INTRODUCTION OF RFID TECHNOLOGIES

IN A MANUFACTURING SYSTEM

A Discrete Event Simulation Approach

Lobna Haouari, Nabil Absi and Dominique Feillet

Ecole des Mines de Saint-Etienne, CMP Site Georges Charpak, 880 route de Mimet, F-13541 Gardanne, France

Keywords:

RFID, Simulation, Discrete event simulation, Manufacturing, Resource allocation.

Abstract:

Radio-Frequency IDentiﬁcation (RFID) is a set of technologies which allow rapid, effective and nearly er-

rorless identiﬁcation of products. It is often compared to identiﬁcation by bar code, and is considered as an

evolution of the latter. In this paper, we discuss the introduction of RFID in a real manufacturing entity which

produces Conﬁgured-To-Order (CTO) printers. A discrete event simulation model of the factory is developed

in order to evaluate the impact of the technology on processes and system performance. Results show that

processing time savings and resource reallocation triggered by RFID use, have an inﬂuence on yield, cycle

times and rate of late orders.

1 INTRODUCTION

Radio-Frequency IDentiﬁcation is a set of technolo-

gies which allow rapid and effective identiﬁcation of

products. Information that allows object identiﬁcation

is stored in a tag.

Main advantages of Radio-Frequency IDentiﬁca-

tion are:

• Remote, without line of sight and simultaneous

products identiﬁcation.

• Individual identiﬁcation of each tagged object, by

contrast to bar codes which generally identify an

object type and not the object itself.

• Possibility of editing of the information which is

stored in tags.

RFID, or more precisely ancestors of it, exist since

the second world war (Landt, 2005), but, only in re-

cent years, it gained signiﬁcant interest from indus-

tries and academics (Sarac et al., 2010). Based on

(Rogers, 1962)’s description of diffusion of innova-

tions, (Housseman, 2011) says that we are probably

witnessing the beginning of a real maturation of RFID

technologies.

Wal-Mart and the US Department of Defense

RFID adoption cases are often cited in the literature,

partly because they were the pioneers. In 2005, Wal-

Mart required its top 100 suppliers to use RFID tags

on shipping crates and pallets (Roberti, 2003).

(Sarac, 2010) gives examples of RFID potential

beneﬁts in supply chains: Reduction of inventory

losses, shrinkage, and misplacement errors, reduction

of theft, reduction of Bullwhip effect, increase of pro-

cesses efﬁciency and speed, improvement of infor-

mation accuracy... However, radio-frequency identi-

ﬁcation is not exclusive to supply chains, studies on

the impact of these technologies covers a wide range

of domains such as healthcare systems (Housseman

et al., 2011), maintenance activities in the aeronautics

industry (Jimenez et al., 2010) and insect tracking in

biology (Vinatier et al., 2010)...

In this paper, we address the issue of RFID in-

troduction in a manufacturing case. Main advantages

of the technology, in this study, are processing time

reduction or suppression and possibility of resource

reallocation thanks to the ﬁrst advantage. Therefore,

a simulation study is conducted to estimate RFID im-

pact on a real system of Conﬁguration-To-Order of

printers, in terms of cycle time, yield, resource uti-

lization and rate of late orders.

The remainder of the paper is organized as fol-

lows. Section 2 presents objectives of the study. Sec-

tion 3 presents the studied problem and the simulation

model. Section 4 describes experiments and results.

Finally, in the last section, some concluding remarks

and research perspectives are discussed.

523

Haouari L., Absi N. and Feillet D. (2011).

INTRODUCTION OF RFID TECHNOLOGIES IN A MANUFACTURING SYSTEM - A Discrete Event Simulation Approach.

In Proceedings of 1st International Conference on Simulation and Modeling Methodologies, Technologies and Applications, pages 523-529

DOI: 10.5220/0003646805230529

 SciTePress

2 OBJECTIVES OF THE STUDY

The manufacturer in this study is currently conducting

a project to increase traceability of its products during

shipping. The project began in late 2008 and will last

three years. Among several technologies, RFID will

be used. On this occasion, a question is raised: Will

system performance be improved if RFID is also used

in internal processes? Indeed, if so, the implementa-

tion of RFID will be facilitated by previous experi-

ence gained through the project.

In addition, the manufacturer is interested in im-

proving its internal processes by other means than

RFID. In fact, improvements upstream of the shipping

may boost performance of the entire supply chain and

proﬁtability of the project. By a careful observation

of the real system, we identiﬁed some directions of

improvement such as reallocation of human resources

based on resource utilization or work in process indi-

cators.

Moreover, for different reasons, the manufacturer

has in mind some scenarios and changes in his inter-

nal processes that he wishes to test. For example, us-

ing a single building instead of two (see Section 3).

Another example is processing new types of products.

Therefore, a simulation model was developed to

answer all these questions. Even thought the study

aims to address all the issues previously raised, this

paper will only address RFID issue. Results of the

simulation are an estimation of impact of RFID intro-

duction in the manufacturing case.

3 PROBLEM DESCRIPTION AND

SIMULATION MODEL

In this study, the simulation model represents a real

activity in a factory, in the north of France. The fac-

tory is part of an international group and has dif-

ferent activities. The activity we are interested in

is Conﬁguration-To-Order (CTO) of printers. It is

spread over two buildings: The Logistic Center (LC)

and the Setup Center (SC). In the ﬁrst building, items

are stored until customers orders are placed. Once this

is done, items are sent to the second building in order

to be assembled together.

3.1 Processes in the Logistic Center

Figure 1 shows the two buildings and processes that

are executed inside them. Even though real and mod-

eled processes are rather complex, they are explained

in a concise and simpliﬁed way below.

In the LC (in orange on Figure 1), activity is di-

vided into two rather separate parts: Goods receiving

and storage, on the one hand, and items destocking

and orders preparation, on the other hand.

Regarding the ﬁrst part of the activity, goods are

delivered by trucks, three times a day. In each truck,

there is a variable number of products. These are

of different types (hundreds types in the real system,

grouped into six types in the model). The arrival of

a truck triggers the beginning of goods receiving pro-

cess. Indeed, LC employees unload the truck, per-

form computer input, bar codes reading, and resize

pallets if needed (in case of oversized and undersized

pallets). When receiving process is ﬁnished for the

entire contents of the truck, pallets are stored one by

one in racks.

The second part of the activity in the LC is orders

destocking and preparing. Each order consists of a

single printer and several options. When the demand

is known, items from different orders are grouped

and destocked by tours in order avoid unnecessary

roundtrips of employees and pallet trucks. During

destocking process, some bar codes readings are per-

formed and can be suppressed if we use RFID. After

destocking of all products of a tour, items of the same

order are placed together on a pallet and their bar

codes are read to prevent discrepancies, this process

is called order preparing. From this step, items of the

same order are gathered together on a single pallet.

Therefore, we shall no longer speak about items but

orders or printers. The last process in the LC is ship-

ping of orders to the SC. Indeed, a computer input is

performed for each tour of orders, items are loaded in

a truck and sent to the SC. Note that computer input

can be suppressed by using RFID.

3.2 Processes in the Setup Center

When orders arrive to the SC, employees unload the

truck and execute a computer input process in order

to update the database. Then, orders are unpacked

in parallel workstations. In order to keep traceability,

bar codes on packaging are cut and held with orders

to conﬁguring process. During the latter, printers are

assembled with their options in parallel workstations.

After conﬁguring, some printers may be defective and

require repair. The other printers go to computer input

process at the exit of the building. In addition to com-

puter input, printers are ﬁlmed, labeled and placed in

a shipping area in order to wait for shipping trucks

arrival.

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Figure 1: Screen shot of the simulation model of the studied factory (Automod).

4 EXPERIMENTATION

The simulation model in this study was developed us-

ing Automod Version 11.2. Simulation was run for

one month of working days, and replicated 120 times

for each scenario, because of the stochastic nature of

the model.

4.1 Performance Indicators

The manufacturer usually measures the performance

of his system by using cycle time and resource uti-

lization indicators. Hence, we keep these indicators

to measure RFID impact on the system. In addition,

yield indicator seems to be an obvious and necessary

issue. Indeed, if simulation results show short cycle

time and low resource utilization, it may be due to low

yield and not to a good performance.

4.1.1 Yield

In all scenarios, the number of orders received dur-

ing a month of simulated time is the same. Moreover,

at the beginning of the simulation, there is the same

number of work in process (WIP), in all scenarios.

At the end of the simulated month, in general, orders

are not completely satisﬁed, some of the orders are

still waiting or being processed in the system. We call

yield the number of ﬁnished goods processed during

the simulated month. Regarding yield, the objective

is to reach its maximum, which is the number of or-

ders placed during the simulation month plus work in

process of the beginning of the simulation.

4.1.2 Resource Utilization

Resource utilization expresses the part of time when

a resource works divided by the time when it is avail-

able. In this study, resource is available during open-

ing hours minus breaks. Resource utilization gives

valuable information about bottlenecks and waste in

the system. When it is too high (> 90%), in a part of

the system, long waiting times might be due to this

part. When it is too low (< 50%), managers could

allocate less resources to execute the task.

4.1.3 Cycle Time

One of the key performance indicators of this study

is cycle time. Indeed, in a competitive environment,

manufacturers and all levels of the supply chain, in

general, try to better satisfy customers. This requires,

among other things, the satisfaction of their orders

at the earliest. In a Conﬁguration-To-Order environ-

ment, assembly begins after the customer’s order is

placed. Therefore, customers wait, at least, for the

cycle time and shipping time, whereas, in a Make-

To-Stock environment, ﬁnished products are made in

advance, and customers orders can be fulﬁlled with-

out any waiting. All this explains the importance of

the cycle time indicator. In this study, cycle time is the

duration between the instant when an order is known

and the instant when it leaves the overall process of

CTO and is waiting for shipping. The manufacturer

has a maximum cycle time objective to meet, but lo-

gistic and conﬁguration buildings are managed sepa-

rately. So the manufacturer prefers to resolve the main

cycle time into two separate cycle times, one for the

LC, and another for the SC.

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4.1.4 Rate of Late Orders

The rate of late orders has a direct effect on customers

satisfaction. If an order is shipped late, the customer

will probably be unsatisﬁed. In our case study, the

manufacturer should fulﬁll orders in 5 days. But, for

the practical reasons explained earlier, the main ob-

jective is resolved into two separate objectives, 2 days

for the LC and 3 days for the SC. In a real system, it

is difﬁcult to completely eliminate orders that are not

fulﬁlled on time. Therefore, the aim for this indicator

is to have a smaller rate of late orders, by using RFID

for example.

4.2 Scenarios

Processes were explained in section 3. Many manual

bar code readings are executed during these processes

and can be suppressed by using RFID. Moreover, us-

ing an RFID technology can shorten or suppress some

tasks (computer input, unpacking...). Table 1 shows

impacts of RFID on LC and SC processes in a de-

tailed way. For experimentation, we use three scenar-

ios: A baseline scenario which represents the current

state of the system and two RFID scenarios. The lat-

ter two are similar, except for a human resource which

is simply suppressed in the ﬁrst case and reallocated

in the second. Indeed, the process of computer input

is completely suppressed in RFID scenarios because

items coming from LC will go through an RFID por-

tal and will be automatically identiﬁed. Therefore,

the human resource allocated to the process will be

suppressed in the ﬁrst RFID scenario, in order to be

used in some other non modeled activity. In the sec-

ond RFID scenario, the human resource is reallocated

to the assembly process, because results show that as-

semblers are the busiest resources of the system (see

Table 2).

4.3 Results

In this section, results are presented per performance

indicator. Figures 2, 3, 4, 5 present values of indi-

cators for each scenario. The baseline scenario is in

blue, the ﬁrst RFID scenario is in purple and the sec-

ond is in green. Table 2 contains the same informa-

tion as ﬁgures plus a comparison between the baseline

scenario and each RFID scenario.

4.3.1 Yield

Figure 2 shows that LC yield increases in a very neg-

ligible manner in both RFID scenarios. While, SC

yield increases by 1% in the ﬁrst RFID scenario and

Figure 2: Yield.

by 4% in the second RFID scenario (always as com-

pared to the baseline scenario). The total yield is the

same as SC yield since SC exit is the system exit.

These results were expected. Indeed, since RFID

shortens some processes, resources may be able to

fulﬁll more orders.

4.3.2 Resource Utilization

Figure 3: Resource utilization.

In Figure 3, we can see that, depending on the re-

source type, resource utilization can either increase

or decrease in RFID scenarios by comparison to the

baseline scenario. Indeed, some tasks are shortened

by using RFID but number of fulﬁlled orders in-

creases in RFID scenarios, as mentioned earlier in

yield section. These two contradictory trends explain

the obtained results. We can also see that perfor-

mances of the ﬁrst and the second RFID scenarios are

close, except for assemblers (we recall that there is an

additional assembler in the second RFID scenario) .

4.3.3 Cycle Time

Figure 4: Cycle time.

In Figure 4 we can see that cycle times decrease in

both RFID scenarios. This is due to shorter process-

ing times enabled by RFID. LC cycle time decreases

by 13% in both RFID scenarios. SC cycle time decre-

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Table 1: Impacts of RFID on processes.

Building Change Where or when Numerical values RFID scenar-

ios

Suppression of bar code reading At the entrance of LC Suppression of all computer input dura-

tion

1 & 2

Suppression of bar code reading Upon loading a pallet on a pallet truck

to be stored

Loading duration − 5sec 1 & 2

Suppression of bar code reading Upon unloading a pallet from a pallet

truck to be stored

Unloading duration − 5sec 1 & 2

Suppression of 2 bar code readings Upon loading a pallet on a pallet truck

to be picked

Loading duration − 2 × 5sec 1 & 2

Suppression of a part of process of

preparing

In the preparing area Preparing duration −60sec 1 & 2

Suppression of computer input process At the entrance of SC

Suppression of the process duration 1 & 2

Suppression of a human resource 1

Reallocation of a human resource 2

Suppression of cutting of bar codes in

packaging process

During unpacking process Unpacking duration − 20sec ×

number o f items

1 & 2

Suppression of bar code reading At the exit of SC Computer input duration − 5sec ×

number o f items

1 & 2

Suppression of bar code reading Upon loading a pallet on a pallet truck

to be loaded in a shipping truck

Loading duration − 5sec 1 & 2

Suppression of bar code reading Upon unloading a pallet on a pallet

truck to be loaded in a shipping truck

Loading duration − 5sec 1 & 2

ases by 16% in the ﬁrst RFID scenario and by 39%

in the second. Note that the use of RFID changes the

ratio between cycle times in LC and SC, indeed, SC

cycle time is more improved than LC cycle time. Re-

thinking the number of respective resources in LC and

SC may be necessary and may, enhance the effect of

RFID by using the same total number of resources.

4.3.4 Rate of Late Orders

Figure 5: Rate of late orders.

Figure 5 shows that there is no late orders in the

LC in all scenarios, while on the contrary, rate of late

orders in the SC increases from 4% in the baseline

scenario to 13% in the 1st RFID scenario and returns

to 4% in the 2nd RFID scenario. The increase of late

orders rate is certainly not desirable, but is due to in-

crease of yield (see Section about yield). We can still

notice that the second RFID scenario has equal per-

formance in terms of rate of late orders, with a higher

yield than the baseline scenario. The total rate of late

orders follows the same pattern as in the SC, with

smaller amplitudes (2%, 4% and 2% for baseline, ﬁrst

and second RFID scenarios respectively). Notice that

late orders in the SC can still be fulﬁlled on time com-

pared to the overall objective of 5 days. This explains

why, the total rate of late orders is smaller than SC

one, in this case.

To conclude about results, for this system, and

with the chosen set of initial conditions, RFID en-

ables higher performance in terms of yield and cycle

time. But rate of late orders is deteriorated or remains

unchanged with RFID. Even though performances of

the second RFID scenario, on the chosen indicators,

are higher than those of the ﬁrst RFID scenario, we

should keep in mind that, in the ﬁrst scenario, a hu-

man resource is released and can be used in other ac-

tivities.

5 CONCLUSIONS AND FUTURE

WORK

In this paper we addressed the issue of RFID intro-

duction in a CTO environment. We developed a sim-

ulation model which is based on a real system, and we

assumed that RFID use can shorten processing times

and free some resources that can be reallocated. RFID

impact was estimated on different performance indi-

cators. Simulation results are yield increase by 2%,

cycle time decrease by 33% and rate of late orders

decrease by 21%.

(Cai et al., 2009) say that there is a gap between

application and research in supply chain performance

measurement and improvement. Therefore, this study

INTRODUCTION OF RFID TECHNOLOGIES IN A MANUFACTURING SYSTEM - A Discrete Event Simulation

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527

Table 2: Table of results.

Measure category Measure Baseline Sce-

nario

RFID 1st Sce-

nario

RFID 2nd

Scenario

Difference between

baseline and RFID

1st Scenario

Difference between

baseline and RFID

2nd Scenario

Yield

Yield of LC 1574 1575 1575 0% 0%

Yield of SC 1491 1505 1558 1% 4%

Total yield 1491 1505 1558 1% 4%

Resource Utilization

LC Employees 77% 64% 64% -17% -17%

Computer Input em-

ployees at SC entrance

55%

SC Unpacking Employ-

ees

72% 71% 72% -1% 0%

SC Assemblers 84% 85% 76% 1% -10%

Computer Input em-

ployees at SC exit

47% 43% 45% -9% -5%

Cycle Time

Cycle Time in LC 42403 36725 36722 -13% -13%

Cycle Time in SC 125357 104963 76906 -16% -39%

Cycle Time (total) 168890 142325 113789 -16% -33%

Late Orders

# of late orders in LC 0 0 0

# of late orders in SC 61 189 68 210% 11%

# of late orders (total) 30 52 24 76% -18%

Rate of Late Orders

Rate of late orders in LC 0% 0% 0%

Rate of late orders in SC 4% 13% 4% 199% 5%

Rate of late orders 2% 4% 2% 70% -21%

gives an estimation of the impact of introducing RFID

in a real system.

As mentioned in Section 2, the objectives of the

study are much larger than results presented in this

paper. Therefore, the study can be further extended,

on the one hand, regarding RFID, and on the other

hand, to address other issues such as resource alloca-

tion, activity reorganization and system performance

under different conditions (high demand, new types

of products...).

We saw, in this study, that RFID allows processing

time reduction, because of rapid tags reading. Never-

theless, we implicitly supposed that the manufacturer

prints the same number of tags no matter if they are

RFID or bar code ones. In the real system on which

this study is based, bar codes are already printed on

items packaging before being received by the man-

ufacturer. In addition, the latter prints a bar code tag

for each received lot of items during receiving process

and a bar code tag for each order during preparing

process. If an RFID technology is adopted, the manu-

facturer will print all RFID tags by himself. Tags for

lots of items and for orders will probably be printed

during the same processes as the current case. By con-

trast, tags on items are not compulsory but may sig-

niﬁcantly increase ﬂows visibility. Hence, if the man-

ufacturer decides to keep items tagging, the task may

be operated before storage or after destocking. We be-

lieve that this choice would inﬂuence system perfor-

mance in terms of cycle time and resource utilization.

For this reason, it can be interesting to investigate this

issue.

Another issue related to RFID is the Return On In-

vestment (ROI). Since cost and ﬁnancial beneﬁts are

key performance indicators in most industrial cases,

we plan to investigate this problem.

Few years ago, the manufacturer had an activity

of assembling which has been delocalized to another

country now. Therefore, there is some vacant space in

the SC building, and the manufacturer would like to

know if it will be effective to relocate logistic activity

in the same building as CTO activity. A scenario of

one building should be soon developed in the simula-

tion model. By comparison to the baseline scenario,

some processes will be modiﬁed, essentially, orders

preparing, shipping to the SC and computer input at

the entrance of SC.

In addition, the manufacturer wishes to measure

impact of processing new types of products. Obvi-

ously, some numerical values in the model will be

changed for this scenario (processing times, repairing

rate, orders’ number of items...), and some processes

may also be modiﬁed.

ACKNOWLEDGEMENTS

This work has been funded by DIRECTION

GENERALE DE LA COMPETITIVITE, DE

L’INDUSTRIE ET DES SERVICES under conven-

tion number 08 2 93 06 49.

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