scholarly journals Operative Production Controlling as Entrance into Controlling 4.0

2021 ◽  
Vol 15 (37) ◽  
Author(s):  
Marcel Rolf Pfeifer
Keyword(s):  
Industry 4.0 ◽  
Transition Period ◽  
Review Literature ◽  
German Language ◽  
Technical Limitation ◽  
Use Of Data ◽  
Data Production ◽  
Computer Aided ◽  
Strategic Controlling ◽  
Smart Factories

Purpose of the article: The paper focuses on the potentials and benefits controlling provides for companies in the transition period towards industry 4.0. Operative production controlling provides data that shall be used in the future to apply the concept of smart factories. This article proposes a controlling archtitecture based on computer-aided standardization. Methodology/methods: The paper develops an architecture on operational production controlling based on an international literature review. Literature on controlling 4.0 are found mostly in publications in German language. While this literature has its focus on controlling as a whole or on strategic controlling, the paper has a look on operational controlling and its further usage and development towards smart factories. Scientific aim: The aim of this article is to develop a model of an operational production controlling architecture that is able to suite the requirements of smart factories by using computer-aided standarization. Findings: Research is working on concepts for industry 4.0 and its way towards real implementation. Competitive advantage in industry 4.0 is created through digitization and robotization. An architecture that fully complies to industry 4.0 is still waiting in real companies due to technical limitation in data storing, retrieval and processing as well as storage capacities. Conclusions: The paper discussed the devlopment of a controlling architecture suitable for industry 4.0. Already today controlling is making use of data. Smart factories shall make use of production data. Production controlling together with the CAS, that is able to provide standardized data on all manufacturing, maintenance, and auxiliary processes, systems are able to make a step forward towards smart factories. The concept of production controlling combined with the strengths of a CAS may be seen as the basis from which to target smart factories and industry 4.0.

scholarly journals The challenges, approaches, and used techniques of CPS for manufacturing in Industry 4.0: a literature review

2021 ◽  
Vol 113 (7-8) ◽  
pp. 2395-2412
Author(s):  
Baudouin Dafflon ◽  
Nejib Moalla ◽  
Yacine Ouzrout
Keyword(s):  
Internet Of Things ◽  
Industry 4.0 ◽  
Cyber Physical Systems ◽  
Review Literature ◽  
Comprehensive Understanding ◽  
Physical Systems ◽  
Fine Grained ◽  
Key Technologies ◽  
Granularity Level ◽  
Human Component

AbstractThis work aims to review literature related to the latest cyber-physical systems (CPS) for manufacturing in the revolutionary Industry 4.0 for a comprehensive understanding of the challenges, approaches, and used techniques in this domain. Different published studies on CPS for manufacturing in Industry 4.0 paradigms through 2010 to 2019 were searched and summarized. We, then, analyzed the studies at a different granularity level inspecting the title, abstract, and full text to include in the prospective study list. Out of 626 primarily extracted relevant articles, we scrutinized 78 articles as the prospective studies on CPS for manufacturing in Industry 4.0. First, we analyzed the articles’ context to identify the major components along with their associated fine-grained constituents of Industry 4.0. Then, we reviewed different studies through a number of synthesized matrices to narrate the challenges, approaches, and used techniques as the key-enablers of the CPS for manufacturing in Industry 4.0. Although the key technologies of Industry 4.0 are the CPS, Internet of Things (IoT), and Internet of Services (IoS), the human component (HC), cyber component (CC), physical component (PC), and their HC-CC, CC-PC, and HC-PC interfaces need to be standardized to achieve the success of Industry 4.0.

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.

Traces and Shadows

2021 ◽  
pp. 111-120
Author(s):  
Rob Kitchin
Keyword(s):  
World Wide ◽  
Digital Data ◽  
Continuous Data ◽  
The Internet ◽  
Store Loyalty ◽  
Smart Systems ◽  
Digital World ◽  
Use Of Data ◽  
The World ◽  
Data Production

This chapter charts the transition from an analogue to a digital world, its effect on data footprints and shadows, and the growth of data brokers and government use of data. The World Wide Web (WWW) started to change things by making information accessible across the Internet through an easy-to-use, intuitive graphical interface. Using the Internet, people started leaving digital traces. In their everyday lives, their digital shadows were also growing through the use of debit, credit, and store loyalty cards, and captured in government databases which were increasingly digital. Running tandem to the creation of digital lifestyles was the datafication of everyday life. This was evident in a paper which examined the various ways in which digital data was being generated and tracked using indexical codes about people, but also objects, transactions, interactions, and territories, and how these data were being used to govern people and manage organizations. Today, people live in a world of continuous data production, since smart systems generate data in real time.

scholarly journals APPLYING INDUSTRY 4.0 AND EDUCATION 4.0 TO ENGINEERING EDUCATION

2019 ◽  
Author(s):  
Irina Neaga
Keyword(s):  
Higher Education ◽  
United Kingdom ◽  
Engineering Education ◽  
Learning Analytics ◽  
Industry 4.0 ◽  
Research Work ◽  
Undergraduate Level ◽  
Industrial Companies ◽  
Master Level ◽  
Smart Factories

This research work-in-progress deals with a holistic analysis of the impacts of Industry 4.0 (I4.0) for engineering education especially for University undergraduate (level 4-6), master (level 7) and PhD related manufacturing, automotive engineering and supply chain management programmes in United Kingdom higher education institutions. This analysis aims at providing support for further consolidated recommendations to enable the development of higher education engineering curriculum for enhancing I4.0 application for smart organisations and industrial companies within the digital supply chains. Also the paper provides an analysis of advancement from digitalisation in engineering education to the implementation of Education 4.0 and related practices of smart labs, and simulation of smart factories leading at the learning factory. A conceptual framework to support the application of big data and learning analytics in the School of Engineering from University of Wales Trinity St David, Swansea, United Kingdom has been identified, discussed and intended to apply in the context of applying learning analytics.

scholarly journals Comparing Approaches for Evaluating Digital Interventions on the Shop Floor

Technologies ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 116 ◽  
Author(s):  
Francisco Lacueva-Pérez ◽  
Lea Hannola ◽  
Jan Nierhoff ◽  
Stelios Damalas ◽  
Soumyajit Chatterjee ◽  
...  
Keyword(s):  
Industry 4.0 ◽  
Shop Floor ◽  
Use Case ◽  
Individual Level ◽  
Ict System ◽  
The One ◽  
Comparison Of The Results ◽  
Future Work ◽  
Self Learning ◽  
Smart Factories

The introduction of innovative digital tools for supporting manufacturing processes has far-reaching effects at an organizational and individual level due to the development of Industry 4.0. The FACTS4WORKERS project funded by H2020, i.e., Worker-Centric Workplaces in Smart Factories, aims to develop user-centered assistance systems in order to demonstrate their impact and applicability at the shop floor. To achieve this, understanding how to develop such tools is as important as assessing if advantages can be derived from the ICT system created. This study introduces the technology of a workplace solution linked to the industrial challenge of self-learning manufacturing workplaces. Subsequently, a two-step approach to evaluate the presented system is discussed, consisting of the one used in FACTS4WORKERS and the one used in the “Heuristics for Industry 4.0” project. Both approaches and the use case are introduced as a base for presenting the comparison of the results collected in this paper. The comparison of the results for the presented use case is extended with the results for the rest of the FACTS4WORKERS use cases and with future work in the framework.

scholarly journals Organization of Quality Control of Manufactured Products in Smart Factories of the Industry 4.0

2020 ◽  
Vol 795 ◽  
pp. 012016
Author(s):  
D A Zakoldaev ◽  
A V Shukalov ◽  
I O Zharinov ◽  
O O Zharinov
Keyword(s):  
Quality Control ◽  
Industry 4.0 ◽  
Manufactured Products ◽  
Smart Factories
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