guide research that enables manufacturers to take advantage of opportunities provided by scalable DMS, including improved agility, flexibility, traceability, dynamic decision making, and utilization of manufacturing resources.

Analysis of Challenges Responsible for the Slow Pace of Industry 4.0 Diffusion

2021 ◽  
pp. 1737-1766
Author(s):  
Chetna Chauhan ◽  
Amol Singh
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Smart Manufacturing ◽  
Relative Importance ◽  
Fuzzy Analytical Hierarchy Process ◽  
Delphi Approach ◽  
Fuzzy Delphi ◽  
Privacy Risks ◽  
Smart Manufacturing Systems ◽  
Hierarchy Process

The pace of Industry 4.0 adoption in manufacturing industries has been slow as it is accompanied by several barriers, specifically in the emerging economies. The current study intends to identify and understand the landscape of these challenges. Further, this paper prioritizes the challenges on the basis of their relative importance. To achieve this objective, the authors combine the fuzzy delphi approach along with the fuzzy analytical hierarchy process. Additionally, a sensitivity analysis is done to enhance robustness of the findings. The global rankings of the challenges reveal that the most significant factors that hamper the full realization of smart manufacturing include cybersecurity, privacy risks, and enormously high number of technology choices available in the market. The analysis offers insights into the reasons for the slow diffusion of smart manufacturing systems and the results would assist managers, policymakers, and technology providers in the advent of manufacturing digitalization.

scholarly journals Defining SMEs’ 4.0 Readiness Indicators

2020 ◽  
Vol 10 (24) ◽  
pp. 8998
Author(s):  
Nilubon Chonsawat ◽  
Apichat Sopadang
Keyword(s):  
Decision Making ◽  
Industry 4.0 ◽  
Production Efficiency ◽  
Cloud Manufacturing ◽  
Smart Manufacturing ◽  
Increase Production Efficiency ◽  
Five Dimensions ◽  
High Stage ◽  
Industrial Internet ◽  
Infrastructure System

Industry 4.0 revolution offers smart manufacturing; it systematically incorporates production technology and advanced operation management. Adopting these high-state strategies can increase production efficiency, reduce energy consumption, and decrease manufacturer costs. Simultaneously, small and medium-sized enterprises (SMEs) were the backbone of economic growth and development. They still lack both the knowledge and decision-making to verify this high-stage technology’s performance and implementation. Therefore, the research aims to define the readiness indicators to assess and support SMEs toward Industry 4.0. The research begins with found aspects that influence the SME 4.0 readiness by using Bibliometric techniques. The result shows the aspects which were the most occurrences such as the Industrial Internet, Cloud Manufacturing, Collaborative Robot, Business Model, and Digital Transformation. They were then grouped into five dimensions by using the visualization of similarities (VOS) techniques: (1) Organizational Resilience, (2) Infrastructure System, (3) Manufacturing System, (4) Data Transformation, and (5) Digital Technology. Cronbach’s alpha then validated the composite dimensions at a 0.926 level of reliability and a significant positive correlation. After that, the indicators were defined from the dimension and aspects approach. Finally, the indicators were pilot tested by small enterprises. It appeared that 23 indicators could support SMEs 4.0 readiness indication and decision-making in the context of Industry 4.0.

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.

scholarly journals Significant directions of digitalization of the Khabarovsk Territory economy in the implementation of the national program “Digital Economy”

2021 ◽  
Vol 128 ◽  
pp. 01016
Author(s):  
Luyciena Piunko ◽  
Elena Tolkacheva
Keyword(s):  
Industry 4.0 ◽  
Resource Planning ◽  
Digital Economy ◽  
Digital Transformation ◽  
International Standards ◽  
Smart Manufacturing ◽  
Computer Algorithms ◽  
Production Processes ◽  
Industrial Internet ◽  
And Control

The research is devoted to the modern development of digital transformation in the Russian economy, including in the Khabarovsk Territory; the difficulties of implementing the directions of the “Digital Economy”. In this study, an attempt is made to compare the strategic goals of the development of the “Digital Economy”, modern processes of digital transformation and such an important component of it as "Integration 4.0" related to the “industrial Internet”, digital production, intelligent components, including the collection of large amounts of data, cyberphysical systems, remote monitoring and maintenance. “Industry 4.0” accelerates production processes, increases its efficiency and the quality of manufactured goods, reduces the cost of delivery, tracks production chains, etc. Currently, the industry of Western countries uses Industry 4.0 standards at the production management level. In developed countries, such as Germany, South Korea, etc., they realize the importance of automation and computerization, which became the main tool of the third industrial revolution, and its tools for the transition to “Industry 4.0”. International standards are developed for industries that use computer algorithms to monitor and control physical things, such as equipment, robots and vehicles. Standards that work on the basis of the Industrial Internet of Things (IIoT) and cyber—physical systems — intelligent autonomous systems that define all components of the supply chain, transforming production processes into “smart” - from smart manufacturing and factories to smart warehouses and logistics. And, the same systems are associated with the previous stage of industrial production, such as enterprise resource planning (ERP). All this ensures a high level of transparency and control over the activities of the organization. At the present stage, there are excellent opportunities for the development of Industry 4.0 in Russia, but there are also difficulties, overcoming which are significant directions of the digitalization processes of the modern economy. The authors devoted their research to the analysis of such difficulties.

scholarly journals Development of an advanced MES for the simulation and optimization of industry 4.0 process

2021 ◽  
Vol 12 ◽  
pp. 23
Author(s):  
Khaled Benfriha ◽  
Chawki El-Zant ◽  
Quentin Charrier ◽  
Abdel-Hakim Bouzid ◽  
Peter Wardle ◽  
...  
Keyword(s):  
Industry 4.0 ◽  
New Technology ◽  
Point Of View ◽  
Theoretical Point ◽  
Manufacturing Execution System ◽  
Proof Of Concept ◽  
Production Lines ◽  
Simulation And Optimization ◽  
Development Stages ◽  
Manufacturing Execution

The concept of Industry 4.0 has been developed a lot from a theoretical point of view. However, the real applications on production lines remain few in number, due to the difficulties of interoperability between the different production entities and also due to the lack of a control system adapted to the expected flexibility and to the management of the data generated. This article focuses on the development and deployment of a manufacturing execution system (MES) on a production system 4.0. The development stages of the system are explained in detail. The new functionalities and the expected level of performance impose a new logic in the design of advanced systems for controlling and optimizing production. Finally, a proof of concept of an MES was developed and tested on a new technology platform 4.0.

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