scholarly journals Trends in Smart Manufacturing: Role of Humans and Industrial Robots in Smart Factories

2020 ◽  
Vol 1 (2) ◽  
pp. 35-41 ◽  
Author(s):  
Linn D. Evjemo ◽  
Tone Gjerstad ◽  
Esten I. Grøtli ◽  
Gabor Sziebig
Keyword(s):  
Industrial Robots ◽  
Smart Manufacturing ◽  
Smart Factories

scholarly journals Human–Robot Collaboration Trends and Safety Aspects: A Systematic Review

2021 ◽  
Vol 10 (3) ◽  
pp. 48
Author(s):  
Janis Arents ◽  
Valters Abolins ◽  
Janis Judvaitis ◽  
Oskars Vismanis ◽  
Aly Oraby ◽  
...  
Keyword(s):  
Early Stage ◽  
Industrial Robots ◽  
Smart Manufacturing ◽  
Safety Issues ◽  
Stage Of Development ◽  
Complex Process ◽  
Human Robot Collaboration ◽  
Smart Factories ◽  
And Robotics ◽  
Safety Action

Smart manufacturing and smart factories depend on automation and robotics, whereas human–robot collaboration (HRC) contributes to increasing the effectiveness and productivity of today’s and future factories. Industrial robots especially in HRC settings can be hazardous if safety is not addressed properly. In this review, we look at the collaboration levels of HRC and what safety actions have been used to address safety. One hundred and ninety-three articles were identified from which, after screening and eligibility stages, 46 articles were used for the extraction stage. Predefined parameters such as: devices, algorithms, collaboration level, safety action, and standards used for HRC were extracted. Despite close human and robot collaboration, 25% of all reviewed studies did not use any safety actions, and more than 50% did not use any standard to address safety issues. This review shows HRC trends and what kind of functionalities are lacking in today’s HRC systems. HRC systems can be a tremendously complex process; therefore, proper safety mechanisms must be addressed at an early stage of development.

The Entrepreneurial State in Action: The Danish Robotics Cluster and the Role of the Public Sector

2020 ◽  
pp. 1-31
Author(s):  
JULIAN LAMBERTY ◽  
JEPPE NEVERS
Keyword(s):  
Public Sector ◽  
Industrial Robots ◽  
Public Programs ◽  
Public Agency ◽  
The Public ◽  
Thought Collective ◽  
Role Of The State ◽  
Risk Takers ◽  
Market Relations

The question of the role of the state in the creation of competitive clusters and innovation systems has drawn increased attention in recent years. Drawing on Mariana Mazzucato’s concept of “the entrepreneurial state,” this article investigates the role of the public sector in the development of the Danish robotics cluster, a world-leading cluster for production of industrial robots that has developed after the closing of Maersk’s shipyard in the city of Odense. In what ways did public programs and actors contribute to the development of this cluster? In what ways did public programs facilitate entrepreneurs, and when did they function as agents or perhaps even risk-takers? To answer these questions, this article tracks three layers of public agency: the local, the national, and the European. This article concludes that there were crucial initiatives at all three levels and that these initiatives were not coordinated, but nevertheless connected by a certain zeitgeist—the idea of public institutions taking responsibility for the competitiveness of private companies, an idea that blossomed in the period of high globalization from the late 1980s to the 2000s. In other words, what united the efforts of the public sector was not any master plan but an underlying thought collective that made the workings of “the entrepreneurial state” flexible and fit for the unpredictable nature of innovation. Thus, this article argues that industrial policy did not wither away in the age of neoliberalism but changed its form in an increasing complexity of state-market relations.

scholarly journals Povećana sigurnost radnika primjenom kolaborativnih robota u proizvodnim procesima Industrije 4.0

Sigurnost ◽  
2020 ◽  
Vol 62 (1) ◽  
pp. 11-18
Author(s):  
Isak Karabegović ◽  
Edina Karabegović
Keyword(s):  
First Generation ◽  
Industrial Revolution ◽  
Industrial Robots ◽  
Smart Manufacturing ◽  
Medium Size ◽  
Collaborative Robots ◽  
Production Processes ◽  
Working Together ◽  
Levels Of Automation ◽  
Complete Automation

SUMMARY: By applying Industry 4.0, modernization of the production processes in industry is achieved. However, the safety of workers must be a priority. Automation of production processes and raising it to a higher level can be achieved by employing collaborative robots working together with workers. The degree of safety measures guarantees that there are no work injuries. In using collaborative robots we exploit all the advantages that they possess over first-generation industrial robots. They work together with workers, workers work in a safe environment, robots take up less space, they are not physically separated from workers, they are easy to manipulate, they are cheaper, and are suitable for small and medium size companies. We have the possibility of introducing different levels of automation in the production process, i.e. we can partially automate the tasks where complete automation is too complex or not economical. The use of collaborative robots will grow in the future, since the goals of the fourth industrial revolution cannot be achieved without collaborative robots, in other words, without the "smart manufacturing process" or "smart factory".

scholarly journals Integrated Circuit Board Object Detection and Image Augmentation Fusion Model Based on YOLO

2021 ◽  
Vol 15 ◽  
Author(s):  
Szu-Yin Lin ◽  
Hao-Yu Li
Keyword(s):  
Real Time ◽  
Image Recognition ◽  
Integrated Circuit ◽  
Manufacturing Process ◽  
Circuit Board ◽  
Smart Manufacturing ◽  
Recognition Model ◽  
Second Stage ◽  
Different Types ◽  
Smart Factories

Industry 4.0 has been a hot topic in recent years. The process of integrating Cyber-Physical Systems (CPS), Artificial Intelligence (AI), and Internet of Things (IoT) technology, will become the trend in future construction of smart factories. In the past, smart factories were developed around the concept of the Flexible Manufacturing System (FMS). Most parts of the quality management process still needed to be implemented by Automated Optical Inspection (AOI) methods which required human resources and time to perform second stage testing. Screening standards also resulted in the elimination of about 30% of the products. In this study, we sort and analyze several Region-based Convolutional Neural Network (R-CNN) and YOLO models that are currently more advanced and widely used, analyze the methods and development problems of the various models, and propose a suitable real-time image recognition model and architecture suitable for Integrated Circuit Board (ICB) in manufacturing process. The goal of the first stage of this study is to collect and use different types of ICBs as model training data sets, and establish a preliminary image recognition model that can classify and predict different types of ICBs based on different feature points. The second stage explores image augmentation fusion and optimization methods. The data augmentation method used in this study can reach an average accuracy of 96.53%. In the final stage, there is discussion of the applicability of the model to detect and recognize the ICB directionality in <1 s with a 98% accuracy rate to meet the real-time requirements of smart manufacturing. Accurate and instant object image recognition in the smart manufacturing process can save manpower required for testing, improve equipment effectiveness, and increase both the production capacity and the yield rate of the production line. The proposed model improves the overall manufacturing process.

Leapfrogging through Smart Manufacturing

2020 ◽  
pp. 261-280
Author(s):  
Padmashree Gehl Sampath
Keyword(s):  
Low Income ◽  
Industry 4.0 ◽  
High Technology ◽  
Low Income Countries ◽  
Smart Manufacturing ◽  
Policy Recommendations

Can shifting pathways from manufacturing to ‘smart’ manufacturing become a successful leapfrogging strategy? Can low-income countries use the new features of smart manufacturing activities to reboot their industrialization processes with smaller, but more targeted investments in high-technology manufacturing niches that have potential for expansion? If so, what is the role of industrial hubs in this context? These are the main questions that this chapter seeks to address, with a particular focus on Africa. The chapter argues that the changed nature of innovation—both the incrementality and modularity—lends itself to a leapfrogging paradigm, and a holistic framework can help countries embark on this important transition. The chapter considers the example of Germany, where the Industry 4.0 framework has focused on empowering small and medium-sized enterprises, and proposes a new, more calibrated vision of industrial hubs to support smart manufacturing, with policy recommendations.

scholarly journals Enhancing Sustainability and Energy Efficiency in Smart Factories: A Review

2018 ◽  
Vol 10 (12) ◽  
pp. 4779 ◽  
Author(s):  
Yuquan Meng ◽  
Yuhang Yang ◽  
Haseung Chung ◽  
Pil-Ho Lee ◽  
Chenhui Shao
Keyword(s):  
Energy Efficiency ◽  
Industrial Revolution ◽  
Rapid Development ◽  
Sustainable Manufacturing ◽  
Business Owners ◽  
Smart Manufacturing ◽  
Future Studies ◽  
Manufacturing Technologies ◽  
New Generation ◽  
Smart Factories

With the rapid development of sensing, communication, computing technologies, and analytics techniques, today’s manufacturing is marching towards a new generation of sustainability, digitalization, and intelligence. Even though the significance of both sustainability and intelligence is well recognized by academia, industry, as well as governments, and substantial efforts are devoted to both areas, the intersection of the two has not been fully exploited. Conventionally, studies in sustainable manufacturing and smart manufacturing have different objectives and employ different tools. Nevertheless, in the design and implementation of smart factories, sustainability, and energy efficiency are supposed to be important goals. Moreover, big data based decision-making techniques that are developed and applied for smart manufacturing have great potential in promoting the sustainability of manufacturing. In this paper, the state-of-the-art of sustainable and smart manufacturing is first reviewed based on the PRISMA framework, with a focus on how they interact and benefit each other. Key problems in both fields are then identified and discussed. Specially, different technologies emerging in the 4th industrial revolution and their dedications on sustainability are discussed. In addition, the impacts of smart manufacturing technologies on sustainable energy industry are analyzed. Finally, opportunities and challenges in the intersection of the two are identified for future investigation. The scope examined in this paper will be interesting to researchers, engineers, business owners, and policymakers in the manufacturing community, and could serve as a fundamental guideline for future studies in these areas.

The Role of Robotics Technology and Internet of Things for Industry 4.0 Realization

2021 ◽  
Vol 10 (2) ◽  
pp. 1331-1339
Keyword(s):  
Internet Of Things ◽  
Industrial Robots ◽  
Robotic Systems ◽  
The Internet ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Key Drivers ◽  
The Internet Of Things ◽  
And Robotics

Robotic systems can already proactively monitor and adapt to changes in a production line. Nowadays, internet of things and robotic systems are key drivers of technological innovation trends.Majorcompanies are now making investments in machine learning-powered approaches to improve in principle all aspects of manufacturing. Connecteddevices, sensors, and similar advancements allow people and companies to do things they wouldn't even dream of in earlier eras.For realizing it time series feature extraction approach is selected.Industrial internet of things solutions are poised to transform many industry verticals including healthcare, retail, automotive, and transport. For many industries, the industrial internet of things has significantly improved reliability, production, and customer satisfaction. The internet of things and robotics arecoming together to create the internet of robotic things. Industrial internet of thingis a subset of industry4.0. Itcan encourage smartness at a bigger level in industrial robots.

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