Messages
Proposals
Get Urgent Help In Your Essays, Assignments, Homeworks, Dissertation, Thesis Or Coursework Writing
100% Plagiarism Free Writing - Free Turnitin Report - Professional And Experienced Writers - 24/7 Online Support
Abstract of smart
manufacturing factory with intelligent assembly technology and systems in
phased Implementations
It can be noted that from the past few years’ technologies have been increased. This is due to the implementation of the Internet of things (IoT), Artificial intelligence (AI), Machine to Machine communication (M2M), Virtual reality (VR), and machine learning. These technologies are implemented in manufacturing, improving product performance, and production processes. Due to this in August 2018, ARTC had launched the first model factory that contained intelligent technology in Singapore. This was done by the collaboration of different technology companies involved in the development of the future of manufacturing (FoM) technologies. Moreover, all of these technologies are based on real problems from different companies based on discrete manufacturing. After some time at the centre of the Model Factory, there was complete digitalized tested was implemented, and then it was expanded in different phases by adding various technologies like a collaborative robot’s assembly setup. Moreover, this setup was enhanced with a digital twin, Smart inventory control, intelligent tracking, Arkite’s Human interface male, Pick to light. In this paper, there is complete information about the experience of adding such features in phases and further enhancement.
Keywords: Internet of Things (IoT); Artificial Intelligence (AI); Virtual Reality (VR); Model Factory; Future of Manufacturing (FoM)
1. Introduction of
smart manufacturing factory with intelligent assembly technology and systems in
phased Implementations
According to the facts the warehouse is
referred as the labour incentive, time consuming and expansive operation in the
manual warehouse. Due to this case, the future of warehouses is going to
convert into smart and automatic warehouses. In such warehouses different
technological equipment and tools will operate for carrying out different kind
of tasks in the organization. Advanced
Remanufacturing and technology centre (ARTC) is built with a private-public
partnership. It was done with the Agency for Science, Nanyang Technological
University, Technology, and research and some other industry partners present
in Singapore. The main aim of this company is to develop some advanced
manufacturing and remanufacturing capabilities for industrial applications. Due
to this case, Industry 4.0 was referred to as the current powerful emerging
trend of data exchange manufacturing and automation in manufacturing
technologies. There are some strategies
implemented in industry 4.0 include cyber-physical systems, cloud computing,
cognitive computing, and industrial internet of things (IIoT) [1]. After this
ARTC started the implementation of digitalized assembly. It was tested in the
Smart Manufacturing factory. There is some information about the data
technologies used by ARTC are given below.
·
The first one is related to the human
collaborative robots Assembly setup (HCRAS). This setup was enhanced with
digital twin technology. It was used for maximizing performance and tracking
during the assembly process [2].
·
The next one is related to intelligent tracking
systems. These systems are based on Ultra-wideband (UWB) and Bluetooth low
energy (BLE). Moreover, it also includes a pressure mat combination that will
allow the smart centralized system. This system can easily detect the presence
of a person present at the lean line area of the model factory. Due to this
workplace safety is increased.
·
The third one is related to the smart inventory
control system. It will help to monitor the quality of the material by applying
different weight sensors and triggers. Moreover, it will update the multiple manufacturing execution
systems (MES). Due to the implementation of multiple MES, it will become simple
to execute the manufacturing process according to the digital standard
operating procedures (SOPs). It will improve and enhance the production output
and it is extremely beneficial for new operators [3].
In this report authors
discussed about lightweight Security Scheme that can be used for Internet of
Things applications. In a specific condition where current situations is not an
effective procedure or exhibit some issues, the effect as well as the
alternative solution is public key infrastructure. The minimization of
communication is the latest approach presented by researchers to overcome the
problems.
Vulnerable
attack of smart manufacturing factory with intelligent assembly technology and
systems in phased Implementations
Upon the IoT system the
Vulnerable attacks is used to steal the information. The connection of the IoT
with the internet creates the authentication as well as integrity issues by the
various internal attacks data. IoT connectivity along with the internet is also
support the physical attacks. Whereas the low-end IoT attacks is not capable to
perform in the efficient manner for the constrain sources. The significant role
of Internet of Things connections in real life improves the way of
communication and interaction with the services. Use of Internet of Things
improves Home Automation, Logistics, smart cities, smart agriculture,
Healthcare, security, and military surveillance. Internet of things is getting appreciable acceptance
and practical usage by applying ipv6. Ipv6 is a larger address space that
enables the Machines to connect through the internet. The network connection of
these devices has some threats; therefore, increasing the number of devices in
the network increases the rate of threats. Machines show Limited energy,
computation processes, and processing powers for future Internet of Things
applications. The security mechanism of IoT system that can increase the
resistance of attacks is considered in many types of research.
Figure 1: Smart industry design
Literature
review of smart manufacturing factory with intelligent assembly technology and
systems in phased Implementations
According to the author
APPLESON (2019), it conducted that for the advanced manufacturing of smart factory
problem the IoT proposed following solution for the system
·
Increased safety
·
Improved efficiency
IoT stands for the
internet of things. It is a system of many related computing devices and
digital devices that are connected over a network that does not require
human-to-human or human-to- computer interaction. One of the best examples of
IoT is smart homes. One of the biggest concerns with IoT devices is security because
of the limited computer power these devices have. One of the biggest security
concerns with IoT devices is on authentication and to cater is the use of
secure communication via TSL and use proper authentication and authorization
mechanism. IoT devices like any device on the web are prone to injection
attacks like SQL injection or injection etc. As IoT devices have to be accessed
remotely, developers need to have an anti-root policy which will detect any
suspicious attempt and will lock out any intercepting traffic. Packet
interception can happen as with limited resources it might not be feasible
because of limited computing resources IoT devices have. To cater to this,
developers ensure TLS communication. It can be seen that the control of smart
factory application is extremely difficult. From the recent few years, it can
be noted that there are some challenges that are faced due to real time
monitoring. In the first section, it is regarding to the existing challenges to
the real time monitoring and the next one related to the challenges related to
the smart grid application control.
According
to the Author Tank, Upadhyay, & Patel(2016), it is conducted that In
Internet of Things, the most challenging issues are probably security and
privacy, and when it is said that have worked over consideration of these two
issues and challenges related to privacy in Internet of Things available
solutions. However, the security issues under higher consideration are
availability and integrity while on the other hand privacy issues include
security of Information and protection of the data; they deal with the
complimentary requirement of IoT networks
Figure 2: IoT systems
The demand of IoT system
is increasing in the market but security issues are major risks. There are six
areas through which developers and manufacturers can minimize the risk and
security of IoT devices can be improved. The six areas include physical security,
manufacturing through back door, secure coding of devices and software,
encryption of data, authentication of the device identity, and streamline
process to update the whole system. The security authentication for individual
devices allows developing device community system along with backend control
system and management console. The only requirement of individual device for
the identification base solution is PKI. The secure coding solution can be
implemented to secure coding practices and to apply devices through software
processing. The data reduction process increases and eventually the reliability
of the network also increase
Figure 3: IoT in industry
Artificial
Intelligence of smart manufacturing factory with intelligent assembly
technology and systems in phased Implementations
The industrial AI use on
the helping of the enterprise monitors, which control and optimizes the behaviour
of the operations along with the systems that enhance the efficiency along with
the performance of the system. Information on the AI by the PLC which is based
on the control systems. One of the most common issues of PLC control system
failure is the consideration for the module failure, bad network connections,
power outages, steam overheating, electromagnetic interferences at different
levels, and the moisture content during operation. Now there is the following
application of the Artificial intelligence (AI) in the industrial control
The automation we all as
control; the engineers have to employ the AI (artificial intelligence) which is
prevents the losses in the production.
Advancement in the PLC
which created the systems by the substantial computing power
Arithmetic instruction in
the PLC involves the basic four operations like the addition, subtraction and
the multiplication and divisions For any modern industrial operation, the
control system is the heart of the system, which is obtained through the
different organization and its seek to reap the benefits of the control of AL
in a PLC circuit. The main issues which focused on the PLC are that the
approaches are independent where the different points are a capture, and the
PLC circuits are intolerant for the variations of the environment in various
positions to manipulating.
These types of machines
are used in huge industries and companies. There are a lot of applications of
such machines some of them are given below
These machines are used
where there is a need to wash the metal parts. The next application is related
to the manufacturing of the clip springs. These machines are also used for
metal stamping. Such machines are also used for manufacturing fabricated steel
or metal sheets. These machines are also useful where there is a need to
manufacture wire forms.
Advantages
and disadvantages of smart manufacturing factory with intelligent assembly
technology and systems in phased Implementations
There are a lot of
advantages and disadvantages of rapid prototypes. In this section, there is a
complete discussion on its pros and cons.
Speed of
smart manufacturing factory with intelligent assembly technology and systems in
phased Implementations
The speed of such
machines is extremely fast. Such machines are able to fabricate the metal parts
in the blink of an eye. Through the help of these machines, it is easy to
design and test the product in a quite small period of time. Through this
machine, it is possible to evaluate the product that is according to the
requirement of the company. If the design of the product is good, then it can
be used, and it is not perfect, they can be discarded easily when there is any
defect in that model
Cost
of smart manufacturing factory with intelligent assembly technology and systems
in phased Implementations
It can be noted that this
machine is highly cost-effective than the others related to prototyping. The
main reason is that the companies that are using these machines are dealing
with low volume production.
Manufacturing of
smart manufacturing factory with intelligent assembly technology and systems in
phased Implementations
Such machines are able to
manufacture any kind of metal part in a proper way. The reason is that the
design is made on the site file and then moved towards that machine. This
machine is able to manufacture any kind of metal.
Disadvantages
of smart manufacturing factory with intelligent assembly technology and systems
in phased Implementations
There are some
disadvantages that include
Less
analysis
The main reason is that
these machines are focusing on limited prototypes. The product developer is
unable to perform a complete analysis while completing this product.
A
low number of options of smart
manufacturing factory with intelligent assembly technology and systems in
phased Implementations
This machine is providing
a quite low number of options for the product developer. In the industry, there
are different options available for the manufacturing of the products, but it
only gives some of them.
Characteristics
of the material involved of smart manufacturing factory with intelligent
assembly technology and systems in phased Implementations
The materials that are
used for the manufacturing of such metal parts from this machine include
stainless steel, aluminium, and titanium. All of these materials are extremely
hard and contains a high melting rate. Also, these materials are highly
flexible and easy to use in that machine.
Description
of the safety consideration
Before making any
product, it is the main duty of the product developer to consider these safety
considerations. He must have to protect his body from the hot metal. The
product developer also has to keep the area completely clean without any dust.
Moreover, he has to use gloves and different things to protect him from any
kind of hazards.
2. Intelligent Robot
Pick-and-Place system
Furthermore, the next technology is related to the intelligent robot, Pick-and-Place system that contains complete motion planning and classifies every part from a trolley by using computer vision technology. There is also the use of the 3D camera that will capture the image of the parts and perfectly analyze its position and then transmit it to the industry PC by OPC unified architecture. Then it will move for further processing and planning of the coordinates used for collaborative movement and enable the system to pick and place the parts according to the required system [4], [5].
Figure 4: Simple pick and place
robotic arm
It can be noted that machines are playing a main role
for making our lives easy and comfortable. It is helping to minimize the
manpower required in factories. This is because most of the work is done by
machines. The human arms are converted into robot arms. The working of pick and
place robot arm is extremely simple. Moreover, this robotic arm can be easily
designed in different ways according to the requirement of the factory. Such
robots are heavily depended on joints. Moreover, all of these joints are used
for joining the two consecutive bodes of the robot. These joints are named as
linear and rotatory. There are some important components present in the robotic
arm.
Controller of smart manufacturing
factory with intelligent assembly technology and systems in phased
Implementations
It is considered as the brain of the system. It will
help the robot to make different kind of movement properly. It is also keeping
proper track of the time, movement of the manipulator and the position of the
joints. This control system is divided into three categories that are
mechanical, hydraulic and electrical.
The mechanical part is considered as most basic part. The means that it is used in the form of programmable devices that are not existed. The main purpose of the robotic arms is to give proper response on the dynamic movement related to the required objective. This is done by mechanical linkage and cam. On the other hand, for hydraulic system Pascal law is used. It is using the values and pistons to control the movement of the robot. This type of controller is also used for such robot arms that are going to lift heavy and precise loads in the factories. This is because such loads requires high precision and accuracy. The last category is related to electrical. It is showing that the type of control is completely convenient, reasonably, quiet, clean and fact. The electrical control is used in such robot arms that requires close tolerance accuracy.
Figure 5: Automatic Pick and
place robotic arm in industry
Manipulator of
smart manufacturing factory with intelligent assembly technology and systems in
phased Implementations
It can be observed that
the entire mechanism of the robot that is involved in providing complete
support and degree of freedom is manipulator. Moreover, the joints of this
manipulator are movable components that will enable pure relative motion
between these links. These links are consisted of arm, base and gripper.
The gripper of the robot
arm is quite same to the human hand. It is also just like the grip of the hand
when it is going to perform any task. Another thing is that the gripper is
involved in securing the work piece during the operation. Moreover, the nature and grip strength is varied
according to the object. This shows that its shape is determined according to
the given task.
The next point is that in
automatic robotic arms there are sensors. These sensors are used to sense the
external and internal state of the robot. It will also allow the robot to make
required functions smoothly and accurately
Figure 6: Pick and place robotic
arm in warehouse
3. Wireless sensor Networks of smart manufacturing
factory with intelligent assembly technology and systems in phased
Implementations
The next technology is related to wireless sensor
networks (WSNs). It will enable the new paradigm of huge measurement for
recording and monitoring the physical condition into proper data and stored in
required locations. Moreover, this technology is implemented in the production
line and it will enable distributed computing, processing data locally, and
then send this information through a wireless system by OPCUA [6]. Moreover, a
smart safety projector is applied on the shop floor with a standard video projector
contain additional input devices. They are connected and build a video to any
flat surface. But the fact is that due to the installation of smart safety
projector at the workplace. It will permit to project a safety barrage
containing a warning. The wireless sensor
network (WSN’s) is composed of a large number of wireless networked sensors and
it works in a hostile environment for the maximum possible duration without
having any kind of human intervention. In the typical case of the sensor node,
the miniature devices are used including sensing unit for the data acquisition,
communication unit for the data reception and transmission between the
connected devices, microcontroller for the processing of local data, memory
operations as a power source with the small battery. The support of wireless
sensor networks (WSN’s) consists of a wide range of applications such as
environmental monitoring, target tracking, health monitoring, and system
control. The goal is to detect the smart manufacturing factor or ordinary
factory method that measures different communication stages with the sensing
ranges. The full coverage implies connectivity between all the active nodes.
There are different types of application scenarios that involve battery-powered
nodes that become active for a long period, external human control, and initial
deployment. If there are not enough energy-efficient techniques, the nodes
drain all the battery of the system within some period. The designed protocol
enables the minimization of energy consumption.
4. The pick to light
technology of smart manufacturing factory with intelligent assembly technology
and systems in phased Implementations
Another technology that is used in the management of the inventory system picks to light. It is shown in figure 1. It is also known as a simplified order fulfillment system. In this technology, the light systems are mounted on the racks, trolleys, and carts. Moreover, each picker is assigned to specific light locations. Whenever there is a need for any product from the inventory system. Then the LED light will blink for attracting the attention of the picker. Furthermore, the picker is able to confirm which type of order is required to pick. After this, the picker will get the order and placed the material correctly in the proper sequence. Then the picker will again the blinking light after completion of the correct order from the inventory. It can be seen that the introduction of Pick to a light system in the line will improve productivity and reduce the searching time for the new material [3].
Figure 7: The pick to light system
Figure 8: Pick to Light Technology
It can be noted that
the Pick to light systems technology is not new in the market. But its main
function is providing ease and relaxation to the huge warehouses. This
technology is operated with the light assisted system. Due to this it will
become extremely easy to pick the material from the desired location. It can be
observed that in small and large warehouses this technology is considered as
the ideal way for improving order services. There are a lot of advantages of
this technology
Figure 6:
Hardware Design of Pick to light system
This technology is
helping the warehouse staff members. Through this, they can easily spot
different kind of items from the warehouse quickly and accurately. Due to this,
the company can easily enhance the productivity. Moreover, another fact is that
it will also increase the accuracy. The main reason is that in manual
warehouses, the humans are making different kind of mistakes in picking up the
order. But through this they are required to put right value of the order then
it will show the right place by LED. Through this the accuracy will be
increased with perfection.
Another advantage is
that the staff members are able to use the time with perfection. This is
because it will decrease the walking time and thinking time for picking up the
item. This means that there will be less time for warehouse staff members. Due
to this technology the KPI will be extremely high during operation. It is also
easy to setup. In this technology the huge display around the picking order is
providing complete information about the required item. The warehouse staff
member can easily complete the order by follow up the instruction completely. This
technology is also scalable and flexible. This is because it can easily scale
up and down according to the requirement of the warehouse. This technology is
also flexible. The main reason is that the warehouse staff members can easily
put this technology anywhere they wanted.
Figure 7:
Pick to light system in Warehouse
Another point is that its integration through URL is quite simple. It
is only using a simple URL system to light up the devices. It can be integrated
easily with Excel or google sheets. Moreover, it also contains cloud services.
This means that there is no need to use on-site server to maintain different
items in the warehouses. It will also help the stockers to operate faster
during receiving of the items. These items can be located easily it will show
less time walk for the stocker. Due to this technology, the price of the good
will be lowered. The main reason is that the human efforts are and productivity
is increased so the cost of good will be decreased
5. Arkite’s Human interface mate of smart
manufacturing factory with intelligent assembly technology and systems in
phased Implementations
The next technology is
related to the Arkite’s Human interface mate and it is shown in figure 2. It is
considered as the operator guidance technology that is involved in transforming
workstations into a specialized digital and interactive environment. This
technology is integrated with the MES and enterprise resource planning (EPR)
tools. Moreover, this setup at the workstation will guide the operator for
applying required assembly processes and also warn them in case of any problem
and error. There are a lot of advantages to this system when it is implemented
in the workstations. This is because it will increase the quality and
efficiency of the assembly processes and also perfectly prevent human errors.
[7]
Figure 8: Arkite Human
Interface Mate (HIM)
Moreover, the human interface mate is considered as
the Virtual Guardian Angel for the smart manufacturing industries. This
technology is looking over the shoulder of the operator and also warning him
about the bad operation decision during progress. There are some advantages of
this technology for smart manufacturing industries.
The most important point is that it is reducing the
cost of the manufacturing products. On the other hand, it will also increase
the efficiency of work through control operations and also creates two way
information between the systems. There is no physical contract is used during
operation. It is based on 3D sensors that contain a smart workflow software
Figure 9:
Arkite’s Human interface mate
6). The Digitalized
Lean Assembly line of smart manufacturing factory with intelligent
assembly technology and systems in phased Implementations
The next technology used in the smart
manufacturing factory is related to the digital lean assembly line. It is shown
in the given figure below. It has consisted of three main stations that include
the shaft assembly, gearbox assembly, and final assembly. For that case,
operators are involved in using each of the stations and it contains only one
material handler and he is the charge of inspected the inventories and gear
parts.
Figure 9: Digitalized
Assembly Line
6.1 Shaft assembly
Figure 10: Manual Workstation Shaft assembly
It is the first station
and shown in the figure 4. In this station, the operator is required to deal
with some hot and heavy parts that will increase safety risk. The next thing is
that time required for assembling the sub-assembly parts by using a hydraulic
press and the induction heater is about 20 minutes. It can be observed that
when a collaborative robot is placed at the station then the operator has to
play a supervisory role by performing some value-added tasks properly.
Moreover, the whole system will increase work efficiency and also enhancing
workshop safety.
Figure 11: Solution for
Manual Setup
Figure 12: Cobot
Station with cobot arm
The next point is
related to the implementation of the 3D scanner and it is implemented with a
part recognition algorithm in the cobot’ station. This 3D scanner will improve
the efficiency of the assembly process by capturing imaging and analyzing its
position of related parts. Then cobot will assemble these parts correctly.
There is a need for image data from the vision controller and it will transmit
through OPCUA to industry PC. Then after this, for obtaining the correct
coordination of the parts of the controller there is a need for analysis.
According to these coordinates, the cobot can easily pick and place the
required parts properly from the trolley. There is also a smart safety
projector and it is assembled at the cobot’s station and it is implemented with
the idea of projecting the wellbeing operators in assembly workstations.
Moreover, the next fact is that a Smart safety projector will project safety
barrage with an efficient warning sign and it will allow the operator to check
the problem present in the workstations.
Figure 13: Scanner to
Cobot
6.2 Station 2 gear assemblies of smart manufacturing
factory with intelligent assembly technology and systems in phased
Implementations
In that station, the
operator will check the gear assembly process and also shafts sub-assembly
produced from station 1. Moreover, at the start of station 2 the main parts of
gears like bearing cups, and covers are placed on the normal bins for the operator
to use. Despite this, when inventory is low then the operator is required to
travel towards the warehouse and replenish the parts required and applied them
to the workstation 2. Moreover, if they wanted to reduce the operator effort
and time then they applied an automated transportation system and it is
implemented with (Mobile industrial robot) MIR technology as shown in the given
figure. It will provide ease to the operator to carry out materials from one
place to another in the workstation. Moreover, MIR will allow the user to
install maps into its software so it will become simple to move around the
workplace without the involvement of human efforts. Another thing is that MIR
will safely control the people and other obstacles on the shop floor because it
contains high-speed cameras and sensors. Moreover, MIR is also smart it can
easily identify its surroundings and take the most efficient route towards its
destination. If its route is blocked then it can easily find another shortest
route towards its destination. Another fact is that its structure part of the
transportation module is extremely versatile. It also contains the trolley
system and it will customize the top module of the system with bins and racks.
Figure 14: Mobile
Industrial Robot (MiR
We also realised that an operator requires carrying a heavy load such as a gear
box around the lean assembly line. Thus, another alternative of helping
operator carry heavy workloads around the shopfloor would be the “THOUZER” (as
shown in Figure 9). At our shopfloor, we apply the “THOUZER” to carry heavy
objects such as gearboxes which weigh about 20kg. It has a maximum payload of
120kg. The operator can either use the vehicle to follow them or manoeuvre it
using the joystick to navigate around the workshop. Thus, this method prevents
the need for the operator to carry heavy loads and increases workplace safety.
Figure 15: THOUZER with complete parts
Moreover, in station 2
there is a manual check of the stock. It is considered an extremely
time-consuming process and also tedious for the operator. This problem can be
solved through the new system and software named as Bossard Smart bin Bossard
smartbin powered by Bossard Armis software. It shown in the given figures. The
main aim of the system to help the operator by identifying the stock levels by
just looking at the colour level on the display screen. It shows that if it is
displaying green colour it means it is completely full. On the other hand, blue
is showing sufficient inventory, yellow is showing low and red is showing
empty. Moreover, this screen will also show the name and serial number and its
estimated quantity. The next point is that in Smart bin there is only the
requirement of remote wireless connections for monitoring stock by weight
sensors. This means that whenever the inventory is low then it will be
reflected in the dashboard of the Bossard ARMIS software and it is connected
with Smart bin. Due to the low stock level, this software will trigger the MIR
system by IIOT platform to carry parts towards the station 2.
Figure 16: Normal Bin to Smart Bin
Figure 17: Smart Bin colour indicator
Moreover, in station 2
there is also a digital Standard Procedure (SOP). It is shown in figure 12.
This system is used for guiding the operator for following certain steps by
video. It will become extremely simple and clear for the new operators working
in a particular environment. It will also help the operator during the work
environment so they can easily update the SOP according to the requirement of
the system.
Figure 18: Digital Standard Operating Procedure
(SOP) Used in Lean Assembly Line
6.3 Station 3 of smart manufacturing
factory with intelligent assembly technology and systems in phased
Implementations
It deals with the final assembly stage. In that particular state, the operator will qualify the inspection on the gearbox and complete its final assembly. It can be noted that the final assembly is extremely important to process for the implementation of the gearbox assurance and its quality. Moreover, it is no easy for the new operator to follow. Due to this, there is a need to implement the Arkite Human interface for guiding new operators for the final assembly process. Due to this system, the new operators can handle tough tasks in the final assembly. It will also help the operator to follow the required steps to assemble the gearbox and also minimize the important errors of the system like implementing the wrong parts for the assembly.
7. Implementation of
technologies of smart manufacturing factory with intelligent assembly
technology and systems in phased Implementations
As explain in the above section of abstract ,
there are following technologies which is implemented This is due to the implementation of the Internet of things (IoT),
Artificial intelligence (AI), Machine to Machine communication (M2M), Virtual
reality (VR), and machine learning. These technologies are implemented in
manufacturing, improving product performance, and production processes.
7.1 Internet of things
(IoT)
By selecting the method
“internets
of things” explained the advanced manufacturing case for the smart factory.
Problem
description of
smart manufacturing factory with intelligent assembly technology and systems in
phased Implementations
Now the statement of the
report is that, the detail analysis on the “advanced manufacturing case for the smart factory” by using the IoT method.
In this research when the data is collected then used the IoT method for the
problem of advanced manufacturing case for the smart factory and obtained da results.
The main issue is that, when the system of IoT is attached with an internet
then it is affected through the different internal attacks. And in this research also used the different
methods as explained below in methodology sections. One critical enabling
technology for advanced manufacturing is “Internet of Things” (IoT) which is
formation of a global information network. IoT stand for “Internet of things”
is a latest trend in the world of internet with the embedded applications.
There are different smart devices that have the large amount of the attacks
data in include in the IoT. The different internal attack is also affected on
the application of IoT which is connected through the internet. Initially, the
uses of the Internet were based on the transfer of data packages between data
sources and users by using specific IP addresses.
7.2 Artificial
intelligence (AI)
In every company, there are different projects that
need to be monitored and managed. Therefore, Artificial intelligence (AI) for
smart manufacturing factory is on rising as well as the AI is also going to
create a smarter decision and help the teams. Teams as well as the project
managers which have to face very complex decisions, complex data, and
repetitive tasks
Figure 10: Artificial
Intelligence system in warehouse
Impact
of Artificial Intelligence on smart manufacturing factory
AI
has the ability to bring out the various remarkable transformations in smart manufacturing factory. There are
some like the routine improvements, minuscule and it could also accumulate over
time and improve the overall long term efficiency in the smart manufacturing. By the increasing
number of business which looks like the manufacturing
factory by the AI abilities for the exact reasons
The
appropriate smart manufacturing factory
has a potential impact on the manufacturing and machine learning
process. This plays an augmenting role in different stages of the investment
process and enables to have independent decision making. The future of
artificial intelligence is promising and for the next generation of hedge
funds, the performance can be measured. Smart
manufacturing of factory increases the commodity trading advisors
(CTAs). AI of smart manufacturing
factory is adaptable to work and enough robust for autonomous
conditions. Despite the availability, the historical data have sufficient
market cycles. The fund methodology considers price predictions for the single
stocks and it builds models for different media channels.
Figure 11:
Artificial intelligence in warehouse
Artificial intelligence
(AI) provides a clear overview of hidden costs and critical issues of an
investment product (e.g. shares, mutual funds, bonds, commodities or corporate
projects). Fund giants hire professionals and exports of artificial intelligence
(AI) and data sciences to assist them in developing and optimizing algorithms.
A recent study present that a US company was capable to generate $1trn annual
revenue by using algorithms and artificial intelligence (AI) in its asset
project management. An estimation that in next 2 to 3 years’ overall investment
in technology-driven roles will become almost half of the total investment.
Firms with advanced artificial intelligence (AI) will invest more in financial
markets because of ease provided to them in the project management system by
artificial intelligence (AI) and algorithms
7.3 Machine to Machine communication (M2M)
8. Methodology of smart manufacturing factory with
intelligent assembly technology and systems in phased Implementations
This research is based on secondary data and
collected data from different manufacturing factories. The data is collected
from smart manufacturing and ordinary manufacturing factory. In smart
manufacturing, there is the implementation of efficient assembly technology and
system. On the other hand, ordinary manufacturing is operated with a human.
Moreover, in this survey, all main assembly operations are analysed properly.
Moreover, all of these industries are located in Singapore. It will analyse the
productivity and also inventory controlling of the smart and ordinary
manufacturing companies.
Build the new factory,
acquired the new distribution centre along with the refurbished equipment .From
the foreign, direct investments, the analysis is expected the future cash flow,
for the analysis of the international investments. The analysis of the capital
budgeting is concerned by the direct investment. Whereas the foreign capital
budgeting has the two main components, the decision of the abroad as part of
the strategic plan, along with the quantitative analysis for the available
data. In the quantitative analysis that follows them to determine the strategic
plan implementations which are feasible financially or desirable. To estimate
the future cash flow, the data based is often required along with also for the
past financial statements
In the present survey
different aspects of the internet of things are considered such as fundamental,
architecture, and technologies. The network optimization process for IoT
comprises of different combinations and methods particularly related to the type
of network problem
1. Applying
a completely known framework of optimization to address the process of smart
factory.
2. Using novel schematic work based on the
heuristic method. Both approaches and mutually exclusive approaches, in this
process faster approximation solution, are analyzed by different assumptions
and algorithms.
Advanced
data processing method of
smart manufacturing factory with intelligent assembly technology and systems in
phased Implementations
With the evolution of
Technology, advanced data processing method was used for constraint analysis of
devices connected to the internet. A large amount of data was transferred
through these devices by IoT network
There
are the following methods where the AI could also potentially revolutionize smart manufacturing factory
·
Cost reduction
·
Predictive Analytics
·
From Disparate data
actionable insights
·
Eliminate repetitive
administrative tasks
·
For early risk decisions
enhancing visibility
In smart manufacturing factory, managers are also required to control
cost and expenses to ensure enhance in profit margin or return on investment.
Artificial intelligence (AI) sheds light on the specifications of the project
or investment product that enable them to control cost by promoting
cost-efficiency. The increase of available resources utilization, reduction of
risk exposure, and increase of concurrent managed projects are the key outcomes
of artificial intelligence (AI) use in project management. While in asset smart manufacturing factory,
artificial intelligence (AI) support managers to select the appropriate asset
while predicting its expected return in the specified time duration. Moreover,
the study has highlighted the usefulness of artificial intelligence (AI) in
representing genetic algorithms and neural networks for the active selection of
various portfolios. The data collected from 40 US companies to study the impact
of artificial intelligence (AI) on smart
manufacturing factory. They identified that companies using artificial
intelligence (AI) and genetic algorithms for project management had more
capability to adjust higher risk returns as compared to other companies with
traditional smart manufacturing factory
systems
Challenges
of the smart factory of
smart manufacturing factory with intelligent assembly technology and systems in
phased Implementations
There are a lot of
challenges relate to real time monitoring that are required to be controlled in
a proper way. One of their main challenges is related to the real time
monitoring of the smart factory. Their first main issue is that proper data is
not transferred to the smart factory from the user end. The data is loss
through different things that may be due to wind or any other thing.
It can be seen that the
smart factory are involved in handling huge amount of data from the user end.
If there is no sufficient capacity is provided to the manufacturing of
factories than may be huge data is lost and also factories are unable to use
its resources in an effective way. This can be explained through the help of an
example. The user is utilizing huge amount of energy that is about 110 KV but
the problem is that the smart factories is unable to detect the correct amount
of data. Then due to this it will not use its complete resources to meet the
demand of the user. The ecosystem of the factories is too much old and there is
need some huge advancement in these systems. For that case there is need of
high quality modification through applying different new technologies. It can
be seen that there is need of such system that is able to handle these
resources and use it according to the demand of the user in an efficient way.
Hacking
problem of smart manufacturing factory with intelligent assembly technology and
systems in phased Implementations
The next challenge is
related to the hacking. Due to advancement in the IoT department there is huge
fear of hacking. It can be seen that from the information about few years the
smart factories are facing huge problems related to hacking. The main reason is
that there are no proper protection system and security protocols. Due to this,
these systems are facing huge problems that are related to loss of real time
data from the user. This the reason the smart factory is working on enhancing
the system by applying different internet protocols.
Use
of artificial intelligence of
smart manufacturing factory with intelligent assembly technology and systems in
phased Implementations
It can be seen that from the last one decade the smart
factories system is applied in different developed countries. But the main
problem is that they are unable to develop such system that is able to meet the
demand in a perfect way. To solve this main problem, the smart factory must
have to use such systems that are intelligent enough to meet the future demand
in an efficient way. If these factories are compared with the old factories
there is no software for meeting the main demand for the future.
An important challenge of
these emerging networks is to empower various terminals for sharing a physical
resource which is concerned with broadcasting the communication channels in an
orderly and efficient manner. Necessarily, such an issue would utilize the layer
of medium access control which corresponds to the link layer’s sub layer of the
OSI or open system interconnection model. This challenge is also accountable
for coordinating the transmissions of frame in different broadcast links.
The specific protocol for
MAC utilized for Internet of Things applications will need to fulfil several
requirements which include increased throughput for meeting the fairness level
along with complying with limitations, requirements, and resources of the
access technology is utilization. In this choice of protocol for MAC, an
important aspect that should be considered is the topology of network and how
much information is possessed by nodes
For examining the fulfilment
of M2M networks and IoT requirements from the perspective of MAC layer in this
case, along with the limitations which are imposed by the abilities of
CubeSats, will inform about the sustainability of providing connectivity of IoT
through the use of nanosatellites. The discussions and reviews presented in the
coming sections address the requirements of M2M and IoT requirements which have
been listed below, except the ones which are associated with data integrity and
data security.
Although aspects of security hold great
significance in the ecosystem of IoT, all interested readers are directed by us
to specialized studies on this concept discussing security mitigations and
threats for different IoT architectures and technologies
One of the challenging
concerns in the wireless sensor network (WSN) is related to battery timing and
how the energy of the nodes can be maintained for accurate and desirable
outcomes. The main objective of the smart factory manufacturing technique is to
maximize the lifetime of the network. This process drastically improves the
lifetime of any single or multiple nodes of the network. In the previous
research, the researchers worked on different suitable context to measure the
situation of wireless sensor network and how the battery saving process can be
improved with energy-efficient routing process
9. Discussion of smart manufacturing
factory with intelligent assembly technology and systems in phased
Implementations
It can be noted that smart manufacturing
factories will be the future of the industrial revolution. This is because all
of these technologies will lower the human efforts and time. Moreover, due to
these technologies, the efficiency of the system is increased and also there
will be quite a low risk of any error in the system. Another important point is
that due to the implementation of these technologies the workload on the human
will be reduced. From these technologies, the Digitalized Lean Assembly line is
considered one of the most efficient ones used in the smart inventory system.
This is because it contains three workstations and every workstation is
efficient in reducing human efforts. This shows that due to such technologies
humans will only play a supervisory and maintenance role in the workstations.
If there is any problem is present in the workstation they will solve it.
But all
operations at the workspace will be carried out through these technologies. The
results of these technologies are extremely efficient. The results are obtained
from the survey and secondary data conducting from smart manufacturing factory
and ordinary factory. The results are showing that these technologies become a
new revolution for the manufacturing industries. This is because it is reducing
the human efforts and also increasing efficiency and productivity in the
workplace. The main reason is that such robots are fast and robust in action.
It contains the latest and premium software applications operated with
artificial intelligence technology so they can easily sense the problem and
solve it properly. It is showing that it is considered an advanced
technological future for the manufacturing factors around the world.
The state of art
techniques is used for Internet of Things (IoT) network Optimization processes
to deal with the challenges and issues of Internet of Things system. Under the consideration of future work issues
and privacy, challenges are also considered in the present work
10. Conclusion
Summing up all the discussion from above, it is concluded that smart
manufacturing factories are the future of industries. In this paper, there is
complete information on the different technologies used for the assembly system
of the factory. All of these technologies are explained with proper information
and figures. For methodology, a complete survey is conducted between smart and
ordinary manufacturing factories. It will highlight some important advantages
of smart technologies in the workplace.
Revolutions are
disruptive and Industry 4.0 is no exception. However, all disruptions bring
great opportunities – and risks. The Model Factory @ARTC helps mitigate some of
that risk for you. A*STAR’s Model Factory has created a safe testing
environment like above where you can test ideas before launching them in a
real-world manufacturing environment.
A*STAR’s Model Factory
initiative brings you real-time manufacturing environments that will allow
companies to learn from, and test newer Industry 4.0 technologies within a
collaborative ecosystem of partners. The industry partners will work with ARTC
to develop Industry 4.0 technologies to improve performance and efficiency in
shop floor production. The results of these technologies are extremely
efficient. The results are obtained from the survey and secondary data
conducting from smart manufacturing factory and ordinary factory.
It
is concluded that the impact of the AI on smart manufacturing factory is bringing changes in the investment
sector and financial markets are the large scales. Artificial intelligence is being used to assist by the
project organization on a gathering of fronts. AI system is
capable to efficiently handle preparation, prompts, as well as follow-ups to remove
a need for human input. Technology and excessive
specifications had made projects management a complex task. While artificial
intelligence (AI) reduces such complexities and provide a clear overview by
using historical information. Conclusively, artificial intelligence (AI) has a
positive impact on project management as it reduces risk factors and increases
the chances of a higher return on investment.
In
the IoT system different network related problems are routing, quality of
service (QoS), heterogeneity, congestion, reliability, energy conversion, and
scalability. Internet of things has a vital role in the modern technology and
development of the world that converts small objects
The
increase of available resources utilization, reduction of risk exposure, and
increase of concurrent managed projects are the key outcomes of artificial
intelligence (AI) use in project management
One
of their main challenges is related to the real time monitoring of the smart
factory.
The
main reason is that there are no proper protection system and security
protocols.
To
solve this main problem, the smart factory must have to use such systems that
are intelligent enough to meet the future demand in an efficient way.
The discussions and
reviews presented in the coming sections address the requirements of M2M and
IoT requirements which have been listed below, except the ones which are
associated with data integrity and data security.
Acknowledgements of smart manufacturing factory
with intelligent assembly technology and systems in phased Implementations
This research is
supported by the Agency for Science, Technology and Research (A*STAR) under its
Advanced Manufacturing & Engineering (AME) Industry Alignment Funding. – Pre-positioning funding scheme
(Project No: A1723a0035)
References: of smart manufacturing
factory with intelligent assembly technology and systems in phased
Implementations
[1] Internet of Things (IoT) Solutions &
Services,” Cisco, 06-Nov-2019.
https://www.cisco.com/c/en/us/solutions/internet-of-things/overview.html
[2] Grieves, M. (2014). Digital Twin:
Manufacturing Excellence through Virtual Factory Replication. US Florida
Institute of Technology.
www.engineering.org.cn/en/10.1016/j.eng.2019.01.014
[3] Bastiansolutions.com. (2019). Pick to
Light | Accurate Order Fulfilment | Bastian Solutions | Bastian Solutions.
https://www.bastiansolutions.com/solutions/service/supply-chain-software/picking-technology/pick-to-light/
[4] Luo, W., Hu, T., Zhang, C., & Wei, Y.
(2019). Digital twin for CNC machine tool: modelling and using strategy.
Journal of Ambient Intelligence and Humanized Computing, 10(3), 1129-1140.
[5] Zhao, R., Yan, D., Liu, Q., Leng, J., Wan,
J., Chen, X., & Zhang, X. (2019). Digital Twin-Driven Cyber-Physical System
for Autonomously Controlling of Micro Punching System. IEEE Access, 7,
9459-9469.
[6] ElProCus - Electronic Projects for
Engineering Students. (2019). Introduction to Wireless Sensor Networks Types
and Applications.
https://www.elprocus.com/introduction-to-wireless-sensor-networks-types-and-applications
Alan W. Mackelprang,
& Nair, A. (2010). Relationship between just-in-time manufacturing
practices and performance: A meta-analytic investigation. Journal of
Operations Management,.
André R.
Fioravanti, Mareček, J., & Robert N. Shorten, M. S. (2017). On classical
control and smart cities. In 2017 IEEE 56th Annual Conference on Decision
and Control (CDC).
APPLESON,
J. (2019, October 20). IoT in Manufacturing: Reduce Energy Consumption,
Increase Safety. Retrieved from https://www.supplychaindigital.com/supply-chain-management/iot-manufacturing-reduce-energy-consumption-increase-safety
Branscombe,
M. (2018, Janurary 12). How AI could revolutionize project management.
Retrieved from
https://www.cio.com/article/3245773/how-ai-could-revolutionize-project-management.html
Corvers,
F. (1997). The impact of human capital on labour productivity in manufacturing
sectors of the European Union. Applied Economics.
DONG,
Y., HARAGUCHI, H., & HAO, X. (2014). Structural Equation Modelling of Human
Factors and Their Impact On Productivity of Cellular Manufacturing. nnovation
and Supply Chain Management .
Granjal,
J., Monteiro, E., & Silva, J. (2015). Security for the internet of things:
A survey of existing protocols and open research issues. . IEEE Commun.
Surv. Tutor. , 17, 1294–1312.
Hezam,
A. A.-g., Konstantas, D., & Mahyoub, M. (2018). A Comprehensive IoT Attacks
Survey based on a Building-blocked Reference Mode. International Journal of
Advanced Computer Science and Applications, 09(03), 10-15.
Jiang,
C., Wang, X., Wang, J., Chen, H., & Ren, Y. (2015, ). Security in space
information networks. . IEEE Commun. Mag., 53, 82–88.
Kardas,
G., & Tunali., E. T. (2006). Design and implementation of a smart card
based healthcare information system. Computer methods and programs in biomedicine.
Kashyap,
V. (2019, September 12). 4 ways AI will change project management: trends in
2019 and the future. Retrieved from
https://bigdata-madesimple.com/ai-project-management-2019-trends/
Matsui,
Y. (2007). An empirical analysis of just-in-time production in Japanese
manufacturing companies. International Journal of production economics.
Milewski,
J. O. (2017). Additive Manufacturing of Metals: From Fundamental Technology
to Rocket Nozzles, Medical Implants, and Custom Jewelry. Springer.
Minet,
P. (2009). , “Energy efficient routing”, in Ad Hoc and Sensor Wireless
Networks: Architectures: Algorithms and Protocols. Bentham Science.
Parmar,
A. (2018, October 5). How AI Will Change the Future of Project Management.
Retrieved from https://www.workamajig.com/blog/ai-project-management
Pomodoneapp.com.
(2019, August 31). Impact of Artificial Intelligence in Project Management.
Retrieved from
https://pomodoneapp.com/blog.html/2019/08/31/impact-of-artificial-intelligence-in-project-management/
Singh
Tomar, G. C. (2020). International Conference on intelligent Computing and
Smart Communication 2019. Algorithms for Intelligent Systems.
Soua,
R., & al, e. (2011). A survey on energy efficient techniques in Wireless
Sensor Networks. IEEE.
Srinidhi,
N. N., Kumar, S. M., & Venugopal, K. R. (2019). Network optimizations in
the Internet of Things: A review. Engineering Science and Technology, an
International Journal, 22(01), 1-21.
Tank,
B., Upadhyay, H., & Patel, H. (2016). A Survey on IoT Privacy Issues and
Mitigation techniques. ICTCS '16, 01(01), 01-04.
Tomás Ferrer, S. C. (2019). Review and Evaluation of MAC Protocols for Satellite IoT Systems Using Nanosatellites. MDPI.
[7] Arkite. (2019). Arkite
- Helping Operators Excel
https://www.arkite.be/tag/helping-operators-excel.
Discuss your homework for free! Start chat
