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Developing Automated and Integrated Flexible
Manufacturing System
Wei Deng Solvang, Hao Yu, Gabor Sziebig
Department of Industrial Engineering, Narvik University College, Narvik, Norway
email: {wds, Hao.Yu, Gabor.Sziebig}@hin.no
Abstract—In order to achieve high-level of competitiveness in
today’s ever changing market, manufacturers have to maintain
high-level of responsiveness to customers’ preference. Due to this
reason, the appropriate implication of flexible manufacturing
system (FMS) is of great significance in determining the success
of a company. FMS enables rapid production of various types of
products with small scale so as to satisfy customer’s requirements
for high-level of product variability, however, the high initial
investment and unit production cost make it become a challenge
especially for small and medium sized enterprises (SMEs). In this
paper, the conceptual design and practical development of an
automated and integrated small-scale FMS at the workshop of
Narvik University College (NUC) is introduced. This study aims
to build up the knowledge in designing and implementing small-
scale FMS in practical context, and it also provides the local
SMEs with knowledge support in their production.
Keywords—Flexible manufacturing system; layout, logiticstcs,
simulation; optimization
I. INTRODUCTION
Flexible manufacturing system (FMS) is a highly
automated and integrated production system where a set of
industrial robots (IRB), multi-functional numerically controlled
(NC) and/or computer numerically controlled (CNC) machine
tools, automated material handling system (MHS) and
intelligent warehouse work together under computer control [1-
3]. Different from mass production system which mainly
focuses on economy of scale, the FMS aims to balance
productivity and flexibility through applying computer aided
technologies in order to achieve high-level of competitiveness
in current market with rapid changes.
FMS enables rapid production of various types of products
with small scale so as to satisfy customers’ requirements for
high-level of product variability, however, transforming from
traditional production system to FMS requires high-level of
investment and knowledge [3]. Technological and managerial
issues, i.e., system design, planning and scheduling, and
operational management, have to be the focuses in a FMS
transformation. Enterprises that convey this transformation
need to understand that the presetting of this transformation is a
positive effort for improving profitability through better
adaptation of the rapid market changes, furthermore, other
advantages, i.e., reduced labor cost, enhanced management,
improved machine and personnel utilization, and reduced WIP,
can also be achieved through applying FMS in an appropriate
manner [4]. However, the high initial investment and unit
production cost make it become a challenge especially for
small and medium sized enterprises (SMEs). In order to help
the SMEs with knowledge support and integrated solutions in
designing and developing FMS for their production, a small-
scale FMS is designed and currently under development at the
workshop of Narvik University College (NUC).
In this study, the conceptual design hierarchy, simulation
and future implementation of the FMS under development at
NUC are presented, and the rest of this paper is presented as
follows. Section II presents a brief introduction of the current
study on system design and development of FMS. Section III
presents the conceptual design and development of a small-
scale automated and integrated FMS at the workshop of NUC.
Section IV illustrates the simulation of FMS developed, and the
physical implementation under development at NUC is also
introduced in this section. Section V summaries this paper and
specifies the future works.
II. LITERATURE REVIEW
Flexibility enables manufacturing systems the capability to
efficiently and effectively cope with the fluctuations in
customer needs as well as other uncertain situations (e.g.
machine malfunction) [4]. In order to achieve the desired level
of flexibility, the appropriate design and planning of FMS is of
great significance. System design is logically the first step for
establishing a FMS, and due to its complexity and high cost, it
requires strong relevant expertise and knowledge-based
decision support [5]. A number of researches have proposed
different methods for the design of FMS [4, 6], and some of the
approaches are reviewed as follows.
Um et al. [6] develop an integrated approach combining
multi-objective non-linear optimization with evaluation
strategy for the design and planning of FMS. The automated
guided vehicle (AGV) system is involved in this study, and
optimal trade-off among three objectives including the
minimization of congestion, the minimization of AGV
utilization, and the maximization of throughput is the focus.
Yildirim et al. [7] proposes a decision support tool using
artificial neural network for the planning of FMS. The aim of
this study is to achieve the desired goal set up by high-level of
managerial board through determining the number of
machines, priority rule as well as the due date in an optimal
manner. Kia et al. [8] formulate a mixed integer programming
(MIP) model for multi-floor layout design of FMS, and a
genetic algorithm approach is also developed for model
computation. The purpose of this model is to minimize the
overall costs of production and intra-floor and inter-floor
437
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978-1-4799-7280-7/14/$31.00 ©2014 IEEE
transportation. Santarek and Buseif [9] int
r
and tool for the design of FMS, which
e
generation of system decisions with
specifications from upper management. Stru
c
design technique (SADT) incorporated wit
h
applied as the main tool in this paper. Lour
e
formulate a genetic heuristic approach
f
grouping problems in the planning of F
M
method has been proved to be more efficien
t
scale optimizations than the commercial
Yang et al. [11] propose a layout design me
t
single material flow, and the aim of this app
r
the productivity of FMS through the opti
m
equipment layout and indoor material flo
w
establish an integrated decision support sys
t
planning of FMS, and simulation and multi-
o
are applied in this DSS. Besides, artificial in
t
(e.g. neural network, expert system) ar
e
decisional process.
In this paper, the conceptual desi
g
development of automated and integrated F
M
through a real-world case study at
N
characteristic of this study is that both tech
n
(e. g. equipment and layout) and manageri
a
p
roduction and inventory management) are i
n
formulate an overall optimal solution for S
M
gap of previous studies.
III. C
ONCEPTUAL
D
ESIGN OF
A
UT
O
I
NTEGRATED
F
LEXIB LE
M
ANUFACUTU
R
In this section, the conceptual design hi
e
first formulated, and the physical desig
n
structure design of the workshop of NUC are
accordance with the conceptual hierarchy.
A. Conceptual Design Hierarchy of FMS
Fig. 1 presents the conceptual design hie
r
shown in the figure, the first step for pla
n
identify the design objective, and this will d
e
methods, equipment requirements, data requ
i
the criteria for performance assessment.
objective of FMS has been determined, som
e
i.e., selection of design methods, data acquis
i
performed in order to fulfill the requireme
n
works. The physical design and managerial s
then conducted at the next phase. Physical d
e
to determine the type and number of equip
m
and finished product storage, internal
m
logistics, which has great influence on t
h
effectiveness of FMS. Managerial structu
r
define the organizational and managerial
integrated FMS, and the manufacturing man
a
an integral part of the overall management
o
holistic organizational design including
departments of a company (e.g. marketi
n
therefore of significance in this phase. The
design will then be tested using simulation s
o
identify if the design objective of FMS is
design of FMS will be implemented if the go
otherwise, the design should be thoroughly
r
oduce the method
e
nables automatic
respect to the
c
tured analysis and
h
IDEF method is
e
nco and Pato [10]
f
or resolving the
M
S, and proposed
t
for solving large-
package CPLEX.
t
hod for FMS with
r
oach is to improve
m
al arrangement of
w
. Chan et al. [12]
t
em (DSS) for the
o
bjective planning
t
elligent (AI) tools
e
applied in the
g
n and practical
M
S are introduced
N
UC. The main
n
ological decisions
a
l decisions (e. g.
n
volved in order to
M
Es, which fills the
O
MATED AND
R
ING
S
YSTEM
e
rarchy of FMS is
n
and managerial
then performed in
r
archy of FMS. As
n
ning a FMS is to
e
termine the design
i
rements as well as
After the design
e
pre-design tasks,
i
tion, etc., are then
n
ts for subsequent
tructure design are
e
sign of FMS aims
m
ents, component
m
aterial flow and
h
e efficiency and
r
e design ai
m
s to
structure of the
a
gement is usually
o
f a company, the
other functional
n
g, sales, etc.) is
integrated system
o
ftware in order to
met. The system
al is perfectly met,
checked from the
b
eginning and optimized
requirements can be fulfilled.
Fig. 1. Design
h
B. Physical Design
The design objective of th
e
highly automated and integr
a
work pieces can be transform
e
minimum human power. The F
for educational and demonstr
local industrial partners, and
modules of the planned FMS.
Fig. 2. Schematic diagram of the fun
c
Based upon the functionali
t
is divided into four interactive
w
so that the pre-determined
h
ierarchy of FMS.
e
FMS at NUC is to establish a
a
ted production system where
e
d into final products by using
MS at NUC will mainly be used
ative purpose for students and
Fig. 2. presents the function
c
tion modules of the workshop at NUC.
t
ies, the FMS developed at NUC
w
ork cells:
W. D. Solvang et al. • Developing Automated and Integrated Flexible Manufacturing System
438
• Intelligent warehousing system;
• Robotic sorting and automation system;
• Machining and manufacturing system;
• Computerized control center.
The system design of this FMS is mainly focused on the
physical design of function module and the management of the
interaction and connection of those function modules in order
to achieve high-level of automation and flexibility of the FMS.
Fig. 3. Schematic diagram of the initial design of the intelligent warehousing
system.
The material flow in this automated and integrated
production system starts from and ends up at the intelligent
warehouse. Fig. 3. illustrates the initial design of the intelligent
warehousing system which is comprised of storage shelf,
movable lifting crane, track, specifically designed tray and
AGV. In this intelligent warehousing system, a lifting crane is
placed on the top of storage shelf for lifting and putting the
work pieces and finished products to appropriate place, and it
can also move along the tracks in order to cover the entire
range of the storage shelf. Specifically designed trays are used
in this system for matching the size of AGV, and those trays
are containers for raw materials and finished products in the
workshop. They can be removed by the crane from the storage
shelf to AGV which will then transport the tray with work
pieces to the robotic automation system through the pre-
determined route.
Fig. 4. Schematic diagram of robotic sorting system.
The robotic sorting and automation system in the FMS
consists of a sorting robot, two IRBs and a conveyor belt
system. The first IRB grabs and lifts the work pieces from the
tray transported by AGV, and put them on the conveyor. The
work pieces are sorted by the sorting robot into two groups for
different types of treatment, and work pieces will either
continue their journey to the machining cell or be stored at the
temporary storage place for other treatment. The second IRB
will take out the work pieces from conveyor belt and put them
into the CNC machine tool, and the work pieces will then be
transported to other machine tools by AGV for further
treatment. Fig. 4. gives the illustration of the robotic sorting
and automation system at the FMS developed in NUC.
Fig. 5. Material flow of the FMS.
After the entire machining process, the finished products
will be transported to storage shelf by AGV, and the internal
material flow is illustrated in Fig. 5. As shown in the figure, the
work pieces flow along the counterclockwise direction through
the entire system. In this logistics system, reverse flow and
cross flow, which increase the work in process (WIP), can be
efficiently avoided and the transport efficiency can be greatly
improved. The design idea for maximizing the logistic
efficiency can be adapted accordingly in the design of a large-
scale manufacturing system so as to dramatically improve the
cost efficiency. The FMS is controlled and monitored by
computerized control system which also provides the platform
for intelligent communications among different function
modules.
C. Managerial Structure Design
In the managerial structure design of the FMS, enterprise
resource planning (ERP) is applied for supporting the holistic
management of different activities. ERP is a comprehensive
management system which integrates different departments and
functions across a company. A traditional company is
comprised of several functionally independent departments,
and those departments are usually isolated and lack of
communication and coordination. ERP system provides a
common basis for data collection, interpretation, transaction
and integration, which enables the on-time delivery of
transactional information to different departments within an
enterprise without any barriers. Through this common basis,
the information can be shared punctually through all the
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CogInfoCom 2014 • 5th IEEE International Conference on Cognitive Infocommunications • November 5-7, 2014, Vietri sul Mare, Italy
relevant of a company, and the communicat
i
among different departments can be signi
f
Besides, through the interpretation and inte
g
data, ERP system can also
p
rovide relat
i
information for decision making. In ord
e
intelligent, flexible and automated
p
roduc
t
system will be used for the overall m
a
workshop at NUC, and the managerial str
u
system is illustrated in Fig. 6.
Fig. 6. ERP managerial structure of the F
M
At the FMS of NUC, the entire business
p
p
lacement to product delivery can be inter
a
and explicitly demonstrated through usi
n
(Mime and Dynamics NAV). Customer or
d
anywhere on campus at any time as long as
M
The transactional information is collected b
y
is automatically standardized and forwarde
d
level. At the workshop level, the ERP syste
m
the inventory list to identify whether there a
r
p
roducts in stock. If the customer orders
c
existing products, the invoice and
documentations will be generated, and orde
r
b
e scheduled. If the stocks of finished prod
u
the customer needs, the production wil
arranged. The ERP system will automa
t
component list needed for this production
will then be checked again for determi
n
production can be proceed by using existing
c
stock of components is sufficient to execute
t
p
roduction plan will then be formulated
manager in accordance with the worksh
o
resource, on-going tasks, etc. When the
p
ro
d
i
on and interaction
f
icantly improved.
g
ration of collected
i
vely more useful
e
r to establish an
t
ion system, ERP
a
nagement o
f
the
u
cture of the ERP
M
S at NUC.
p
rocess from order
a
ctively connected
n
g ERP software
d
ers can be placed
M
ime is accessible.
y
ERP system and
d
to the workshop
m
will firstly check
r
e eno
u
gh finished
c
an be fulfilled by
other relevant
r
delivery will then
u
cts can not satisfy
l be accordingly
t
ically create the
and the inventory
n
ing whether the
c
omponents. If the
t
he production, the
by the workshop
o
p capacity, labor
d
uctio
n
is finished,
the
p
roducts will be checked t
then be registered as finished
system. As mentioned above,
finished product inventory
a
delivery. If the component in
v
this production, the inventory l
e
supplier list will be provided
b
making. The workshop manag
several suppliers for replenish
m
future production plan. Th
e
forwarded to suppliers, and w
h
received at workshop, they
w
inventory. After that, the prod
u
accordingly organized as same
IV. P
REPARATION
The conceptual design of t
h
p
revious section, and the pre
p
currently in process for estab
l
This section presents a brief i
n
carried out at NUC.
A. Simulation and Optimizati
o
In order to test the syste
m
series works of simulation
a
performed at NUC. Simulati
o
testing the system performanc
e
has been applied in the visuali
z
for many years. Simulation an
d
can be categorized into fou
r
control and evaluation [4].
p
revious works in the simulati
o
respect to different types of pr
o
TABLE I. P
REVIOUS
W
O
R
O
PTIMIZA
T
Type of
problem Reference
Planning Mohamed [13]
Gultekin et al. [14]
Scheduling
Ferrolho and
Crisostomo [15]
Kesen et al. [16]
Zhang et al. [17]
Solimanpur and Elm
i
[18]
Control
Lauzon et al. [19]
Bellmunt et al. [20]
Pouyan et al. [21]
Evaluation
Tuysuz and Kahram
a
[22]
Aldaihani and Savsa
r
[23]
Savsar and Aldaihan
i
[24]
In this study, the visualiza
t
of the system design of FM
S
scenarios. Visualization
p
ro
v
o guarantee reliable quality and
product inventory by the ERP
the ERP system will check the
a
gain and schedule the order
v
entory is inadequate to execute
e
vel of existing components and
b
y the ERP system for decision
er will place an order to one or
m
ent according to ongoing and
e
order can be automatically
h
en the ordered components are
w
ill be registered as component
u
ction and order delivery will be
as previous situation.
AND
I
MPLIMENTATION
h
e FMS at NUC is introduced in
p
aration and implementation are
l
ishing the physical installation.
n
troduction of the current work
o
n
m
performance of the design, a
a
nd optimization are currently
o
n is a very powerful tool for
e
in complex environment, and it
z
ation and optimizatio
n
of FMS
d
optimization problems of FMS
r
types: planning, scheduling,
Table I presents some of the
o
n and optimization of FMS with
o
blems.
R
KS
R
ELATED TO
S
IMULATION AND
T
ION OF
FMS
Method
Computational optimization
Multi-objective programming
Software tools and genetic
algorithm
Genetic algorithm
Genetic algorithm with tabu
search
i
Mixed integer programming
with tabu search
Conjunction theory and PLC
technology
PLC technology
Petri net based control model
a
n Stochastic Petri nets with
fuzzy programming
r
Stochastic programming
i
Stochastic programming
t
ion and performance evaluation
S
are performed under different
v
ides audience with intuitive
W. D. Solvang et al. • Developing Automated and Integrated Flexible Manufacturing System
440
illustration of how the FMS works, and performance evaluation
enables the comparison of different system configuration under
dynamic environment. Fig. 7. presents a student project for
visualizing the operation and evaluating the system
performance of the sorting function module with multiple
choices for machining and processing under stochastic
environment. As shown from the figure, four types of
components will be sorted for different machining methods,
and the simulation result provides valuable information for the
system performance (e. g. the bottleneck in production,
throughput rate, etc.) with different configurations. The
simulation was conducted using professional simulation
software AutoMod, and the simulations for different scenarios
are also under development with the help of FlexSim and
Simio, which are also powerful simulation tools, in order to
have a deep insight of the overall performance of the system
design of FMS.
Fig. 7. Simulation in AutoMod for sorting system with the consideration of
multiple choices for machining and processing.
B. Physical Installation
The physical reconfiguration of the workshop at NUC is
currently under development. Some equipment will be
upgraded or replaced by advanced multi-functional CNC
machine tools. The intelligent warehouse and sorting robot
have been placed, while some other equipment is still in
process of purchase. Fig. 8. presents the vertical lifting
intelligent warehouse and the sorting robot. It is noteworthy
that the initial design of the intelligent warehousing system is
modified and replaced by a vertical lifting intelligent
warehouse which is much more technically established and
programmable. Besides, the intelligent vertical lifting
warehousing system has more space utilization and better
adaptation to any production system, and the sealing structure
provides better protection for the operators as well as the
components and products it stores. Due to the aforementioned
advantages, the intelligent vertical lifting warehouse is applied
in the physical installation of the automated and intelligent
FMS at NUC.
At the present time, the new equipment is being
programmed and adjusted, and some student projects are
designed accordingly for the expertise buildup of the
programming and control of the vertical lifting intelligent
warehouse and the sorting robot. In addition, comparing with
physically connecting those function modules, it is of much
higher level of difficulty that those function modules can work
automatically and collaboratively in the integrated FMS. It is a
cognitive process that to “train”, “communicate”, and
“interact” with those function modules so that they can work
collaboratively for a specific task. As addressed by Sziebig
[25], the long term expectation for the control of FMS is that
the operators are able to give the working tasks, through CAD
documentations or verbal communications, to the FMS or a
specific function module in the same way that they give orders
to their colleagues. Therefore, the development of cognitive
control and info-communication technologies for the workshop
communication is also of importance.
Fig. 8. Vertical lifting intelligent warehouse (Left) and ABB sorting robot
(Right).
V. SUMMARY AND FUTURE WORKS
This paper has presented the entire process for conceptual
design and physical development of an automated and
integrated FMS at the workshop of NUC. The conceptual
design hierarchy is first formulated, and the conceptual design
of the FMS at NUC is then conducted in accordance with the
design hierarchy. The objective of the system design of the
FMS at NUC is for building up the knowledge and expertise in
the design and development of highly automated and integrated
FMS, and the educational and demonstrative purpose for
students and local industries are also emphasized. The FMS
designed in this study is comprised of for independent function
module, and the internal logistics is considered as the most
important influencing factor for the layout design of the FMS.
Besides, the management structure design is also conducted in
this study in order to take the overall account of the system
performance. Compared with existing literature, the
characteristic of this study is that both physical design and
managerial structure design are taken into consideration.
In this paper, the current development of physical
installation of the FMS is also briefly introduced, and some
future works are specified as follows.
1) Visualization, simulation and optimization: Several
simulations with the help of professional simulation software
(AutoMod, Flexsim and Simio) will be conducted to test the
441
CogInfoCom 2014 • 5th IEEE International Conference on Cognitive Infocommunications • November 5-7, 2014, Vietri sul Mare, Italy
system performance of the designs with different
configurations under stochastic environment.
2) Programming and adjustment of existing equipment:
Student projects have been defined accordingly for the
programming and adjustment of the existing equipment.
3) Purchase of relevant equipment: Relevant equipment
(e.g. robots, multi-functional CNC machine tool) will be
purchased for building up the physical installation of the FMS
at NUC.
4) Knowledge buildup in ERP software and
implementaton: The education of ERP system (Mime and
Dynamics NAV) has been conducted at NUC, and the further
implementation in the FMS will be focused.
5) Knowlegde build up in multi-level control system of
FMS: The development of coginitive info-communication
technologies in FMS is emphasized in order to achieve high-
level of automation and integration of FMS.
ACKNOWLEDGMENT
This research was conducted with the financial support
from Sustainable Manufacturing and Engineering (SMaE)
Project (Ref. 38005). The aim of SMaE project is to provide
established solutions and “toolbox” to small and medium sized
enterprises (SMEs).
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