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Journal PROCEEDINGS IN MANUFACTURING SYSTEMS |
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ISSN 2343–7472 ISSN-L 2067-9238 |
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Journal PROCEEDINGS IN MANUFACTURING SYSTEMS
□ Volume 15, Issue 3, 2020
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Gicu
Călin DEAC, Crina Narcisa GEORGESCU, Cicerone Laurențiu POPA, Costel Emil
COTEȚ
Implementation of a virtual reality collaborative platform for Industry 4.0
offices
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Crina Narcisa DEAC, Gicu Călin DEAC, Cicerone Laurențiu POPA, Costel Emil
COTEȚ
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Lucian Nicolae DEMETER, Radu CALISTRU, Bogdan VĂRĂTICEANU, Paul
MINCIUNESCU, Paula ANGHELIȚĂ
Cloud based maintenance IIoT platform for smart manufacturing
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Tiberiu Gabriel DOBRESCU, Cristina Vasilica ICOCIU, Cătălin SILVESTRU,
Nicolae POSTĂVARU
Perspectives in the frame of Resetting Education
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Victor IOSUB, Adrian Florin NICOLESCU, Cristina PUPĂZĂ
Software development for optimizing the palletizing process of KLT
crates
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Liliana STAN, Adrian Florin NICOLESCU, Cristina PUPĂZĂ
Implementation of a virtual reality collaborative platform
for Industry 4.0 offices
Gicu Călin DEAC1,*,
Crina Narcisa GEORGESCU2,
Cicerone Laurențiu
POPA3,
Costel Emil COTEȚ4
1)
PhD student,
Robots and
Manufacturing Systems, University
Politehnica of Bucharest,
Bucharest, Romania
2) PhD student,
Robots and
Manufacturing Systems, University
Politehnica of Bucharest,
Bucharest, Romania
3)
Associate Prof., Ph.D., Robots and Manufacturing Systems,
University Politehnica of Bucharest, Bucharest, Romania
4)
Prof., PhD, Robots and Manufacturing Systems, University
Politehnica of Bucharest, Bucharest, Romania
Abstract:
This paper describes some results of authors'
research for developing a Virtual Reality collaborative
platform for remote teams able to work in a fully equipped
environment that resemble as close as possible
a real
office. The
platform
allows real-time
interaction between user’s
avatars,
using high
quality surround audio messaging, gestures and
physics and includes a large number of tools for
collaborative working such as: remote desktop,
videoconference, white-board, screen sharing, slide
presenter, synchronized
video
player, web
applications,
individual and group
teleporting, animated 3D
model
viewer, advanced user management, IoT telemetry data
visualization, smart factory digital twin
integration.
The platform was implemented for few business cases for
virtual offices, conferences, e-Learning, trade shows and as
a virtual reality interface for a digital tween.
Computerized maintenance
management system (CMMS) IOTIA – maintenance platform implementation for
Industry 4.0
Crina Narcisa DEAC1,*, Gicu Călin DEAC2,
Cicerone Laurențiu POPA3, Costel Emil COTEȚ4
1)
PhD
student, Robots
and Manufacturing Systems, University
Politehnica of Bucharest,
Bucharest, Romania
2)
PhD student,
Robots and
Manufacturing Systems, University
Politehnica of Bucharest,
Bucharest, Romania
3)
Associate Prof., Ph.D., Robots and Manufacturing Systems, University
Politehnica of Bucharest, Bucharest, Romania
4)
Prof., PhD, Robots and Manufacturing Systems, University Politehnica of
Bucharest, Bucharest, Romania
Abstract: IOTIA (Internet of Things and Industrial Automation) Platform is a computerized maintenance management system which manages all type of maintenance within a company: breakdown maintenance, preventive maintenance, predictive maintenance and prognostics and health management, aimed at improving maintenance operations, coordinotion of teams and communication between production and maintenance departments. This software application, unlike existing solutions on the market, is intended to facilitate monitoring, prediction and maintenance interventions at the component / subassembly level and not at the machine level, by creating a virtual configurator based on which production lines can be subsequently defined by simply instantiating all the existing machines in the factory, which have been previously defined and configured in this configurator. Through the configurator, within each machine, its subassemblies and components can be defined, thus optimizing the maintenance process, with a much better view at the component level. Thanks to this virtual configurator, the application becomes very flexible and can be extended, as it can configure any type of machines / production lines and can define any types of maintenance operations. The IOTIA software application is connected to an augmented reality AR application, for tablet / mobile, designed to facilitate the work of field maintenance operators, by quickly and focused visualization of scanned information using QR codes assigned to subassemblies / machines and an application video conference implemented in the IOTIA application, for communication and remote support for maintenance operations.
Cloud based maintenance IIoT platform for smart
manufacturing
Lucian Nicolae DEMETER1,*, Radu CALISTRU2,
Bogdan VĂRĂTICEANU3,
Paul MINCIUNESCU4, Paula ANGHELIȚĂ5
1)
PhD Student, Research engineer, ICPE, Servomotors
Department, Bucharest, România
2)
Research engineer, ICPE, Servomotors Department, Bucharest,
Romania
3)
PhD, Research engineer, ICPE, Servomotors Department,
Bucharest, Romania
4)
PhD, Research engineer, ICPE, Servomotors Department,
Bucharest, Romania
5) PhD, reseArch
engineer, ICPE, Servomotors Department, Bucharest, Romania
Abstract:
The main
objective of CM4SMART project was to perform research,
development, simulation and production implementation of a
smart manufacturing maintenance solution based on cloud
technologies. The result of the project will enable digital
transformation of the production in the direction of smart
maintenance and new data driven production efficiency models
for the SME sector. Following the key Industry 4.0 design
principles, the project has succeeded to interconnect
business level software systems with operational data from
the field thus aligning production schedules with
maintenance activities. Innovative machine learning
algorithms for predictive maintenance analyses data and
propose both preventive and optimization actions before
machine failures take place thus aiming at zero downtime,
zero defected manufacturing and a greener enterprise.
Perspectives in the frame of resetting education
Tiberiu Gabriel DOBRESCU1,*, Cristina Vasilica ICOCIU2, Cătălin SILVESTRU3, Nicolae POSTĂVARU4
1)
Prof., PhD,
Robots and Manufacturing Systems Dept, University "Politehnica" of
Bucharest, Romania
2)
Lecturer, PhD,
Economic Engineering
Dept,
University "Politehnica" of Bucharest, Romania
3)
Assoc.
Prof.,
PhD,
Robots and Manufacturing Systems Dept, University
"Politehnica" of Bucharest, Romania
4)
Prof.,
PhD, Metal structures, management and graphics
engineering
Dept, Technical University of Civil Engineering Bucharest,
Romania
Abstract: With the global reset, we must understand that all economic sectors will regroup, rearrange and reposition in relation to the individual and its values. These include the education sector which, based on the principle of mobility and transparency, must be reconsidered in terms of approach and strategy, in order to meet the requirements of the labour market. The European markets, both education and labour market, in which the free movement of people, goods and services is upheld, change to adapt to global trends, while also putting pressure on markets such as those from Romania, to adapt together. Taking into account this framework, in this article we present some of the measures for the period 2025-2030 that are growing at European level, including digitalization, which is best known in our environment, but it comes with a number of measures that can leave education in Romania behind and increase the distance between the Romanian labour market and the European labour market. We argue in favour of keeping up with the European trends and changes, as these are and will continue to be important for future generations. In order for this to happen, we argue that it is needed to rethink and reinvent education, in line with these trends and changes, in order to align to the rest of the world and continue to be mobile in EU and beyond.
Software development for optimizing the palletizing process of KLT crates
Victor IOSUB1,*, Adrian Florin NICOLESCU2, Cristina PUPĂZĂ3
1)
Eng.. PhD Student, Robotic Specialist, Development and Production
Department, Robital Industrial Supplier SRL, Bucharest, Romania
2) 3) PhD, Prof., Robots and Manufacturing Systems Department., University
"Politehnica" of Bucharest, Romania
Abstract:
The paper presents the
current development of a new software interface for optimizing the
palletizing process of the KLT crates. The algorithm generates a text file
with the coordinates of each box that will be placed on the pallet.
Furthermore, the file is than loaded in the robot controller for changing
the palletizing format. The novelty of the research consists in the software
developed using Visual Studio IDE and programmed in C# language. At this
stage of the development, the resulting file is loaded in the offline
programming and simulating software for Kawasaki Robots, K-ROSET. The
research also comprises an overview of the concepts, a test case, and a
virtual robotic cell designed
in K-ROSET. The virtual model of a palletizing cell was also included.
Reinforcement learning for assembly robots: A review
Liliana STAN1,*, Adrian Florin NICOLESCU2, Cristina PUPĂZĂ2
1)
PhD, student, Robots and Manufacturing Systems Department, Politehnica
University of Bucharest, Romania
2)
Prof. PhD, Robots and Manufacturing Systems Department, Politehnica
University of Bucharest, Romania
Abstract:
This paper
provides a comprehensive introduction to Reinforcement Learning (RL),
summarizes recent developments that showed remarkable success, and discusses
their potential implications for the field of robotics. RL is a promising
approach to develop hard-to-engineer adaptive solutions for complex and
diverse robotic tasks. In this paper RL core elements are reviewed, existing
frameworks are presented, and main issues that are limiting the application
of RL for real-world robotics, such as sample inefficiency, transfer
learning, generalization, and reproducibility are discussed. Multiple
research efforts are currently being directed towards closing the sim-to-real
gap and accomplish more efficient policy transfers methods, making the
agents/robots learn much faster and more efficiently. The focus of this work
is to itemize the various approaches and algorithms that center around the
application of RL in robotics. Finally, an overview of the current
state-of-the-art RL methods is presented, along with the potential
challenges, future possibilities, and potential development directions.
Electronic mail: orgcom@icmas.eu |
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