International Journal of Electronic Business Management, Vol. 2, No. 1, pp. 59-68 (2004)
59
A HIERARCHY PLANNING MODEL FOR
TFT-LCD PRODUCTION CHAIN
James T. Lin*, Tzu-Li Chen and Chien-Chung Huang
Department of Industrial Engineering and Engineering Management
National Tsing Hua University
Hsinchu (300), Taiwan
ABSTRACT
Due to the progress of high technology, TFT-LCD (Thin Film Transistor – Liquid Crystal
Display) has been widely put in use recently. The manufacturing technology of the
TFT-LCD industry mainly consists of array, cell, module processes, in which there exists
special characteristics such as different objectives of individual process’s scheduling,
complexity of manufacturing processes, and multi-site production, etc. It is important to
synchronize to meet customers’ demand effectively and to interactively plan between
up-stream and down-stream in the TFT-LCD production chain. This research proposes a
analytic framework for TFT-LCD Production Chain planning and scheduling which is
verified by a practical example of a TFT-LCD company in Taiwan. First, it discusses the
production chain structure of the company and its current (as-is) planning model. And then,
it constructs the planning models from three stages which are production strategy, planning
process, and planning algorithm, where a future (to-be) planning model is developed and
named as ATO (assemble-to-order) production strategy, ATO planning process and CBS
(constraint-based simulation) algorithm. The model includes order management, mid-term
sales and operations planning (or master production chain planning), and short-term master
scheduling. Moreover, this paper also discusses how to effectively allocate critical
resources, such as key materials and limited capacity between both supply and demand
sides.
Keywords: Production Planning, TFT-LCD, Production Chain, Simulation, Hierarchy
Planning Model
1. INTRODUCTION
TFT-LCD is a key technology in a wide range
of electronic products. TFT-LCD products are
becoming increasingly popular. However, research on
TFT-LCD production planning is scarce, and most
studies focus only on production technology. More
and more companies are becoming to face their
production and supply chain strategy and reconsider
the coordination of demand and supply in the
production chain.
A TFT-LCD manufacturing process consists of
three main sub-processes - Array, Cell and Module
process as shown in Figure 1. Each process may have
more than one factory, constituting a multi-site
manufacturing environment. The planning system of
each process has different planning goals. For
example, Array and Cell processes are together
features of the capacity-oriented production that
emphasize the high utilization of machines, and
*
Corresponding author: jtlin@ie.nthu.edu.tw
reduce loss of capacity. That is because the
production equipment is critical resource in these
processes. However, the Module process involves a
material-oriented production environment that
depends on the availability of the key parts or
components. How to match the key parts with the
demand will decide the customer fulfillment rate and
inventory level, which are the important performance
for TFT-LCD industry.
Figure 1: The manufacturing process of TFT-LCD
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International Journal of Electronic Business Management, Vol. 2, No. 1 (2004)
This article proposes an analytic framework for
production chain planning and scheduling in
TFT-LCD industry and analyzes whole planning
system from production strategy and production
planning process to production planning algorithm.
Compared the current (as-is) with future (to-be), this
paper also provides the planner with a better decision
model.
For planning and scheduling, the cell process
will have these characters such as manufacturing
leader time varies, material matching and so on. In
the cell process, each of machines group manufacture
different batch. This makes the leader time hard to
define. And if it can release, it needs the same kind of
CF and TFT to match. It will need to concert the
material and capacity together.
2. INTRODUCTIONS FOR
TFT-LCD INDUSTRY
In TFT-LCD industry, in general, there exists
some specific characteristics, such as unexpected
demand fluctuation, customized product that each
customer will designate the specific key components,
long lead time of procurement, and short product life
cycle. Herein the details of the mentioned three main
processes of TFT-LCD manufacturing, the various
objective functions associated to each process, and
the constraints for production planning and
scheduling are discussed as below.
2.1 TFT-LCD Manufacturing Process
2.1.1 Array Process
Array process in TFT-LCD manufacturing is
very similar to semiconductor wafer fabrication
except the material components. As shown in Figure
2, the main raw material of Array process is the glass
substrate which must be processed 5-7 times through
cleaning, coating, exposure, developing, etching, and
strip, etc.
Figure 3: Cell process [7]
2.1.3 Module Process
Module process is the last stage of TFT-LCD
manufacturing process where the TFT-LCD panels
passed from liquid crystal process are assembled with
all the necessary parts such as black lights, IC, and
PWB, to complete the final TFT-LCD product as
shown is Figure 4.
Figure 4: Module process [7]
Figure 2: Array process [7]
2.1.2 Cell Process
Cell process is the special step in TFT-LCD
manufacturing, in which two components, Color
Filter and TFT will be processed through cleaning,
alignment-Layer printing and rubbing. Then Color
Filters will be added on the seal and be appended to
TFT. After assembling, the liquid crystal will be
injected into the spacer as shown in Figure 3.
2.2 The Objective of TFT-LCD Manufacturing
Process
Due to the manufacturing of variety in each
process, different objective functions are conducted.
In the global view, to enhance the fulfill rate to
customer is the common cognition of the three stages,
while various goals are designed during each process
in the local view. The features of Array process are
the recycling production and sharing jointly finite
facilities, in which the primary goal is to maximize
the utilization of resources under satisfying the
requirements of customers. Similarly, the important
considerations of Cell process are the availability of
color filters and the objective is the same as Array
process. Therefore, both of Array and Cell processes
are belonged to capacity-oriented production
J. T. Lin et al.: A Hierachy Planning Model for TFT-LCD Production Chain
planning. However, the key factor of Module process
is emphasized that the key materials are appropriately
adopted. So Module process could be classified into
material-oriented production planning and the related
goal is to meet customer’s varied demands, such as
specific materials or diverse grades of TFT-LCD
products.
2.3 Constraints and Characteristics
According to the characteristics of TFT-LCD
manufacturing process, some constraints on the
production planning and scheduling are summarized
as follows:
1. Multi-site planning: Due to the increasingly
complicated manufacturing processes, the
business size is enlarged. The TFT-LCD
manufacturing processes are distributed to various
areas, in which a Multi-site planning of
production chain should be taken into account.
2. The capacity’s constraint of each plant: Under the
multi-site production framework, each plant has
its own capacity limitation due to the finite and
expensive machines.
3. The capacity’s constraint for each product in a
certain plant: Due to the different requirement in
each product, such as panel’s size, glass substrate
thickness, specified materials, and limited
flexibility of machines, the yield of each product
is limited.
4. Fully loaded capacity for array process: Array
process is a bottleneck stage through a TFT-LCD
production line and the machines in Array process
are very expensive and costly. So it must reach the
upper limit of its capacity when planning to put
into production for Array process.
5. Key materials’ constraint: In general, glass, color
filter, polarizer, driver IC, PWB and back light are
key materials in TFT-LCD manufacturing process.
The lead-time for the procurement of these key
materials is longer (over one month) and different
with each other. Time to the acquisition of theses
material must be concerned when implementing
the production plan. In addition, the allocation of
key materials is also an important factor while
different products compete with the common key
materials.
6. The constraint of product’s ranking: The ranking
of the products in a TFT-LCD process can be
classified as shown as Figure 5. First, all products
are classified in terms of size and each product
will be categorized again according to the
divergence of glass’s thickness in Array process.
After Cell process, products are assorted as
H-grade, M-grade and L-grade. L- continuously.
Products will be classified again in Module
process due to the specific materials are requested
by customers. Finally, every product will be tested
in the inspection stage and ranked as A, B, C, D
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and E grades. Planners must determine the rate of
the distribution of final five grades according to
past experience. Different customers may have
different demands due to the materials and
product’s grades. For example, one customer
needs SG01-A-grade product and another needs
SG03-C-grade product. Planners must aggregate
these diverse demands and calculate back by way
of the known rate of the distribution of final five
grades so as to obtain the production plan of
putting into Array process initially.grade products
usually are scraped and M-grade products are put
into production in Module process if customers
are willing to accept them. In general, only
H-grade products will be processed in Module
process
Figure 5: The ranking of the products in TFT-LCD
process
7. The constraint of production batch: During the
Array process, a batch production approach in
which one lot contains 20 sheets of glass
substrates is adopted. In the front stage of Cell
process, products are processed by the “sheet”
mode. It will be split into 2, 4, or 6 pieces through
the partition operation in Cell process. Finally,
products are made by the “piece” mode in Module
process.
8. The constraint of manufacturing process’s paths:
Operational routing of each product is different
due to the requested sizes, thickness, and features
of products. Therefore, each product has its own
manufacturing routing. For example, the products
with 15 inches only can be produced in some
specific plants but 14 inches ones are unrestricted.
9. The influence of the defective rate: The
information about the defective rate should be
predicted in advance before planning. In general,
the actual output of production every month (or
day) is obtained by subtracting the number of
defective products from the yield of putting into
Array process.
10. The constraint of the specified materials by
customers: This problem is mainly occurred in
Module process, in which the customer will
specify a certain supplier that provides the
components such as drive IC, PWB and
backlights.
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3. LITERATURE REVIEW
In the literature, researches classified three
different catalogs to discuss how to analyze and
distinguish various different production strategies.
First, some researches differentiate distinct
production strategy through Order Penetration Point
(OPP) concepts. OPP is the point of pulling inventory
from the activities of manufacturing, assembly,
packaging, or distribution when receiving customer
order. Second, another researchers differentiate
distinct production strategy in accordance with
Customer Order Decoupling Point（CODP）. CODP is
the point at which forecast-driven and order-driven
activities meet in the supply chain. Finally, other
researchers differentiate distinct production strategy
according to the concept of postponed manufacturing.
A supply chain is the process of transferring
goods from their points of origin to markets or to end
consumers. The supply chain of a packaged consumer
goods manufacturer, for instance, comprises
manufacturing, packaging, distribution, warehousing,
and retailing. The order penetration point (OPP) is the
place in the supply chain where the supplier allocates
the goods ordered by the customer [5]. Goods might,
for instance, be produced after orders come in ("make
to order", MTO) or allocated from a warehouse once
the orders have been received ("ship to order", STO).
Each order penetration point has different costs and
benefits for the supplier and its customer. When the
supplier allocates orders from its distribution center, it
can deliver them quickly if they are in stock. Rapid
delivery (a benefit for the customer) therefore
depends on holding a large inventory (a cost for the
supplier). Of course, the wider the product range, the
bigger the inventory, so the supplier either incurs
large inventory costs to minimize delivery times or
cuts inventory and risks delays in fulfilling orders.
As Figure 6, it illustrates three mainly OPP
places in supply chain [5]. This "pack to order"
approach gives the supplier the benefit of lower
inventory expenses, but the customer must wait for
the goods to be packaged (a cost). To reduce that
delay (a benefit for the customer), the supplier must
bear the cost of additional packaging capacity.
Moving the OPP back still further to manufacturing
on demand makes it possible for the supplier to meet
the specifications of individual customers (a benefit
for them). But the delivery time rises (a cost for
them), and the supplier process efficiency declines
each time a customized design replaces a standard
one (a cost for the supplier and the customer alike).
Yang [10] explains that Customer Order
Decoupling Point (CODP) is the point at which
forecast-driven and order-driven activities meet in the
supply chain. The upstream activity of this point is
operated according to forecasting information. When
receiving customer order, the downstream activity of
this point is operated according to actual customer
order.
Figure 6: Three mainly OPP places in supply chain
[5]
Vander [9] divided the location of CODP into
five various models. See Figure 7. First model, when
receiving actual customer order, the finished stock at
distribution phase will be pull out and directly sold.
The activities of manufacturing and assembly are
operated according to forecasting information.
Second model, the finished stock at assembly phase
will be pulled out and delivered through distribution
and sales after receiving actual customer order. This
model is also called “make to stock.” Third model,
the finished stock at manufacturing phase will be
pulled out and delivered through assembly,
distribution and sales after receiving actual customer
order. It is also called “assemble to order.” Four
model, “make to order,” when receiving actual
customer order, it must be processed through the
activities of manufacturing, assembly, distribution
and sales and then delivered to customer. Final
model, when receiving actual customer order, it must
be processed through all activities and then delivered
to customer.
Figure 7: The locations in five various models of
CODP [9]
The concept of “postponement” is about
delaying activities until exact demand can be
J. T. Lin et al.: A Hierachy Planning Model for TFT-LCD Production Chain
identified. Alderson in 1950 originally introduced
“Postponement” in the marketing literature. Fifteen
years later, Bucklin [2] extended and analyzed it in
the context of shifting risk. Bowersox [1] thought that
“postponement” can take three forms：time (delaying
activities until orders are received in time), place
(delaying moving goods until orders are received,
thus keeping goods centrally and not making them
place specific), and form (delaying activities that
determine the form of specific end products until
demand is known). “Time” and “place”
postponement, when applied in combination, are
referred to as logistics postponement. When “form”
postponement is added to logistics postponement,
postponed manufacturing occurs.
In applying postponement, van Hoek [4]
mentioned that firms can customize and localize
products according to customer demand and local
market circumstances from a vantage point close to
the market. This enhances the efficiency of various
operations and avoids uncertainty about the
specification of orders and order mixes. Besides
customizing postponed operations, those activities
that are not postponed (for example, up-stream
activities) can be run in a mass production
environment, thereby maintaining
efficiency.
Postponement may be applicable in many industries.
Yet the specific customization level and the extent to
which postponement is applied can vary. In the
electronics and automotive industry, modular product
design allows for postponement in manufacturing. In
process industries such as pharmaceuticals, some
processing cycle times may last longer than the
customer order lead time, while the process cannot be
decoupled at an intermediate stage. Thus operating
characteristics influence the feasibility of various
postponement forms. In addition to product and
process design (continuous or decoupled process), the
implementation of postponement also affects the
supply chain structure.
Pagh and Cooper [8] also proposed the
concepts of “speculation” and “postponement” about
supply chain. They analyzed generic supply chain
strategies by combining manufacturing and logistics
postponement and speculation. Thus, P/S strategies
can be classified as four types of the full speculation
strategy, the manufacturing postponement strategy,
the logistics postponement strategy, and the full
postponement
strategy.
The
manufacturing
postponement is to retain the product in a neutral and
noncommittal status as long as possible in the
manufacturing process. This means to postpone
discrepancy of form and identity to the latest possible
point. The logistics postponement is to maintain
anticipatory inventory at one or a few strategic
locations. This means to postpone changes in
inventory location downstream in the supply chain to
the latest possible point as shown as Figure 8.
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Figure 8: Manufacturing postponement and
manufacturing speculation strategy [8]
According to the preceding four P/S strategies,
Pagh and Cooper further provided a “profile analysis”
method, as Figure 9. This table can help managers
how to decide a appropriate P/S strategy for own
company and identify the discrepancy and features in
the different decision points that include product (life
cycle, property and value), market demand (relative
delivery lead-time, uncertainty of demand),
manufacturing and logistics (economies of scale,
special capabilities) and so on. In sum, managers can
understand how a company transfers the production
model by this “profile analysis” method.
Figure 9: The profile analysis [8]
4. PRODUCTION CHAIN
ANALYTIC FRAMEWORK
Most research in this area focuses on
production strategy models. However, many
questions remain in other areas. Analyzing the whole
system in a real case, such as in the TFT-LCD
industry, is important. The first question concerns
how to analyze and how to improve the model.
This work will propose an analytic framework
for modeling the production chain in TFT-LCD, and
improve the planning model in the past. As in Figure
10, this analytical framework includes three levels of
planning hierarchy on the y axis such as production
strategy, planning process and planning algorithms.
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International Journal of Electronic Business Management, Vol. 2, No. 1 (2004)
The x-axis marks as-is model and to-be model to
enable change to the model to be indicated. This
matrix helps to analyze production chain models.
Figure 10: The analytic framework for production
chain in TFT-LCD
5.2 As-Is Production Planning Process
The MTS production strategy involves the
planning process directly. As indicated in Figure 12,
over the medium-term, of about six months, sales
departments collect all forecasts from their different
customers. Almost all customers provide monthly
forecasting quantities of each product. The sales
department aggregates the customers’ forecasts and
the manufacturing department then makes an over the
medium-term plan to decide monthly production and
key-parts purchasing quantities. They must be aware
of constraints such as monthly capacities, and
quantities promised by suppliers over the
medium-term. The aggregated planning horizon is
near six months. According to the monthly production
plan, the material management department roughly
drafts a long-term monthly purchasing plan.
Based on the matrix, the proposed
methodology is first used to analyze the TFT-LCD
as-is model, top-down, from planning strategy,
planning process to planning algorithms. Second,
questions are classified into these categories in the
as-is model. Finally, a new to-be model of TFT-LCD
is proposed and a new planning framework is
developed.
5. AS-IS PRODUCTION CHAIN
MODEL AND PLANNING
PROCESS
The planning system of the TFT-LCD industry
is highly complicated. The proposed framework
divides the system into three different parts, whose
mutual relationships are very clear.
5.1 As-Is Production Strategy
The current production strategy of TFT-LCD
industry is called MTS (Make to Stock). MTS means
that all of the manufacturing processes are
implemented according to demand forecast and
promised orders. When new orders are received, the
quantity of finished goods on hand is checked. Then,
as shown in Figure 11, whether the order can be met
is determined. Array, cell and module processes are
scheduled based on the forecast. The quantity of
finished goods will be the same as ATP (available to
promise). New orders will be processed if the
associated quantities are less than ATP.
Figure 11: The MTS production strategy
Figure 12: The MTS production planning
process
For the short-term planning, the manufacturing
department plans the master scheduling which is the
so-called daily production plan with reference to the
monthly production plan. The currently used planning
algorithms are implemented based on trial and error.
The schedulers set schedules and check the materials
and capacity. If the materials and capacities are
insufficient, they will adjust them to generate the first
draft of the production plan.
When the monthly production plan is
determined, the sales department allocates the
inventory to each customer. They will at first check
the product demand and planned monthly production.
If the planned monthly production is less than the
demand for the product, they need to allocate the
demand to each customer.
In the short-term, the orders are received. The
sales department will check the quantity allocated
over the medium-term. If the customer orders are
more than allocated quantity, then some re-allocation
may be performed. After checking, the sales
department schedules shipping. This scheduling is
unrelated to the master schedule.
The two plans, the shipping schedule and the
master schedule, are different, as in Figure 13. Each
schedule is separately planned. The planner must
coordinate them to define the common version.
J. T. Lin et al.: A Hierachy Planning Model for TFT-LCD Production Chain
However, any change in the shipping schedule may
violate commitments to customers. If the master
schedule is changed, the daily production should be
modified too. Therefore, these plans must adjust less
as possible.
Figure 13: The MTS production planning process
question
5.3 As-Is Production Planning Algorithm
The process includes many different planning
and scheduling issues, including master scheduling
and aggregation planning. In each planning issue, it
has a planning algorithm to solve it. The way is
difficult to meet the objective. In the as-is model,
most of the planning is straightforward. The
aggregation planner initially fills the monthly
production plan with the demanded quantities. He
then tunes the plan to satisfy any constraints.
Accordingly, meeting objective is difficult. The
master scheduling algorithm is also in the same way.
Specifying monthly production, the master
scheduling can be determined from average
quantities. If some order is likely to be met late, then
the master schedule is tuned to satisfy it.
Consider an example. Today is in May and the
daily production plan for June is to be planned. When
the monthly production plans are determined, the
array of daily input quantities must be planned.
Figure 14 indicates the monthly production quantity.
If June has 28 days, for 14 inches products the daily
input quantity in array process will be ten lots. The
cell and module the array of daily input quantities but
consider more detail constraints, such as number of
unit transferred, yield and others.
Figure 14: The example of push planning algorithm
This algorithm is called the push algorithm from
the array process to the module process. When the
shipping schedule is determined, the module’s supply
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and demand may not balance. The daily production
plan of the module must then be tuned. The cell
process and the array process must pull to fulfill the
shipping schedule. This is called the pull-planning
algorithm.
5.4 The Disadvantage of the As-Is Module
Some disadvantages are summarized as
follows:
1. High level of Inventory of finished goods:
TFT-LCD is a product with a short life cycle. If the
inventory of finished goods is too high, then it will
be wasted when the demand changes. The stock of
finished goods must be reduced to decrease costs.
2. Severe planning fluctuation: The shipping
schedule and the master schedule are not the same
because they are planned independently without
any exchange of information, which makes the
corresponding plans hard to execute. Coordinating
these plans disrupts alters their preview versions,
making the resulting plan hard to execute.
3. Lack of customization: In the TFT-LCD industry,
customers always specify preferred components.
Sometimes they designate a supplier who supports
their preferred components. The manufacturer
must take apart the device and reassemble it from
the preferred components. Such customization is
difficult.
6. TO-BE PRODUCTION CHAIN
MODEL AND PLANNING
PROCESS
The disadvantages of traditional planning are
such that the TFT-LCD industry should change its
production chain model to improve its performance.
This work initially classifies these disadvantages into
three levels, based on which, the TFT-LCD industry
must change its model from a production strategy to a
production planning algorithm. Finally, this work will
introduce solutions how to change it.
6.1 Production Strategy Analysis
Traditional planning has some disadvantages in
the three areas of production strategy, planning
process and the planning algorithm. Some issues,
such as the high cost of holding inventory, can be
addressed with reference to the production strategy.
The MTS production strategy requires that enterprises
manufacture TFT-LCD panels into finished goods.
However, if a customer changes an order, such panels
become useless inventory holdings. This is just one
example. Other disadvantages such as planning
fluctuate questions are related to the planning process
without supply and demand information sharing.
The three different levels are related. When the
production strategy has been chosen, the planning
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International Journal of Electronic Business Management, Vol. 2, No. 1 (2004)
process will follow and is developed. Based on
dissimilar processes, the input and the output data of
each building block differ. The algorithms therefore
differ.
This work finds that the model also has some
disadvantages. If the production strategy causes
problems, it must be changed. A process and
algorithm are developed base on it. If the process, and
not the strategy, is causing problems, then the strategy
should not be changed. The process must be
improved. Some of the disadvantages of the
TFT-LCD As-Is model are related to strategy.
Therefore, the first step is to develop a production
strategy for TFT-LCD Industry. As indicated in Fig.
10, the as-is top-down model is very clear, and is
changed according to specify and a new solution is
developed.
6.2 To-Be Production Strategy
The to-be production strategy can be analyzed
from
four
perspectives:
product,
demand,
manufacturing process and inventory. TFT-LCD
products vary greatly and some are highly
customized. Each customer specifies some materials
or a supplier of materials. Requirements therefore
vary widely. Forecasting demands of finished goods
over the next six months is difficult. TFT-LCD has a
long manufacturing lead-time. The machines are very
expensive so that the TFT-LCD Industry must utilize
their capacity. Inventories are also a key performance
indicator for this industry. Holding wastes must gross
profit because the key components are also very
expensive.
Pagh and Cooper [1] proposed the concept of
postponement to determined whether the industry
should or should not choose to postpone manufacture
or logistics. This study applies their analysis of
profitability to the TFT-LCD industry to determine
the production strategy of the to-be model. As
depicted in Figure 15, the manufacturing
postponement strategy is found to be valuable for this
industry, improving most key performance indicators.
Figure 15: The analysis profile for TFT-LCD
The manufacturing postponement strategy can
be the MTO or the ATO strategy. These two models
differ in their point of the decoupling point. In MTO
models, the decouple point is outer than
manufacturing process that means that company will
manufacturing when receives the order ； In ATO
models, the decouple point is on the manufacturing
process. The company will manufacture the common
accompaniments. When it receives an order, it need
only perform final assembly.
Te key to choosing the ATO or MTO strategy is
to choose the decouple point. The decouple point of
the TFT-LCD manufacturing process depends on the
strategy and analyzing the manufacturing process is
crucial to the choice of the decouple point. High
utilization of resources is the critical consideration of
the array and cell processes in TFT-LCD
manufacturing. Capacity lost is equivalent to the
global output lost, even when no customer has placed
an order. In the module process most of the key parts
assembly is variety. It has a short lead time, but many
configurations are required to fulfill the customer
order. According to a manufacturing analysis, this
study proposes the decouple point between the cell
process and the module process. The TFT-LCD
industry can fulfill various orders by making the
component. Neither array nor cell capacity is wasted
and the module process meets the customers’ needs.
As shown in Figure 16, when receiving customers’
orders, enterprises assemble products.
Figure 16: The ATO production strategy
6.3 To-Be Production Planning Process
Based on the ATO manufacturing strategy, the
next question is the planning process. From the MTS
to ATO manufacturing strategy, the mainly change is
the order entry. In MTS, order entry will check the
finish goods to promise the customer, but in ATO it
will check all the components and module capacity
and so on. The order promising process will be
change.
Figure 17 depicts the planning process based
on the ATO strategy. The decouple point will change
the process. The scope of the master schedule is
reduced and then the final assembly scheduling is
scheduled in the module factory.
Over the medium -term, the personnel in P.P.
dept. will first develop monthly production plan
according to the information sales dept. provided
about the aggregate forecast demands and relative
materials supplying planning and other capacity
constraints. This monthly production plan will have
three functions. First, the personnel of M.C. dept.
provided the monthly plan to upstream suppliers so
J. T. Lin et al.: A Hierachy Planning Model for TFT-LCD Production Chain
that these suppliers have sufficient time to be ready
for required materials in mid-term time. Second, the
personnel of sales dept. can match the monthly plan
with the forecast demands of products so that they
engage in allocation planning (the output of this
action is allocated ATP, AATP). Third, short-term
planning personnel of P.P. dept. can develop daily
production plan in Array and Cell processes.
Figure 17: The ATO production planning process
In short-term planning when quotation orders
enter, it first determines if the order is a “rush order”,
if not, the order enters in the “order promise” module.
If the quoting time of orders is over the planning
horizon (about one month) of short-term master
schedule (MS) , planners will roughly estimate
whether the quotation order can be received or not by
way of the information of monthly AATP. If the
orders can be received, then the orders become the
confirmed orders.
And if the quoting time of orders is within the
planning horizon (less than one month) of short-term
MS plan, “order promise” module will evaluate in
detail whether the quotation order can be received or
not by way of the information of panel’s ATP and the
daily materials supply plan in Module process. If the
orders can be received, then the orders become the
confirmed orders.
The orders above belong to non-rush orders. If
the quotation orders are “rush orders”, then they
directly entering in “Quoting rush order” module.
Planners will examine the remaining materials and
the remaining capacity in final Module process so as
to decide whether the rush order can be received or
not. Similarly, if the orders can be received, then the
orders become the confirmed orders.
Therefore, confirmed order can be classified as
two types. One is a “non-rush” confirmed order and it
will enter in MS planning module so as to develop
master production schedule (MPS) in every process.
Necessarily, the MPS can be adjusted flexibly in the
former processes’ production plan so as to meet
customers’ demands. Another is a “rush” confirmed
order and it will only directly enter in “Final
Assembly Schedule (FAS)” module to satisfy
demands of rush order according to the current
condition of the remaining materials and the
remaining capacity in final Module process.
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6.4 To-Be Production Planning Algorithm - CBS
When the process is changed, the
corresponding algorithm changes considerably. The
multi-site and final-assembly are change to ensure
that planning and scheduling satisfy the many
constraints, concerning material, capacity and other
factors. This work uses a constraint-based simulation,
CBS, to solve the multi-constrained problems. CBS
integrates the three concepts of time windows,
multi-constraints, and discrete event simulation, DES.
Any difficult constraint can be built into the
simulation models. Time windows are used by the
CBS to eliminate periods in which the constraints
cannot be satisfied. Finally, it will remind the time
windows in which all constraints are satisfied.
The CBS planning process is described as
follows. First, CBS determines the earliest start time
of each job by forward simulation, and eliminates the
period before this earliest start time. Second, CBS
determines the latest start time by backward
simulation, and also deletes the period after the latest
due date. These two steps determine the time
windows for all constraints, as shown in Figure 18.
The best start time is determined according to
objective. If the objective is to maximize utilization,
then CBS will choose the earliest possible time. If the
objective is to minimize the number of finished
goods, then CBS will choose the latest possible start
time.
forward simulation
Type1 & Type2 Constraints
earliest start time
backward simulation
Type2 & Type3 Constraits
latest start time
Order Due Date
search order release time
according objective
forward simulation
Type1 & Type3 Constraints
earliest start time
backward simulation
Type2 & Type3 Constraints
latest start time
Order Due Date
Figure 18: The CBS concept
7. CONCLUSION
This work presents an analytical framework of
a production chain. In the past, fewer research
focuses on the planning model analysis and model
changing. This work uses this framework to analyze
the TFT-LCD production chain in terms of strategy,
process and algorithm. The as-is planning hierarchy
model is adapted from the MTS to the ATO
production strategy to reduce the inventory cost and
increase customization. Finally a new planning
process and algorithm are generated specifically for
this industry. A real case demonstrates the validity of
the analysis.
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International Journal of Electronic Business Management, Vol. 2, No. 1 (2004)
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ABOUT THE AUTHORS
James T. Lin is a Professor in the Department of
Industrial Engineering and Engineering Management
at National Tsing-Hua University (NTHU), Taiwan
R.O.C. He received his Ph.D. degree in Industrial
Engineering at Lehigh University in 1986. His current
research and teaching interests are in the general area
of Supply Chain and Production Management. In
particular, he is interested in Supply Chain
Management, Simulation Modeling of Manufacturing
Systems, Advanced Planning and Scheduling. He is a
member of IIE, SCS, and CIIE.
Tzu-Li Chen is a Ph.D graduate student of Industrial
Engineering and Engineering Management at
National Tsing-Hua University (NTHU). His research
interests are Simulation, Planning and Scheduling.
Chien-Chung Huang received his MS degree from
Industrial Engineering and Engineering Management
Department at National Tsing-Hua University
(NTHU). His research interests are Simulation,
Planning and Scheduling.
(Received July 2003, revised September 2003,
accepted November 2003)
International Journal of Electronic Business Management, Vol. 2, No. 1, pp. 59-68 (2004)
TFT-LCD 生產鏈之階層式規劃模式
林則孟*、陳子立、黃建中
國立清華大學工業工程與工程管理學系
新竹市光復路二段 101 號
摘要
由於科技之高度發展，TFT-LCD（Thin Film Transistor-Liquid Crystal Display）目前已
被廣泛地使用。TFT-LCD產業具有三大製程―列陣、組立以及模組製程，各自位於不
同的廠區。以往規劃方式採用各自獨立規劃，造成許多缺失。為了解決此缺失，本研
究首先彙整TFT-LCD產業的生產製程、生產規劃上的限制、產業特性以期能了解該產
業。而後，分析現有的生產模式、規劃流程以及規劃流程的演算法，並將現行缺失區
分為三個層次，分別為生產模式、流程以及規劃方式的問題。有鑑於此，本研究提出
以接單後組裝（Assemble-to-Order，ATO）為生產模式的規劃流程，以解決現行缺失。
然而，其衍生在ATO生產模式下，如何將現有各種資源，包含物料資源、廠區產能，
分配供給於各種需求，並同時排定需求在各廠區的投入產出排程的多廠區規劃排程問
題。在此問題下，本研究提出可同時規劃多廠區，同步考量將物料分配與各廠區主排
程規劃的演算法-以限制為基礎的模擬（Constraint-Based Simulation，CBS）
，以期能解
決此生產規劃問題。以限制為基礎的模擬是將限制與時間推進機構加以整合，利用限
制的不可違背性，透過時間推進機構的計算，將不合理的時窗加以去除。最後，在剩
餘的時窗內，根據目標，透過派工法則，搜尋較佳的解。經由案例的驗證，確認CBS
演算法的可行性。並將此案例及演算法建構於模擬軟體，比較不同的規劃方法，是否
在不同環境下會有不同的績效值。從分析結果可以得知，CBS規劃演算法均具有一定
的效益。
關鍵詞：生產計畫、TFT-LCD、生產鏈、模擬、層級式規劃模式
（*聯絡人：jtlin@ie.nthu.edu.tw）
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