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Production, Supply, Logistics and Distribution 54.5 Emerging Trends and Challenges 955

ment justiﬁcation by determining success on how well

the solution isable tocreate value for customers through

services or products. What are customers looking for?

Is it on-shelf availability at a slightly higher price?

A highly computerized ASRS (automated storage and

retrieval system) may provide increased throughput,

less errors, and speed in distribution. What if the cus-

tomers change how and where products are required?

An AS/RS may not be ﬂexible enough to adjust quickly

to changes in demand patterns or shifts in the demand

network nodes. The correct solution should address cus-

tomers’ expectations regarding product quality, order

response times, and service costs, seeking to obtain and

sustain customer loyalty.

54.5 Emerging Trends and Challenges

The use of automation in production and supply chain

processes has expanded dramatically in recent years.

As globalization advances along with product and pro-

cess innovation, it would seem that the importance of

automation will continue to intensify into the future.

The landscape of global manufacturing is chang-

ing. More and more production plants are being built

in India, Brazil, China, Indonesia, Mexico, and other

developing countries. The playing ﬁeld is rapidly be-

ing leveled. However, by crossing borders, companies

also increase the complexity of operations and supply

chains. Virtually seamless horizontal and vertical inte-

gration of information, communication, and automation

technology throughout the organization is needed by

companies such as Wal-Mart, Kimberly-Clark, Procter

and Gamble, Clorox, and Nestle, in order to address the

dynamics of today’s manufacturing environment. Col-

laborative design, manufacturing, planning, commerce,

plant-to-business connectivity, and digital manufactur-

ing are just some of the many models that seem to be

on the horizon for leading manufacturing companies in

order to induce further integration of processes. Sev-

eral technologies and systems are reaching the required

level of maturity to support these models, and thereby

accelerate the adoption of automation in production and

supply chains. Examples of these technologies would

be:

•

Supply chain planning systems

•

Supply chain security

•

Manufacturing operations management solutions

•

Active radiofrequency identiﬁcation (RFID)

•

Sensor-based supply functions

•

Industrial process automation.

Furthermore other technologies such as manu-

facturing process management frameworks, supplier

relationship management suites, supply chain execu-

tion systems, passive RFID technology, Six-Sigma IT

(information technology), and lean manufacturing sys-

tems are more on an emerging or adolescence level of

maturity [54.3,4].

In addition, collaborative e-Work theory and tech-

niques are emerging as powerful automation support for

production, supply, logistics, and distribution [54.14,

15] (see also Chap.88).

54.5.1 RFID Technology in Supply Chain

and Networks

An emerging technology with great promise is the use

of radiofrequency identiﬁcation (RFID) to automate

the collection of data. A RFID tag is a small com-

puter chip that can send via radiofrequency a small

amount of information a short distance. The signal is

captured by a RFID antenna and then transferred to

a computer network for data processing (Fig. 54.8).

The general RFID system architecture, applications,

frequencies, and standards are shown in Fig.54.9 and

Table 54.2.

“Who are you”

Antenna

ReaderRFID server

• RFID server sends “talk” request to

reader

• Antenna broadcasts “talk” request

• Tags within RF field “wakes up” and

exchange EPC data

• Antenna recognizes tag signal and

transmits data back to reader

• Reader communicates collected EPC

data back to RFID server for

applications and analytics

EPC number

EPC attributes

Identify yourself

Fig. 54.8 How RFID works

Part F 54.5

956 Part F Industrial Automation

Raw materials and components for

production can be tagged to automate

receiving, tracking of inventory, lot

control, etc. The result is more

streamlined operations

RFID possible-state vision

Manufacturer

produces products and

packages them in cartons on

pallets. Each carton and/or

pallet can have RFID tag.

The unique EPC number can be

assigned when the tag is first

created (factory programmed)

or can be “written” later (field

programmable).

Order information is

integrated throughout a cross-

dock operation–receiving,

sorting, staging, and shipping

are streamlined.

Readers allow more accurate

picking and shipping, record all

products that leave the factory,

and report status to the

inventory system of record.

Inventory

system of

record

Warehouse

management

system (WMS)

Consolidated

point-of-sale data

Load authentication is

streamlined by allowing truck

weight to be compared to

attributes of the contents

reported by the tags. Errors

are detected earlier.

Tags can be integrated into

the cartons that will contain

the products.

Sensors in the shipment can

record temperature, humidity,

and other conditions during

transit and report them at the

end of the journey.

Authentication of import

products links digital certi-

fication to specific EPC

numbers, speeding customs

inspections and decreasing

opportunities for Counterfeit

products to enter the supply

chain.

Warehouse management

system tracks and updates all

inventory movement in real

time with each read event.

Validation to ensure that

products, quantities, and

destinations are correct is

facilitated by readers that can

trigger a warning before the

products are loaded on trucks.

RFID readers detect all

product moves within store

and can automatically prevent

stock-out conditions.

Tracking products

throughput the supply chain

reduces loss and theft of

inventory. In the event of a

tampering incident, lot control

information is available to trace

the problem to its source.

Product recall

management is simplified

because tags allow monitoring

of cases and pallets as they

move backwards through

the supply chain.

RFID readers on recycling

bins can monitor tags

attached to cartons and deduce

that individual products have

been put on the retail shelves.

Automatic inventory

replenishment orders can

be accelerated and more

accurate by supplementing the

POS system information with

RFID data.

Arriving products are

automatically detected through-

out the distribution center.

Manual steps are eliminated so

costs are reduced and accuracy

is improved.

Fig. 54.9a,b RFID in the supply chain (courtesy of BearingPoint’s RFID solution)

Part F 54.5

Production, Supply, Logistics and Distribution 54.5 Emerging Trends and Challenges 957

Table 54.2 RFID functions, frequencies, and standards

[54.16]

Applications Frequencies Standards

Animal, < 135 kHz ISO 18000–2

identiﬁcation

ISO 11784

dogs, cats, cattle

ISO 11785

ISO 14223

Smart cards, 13.553–13.567 MHz ISO 18000–3

passport, books

ISO 7618

at library

ISO 14443

ISO 15693

13.56MHz

ISM band class 1

Supply chain 868–928 MHz EPC global

class 1 Gen-2

for retail

ISO 18000–6

RFID is becoming increasingly prevalent as the

price of the technology decreases. Some RFID appli-

cations are summarized in Table 54.3. In supply chain

applications, current uses of RFID technology are fo-

cused on location identiﬁcation of products. These are

as varied as identifying trailers and ocean freight trail-

ers in a trailer yard, stopping of shoplifting of small

but higher-priced fast-moving consumer goods such as

razor blades, as well as an alternative to a WMS.In

broader uses Wal-Mart is discovering RFID technology

Table 54.3 RFID applications and examples

Application Examples

Documents (e.g., passports) Year 2000: Malaysia, Year 2005: New Zealand, The Netherlands,

Norway, Year 2006: Ireland, Japan, Pakistan, Germany, Portugal,

Poland, Year 2007: UK, Australia, and USA

Transportation payments Electronic Road Pricing (Canada)

T-Money (Korea)

Octopus Card (Hong Kong)

Super Urban Intelligent Card (Japan)

Chicago Card and the Chicago Card Plus, PayPass, CharlieCard (USA)

Product tracking Cattle tracking

Jewelry tracking

Library book or bookstore tracking

Truck and trailer tracking

Supply chain network Wal-Mart inventory system

Boeing 787 Dreamliner maintenance and inventory system

Promotion tracking

How the technology works

ONS server matches the EPC

number from a tag-read event

(the only data stored on an RFID

tag) to the address of a specific

server on the EPC Information

Services Network.

EPC network

contains detailed

information about

individual products.

Companies establish

rules to govern data,

access, and security

among trading

partners.

Middleware filters

raw data and applies

relevant business

rules to control what

goes into the core

system.

Reader beams

radio signal that

“wakes up” the tag

so it can reply with

its EPC number.

Less

than

Radio waves allow tags to be

detected at specific points in the

supply chain even when products

are concealed in shipping contain-

ers. Any tag that's within range of

the reader will be detected.

Tag includes a

microchip with an

antenna atteched.

Typically attached to

a self-adhesive label.

Tag

Tag stores a unique

electronic product

code (EPC) to identify

the product. Can be

integrated with the

package or with the

product itself. The

EPC functions like a

key, unlocking a

wealth of detail about

the product.

Enterprise

Transactional

System

Internet

EPC networkMiddleware

Reader

ONS server

Fig. 54.9 (b)

can help it increase sales by making sure inventory at

the store’s loading dock is actually placed on the shelf.

The barriers to implementing RFID technology are

cost, effectiveness, and fears of a loss of personal pri-

vacy. The cost of a RFID tag has declined 90% in the

past few years, but is still expensive and their use is

usually limited to pallets and not on individual cases,

products or boxes. It is believed that the uses of RFID

Part F 54.5

958 Part F Industrial Automation

tags on individual packages is many years away. The

other cost barrier is the investment in antennas. For

a company such as Wal-Mart to utilize RFID tech-

nology, they need to install antennas in all of their

distribution centers as well as all of their stores. Also

RFID technology has problems sending signals through

certain dense materials such as liquids, which limits

their use. Finally, some people feel that, if RFID tech-

nology improves in terms of the distance a signal can be

sent, then people will be able to determine which prod-

ucts are in people’s homes, and thoughts of Big Brother

come to mind. Currently the technology is not capa-

ble of fulﬁlling these privacy concerns, but the concern

will continue to slow the acceptance of the technology.

See also Chap.49 on Digital Manufacturing and RFID-

Base Automation.

54.6 Further Reading

•

A. Dolgui, J. Soldek, O. Zaikin: Supply Chain

Optimization: Product/Process Design, Facility Lo-

cation andFlow Control (Springer, NewYork 2005)

•

A.G. Kok, S.C. Graves: Supply Chain Management;

Design, Coordination, and Operation, 1st edn. (El-

sevier, Amsterdam Boston 2003)

•

A. Rushton, P. Croucher, P. Baker: The Handbook

of Logistics and Distribution Management (Kogan

Page 2006)

•

B. Kim: Supply Chain Management (Wiley (Asia),

Hoboken 2005)

•

C.E. Heinrich: RFID and Beyond: Growing Your

Business through Real World Awareness (Wiley, In-

dianapolis 2005)

•

D.E. Mulcahy: Warehouse Distribution and Opera-

tions Handbook (McGraw Hill, New York 1993)

•

D.F. Ross: Distribution: Planning and Control

(Springer, London 1995)

•

D.J. Bowersox, D.J. Closs, M.B. Cooper: Supply

Chain Logistics Management, 2nd edn. (McGraw-

Hill/Irwin, Boston 2007)

•

E.W. Schuster, S.J. Allen, D.L. Brock: Global

RFID: The Value of the EPC Global Network

for Supply Chain Management (Springer, London

2007)

•

G. Simson: RFID: Applications, Security, and

Privacy (Addison-Wesley, Upper Saddle River

2006)

•

H. Chen, P.B. Luth: Scheduling and coordination

in manufacturing enterprise automation, Proc. 2000

IEEE international Conference on Robotics and Au-

tomation (2000), pp.389–394

•

Harvard Business School Press: Harvard Business

Review on Supply Chain Management (Harvard

Business Review, Boston 2006)

•

I.Bose,R.Pal:Auto-ID: Managing anything, any-

where, anytime in the supply chain, Commun. ACM

48(8), 100–106 (2005)

•

J. Berger, J.L. Gattorna: Supply chain cybermas-

tery: building high performancesupply chains of the

future (Gower Publishing Company 2001)

•

J.J. Coyle, E.J. Bardi, C.J. Langley: The Manage-

ment of Business Logistics: A Supply Chain Per-

spective (South-Western/Thomson Learning, Ma-

son 2003)

•

J.-S. Song: Supply Chain Structures: Coordination,

Information and Optimization (Springer, London

2001)

•

N. Nicosia, N.Y. Moore: Implementing Purchasing

and Supply Chain Management: Practices in Mar-

ket Research (RAND, Santa Monica 2006)

•

N. Viswanadham: Supply chain engineering and

automation, Proc. 2000 IEEE international Confer-

ence on Robotics and Automation (2000) pp. 408–

413

•

N. Viswanadham: The past, present and future of

supply-chain automation, IEEE Robot. Automat.

Mag. 9(22), 48–56 (2002)

•

T.E. Vollmann, W.L. Berry, D. Clay: Manufacturing

Planning and Control System for Supply Manage-

ment, 5th edn. (McGraw-Hill, New York 2005)

•

S. Chopra, P. Meindl: Supply Chain Management:

Strategy, Planning, and Operation, 2nd edn. (Pren-

tice Hall, Upper Saddle River 2004)

Part F 54.6

Production, Supply, Logistics and Distribution References 959

References

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worked enterprises – parallelism, error recovery

and conﬂict resolution, Comput Ind. 42,275–287

(2000)

54.2 F. Keenan: Logistics Gets a Little Respect, Bus.

Week, 112–115 (2007)

54.3 Gartner, Inc.: Hype Cycle for Manufacturing 2005,

Gartner’s Hype Cycle Special Report (2005)

54.4 S.-L. Jämsä-Jounela: Future trends in process

automation, Annu. Rev. Control 31(2), 211–220

(2007)

54.5 H. Jack: Integration and Automation of Manufac-

turing Systems (2001)

54.6 R.A. LeMaster: Lectures on Automated Production

Systems (Department of Engineering, University of

Tennessee at Martin)

54.7 F. Gómez-Estern: Cintas Transportadoras en Au-

tomatización de la Producción, in Spanish

54.8 M. Piszczalski: Plant control evolution - technology

update information, Automot. Des. Prod. (2002),

http://www.thefreelibrary.com/Plant+control+

evolution.+(Technology+Update+Information).

-a084237484

54.9 R.S. Russell, B.W. Taylor III: Operations Manage-

ment, 4th edn. (Prentice Hall, Upper Saddle River

2003)

54.10 K.C. Laudon, J.P. Laudon: Management Informa-

tion Systems, 9th edn. (Prentice Hall, Upper Saddle

River 2006)

54.11 E. Turban, D. Leidner, E. Mclean, J. Wetherbe: In-

formation Technology for Management, 6th edn.

(Wiley, New York 2008)

54.12 J.F. Shapiro: Business Process Expansion to Exploit

Optimization Models For Supply Chain Planning

(2002)

54.13 P. Anussornnitisarn, S.Y. Nof: e-Work: the chal-

lenge of the next generation ERP systems, Prod.

Plan. Control 14(8), 753–765 (2003)

54.14 S.Y. Nof: Collaborative control theory for e-Work,

e-Production, and e-Service, Annu. Rev. Control

31, 281–292 (2007)

54.15 S.Y. Nof, F.G. Filip, A. Molina, L. Monostori,

C.E. Pereira: Advances in e-Manufacturing, e-

Logistics, and e-Service systems. Milestone report,

Proc. IFAC Congress’08 (Seoul 2008)

54.16 EPCglobal: http://www.epcglobalinc.org

Part F 54

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961

Material Hand

55. Material Handling Automation in Production

and Warehouse Systems

Jaewoo Chung, Jose M.A. Tanchoco

This chapter presents material handling automa-

tion for production and warehouse management

systems that process: receipt of parts from ven-

dors, handling of parts in production lines, and

storing and shipping in warehouses or distri-

bution centers. With recent advancements in

information interface technology, innovative sys-

tem design technology, and intelligent system

control technology, more sophisticated systems

are being adopted to enhance the productivity

of material handling systems. Information inter-

face technology utilizing wireless devices such as

radiofrequency identiﬁcation (RFID) tags and mo-

bile personal computers signiﬁcantly simpliﬁes

information tracking, and provides more accurate

data, which enables the development of more re-

liable systems for material handling automation.

Highly ﬂexible and efﬁcient automated mater-

ial handling systems have been newly designed

for various applications in many industries. Re-

cently these systems have been connected into

large-scale integrated automated material

55.1 Material Handling Integration ............... 962

55.1.1 Basic Concept and Conﬁguration .. 962

55.2 System Architecture .............................. 964

55.2.1 Material Management System ...... 965

55.3 Advanced Technologies ......................... 969

55.3.1 Information Interface Technology

(IIT) with Wireless Technology ...... 969

55.3.2 Design Methodologies for MHA..... 971

55.3.3 Control Methodologies for MHA .... 972

55.3.4 AI and OR Techniques for MHA ..... 975

55.4 Conclusions and Emerging Trends .......... 977

References .................................................. 977

handling systems (IAMHS) that create synergy with

material handling automation by proving speedy

and robust infrastructures. As a beneﬁt of high-

level material handling automation, the modern

supply chain management (SCM) successfully syn-

chronizes sales, procurement, and production in

enterprises.

In today’s competitive environment, suppliers must be

equipped with more cost-effective and faster supply

chain systems to remain in the market. Companies are

investing in material handling automation (MHA) not

only to reduce labor cost, delivery time, and product

damage, but also to increase throughput, transparency,

and integratability in production and warehouse man-

agement systems. The material handling industry has

grown consistently over many years. The Material Han-

dling Industry of America (MHIA) estimates that, in

2006, new orders of material handling equipment ma-

chines (MHEM) grew 10% compared with 2005 and set

a new record high at US$ 26.3billion in the USA [55.1].

In the past, labor cost was the most important el-

ement for estimating the return on investment (ROI)

of a stand-alone automated material handling system

(AMHS), and the system was a relatively small part

of the production or warehouse facility. Nowadays,

the impact of the system throughout the supply chain

is becoming larger and more complicated; for ex-

ample, a radiofrequency identiﬁcation (RFID) system

enhances customer satisfaction by providing conve-

nience in data tracking as well as reducing order picking

times and shipping errors in warehouse. AMHSs are

not alternatives selected after prudent economic ana-

lysis, but are rather major components in a production

and warehouse facility. Also, the sizes of systems

and the complexities of their operations are increas-

ing. Multiple AMHSs consisting of RFID systems,

automated guided vehicles (AGVs) systems, and au-

Part F 55

962 Part F Industrial Automation

Free-size AS/RS

Floor

storage area

Piece picking

system

Pallet AS/RS

Receiving and inspection

Load handling area

Vertical stacker pallet retrieval line

Small cargo delivery line

Filling in /packing/

transportation

line

a) Warehouse system for pharmaceutical industry

b) Material flows in warehouse system above

Fig. 55.1a,b IAMHS for pharmaceu-

tical industry (courtesy of Murata

Machinery).

(a) Warehouse system

for pharmaceutical industry,

(b) ma-

terial ﬂows in warehouse system

above

tomated storage and retrieval systems (AS/RSs) are

typically installed in a production and warehouse fa-

cility as a connected system. As its complexity has

increased, optimization of the design and operation of

these systems has become of interest to both AMHS

vendor companies and their customers. Many exam-

ples of these integrated systems can be observed in the

semiconductor [55.2], automotive [55.3], and freight in-

dustries [55.4,5].

This chapter introduces practical applications of

MHA for production and warehouse systems. It starts

by introducing a concept of the IAMHS that uses sev-

eral types of the AMHS in a single integrated system

(Figs. 55.1 and 55.2). The focus is particularly on what

an IAMHS consists of and how it collaborates with

other systems in SCM. Based on this introduction, com-

ponents of the IAMHS and their recent technology

advancement in the MHA will be reviewed.

55.1 Material Handling Integration

55.1.1 Basic Concept and Conﬁguration

An IAMHS integrates different types of automated

material handling equipment in a single control en-

vironment. A simple type of IAMHS was used for

seaport or airport cargo terminals, which are served

by stacker cranes and AGV systems [55.5]. The main

issue of the simple IAMHS is how to reduce wait-

Part F 55.1

Material Handling Automation in Production and Warehouse Systems 55.1 Material Handling Integration 963

Fig. 55.2 New IAMHS design for next-generation semi-

conductor fab (courtesy of Middlesex)

ing time during job transition between two different

AMHSs to increase throughput; for instance, an AGV

has to wait after arriving at the load position if the

crane is not ready to unload a container to the AGV.

If their jobs are poorly synchronized, the waiting time

will be longer, and as a consequence throughput will

drop.

Recently IAMHSs with more complicated com-

ponent systems have been implemented for many

companies in different industries. Figure 55.1 shows

an example IAMHS used in a warehouse system in

the pharmaceutical industry [55.6]. In this conﬁgura-

tion, there are ﬁve different types of the AMHS. First,

a pallet AS/RS is installed and the temperatures of

each shelf in the AS/RS can be controlled according

to the characteristics of the products stored to main-

tain product quality. Second, a free-size AS/RS is used

for storage of individual orders and items that are fre-

quently replenished. It can store items regardless of

their size, shape, or weight since it uses a hoisting car-

riage that can handle a wide range of products. Third,

an automated overhead traveling vehicle is installed to

replenish items with minimum labor cost and waiting

time. It uses overhead space to increase space efﬁ-

ciency. Another AMHS used is a digital pickingsystem,

providing convenience for picking tasks by displaying

directions on a digital panel installed on the shelves.

Finally, the IAMHS is operated by handheld termi-

nals providing many applications in the warehouse.

It is equipped with an RFID or barcode reader that

allows ﬂexible adaptation to changes in distribution

quantity.

The semiconductor industry is equipped with one

of the most complex IAMHSs for wafer fabrication

(fab) lines (Fig. 55.3). A fab line may consist of more

than 300 steps and 500 process tools. Material trans-

portation between tools in a wafer fab line is fully

automated by the overhead hoist transporter (OHT)

system, which is a type of rail-guided vehicle (RGV)

system, an AS/RS called the stocker, a lifting system

that transfers wafer carriers between different ﬂoors,

and a mini-environment that is used for a standard

interface of machineswith the AMHS.Forthenextgen-

eration of IAMHS in a fab line, Middlesex has proposed

a new concept using conveyor systems (Fig.55.2)in-

stead of OHT systems and stockers, which guarantees

larger-capacity transfers and quick response times for

deliveries. Middlesex has focusedon high-endconveyor

systems for many years. More reviews of the IAMHS in

the semiconductor industry are provided by Montoya-

Torres [55.2].

These IAMHSs are generally highly ﬂexible in

design for customized usage, and some of them are

even unique and revolutionary. Kempfer [55.7]in-

troduced an order picking system utilizing a voice

recognition system and RFID system in a large-

scale automated distribution center. The article reports

that the average order picking performance was im-

proved from 150 cases per man-hour to 220 cases

per man-hour by reducing operators’ information han-

dling time. A few companies also achieved similar

Master planning

Transfer command A

Transfer command B

ERP systemEDI server

MES

MMS

IAMHS

Data

server

AS/RS

controller

AGV

controller

Other systems

in SCM

Conveyor

controller

RFID

system

SDSWMS

Fig. 55.3 IAMHS in hierarchical system architecture

Part F 55.1

964 Part F Industrial Automation

improvements by adopting an integrated RFID and

voice recognition system [55.8,9]. Chang et al. [55.9]

proposed an integrated multilevel conveying device

for an automated order picking system that transfers

articles between two different levels of a multi-

storey building to improve the operational and spa-

tial efﬁciency of the warehouse system. The system

employs a specially designed device comprised of

a stacker crane, a vehicle-based transporter, and con-

veyor system.

55.2 System Architecture

In the design of a large-scale IAMHS, a well-structured

system reduces the redundancies of functions in differ-

ent modules, unnecessary transactions between mod-

ules, and system errors caused by large and complex

individual functions of these modules. An algorithm

ignoring the system architecture sometimes tends to

create many problems during implementation, mainly

because of the lack of necessary information and dif-

ﬁculty in interacting with existing systems [55.10].

Examples of this limitation can be found in the liter-

ature. An AGV scheduling algorithm under an FMS

environment determines a sequence of the AGV route

within a certain time horizon, considering the informa-

tion from both the work centers and AGV systems on

a shop ﬂoor. However, under this system architecture, it

is very difﬁcult for an AGV controller to take into con-

sideration complex constraints of work centers such as

machine status, processing times, and setup times be-

cause of the long calculation time. Therefore, generally,

job sequencing and scheduling are performed indepen-

dently by the scheduling and dispatching system, which

is then connected to the AGV controller using a se-

quence of protocols. An AGV controller only takes

care of requested transfer commands, which specify

source and destination locations, priorities, and com-

mand trigger times. There is already too much load

on the AGV controller in its original tasks, which in-

clude path planning for a vehicle, job dispatch for

a newly idle vehicle, vehicle dispatch for a new job

requested, error recovery, etc. [55.11]. Therefore, the

developed AGV scheduling algorithm should be mod-

iﬁed based on the structure of the system architecture.

One way to carry out this modiﬁcation is to break up

the algorithm for different modules in the system struc-

ture. During this break-up process, it is unavoidable

to change the algorithm depending on the availabil-

ity of information to the module, which sometimes

causes signiﬁcant performance degradation compared

with the original algorithm. As the number of subsys-

tems being used in production and warehouse systems

continues to increase, a well-structured system will be

beneﬁcial for facilitating collaborations between dif-

ferent departments as well as these systems. However,

it is an open challenge to construct a well-designed

system structure that accommodates all the different

types of AMHS regardless of the size of the sys-

tem and the type of business on which the IAMHS is

centered.

Various types of system architecture can be used to

design an IAMHS with other application systems, de-

pending on the manufacturing type of the shop ﬂoor,

the size of the total system, the number of transactions

per second, etc. Figure 55.3 illustrates a design exam-

ple of the system architecture for the IAMHS presented

in Fig.55.1. The focus of this ﬁgure is on software mod-

ularity. Each AMHS has its own controller (the four

controllers at the bottom of Fig. 55.3), which is respon-

sible for its own tasks and communication with the

material management system (MMS), which is a high-

level integrating system that will be explained later in

more detail; for example, an AGV controller addresses

job allocation, path planning, and collision avoidance,

receives a transfer command from the MMS (trans-

fer command B in Fig.55.3), and reports necessary

activities such as vehicle allocation and job comple-

tiontotheMMS so that data are kept for tracking in

the future. Each controller also has to process error-

recovery routines for robustness of the system control.

The MMS manages multiple controllers of different

AMHSs, and has a database server to store all trans-

actions of the subsystems in the IAMHS. It receives

transfer commands or short-term scheduling results of

processing machines from the scheduling module in

a higher-level system in the SCM (transfer command A

in Fig.55.3). In this structure,long-term optimization of

processing machines is responsible for the higher-level

system, and the MMS focuses on efﬁciencies during

the transportation of unit loads within production and

warehouse facilities. Details of the MMS are explained

in the next section. As shown in Fig.55.3, the higher-

level systems of the

MMS can be a manufacturing

execution system (MES), warehouse management sys-

Part F 55.2