scholarly journals Energy Efficiency in Industry 4.0: The Case of Batch Production Processes

2020 ◽  
Vol 12 (16) ◽  
pp. 6631 ◽  
Author(s):  
Giancarlo Nota ◽  
Francesco David Nota ◽  
Domenico Peluso ◽  
Alonso Toro Lazo
Keyword(s):  
Energy Consumption ◽  
Industry 4.0 ◽  
Production Systems ◽  
Decision Makers ◽  
Batch Processes ◽  
Energy Losses ◽  
Manufacturing Processes ◽  
Batch Production ◽  
Production Processes ◽  
Cyber Physical Production Systems

We derived a promising approach to reducing the energy consumption necessary in manufacturing processes from the combination of management methodologies and Industry 4.0 technologies. Based on a literature review and experts’ opinions, this work contributes to the efficient use of energy in batch production processes combining the analysis of the overall equipment effectiveness with the study of variables managed by cyber-physical production systems. Starting from the analysis of loss cause identification, we propose a method that obtains quantitative data about energy losses during the execution of batch processes. The contributions of this research include the acquisition of precise information about energy losses and the improvement of value co-creation practices so that energy consumption can be reduced in manufacturing processes. Decision-makers can use the findings to start a virtuous process aiming at carbon footprint and energy costs reductions while ensuring production goals are met.

scholarly journals Resilience in Industry 4.0 Digital Infrastructures and Platforms

2021 ◽  
Author(s):  
Daniel Ribeiro ◽  
António Almeida ◽  
Américo Azevedo ◽  
Filipe Ferreira
Keyword(s):  
Industry 4.0 ◽  
Production Systems ◽  
Mitigation Strategies ◽  
Manufacturing Processes ◽  
Digital Platforms ◽  
New Methodologies ◽  
Product Customization ◽  
Physical Assets ◽  
Cyber Physical Production Systems ◽  
And Control

We live in a world where companies are shifting to the industry 4.0 paradigm. One of the pillars of Industry 4.0 is the digitalization of physical assets and manufacturing processes, moving toward the Cyber-Physical Production Systems concept (CPPS). In these systems, every component of the production process – machines, tools, workstations, etc. – is equipped with sensors, possesses information about itself, and can interact with each other, allowing the production of smaller batches at lower prices and increase product customization through adaptative processes. Consequently, companies are evolving their information systems to have more visibility and control over their production systems. This change increases both the production system’s agility and its vulnerability to communication and information related disruptions. Hence, companies that adhere to Industry 4.0 enabling technologies must adopt new methodologies and tools to become aware of the new risks that arise by the introduction of new digital platforms, their impacts in the production systems, and how they may react to remain resilient. In this paper, disruption events and adequate mitigation strategies are analysed, modelled, and simulated as part of a methodology designed to measure the impacts of disruptive events on the production system.

scholarly journals Challenges of Digital Twin System

2019 ◽  
Vol 12 (3) ◽  
pp. 252-267
Author(s):  
Cristina Rosaria Monsone ◽  
János Jósvai
Keyword(s):  
Industry 4.0 ◽  
Production Systems ◽  
Communication Technologies ◽  
Vital Role ◽  
Manufacturing Processes ◽  
Assembly Systems ◽  
Twin System ◽  
Cyber Physical Production Systems ◽  
Learning Analysis ◽  
Manufacturing Science

Today’s manufacturing and assembly systems have to be flexible to adapt quickly to an increasing number and variety of products. The Industry 4.0 conceptualization has several potentials, i.e. flexibility in business and manufacturing processes, where the intelligent and interconnected systems, in particular the Cyber-Physical Production System (CPPS), play a vital role in the whole lifecycle of eco-designed products. In particular, the CPPS represents a suitable way for manufacturers that want to involve their customers, delivering instructions to machines about their specific orders and follow its progress along the production line, in an inversion of normal manufacturing. The development of Info Communication Technologies (ICT) and Manufacturing Science and Technology (MST) enables the innovation of Cyber-Physical Production Systems. However, there are still important challenges that need to be addressed in particular at technological and data analysis level with the implementation of Deep Learning analysis.

One-of-a-kind Production in Cyber-Physical Production Systems Considering Machine Failures

2021 ◽  
pp. 1-20
Author(s):  
Guido Vinci Carlavan ◽  
Daniel Alejandro Rossit
Keyword(s):  
Industry 4.0 ◽  
Information Technologies ◽  
Job Shop ◽  
Production Systems ◽  
Dispatching Rules ◽  
Shop Floor ◽  
Due Dates ◽  
Efficient Manner ◽  
Large Variability ◽  
Cyber Physical Production Systems

Industry 4.0 proposes the incorporation of information technologies at all levels of the production process. By incorporating these technologies, Industry 4.0 provides new tools for production planning processes, allowing to address problems in an innovative and efficient manner. From these technologies and tools, it is that in this work a One-of-a-Kind Production (OKP) process is approached, where the products tend to be highly customized. OKP implies working with a very large variability within production, demanding very efficient planning systems. For this, a planning model based on CONWIP-type strategies was proposed, which seeks to level the production of a shop floor configured in the form of a job shop. Even more, for having a more realistic shop-floor representation, machine failures have been included in the model. In turn, different dispatching rules were proposed to study the performance and analyze the behaviour of the system. From the results obtained, it is observed that, when the production demand is very exigent in relation with the capacity of the system, the dispatching rules that analyze the workload generated by each job tend to perform better. However, when the demand on the capacity of the production system is less intense, the rules associated with due dates are the ones that obtain the best results.

scholarly journals Simulation von Cyber-Physischen Produktionssystemen in einer Forschungsinfrastruktur

2020 ◽  
Author(s):  
Iris Gräßler
Keyword(s):  
Communication Technology ◽  
Information Acquisition ◽  
Industry 4.0 ◽  
Production Control ◽  
Production Systems ◽  
General Concept ◽  
Radio Network ◽  
Systems Research ◽  
Digital Twins ◽  
Cyber Physical Production Systems

The article describes the setup of an experimentation and validation environment by extending a production laboratory: All relevant elements of the production laboratory were equipped with computer systems, so-called "industry 4.0 boxes", and interconnected via a peer-to-peer radio network. The "industry 4.0 boxes" are used to upgrade dedicated sensors for recording machine behaviour and communication technology to be integrated into decentralized production control. In addition, digital twins were implemented to map machine and user behaviour, enable control and support information acquisition and processing. Thereby, a research infrastructure is created for research on potentials of cyber-physical production systems. Research outcomes will be used as a decision basis for companies and for validation of production optimizations. This paper describes the concept and implementation of industry 4.0 functionalities and derives a general concept of simulation platforms for CPPS.

The Implementation of Industry 4.0 by Using Industrial and Service Robots in the Production Processes

2020 ◽  
pp. 1-30 ◽  
Author(s):  
Isak Karabegović ◽  
Edina Karabegović ◽  
Mehmed Mahmic ◽  
Ermin Husak
Keyword(s):  
Radio Frequency Identification ◽  
Industry 4.0 ◽  
Production Systems ◽  
Service Robots ◽  
Production Processes ◽  
New Business ◽  
3D Printers ◽  
Frequency Identification ◽  
Smart Factories ◽  
The Internet Of Things

From the very knowledge of Industry 4.0, its implementation is carried out in all segments of society, but we still do not fully understand the breadth and speed of its implementation. We are currently witnessing major changes in all industries, so new business methods are emerging. There is a transformation of production systems, a new form of consumption, delivery, and transportation, all thanks to the implementation of new technological discoveries that cover robotics and automation, the internet of things (IoT), 3D printers, smart sensors, radio frequency identification (RFID), etc. Robotic technology is one of the most important technologies in Industry 4.0, so that the robot application in the automation of production processes with the support of information technology brings us to smart automation (i.e., smart factories). The changes are so deep that, from the perspective of human history, there has never been a time of greater promise or potential danger.

Integration of Cutting-Edge Interoperability Approaches in Cyber-Physical Production Systems and Industry 4.0

2021 ◽  
pp. 144-172
Author(s):  
Luis Alberto Estrada-Jimenez ◽  
Terrin Pulikottil ◽  
Nguyen Ngoc Hien ◽  
Agajan Torayev ◽  
Hamood Ur Rehman ◽  
...  
Keyword(s):  
Industry 4.0 ◽  
Production Systems ◽  
Heterogeneous Systems ◽  
Smart Manufacturing ◽  
Use Case ◽  
Integrative Framework ◽  
Data Formats ◽  
Exchange Information ◽  
Cyber Physical Production Systems ◽  
Physical Components

Interoperability in smart manufacturing refers to how interconnected cyber-physical components exchange information and interact. This is still an exploratory topic, and despite the increasing number of applications, many challenges remain open. This chapter presents an integrative framework to understand common practices, concepts, and technologies used in trending research to achieve interoperability in production systems. The chapter starts with the question of what interoperability is and provides an alternative answer based on influential works in the field, followed by the presentation of important reference models and their relation to smart manufacturing. It continues by discussing different types of interoperability, data formats, and common ontologies necessary for the integration of heterogeneous systems and the contribution of emerging technologies in achieving interoperability. This chapter ends with a discussion of a recent use case and final remarks.

scholarly journals TEACHING NETWORK TECHNOLOGIES THAT SUPPORT INDUSTRY 4.0

2015 ◽  
Author(s):  
Ishwar Singh ◽  
Nafia Al-Mutawaly ◽  
Tom Wanyama
Keyword(s):  
Industry 4.0 ◽  
Production Systems ◽  
Manufacturing Plants ◽  
Electrical Grid ◽  
Distributed Intelligence ◽  
Industrial Networks ◽  
Manufacturing Competitiveness ◽  
Manufacturing Productivity ◽  
Cyber Physical Production Systems ◽  
Network Technologies

Industry 4.0 is a combination of many elements, including distributed intelligence, network security, massive data, cloud computing, and analytics, among other things. Such elements are critical to the “Digital Factory”, a term that has been recently introduced by many companies indicating a comprehensive portfolio of seamlessly integrated hardware, software and technology-based services, with the aim to enhance manufacturing productivity and improving efficiency. Typically, industrial networks enable the gathering of extensive data from productionlines and plants, which are increasingly becoming distributed. The gathered data is transmitted to analysis centers where it is transformed into information and used to make better informed decisions. In addition, modern industrial networks allow plant data to be automatically filtered and transmitted to various production controllers. Ultimately, industrial networks enable Industry 4.0 to have the following benefits: improved safety, increase uptime, lower energy costs, and improved maintenance;all of which lead to manufacturing competitiveness in cyber-physical production systems supported by Smart Grid implementations. This paper presents the extent to which industrial networks are taught at the School ofEngineering Technology at McMaster University. Further, the paper covers teaching methods of industrial networks and their related applications within manufacturing plants and electrical grid.

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