ArticlePDF Available

Cyber- Physical Systems and Education 4.0 –The Teaching Factory 4.0 Concept

Authors:
  • University of Patras Lab. For Manufacturing Systems and Automation (LMS)
  • Laboratory for Manufacturing Systems and Automation

Abstract and Figures

Manufacturing, through the Industry 4.0 concept, is moving to the next phase of digitalization. Industry 4.0 supported by innovative technologies such as Internet of Things, Cloud technology, Augmented and Virtual Reality will also play an important role in manufacturing education, supporting advanced life-long training of the skilled workforce. Advanced education, also called Education 4.0, and networked ecosystems will develop skills and build competences for the new era of manufacturing. Towards that, this work will present how the adoption of cyber-physical systems and Industry 4.0 technologies, under the teaching factory paradigm will re-shape manufacturing education, addressing the increased need for highly-skilled employees. A teaching factory paradigm supported by Industry 4.0 technology will be presented, considering the construction of a radio-controlled car.
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ScienceDirect
Available online at www.sciencedirect.com
Available online at www.sciencedirect.com
ScienceDirect
Procedia Manufacturing 00 (2017) 000–000
www.elsevier.com/locate/procedia
* Paulo Afonso. Tel.: +351 253 510 761; fax: +351 253 604 741
E-mail address: psafonso@dps.uminho.pt
2351-9789 © 2017 The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the scientific committee of the Manufacturing Engineering Society International Conference 2017.
Manufacturing Engineering Society International Conference 2017, MESIC 2017, 28-30 June
2017, Vigo (Pontevedra), Spain
Costing models for capacity optimization in Industry 4.0: Trade-off
between used capacity and operational efficiency
A. Santanaa, P. Afonsoa,*, A. Zaninb, R. Wernkeb
a University of Minho, 4800-058 Guimarães, Portugal
bUnochapecó, 89809-000 Chapecó, SC, Brazil
Abstract
Under the concept of "Industry 4.0", production processes will be pushed to be increasingly interconnected,
information based on a real time basis and, necessarily, much more efficient. In this context, capacity optimization
goes beyond the traditional aim of capacity maximization, contributing also for organization’s profitability and value.
Indeed, lean management and continuous improvement approaches suggest capacity optimization instead of
maximization. The study of capacity optimization and costing models is an important research topic that deserves
contributions from both the practical and theoretical perspectives. This paper presents and discusses a mathematical
model for capacity management based on different costing models (ABC and TDABC). A generic model has been
developed and it was used to analyze idle capacity and to design strategies towards the maximization of organization’s
value. The trade-off capacity maximization vs operational efficiency is highlighted and it is shown that capacity
optimization might hide operational inefficiency.
© 2017 The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the scientific committee of the Manufacturing Engineering Society International Conference
2017.
Keywords: Cost Models; ABC; TDABC; Capacity Management; Idle Capacity; Operational Efficiency
1. Introduction
The cost of idle capacity is a fundamental information for companies and their management of extreme importance
in modern production systems. In general, it is defined as unused capacity or production potential and can be measured
in several ways: tons of production, available hours of manufacturing, etc. The management of the idle capacity
Procedia Manufacturing 23 (2018) 129–134
2351-9789 © 2018 The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the scientific committee of the 8th Conference on Learning Factories 2018 - Advanced Engineering
Education & Training for Manufacturing Innovation.
10.1016/j.promfg.2018.04.005
10.1016/j.promfg.2018.04.005 2351-9789
© 2018 The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the scientic committee of the 8th Conference on Learning Factories 2018 - Advanced Engineering
Education & Training for Manufacturing Innovation.
Available online at www.sciencedirect.com
ScienceDirect
Procedia Manufacturing 00 (2017) 000–000
w
ww.elsevier.com/locate/procedia
2351-9789 © 2018 The Authors. Published by Elsevier B.V.
Peer review under responsibility of the scientific committee of the 8th Conference on Learning Factories 2018 -
Advanced Engineering Education & Training for Manufacturing Innovation
8th Conference on Learning Factories 2018 - Advanced Engineering Education & Training for
Manufacturing Innovation
Cyber- Physical Systems and Education 4.0 –The Teaching Factory
4.0 Concept
D. Mourtzisa*, E. Vlachoua, G. Dimitrakopoulosa, V. Zogopoulosa
aLaboratory for Manufacturing Systems and Automation, Department of Mechanical Engineering and Aeronautics, University of Patras, Rio
Patras, Greece
Abstract
Manufacturing, through the Industry 4.0 concept, is moving to the next phase of digitalization. Industry 4.0 supported by innovative
technologies such as Internet of Things, Cloud technology, Augmented and Virtual Reality will also play an important role in
manufacturing education, supporting advanced life-long training of the skilled workforce. Advanced education, also called
Education 4.0, and networked ecosystems will develop skills and build competences for the new era of manufacturing. Towards
that, this work will present how the adoption of cyber-physical systems and Industry 4.0 technologies, under the teaching factory
paradigm will re-shape manufacturing education, addressing the increased need for highly-skilled employees. A teaching factory
paradigm supported by Industry 4.0 technology will be presented, considering the construction of a radio-controlled car.
© 2018 The Authors. Published by Elsevier B.V.
Peer review under responsibility of the scientific committee of the 8th Conference on Learning Factories 2018 -
Advanced Engineering Education & Training for Manufacturing Innovation
Keywords: Education 4.0; Teaching Factories; Industry 4.0; Cyber-physical systems
1. Introduction
Manufacturing is an ever-growing economic sector. It is estimated that over the next decade more than 3 million
new jobs will be needed in manufacturing, due to retirements and economic growth [1]. In order to avoid a shortage
of properly trained personnel in all the levels of manufacturing that are capable of dealing with the knowledge
*Corresponding author. Tel.: +30-2610-910-160; fax: +30-2610-997-314
E-mail address: mourtzis@lms.mech.upatras.gr
Available online at www.sciencedirect.com
ScienceDirect
Procedia Manufacturing 00 (2017) 000–000
w
ww.elsevier.com/locate/procedia
2351-9789 © 2018 The Authors. Published by Elsevier B.V.
Peer review under responsibility of the scientific committee of the 8th Conference on Learning Factories 2018 -
Advanced Engineering Education & Training for Manufacturing Innovation
8th Conference on Learning Factories 2018 - Advanced Engineering Education & Training for
Manufacturing Innovation
Cyber- Physical Systems and Education 4.0 –The Teaching Factory
4.0 Concept
D. Mourtzisa*, E. Vlachoua, G. Dimitrakopoulosa, V. Zogopoulosa
aLaboratory for Manufacturing Systems and Automation, Department of Mechanical Engineering and Aeronautics, University of Patras, Rio
Patras, Greece
Abstract
Manufacturing, through the Industry 4.0 concept, is moving to the next phase of digitalization. Industry 4.0 supported by innovative
technologies such as Internet of Things, Cloud technology, Augmented and Virtual Reality will also play an important role in
manufacturing education, supporting advanced life-long training of the skilled workforce. Advanced education, also called
Education 4.0, and networked ecosystems will develop skills and build competences for the new era of manufacturing. Towards
that, this work will present how the adoption of cyber-physical systems and Industry 4.0 technologies, under the teaching factory
paradigm will re-shape manufacturing education, addressing the increased need for highly-skilled employees. A teaching factory
paradigm supported by Industry 4.0 technology will be presented, considering the construction of a radio-controlled car.
© 2018 The Authors. Published by Elsevier B.V.
Peer review under responsibility of the scientific committee of the 8th Conference on Learning Factories 2018 -
Advanced Engineering Education & Training for Manufacturing Innovation
Keywords: Education 4.0; Teaching Factories; Industry 4.0; Cyber-physical systems
1. Introduction
Manufacturing is an ever-growing economic sector. It is estimated that over the next decade more than 3 million
new jobs will be needed in manufacturing, due to retirements and economic growth [1]. In order to avoid a shortage
of properly trained personnel in all the levels of manufacturing that are capable of dealing with the knowledge
*Corresponding author. Tel.: +30-2610-910-160; fax: +30-2610-997-314
E-mail address: mourtzis@lms.mech.upatras.gr
130 D. Mourtzis et al. / Procedia Manufacturing 23 (2018) 129–134
D. Mourtzis et al. / Procedia Manufacturing 00 (2017) 000–000
requirements of an ever-changing sector that integrates technological breakthroughs, it is important to reshape the
methods of manufacturing education, connecting the industry with the engineering educational organizations.
Industry 4.0 era is gradually finding its way of application on the current manufacturing systems, while more and
more studies are focusing on possible future integrations [2]. Industry 4.0 concept introduces innovative technologies
in manufacturing that propose new ways of connectivity and data management (Cloud Technology) and new
environments for knowledge sharing and training (Augmented and Virtual reality) that become embedded in
production. This effort reshapes the current form of production machinery and to upgrade it to cyber-physical systems.
The same technologies may play an important role in manufacturing education. These key enabling technologies
allow the knowledge to be effectively be passed on to future workforce, creating a novel framework of advanced
manufacturing education; Education 4.0. This education system aims to bring new and experienced workforce up to
speed with the innovative proposals of Industry 4.0, creating a sustainable environment that will accelerate its adoption
in manufacturing.
The aim of this paper is to present how the adoption of Education 4.0 systems may affect manufacturing education,
increasing its effectiveness, and how Industry 4.0 technologies may be applied. The technologies will be integrated
under a teaching factory (TF) paradigm that focuses on the design and manufacturing of a radio-controlled car.
2. State of the art
As digitalization increases its effects in modern manufacturing, producing promising results, more and more
companies are marching towards integrating Industry 4.0 technologies in their systems. The applications are targeting
all the steps of design and production, exploiting the increasing acceptance of mobile device applications and Internet
of Things and the advanced connectivity capabilities offered by modern networks [3]. Mobile devices provide a
digitalized input device, that integrates customers in product design [4] and customization [5], while also allowing
production line technicians to monitor production status and call related data and knowledge [6]. Internet of Things
improves customers’ products by transmitting service- supporting data that improve their experience throughout
product’s life cycle [7] while also support the development of shopfloor monitoring and communication applications
[8]. Modern wireless networks, such as 5G, support higher data capacity and connected devices density than ever
before, connecting end- users, smart Things and production related software [9].
Fusing sensors, actuators and high fidelity connectivity on production machinery upgrades it to a Cyber- Physical
System (CPS). CPS embed sensing of their state, that is shared and monitored via network and, based on analysis of
the provided data, actuation and adaptation [10]. Through this channel, the CPS systems are also capable of interacting
with other systems and users of the shop floor creating an Industry 4.0 ecosystem: smart factory [11]. To manage the
growing amount of data, Big Data analytics methods have been used so as to handle, store and analyze them [12]. All
the aforementioned technologies create a complex environment, with multiple system interconnections, which may
be dissuasive for young talents. Teaching factories have arisen as a way to involve practitioners in task-specific
industrial problems in groups, so as to familiarize with the technologies and develop personal skills, while also
providing a useful link for the industry with the educational institutes and the available knowledge [13]. The
participants get to know the industrial practices and experience real industrial cases [14].
Teaching factories are an important way of practicing the technical knowledge that is included in the emerging
Education 4.0 concept. Education 4.0 considers, on the one hand the exploitation of the developed technologies (e.g.
advanced visualization techniques that integrate virtual reality) to facilitate the teaching process and on the other hand
the methods and the workshops that will familiarize the aspiring engineers with these technologies, as will work in
Industry 4.0 environments [15]. As the technology rushes forward, this education concept is becoming more and more
a need and international organizations consider its integration [16]. More specifically, institutions try to establish new
ways of connecting the theoretical knowledge in their faculties with the real cases and implementation of CPS in
industries, creating a win-win situation for both parties.
Although Industry 4.0 has begun being integrated into manufacturing, there is still much to be achieved in the
domain of educating and attracting young talents in the industry. Aiming to bridge the gap between the implementation
of CPS and educational organizations that focus on this field, this study focuses on the development of a contemporary
teaching factory. The study presents all the technologies, the connections that may be implemented under the umbrella
of Education 4.0 so as to upgrade a traditional manufacturing course to a teaching factory 4.0. The combination of
D. Mourtzis et al. / Procedia Manufacturing 00 (2017) 000–000
traditional methods and Industry 4.0 technologies will create a result that will be highly interesting and at the same
time educating for its attendees, aiding their smoothen integration in manufacturing.
3. Architecture of proposed Teaching Factory
The aim of the teaching factory paradigms is to involve aspiring engineers in an environment in close collaboration
with experts on the field so as to familiarize them with its requirements and enhance the collaboration between
involved parties with different knowledge and background. Moreover, it is important to upgrade traditional teaching
factories and expand their contribution, adding emerging digital technologies. Shifting from the traditional teaching
courses to the framework of Education 4.0 requires a careful design and combination of the traditional manufacturing
techniques with the technologies introduced by Industry 4.0. In the figure below, the architecture of the transformation
of a teaching factory towards a Teaching Factory 4.0 paradigm is depicted.
Fig.1. Architecture of the proposed approach.
The goal of the teaching factory 4.0 is the design and manufacturing of a radio-controlled electric car. The
participants, separated in groups, are given the initial requirements of the final solution, some specifications that need
to be met, a set of standardized parts that need to be included in their designs and the available resources for
manufacturing it. In the context, of the proposed architecture, a number of IoT technologies have been integrated:
NFC, AR, VR, Human- Robot collaboration, process data gathering and Big Data analytics. In order to monitor and
evaluate their progress, a near field communication (NFC) card is given to each group; in every stage of the LF, the
group registers the time of start- end and also stores useful information about the task to a cloud database. The
information from each stage is stored in the cloud database and can be assessed by the aspiring engineers so as to
evaluate their performance in each stage.
The first stage is the design of the product. In this stage, the aspiring engineers are called to prepare the initial
design of their product in a Computer Aided Design (CAD) software. The designs from each group are stored to a
central database. The product designs are then used for an augmented/ virtual reality evaluation workshop. The
participants are called to validate their designs in real scale using Augmented Reality and then to simulate the assembly
D. Mourtzis et al. / Procedia Manufacturing 23 (2018) 129–134 131
D. Mourtzis et al. / Procedia Manufacturing 00 (2017) 000–000
requirements of an ever-changing sector that integrates technological breakthroughs, it is important to reshape the
methods of manufacturing education, connecting the industry with the engineering educational organizations.
Industry 4.0 era is gradually finding its way of application on the current manufacturing systems, while more and
more studies are focusing on possible future integrations [2]. Industry 4.0 concept introduces innovative technologies
in manufacturing that propose new ways of connectivity and data management (Cloud Technology) and new
environments for knowledge sharing and training (Augmented and Virtual reality) that become embedded in
production. This effort reshapes the current form of production machinery and to upgrade it to cyber-physical systems.
The same technologies may play an important role in manufacturing education. These key enabling technologies
allow the knowledge to be effectively be passed on to future workforce, creating a novel framework of advanced
manufacturing education; Education 4.0. This education system aims to bring new and experienced workforce up to
speed with the innovative proposals of Industry 4.0, creating a sustainable environment that will accelerate its adoption
in manufacturing.
The aim of this paper is to present how the adoption of Education 4.0 systems may affect manufacturing education,
increasing its effectiveness, and how Industry 4.0 technologies may be applied. The technologies will be integrated
under a teaching factory (TF) paradigm that focuses on the design and manufacturing of a radio-controlled car.
2. State of the art
As digitalization increases its effects in modern manufacturing, producing promising results, more and more
companies are marching towards integrating Industry 4.0 technologies in their systems. The applications are targeting
all the steps of design and production, exploiting the increasing acceptance of mobile device applications and Internet
of Things and the advanced connectivity capabilities offered by modern networks [3]. Mobile devices provide a
digitalized input device, that integrates customers in product design [4] and customization [5], while also allowing
production line technicians to monitor production status and call related data and knowledge [6]. Internet of Things
improves customers’ products by transmitting service- supporting data that improve their experience throughout
product’s life cycle [7] while also support the development of shopfloor monitoring and communication applications
[8]. Modern wireless networks, such as 5G, support higher data capacity and connected devices density than ever
before, connecting end- users, smart Things and production related software [9].
Fusing sensors, actuators and high fidelity connectivity on production machinery upgrades it to a Cyber- Physical
System (CPS). CPS embed sensing of their state, that is shared and monitored via network and, based on analysis of
the provided data, actuation and adaptation [10]. Through this channel, the CPS systems are also capable of interacting
with other systems and users of the shop floor creating an Industry 4.0 ecosystem: smart factory [11]. To manage the
growing amount of data, Big Data analytics methods have been used so as to handle, store and analyze them [12]. All
the aforementioned technologies create a complex environment, with multiple system interconnections, which may
be dissuasive for young talents. Teaching factories have arisen as a way to involve practitioners in task-specific
industrial problems in groups, so as to familiarize with the technologies and develop personal skills, while also
providing a useful link for the industry with the educational institutes and the available knowledge [13]. The
participants get to know the industrial practices and experience real industrial cases [14].
Teaching factories are an important way of practicing the technical knowledge that is included in the emerging
Education 4.0 concept. Education 4.0 considers, on the one hand the exploitation of the developed technologies (e.g.
advanced visualization techniques that integrate virtual reality) to facilitate the teaching process and on the other hand
the methods and the workshops that will familiarize the aspiring engineers with these technologies, as will work in
Industry 4.0 environments [15]. As the technology rushes forward, this education concept is becoming more and more
a need and international organizations consider its integration [16]. More specifically, institutions try to establish new
ways of connecting the theoretical knowledge in their faculties with the real cases and implementation of CPS in
industries, creating a win-win situation for both parties.
Although Industry 4.0 has begun being integrated into manufacturing, there is still much to be achieved in the
domain of educating and attracting young talents in the industry. Aiming to bridge the gap between the implementation
of CPS and educational organizations that focus on this field, this study focuses on the development of a contemporary
teaching factory. The study presents all the technologies, the connections that may be implemented under the umbrella
of Education 4.0 so as to upgrade a traditional manufacturing course to a teaching factory 4.0. The combination of
D. Mourtzis et al. / Procedia Manufacturing 00 (2017) 000–000
traditional methods and Industry 4.0 technologies will create a result that will be highly interesting and at the same
time educating for its attendees, aiding their smoothen integration in manufacturing.
3. Architecture of proposed Teaching Factory
The aim of the teaching factory paradigms is to involve aspiring engineers in an environment in close collaboration
with experts on the field so as to familiarize them with its requirements and enhance the collaboration between
involved parties with different knowledge and background. Moreover, it is important to upgrade traditional teaching
factories and expand their contribution, adding emerging digital technologies. Shifting from the traditional teaching
courses to the framework of Education 4.0 requires a careful design and combination of the traditional manufacturing
techniques with the technologies introduced by Industry 4.0. In the figure below, the architecture of the transformation
of a teaching factory towards a Teaching Factory 4.0 paradigm is depicted.
Fig.1. Architecture of the proposed approach.
The goal of the teaching factory 4.0 is the design and manufacturing of a radio-controlled electric car. The
participants, separated in groups, are given the initial requirements of the final solution, some specifications that need
to be met, a set of standardized parts that need to be included in their designs and the available resources for
manufacturing it. In the context, of the proposed architecture, a number of IoT technologies have been integrated:
NFC, AR, VR, Human- Robot collaboration, process data gathering and Big Data analytics. In order to monitor and
evaluate their progress, a near field communication (NFC) card is given to each group; in every stage of the LF, the
group registers the time of start- end and also stores useful information about the task to a cloud database. The
information from each stage is stored in the cloud database and can be assessed by the aspiring engineers so as to
evaluate their performance in each stage.
The first stage is the design of the product. In this stage, the aspiring engineers are called to prepare the initial
design of their product in a Computer Aided Design (CAD) software. The designs from each group are stored to a
central database. The product designs are then used for an augmented/ virtual reality evaluation workshop. The
participants are called to validate their designs in real scale using Augmented Reality and then to simulate the assembly
132 D. Mourtzis et al. / Procedia Manufacturing 23 (2018) 129–134
D. Mourtzis et al. / Procedia Manufacturing 00 (2017) 000–000
process using Virtual Reality; the process is also validated by engineers experienced in product design who may
provide remarks and suggestions. In the first phase, the teaching factory participants get to interact with their design,
examine it and detect any flaws that could drastically affect the final assembly and the functionality of the final
solution. As the participants lack the experience to early detect these flaws and to produce a first-time-right design,
this digital prototype and the realistic interaction with it facilitates them to detect their errors, at this early stage.
Moreover, through the virtual reality simulation of the assembly, they may test the assembly of the designed parts.
The time it takes them to complete the virtual assembly is tracked and stored; any delays detected at this stage should
be noted as it may reflect potential errors in the initial design.
The second part of the teaching factory revolves around the manufacturing of the parts of the remotely controlled
car. Based on their designs, the participants are called to simulate and schedule a production line that will be
manufacturing the designed product. The aspiring engineers are called to use novel software packages that support
the simulation of the production line and the scheduling of the task so as to meet different demand profiles. The
provided cases simulate realistic scenarios provided by the collaborating engineers that the aspiring engineers will be
called to face in their future involvement in manufacturing. Additionally, in the proposed framework, the data from
each group are directly stored in the TF database, where the participants may compare their proposed shop floor setup
and the achieved performance with the other groups, evaluating their own proposals. This procedure aims to involve
the group in a self- evaluating improvement, during which they familiarize with a simulation software and eventually
the requirements of a production line. After simulating the production and familiarizing with the theoretical
background of each process required, the participants are called to manufacture the parts for their product. The
teaching factory offers them three processes to utilize: milling, drilling and turning. Each station/ machinery is
upgraded in a Cyber- Physical System (CPS) equipped with sensors that monitor the process and are connected with
a wireless network that collects all the recorded data and stores them in the TF database. Each group uses the given
NFC card to state their group number and the starting time of each process, and under the supervision of an experienced
operator of the machinery, create the required parts. The data from the installed sensors are recorded and sent to the
central database and also to a mobile device application from which the participant may read the recorded data in real
time, monitor the status of the machine and notice any deviations. Through this part of the teaching factory 4.0, the
participants familiarize themselves with the Industry 4.0 technologies that shape manufacturing and start to be
integrated into production lines.
The final phase of the teaching factory is the assembly of the final product, which is performed in two parts. The
first part is performed with the aid of a robotic arm, also under the human-robot collaboration framework. Since the
majority of the assembly processes in modern manufacturing is performed by automations, it is important that
Education 4.0 integrates these approaches in the courses and learning workshops. The aspiring engineers are called to
collaborate with the robot in an assembly process, using augmented reality goggles to see the instructions and find out
what to do, the trajectory of the robot when it is moving, and also communicate with it through a smart watch [17].
Through the smart watch, the operator may interact wirelessly with the robot, confirming the completion of an action,
seeing useful notifications and validating the completion of the whole task. During the task, each group collects data
about the time required for task completion and also from the PLC of the robot, thus creating a useful dataset about
the task, from which they may draw some information. Furthermore, the aspiring engineers are called to manually
finalize the assembly of the radio-controlled electric car, supported by an experienced technician. Following the
directives of digitalization introduced by Industry 4.0, the participants wear a smart glove during the assembly process.
The smart glove hosts sensors that track the movements, grasps and assemblies of the operator creating a map of its
movements. Using the NFC card, each group indicates the beginning and competing time of each assembly step.
Moreover, to support this process, the operator may use a mobile device application that utilizes augmented reality to
visualize assembly instructions for the standardized parts of the designed car. Through the recorded data and in close
collaboration with an experienced operator, each group may evaluate their performance in the assembly process, by
monitoring the required time and detecting redundant movements that could result in an error in the original design
or manufacturing.
After the completion of the final assembly, each group tests the produced radio-controlled electric car, testing it in
a sequence of trials. All and all, completing the teaching factory 4.0, the participants acquire a set of highly useful
skills that will support their integration in manufacturing. Apart from familiarizing themselves with the traditional
steps of product design and manufacturing tools, the aspiring engineers become educated in the technologies dictated
D. Mourtzis et al. / Procedia Manufacturing 00 (2017) 000–000
by Industry 4.0 and will shape future manufacturing. Teaching factories, following the technological breakthroughs,
are evolving under the Education 4.0 concept, providing an environment that will support the industry in implementing
novel technologies in their activities, exploiting the knowledge provided by the technological institutes. Additionally,
it makes the aspiring engineers used to working in the industrial environments, in realistic conditions and considering
resources and design limitations formed together with industry experts, as they will be called to do in their future
careers.
4. Case Study
The developed approach is tested on a teaching factory course use case. The course is broken down into seven
steps, where the participants, separated in groups, go from the design to the manufacturing and the assembly of a
radio-controlled car. In each part, Industry 4.0 technologies have been considered, creating a holistic experience for
the participants, and also providing input for the collaborating engineers regarding the challenges and possibilities
offered by the novel technologies.
Fig.2. Teaching Factory 4.0 paradigm.
More specifically, in the design phase the participants are called to initially design the car, using a set of given
electrical parts, visualize how the car looks using Virtual Reality and then simulate the scheduling of producing this
car in a production line to meet certain production volume requirements. Then, they proceed to the manufacturing of
the required parts through material removal processes, such as drilling, milling and turning, after that they assemble
the parts with an industrial robot and then manually. This teaching factory educated the participants on the phases
required in product design and production, while getting practical experience in manufacturing processes. Education
4.0 directives were applied in the current method, in an effort to familiarize the students with the novel technologies.
Each group is equipped with an NFC card, which is used to track the progress of the group throughout the process
while also the team may gather useful data from sensors installed on the machines they utilize. All the steps of the
process were digitalized so as to provide data on the corresponding task that can be analyzed by the participants and
evaluate their performance. Design was connected with advanced visualization technologies, such as virtual and
augmented reality, for digital prototyping, manufacturing was supported by data gathering from the machines using
sensors, collaboration between the operators and robots in assembly tasks that was supported by mobile devices, such
as smartwatches and tablets, which increased the available knowledge during the task. Using these technologies under
a teaching factory 4.0 paradigm, introduces the aspiring engineers in the utilization of advanced visualization and
simulation techniques that can be used in product design and familiarizes the participants with the cyber- physical
systems that shape modern manufacturing.
Familiarizing with these features that are forming the cyber-physical systems of future production lines, prepares
the aspiring engineers for the manufacturing environments that they will work in the future. Data integration and
analysis on the data gathered from the simulation, the manufacturing processes and the assembly of the final parts,
provides an insight for the students to better understand the steps of product design and manufacturing and evaluate
their performance during the teaching factory 4.0. Through data analysis, the participants become aware of their
D. Mourtzis et al. / Procedia Manufacturing 23 (2018) 129–134 133
D. Mourtzis et al. / Procedia Manufacturing 00 (2017) 000–000
process using Virtual Reality; the process is also validated by engineers experienced in product design who may
provide remarks and suggestions. In the first phase, the teaching factory participants get to interact with their design,
examine it and detect any flaws that could drastically affect the final assembly and the functionality of the final
solution. As the participants lack the experience to early detect these flaws and to produce a first-time-right design,
this digital prototype and the realistic interaction with it facilitates them to detect their errors, at this early stage.
Moreover, through the virtual reality simulation of the assembly, they may test the assembly of the designed parts.
The time it takes them to complete the virtual assembly is tracked and stored; any delays detected at this stage should
be noted as it may reflect potential errors in the initial design.
The second part of the teaching factory revolves around the manufacturing of the parts of the remotely controlled
car. Based on their designs, the participants are called to simulate and schedule a production line that will be
manufacturing the designed product. The aspiring engineers are called to use novel software packages that support
the simulation of the production line and the scheduling of the task so as to meet different demand profiles. The
provided cases simulate realistic scenarios provided by the collaborating engineers that the aspiring engineers will be
called to face in their future involvement in manufacturing. Additionally, in the proposed framework, the data from
each group are directly stored in the TF database, where the participants may compare their proposed shop floor setup
and the achieved performance with the other groups, evaluating their own proposals. This procedure aims to involve
the group in a self- evaluating improvement, during which they familiarize with a simulation software and eventually
the requirements of a production line. After simulating the production and familiarizing with the theoretical
background of each process required, the participants are called to manufacture the parts for their product. The
teaching factory offers them three processes to utilize: milling, drilling and turning. Each station/ machinery is
upgraded in a Cyber- Physical System (CPS) equipped with sensors that monitor the process and are connected with
a wireless network that collects all the recorded data and stores them in the TF database. Each group uses the given
NFC card to state their group number and the starting time of each process, and under the supervision of an experienced
operator of the machinery, create the required parts. The data from the installed sensors are recorded and sent to the
central database and also to a mobile device application from which the participant may read the recorded data in real
time, monitor the status of the machine and notice any deviations. Through this part of the teaching factory 4.0, the
participants familiarize themselves with the Industry 4.0 technologies that shape manufacturing and start to be
integrated into production lines.
The final phase of the teaching factory is the assembly of the final product, which is performed in two parts. The
first part is performed with the aid of a robotic arm, also under the human-robot collaboration framework. Since the
majority of the assembly processes in modern manufacturing is performed by automations, it is important that
Education 4.0 integrates these approaches in the courses and learning workshops. The aspiring engineers are called to
collaborate with the robot in an assembly process, using augmented reality goggles to see the instructions and find out
what to do, the trajectory of the robot when it is moving, and also communicate with it through a smart watch [17].
Through the smart watch, the operator may interact wirelessly with the robot, confirming the completion of an action,
seeing useful notifications and validating the completion of the whole task. During the task, each group collects data
about the time required for task completion and also from the PLC of the robot, thus creating a useful dataset about
the task, from which they may draw some information. Furthermore, the aspiring engineers are called to manually
finalize the assembly of the radio-controlled electric car, supported by an experienced technician. Following the
directives of digitalization introduced by Industry 4.0, the participants wear a smart glove during the assembly process.
The smart glove hosts sensors that track the movements, grasps and assemblies of the operator creating a map of its
movements. Using the NFC card, each group indicates the beginning and competing time of each assembly step.
Moreover, to support this process, the operator may use a mobile device application that utilizes augmented reality to
visualize assembly instructions for the standardized parts of the designed car. Through the recorded data and in close
collaboration with an experienced operator, each group may evaluate their performance in the assembly process, by
monitoring the required time and detecting redundant movements that could result in an error in the original design
or manufacturing.
After the completion of the final assembly, each group tests the produced radio-controlled electric car, testing it in
a sequence of trials. All and all, completing the teaching factory 4.0, the participants acquire a set of highly useful
skills that will support their integration in manufacturing. Apart from familiarizing themselves with the traditional
steps of product design and manufacturing tools, the aspiring engineers become educated in the technologies dictated
D. Mourtzis et al. / Procedia Manufacturing 00 (2017) 000–000
by Industry 4.0 and will shape future manufacturing. Teaching factories, following the technological breakthroughs,
are evolving under the Education 4.0 concept, providing an environment that will support the industry in implementing
novel technologies in their activities, exploiting the knowledge provided by the technological institutes. Additionally,
it makes the aspiring engineers used to working in the industrial environments, in realistic conditions and considering
resources and design limitations formed together with industry experts, as they will be called to do in their future
careers.
4. Case Study
The developed approach is tested on a teaching factory course use case. The course is broken down into seven
steps, where the participants, separated in groups, go from the design to the manufacturing and the assembly of a
radio-controlled car. In each part, Industry 4.0 technologies have been considered, creating a holistic experience for
the participants, and also providing input for the collaborating engineers regarding the challenges and possibilities
offered by the novel technologies.
Fig.2. Teaching Factory 4.0 paradigm.
More specifically, in the design phase the participants are called to initially design the car, using a set of given
electrical parts, visualize how the car looks using Virtual Reality and then simulate the scheduling of producing this
car in a production line to meet certain production volume requirements. Then, they proceed to the manufacturing of
the required parts through material removal processes, such as drilling, milling and turning, after that they assemble
the parts with an industrial robot and then manually. This teaching factory educated the participants on the phases
required in product design and production, while getting practical experience in manufacturing processes. Education
4.0 directives were applied in the current method, in an effort to familiarize the students with the novel technologies.
Each group is equipped with an NFC card, which is used to track the progress of the group throughout the process
while also the team may gather useful data from sensors installed on the machines they utilize. All the steps of the
process were digitalized so as to provide data on the corresponding task that can be analyzed by the participants and
evaluate their performance. Design was connected with advanced visualization technologies, such as virtual and
augmented reality, for digital prototyping, manufacturing was supported by data gathering from the machines using
sensors, collaboration between the operators and robots in assembly tasks that was supported by mobile devices, such
as smartwatches and tablets, which increased the available knowledge during the task. Using these technologies under
a teaching factory 4.0 paradigm, introduces the aspiring engineers in the utilization of advanced visualization and
simulation techniques that can be used in product design and familiarizes the participants with the cyber- physical
systems that shape modern manufacturing.
Familiarizing with these features that are forming the cyber-physical systems of future production lines, prepares
the aspiring engineers for the manufacturing environments that they will work in the future. Data integration and
analysis on the data gathered from the simulation, the manufacturing processes and the assembly of the final parts,
provides an insight for the students to better understand the steps of product design and manufacturing and evaluate
their performance during the teaching factory 4.0. Through data analysis, the participants become aware of their
134 D. Mourtzis et al. / Procedia Manufacturing 23 (2018) 129–134
D. Mourtzis et al. / Procedia Manufacturing 00 (2017) 000–000
mistakes in the earlier steps of design, thus preventing errors that may be critical in the next steps, while also
familiarizing themselves with machine monitoring, understanding of the recorded data and how they may be utilized
for predictions.
5. Conclusions and Future work
This paper presents a holistic approach for moving from the traditional teaching factory to teaching factory 4.0,
integrating Cyber- Physical Systems and Industry 4.0 technologies. The developed framework aims to support the
Education 4.0 concept, where the trainers utilize Industry 4.0 technologies to actively involve the aspiring engineers
in realistic simulations that increase the perception of the studied material. Additionally, teaching factories 4.0 serve
as an introduction for the aspiring engineers to the newly developed and implemented technologies, through
workshops that call the participants to utilize these technologies as a mean that will improve the quality and the
effectiveness of their tasks, potentially unlocking new capabilities. The implementation of these technologies in the
teaching factories will also boost their integration in manufacturing, as the new engineers that have familiarized
themselves with the true potential and the capabilities offered by Industry 4.0 will seek for opportunities to consider
these technologies in their works.
Future work on the proposed approach will focus on the integration of other technologies of Industry 4.0 in the
proposed teaching factory. Additionally, based on the proposed teaching factory paradigm, another teaching factory
course will be developed, which will focus on high school students, providing them a brief insight about the tasks that
undergo in product design and manufacturing and how emerging digital technologies have affected them so as to raise
their interest from a younger age to be involved in a manufacturing related career.
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