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Economic models of offshore assembly in a printed circuit board assembly system
Economic Models of Offshore Assembly in a Printed Circuit Board Assembly System Jeffrey L. Funk, Westinghouse Science and Technology Center, Pittsburgh, Pennsylvania
needed to repair the problem (for example, replacing a defective or incorrectly inserted component). Inventory related costs can be divided into four categories: the personnel needed to handle (for example, indirect labor and stock room, shipping, and receiving personnel) and transact (for example, production, planning and control, inventory control, and accounting) inventory; the space to store inventory; the cost of money; and the financial losses from inventory that becomes obsolete each year due to changes in market demand or in engineering strategy. This paper describes economic models that address the concerns of manufacturing overhead costs and that can be used to compare both diverse methods of component control/component insertion and various U.S./offshore assembly systems for PCBs. These models represent nonequipment overhead costs for retrieval and kitting labor costs of individual components; inventory costs of boards and components; rework costs for various methods of component control/component insertion; and for the number of plants in the assembly system. The methods of component control include "kit-to-order," "kit-tostore," and "total Kanban". In addition to having different retrieval and kitting labor costs as well as different inventory costs, each method can affect component insertion labor costs: The inventory related expenses are included in the inventory carrying rate that seems to range between 12% and 25%, depending on both the overhead costs included in the rate and the efficiency of the manufacturing system. The lower bound includes
Abstract Although nonequipment overhead costs typically represent greater than 80% of manufacturing costs, few models of these costs have been developed and therefore, such expenditures are usually not explicitly considered when choosing a manufacturing system. This paper develops and uses models of retrieval and kitting labor costs along with component and board inventory costs--which together represent a large percentage of manufacturing overhead expenses--to compare U.S. and offshore assembly systems. Due to its higher inventory, other overhead, and shipping costs, offshore assembly is found to be less economically advantageous than previously believed.
Keywords: Assembly, Economics, Offshore, Kitting, Inventory, PCBs.
Introduction Manufacturing overhead costs have steadily risen in electronic industries and now exceed 80% of the value-added in most of these businesses. ~Further, although most economic models of electronic and mechanical assembly systems emphasize direct labor and equipment costs,2-a more than 80% of manufacturing overhead costs are for nonequipment costs. ~A large percentage of these costs in printed circuit board (PCB) assembly can be attributed to retrieval and kitting of electronic components, rework-related costs, and the storage of components and boards (that is, inventory). Rework costs include the time 274
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only the cost of money, while the upper bound includes all of the inventory related costs mentioned for an "inefficient" manufacturing system*. Because a just-in-time (JIT) "pull" system is becoming the standard production system within the commercial part of many manufacturing companies, the inventory models are developed for this type of production system. The pull system, originally developed in Japan, has become popular with a number of U.S. firms due to its low operating cost (for example, it requires fewer production, planning, and control personnel) and its positive effect on delivery times and inventory costs/ The diverse methods of component control/ insertion and of various U.S./offshore assembly systems are compared using Eq. (1):
Economic Models A generic PCB assembly system that uses a "pull" system for material control is outlined in Figure 1. The assembly system can have multiple plants (typically 1-3) with each plant having one "supermarket" and multiple "mini-markets." The supermarkets are used to store PCBs and components, while the mini-markets are used to store kits and components. Suppliers deliver unpopulated PCBs and electronic components to the first plant where they are stored in the plant's "supermarket." When a populated board is requested by a product assembly line or a partially populated board is requested by a second plant in the PCB assembly system, the supermarket releases the unpopulated PCBs and/or kits to a station in the assembly system. The supermarket also delivers electronic components to each minimarket when it requests them. A Kanban card or signal (electronic) is generally used to request either a particular PCB or electronic component from a supermarket. The components can be delivered from a supermarket to workstations in three ways and typically multiple methods are used in one factory as shown in Figure 2. Kit-to-Order. With the first method, "kits" can be made that contain the exact number of components needed to assemble one lot of a particular board type. This method is called "kit-to-order." When the product assembly line or a second plant in the PCB assembly system requests a specific board type, the components are retrieved from the supermarket, then counted into a kit, and the board is assembled. This method of component control is commonly used for very low-volume factories that use expensive and/or nonstandard components because it does not require components or kits to be stored at a mini-market. The component control cost per board (CCCkt o) for the kit-to-order method is represented by Eq. (2):
TA C = CCC + CILC + ECPB + TLC + BICC + SC (1)
where: TAC is the total assembly cost per board, CCC is the component control cost per board, CILC is the component insertion labor cost per board, ECPB is the equipment cost per board, TLC is the test labor cost per board, BICC is the board inventory carrying cost per board, and SC is the shipping cost. Component control costs are develo/ged in the section on economic models of component control, and they are represented by Eqs. (2), (7), and (12). Models of component insertion labor cost and equipment cost per board are developed in a later section, these are represented by Eqs. (18) and (19) respectively. Board inventory carrying, test labor, and shipping cost models are likewise developed in the subsequent section and are represented by Eqs. (21) through (25) respectively. In the first section of this paper, component control cost models are developed to compare three methods of component control. These include retrieval and kitting labor and component inventory carrying cost models. The next section combines these with component insertion labor and equipment cost per board models in order to compare four component control and insertion alternatives. The third section develops board inventory carrying, test labor, and shipping cost models and combines these with the other models to compare two U.S. and three offshore assembly systems.
C C C k t o = e z c k , o + C t C + ClCCsra
(2)
where: retrieval (RLCkt o) and counting labor costs (CLC) and component inventory carrying cost per board in the supermarket (CICCsm) are repres-
* The author is presentlydevelopingmodelsthat explicitlyrepresentthe inventoryrelated overheadcosts as a functionof parameters such as the type of production system (that is, push vs. pull), the amount of continous-flowmanufacturing,and the amount of standardization in the product. These modelswouldprovide a more accurate representationof the discussedissues.
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PCB and ComponentSuppliers [
Superaarket
I I
Plant ~I
#1
Boards ] Components
[ Comp. Insertion [
Kittlag
I
[ICo-ponentl
i,, 0o-oo, 1,,_
]
"Kit
to Order"
'Kit
to
Store'
I
IMini-aarket #I.I [
Minl-m~rket #1.M[ Coap. Insertlon[ "'" [ Comp. Insertion I Insertion Board Test
Components
]
WComplete Kanban'
Figure 2
An Outline of Three Component DeliveryMethods (TABVsI) that uses the supermarket. With respect to retrieval and counting labor costs, RTsI is the time for one retrieval from a supermarket, NPN is the number of part numbers that must be retrieved for a typical board, DL is the direct labor rate - including benefits, BLS is the board lot size, ABV is the annual board volume for a typical board, CT is the time to count one component, and NOC is the number of components that must be counted for a typical board. The component inventory carrying costs are represented by Eqs. (5) and (6), where the inventory costs are summed over each type of component stored in the supermarket. In Eq. (5), NDCsm is the number of different components stored in the supermarket, CV i is the component value or cost for component i, ICR is the inventory carrying rate, LSM i is the number of lots stored in the supermarket for component type i and CLS,p is the component lot size delivered by the supplier.
Plant ~N
Supermarket #N Boards [ Components
[ Comp. Insertion [
Kitting
I
Iilini-aarket #N. 11 [Minl-market #N.i/ Comp. Insertion[ "'" [ Comp. Insertion I
Storage
]
Assembly
Figure 1
Outline of a Generic PCB AssemblySystem ented by Eqs. (3), (4), and (5) respectively.
LSM i =
CICCsm
=
RLCkt o = RT, m*NPN*DL/BLS
(3)
CLC = CT*NOC*DL
(4)
DCV i CRSTst, / CLSsp
(6)
Equation 6, which estimates LSM i, is based on the number of Kanban cards/containers needed to transport component type i between each supplier and the plant, where the safety factor is assumed to be zero for simplicity. DCV i is the daily component volume for component type i, and CRST~p is the response time between the supplier and the supermarket.** The effect of each of these variables on carrying cost per part can be found in Funk ' 8 9 . 6
~ c'n CVi*ICR*LSMi*CLSstj/TABVsm (5)
i=1
The retrieval and counting labor costs are estimated for a "typical" board, while the component inventory costs are estimated for the plant and then amortized over the total annual board volume
** Although the component lot sizes and response times for deliveries between suppliers, supermarkets, and mini-markets vary among components, these equations assume that they are the same for simplicity's sake.
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NDCmm (number of different components in the minimarket), CLS~p with CLSmm, RSTsp with RSTs, (response time between the supermarket and a minimarket), TABVsm with TABVmm (total annual board volume handled by the mini-market), and LSM with LMM (number of lots stored in the mini-market for component type z). The kit inventory carrying cost (KICCmm) can be developed from Eq. (9) by summing the inventory costs over each type of component in a kit (NPN), as opposed to each component in the mini-market, (NDCmm) and by multiplying Eq. (9) by the number of different kits/boards (NDB) that are assembled using the kit-to-store method, as shown in Eq. (11). Further, the product of LMMi and CLSm,. is replaced by CLSkit,which is the number of components stored in each component bin of the kit.
Kit-to-Store. Kits produced by the second method can be stored in a mini-market in which each kit contains a large, nonfixed number of components for each type of component in a particular board type. This approach is called "kit-to-store." When the product assembly line or a second plant requests a specific board type, a kit is sent from the minimarket to a workstation served by that mini-market, and then the board is assembled. Before the kit is sent to the workstation, a "handful" of components are added to each component bin that is nearly empty in the kit. Components are delivered between the supermarket and mini-markets as they are requested by the mini-market via Kanban, as shown in Figure 2. Kit-to-store is typically used for inexpensive and nonstandard components. Although it requires the storage of kits and components at each minimarket, components do not have to be counted into a kit for each lot, and this method only requires component retrieval operations when components are needed either by a mini-market or to fill one component bin in a kit. The component control costs per board (CCCkt~) for the kit-to-store method are represented by Eq. (7):
NPN K1CCmm =
The retrieval labor costs per board (RLCkt~) from the supermarket and the mini-market can be represented by Eq. (8): RLCki t = RTsm * NOC* DL/ CLSIm + (8)
CLSm,. is the component lot size used in delivering components from the supermarket to a minimarket via Kanban. RTm,. is the time for one retrieval from a mini-market, and CLSki t is the component lot size used for filling a component bin in a kit from a mini-market. The component inventory carrying cost per board in the supermarket (CICC,,,) and mini-market (CICCmm)are represented by Eqs. (5), (9), and (10): ClCCmm = N~Cmra CV i*ICR~LMMiCLSmra/TABVmI (9) i=1
L M M i = D C V i * RSTsm / CLSmm
i=1
CVi*ICR*CLSkit/TABVmm (1 1)
Complete Kanban. Using a third method called complete Kanban, each workstation can be made a mini-market in which it stores each component used by that workstation. The components are delivered from the supermarket to a mini-market as requested by that mini-market via Kanban. This method is typically used in medium- to high-volume operations because although it requires very few retrievals and no counting of components into kits, it requires components to be stored at each workstation. The component control costs for this method (CCCka.) can be represented by Eq. (12). The retrieval labor costs (RLCka.) can be developed from Eq. (8) by replacing CLS,, m with CLSws(lot size for delivering components from the supermarket to a workstation), as shown in Eq. (13). The component inventory cost in the supermarket is represented by Eq. (5), and the component inventory cost at the workstation (CICCws) can be represented by Eqs. (14) and (15). Equations (14) and (15) are developed from Eqs. (9) and (10) by replacing TABVmm with TABVws (total annual board volume at the workstation), NDCmra by NDCw~(number of different components stored at the workstation), LMM with LWS (number of lots stored at a workstation for component type t), and CLS,, m with CLSw~.
CCCkts = RLCkit 4- CICCsm + CICCm m + KJCCmm (7)
RTmm*NOC*DL/CLSki t
NDB* ~
( 1O)
where: the inventory costs are summed over each type of component stored in the supermarket and mini-markets. Equations (9) and (10) are developed from Eqs. (5) and (6) by replacing NDC~,n with
277
CCCka~ = RLC~,, + CICC~,. + CICCw~
(12)
RLCka. = RTka,*NOC*DL/CLSw~
(13)
Journal of ManuJacturing Systems Volume 8/No. 4
CICCws =
~
Lws
i=1
Table I List of Component Control Cost Variables and theirDefault Values
CVi*ICR*LWSi* CLSws/ TABVws (14)
LWS i =
DCV~*RSTsm/CLSws
(15)
CateKor ~
Although most of the variables used in Eqs. (2) through (15) are independent, some of them are not. The component volumes (DCVi) used to estimate component inventory costs in a supermarket, minimarket, or workstation should match the product of the average number of components in each board (NOC) and the board volumes handled by the supermarket, mini-market, and workstation (TABV). Therefore, daily component volume (DCVi), the number of components/board (NOC), total annual board volume (TABV), and the number of different components (NDC) are related by Eq. (15), where (TABV) and (NDC) are for a supermarket, mini-market, or workstation. Each side of Eq. (15), which assumes that there are 240 working days in a year, represents the total number of components that are used by a supermarket, mini-market, or workstation.
Time
E i=1
DCVi
Definition
Board and
Value
CT
Time to count one component
RSTsm
Response time between the supermarket
1.2 see. .5 days
mad mini-market
RTsm NDCmm
R e t r i e v a l time from the supermarket Average number of d i f f e r e n t
NPN
Number of different part
Component
30 see. 1000
components per mini-mLrket
Diversity
I00
numbers per board
Volume
NCC
Number of components per board
250
TABYmm T o t a l ~nnuml board volume s e r v e d by a mini-market
13,500
TABVws Total annuml board volume of a
4,320
workstation Cost
DL
Direct Labor rate
ICR
Inventory carrying rate
$20/hr 25~
semiautomatic workstation, and the value for TABVmm assumes ten manual workstations working at full capacity for one shift. The results are shown in Figures 3-5 using a 2-level, 3-factor experiment. Each figure shows the effect of three variables on one method of component control. For example, the trials with a lower board lot size are shown on the left side of the cube in Figure 3, and the trials with a larger board lot size are shown on the right side of the cube. Similarly, low- and high-retrieval times are shown on the front and back of the cube respectively, while low and high values for NPN are shown on the bottom and top of the cube.
NDL
TABV*NOC/240=
¥ariable
(16)
Equations (5), (9), (11), (14), and (16) can be simplified using average component values in place of summing over the values for each component type. For example, the summation in Eq. (5) can be eliminated by multiplying the equation by the number of different components (NDCsI) and replacing CVi and NOCi with CV and NOC. Similarly, the summations in Eqs. (9), (11), (14), and (16) can be eliminated by multiplying Eq. (9) by NDCmm, Eq. (1 1) by NDCmm, Eq. (14) by NDCws, and the righthand side of Eq. (16) by NDC. Cost Comparison Between Methods. The three methods of component control are compared using Eqs. (2) through (16) for various values of BLS, NPN, RTsm , NDB, CV, RTmm and NDCw,. Since the component inventory carrying costs in the supermarket (CCC,m) are the same for each method of component control, Eqs. (5) and (6) are not considered in this section. The optimal lot sizes (CLSsm, CLSmm , and CLSws) are calculated in the Appendix by minimizing the sum of inventory carrying and retrieval labor costs. DCV is calculated for the mini-markets and workstations using Eq. (15). The values for the other variables are shown in Table 1 and are for a typical high-volume, high-mix factory. For example, the value for TABVw~assumes a two-shift, full capacity,
NP
35
Ts= (sec) 50
lO ~
D 2o BLS
Figure 3 Component Control Cost per Board ($) vs. BLS, RTsrn and NPN for the Kit-to-Order Method
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Figures 3-5 show that the Kanban procedure is
lo I .o5 I .1<1 cv
(s)
Figure 4 Component Control Cost per Board ($) vs. CV, RT=_ and NDB for the Kit-to-Store Method where ~PN = 100 and RTsm = 30 see.
NDCws
3~S mCsee)
I00
831 25 cv
(s)
D.5
the least costly method of component control, except for a combination of high values of CV (>$.50) and NDCws(>700) and low values of NPN (<50). In this case, kit-to-order is the lowest cost method of component control. The kit-to-store method is never the least costly method of component control. It is always the most expensive means, except when a low diversity of boards (NDB) is assembled and/or there are low component values (CV). In this case, the kitto-order method proves the most expensive. The method of component control used can also affect component insertion labor cost, however, "kit-to-order" and "kit-to-store" can increase the setup time for nonmanual insertion, while "complete Kanban", can increase manual insertion time. Setup time is increased when using kit-to-store or kit-toorder, because each component tube or reel must be loaded onto the automatic insertion equipment or each component bin must be filled with components for each individual lot. Manual insertion time is increased when using the complete Kanban method of component control because it may take longer to locate the correct component in the mini-market than in the kit. Therefore, kit-to-order and kit-tostore are typically used only with manual and one method of semiautomatic insertion because kitting only has a small effect on setup time. Likewise, complete Kanban is used only with semiautomatic, automatic, or robotic insertion because the equipment automatically delivers the components to either the insertion head or operator with these insertion methods. Described in the next section are some economic models and results for typical combinations of methods of component control and component insertion.
Economic
Figure 5 Component Control Cost per Board ($) vs. CV, RTsm and NDC for the Kanban Method
Models
Components can be manually, semiautomatically, automatically, or robotically inserted. Manual insertion requires an operator to read the process instructions and typically the operator verifies that all of the parts are in the kit or in the mini-market before insertion begins. The operator then acquires each component from the kit or mini-market, forms it if necessary (axial components), inserts it and cuts and clinches the leads. Semiautomatic equipment can be "light-directed" or "auto-place". The light-directed type of
Different variables are shown in each figure because most of the variables only have an effect on one method of component control. For example, NDB and RTmmonly affect the kit-to-store method. Similarly, NDCwsonly affects the Kanban method, and BLS only affects the kit-to-order method. The default values of these variables when they are not shown in Figures 3-5, are also shown in Table 1.
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semiautomatic insertion equipment uses a program to step the operator through a specific board. The operator loads a program, and the equipment presents or lights up the correct component bin or tube. The equipment also lights up the correct component insertion location for the operator who acquires the component and then inserts it. The auto-place type of semiautomatic insertion equipment requires the operator to move the board underneath the insertion head and the equipment automatically inserts the component. The component bins or tubes that apply to a particular board type may have to be loaded onto both types of semiautomatic equipment before insertion can begin. This is required when the components are "kitted", or when a component is inserted that does not have a dedicated location on the equipment when the components are "Kanbanned." Automatic insertion equipment independently performs all of the necessary operations. However, it still requires an operator to load and unload boards and to fix jams. The component tubes or reels may also have to be changed before insertion can begin. Even without these changes, the setup time is often long because the PCB must be adjusted within the board fixture before insertion can be performed correctly. Robotic insertion is slower than automatic insertion equipment, but its setup times are typically shorter and it can be used to insert nonstandard components. However, because special grippers and part feeders are needed for these nonstandard components, robotic insertion is applicable only for highvolume nonstandard components 3 For this reason, it is not considered further in this paper. Cost Models. Component insertion costs (CIC) per board can be represented by Eq. (17) where component insertion labor costs per board (CILC) and equipment costs per board (ECPB) can be represented by Eqs. (18) and (19) respectively. Component insertion costs are summed over each method of insertion (4 methods) since multiple methods are typically used to assemble a board. Equipment costs are annualized and then amortized over the annual board volume. CIC = CILC + ECPB
is the interest rate and N is the life of the equipment. 4
CILC = ~, (SUT)moi/BLS + ITmoi*NOCraoi + moi=l NOCmo i *oRmo i* DRT)* DL
ECPB =
TEC*I*(I+ 1)N TBV*[(I+ I )N-1]
(18) (19)
Total equipment costs can be represented by summing over each type of insertion equipment used in the system as shown in Eq. (20), where IEC is the individual equipment cost, ECP is the equipment's capacity in components per day, and TABV is total annual board volume. The value of TBV*NOC/ECP in Eq. (20) must be an integer because it represents the number of each type of equipment needed to handle the board volume. 4
TEC = raoiffil ~ IECmoi*TABV*NOC,~oi/ (ECPmoi*250X20)
Typical values of setup time, insertion time, defect rate, equipment cost and equipment capacity are shown for each method of insertion in Table 2. These values, particularly the defect rate, depend on the factory in question. The defect rates shown in Table 2 represent an average of a few manufacturing facilities. Since the typical defect repair time (to identify, remove, and replace the component) in one factory is 3600 seconds, the defect repair time per component can sometimes be greater than the insertion time per component. For example, the average defect time per component is 3.65 seconds for semiautomatic insertion (3600 seconds per component × 1 defect per 1000 components), and the average semiautomatic insertion time is 3.5 seconds. This simple numerical calculation supports the recent realization that quality should receive greater emphasis in American manufacturing. Cost Comparison Between Alternatives. Since standard components are typically inserted using more automated methods than nonstandard components, this section compares alternatives that contain multiple methods of insertion. The first alternative uses manual insertion and the kit-to-order method of component control. The second alternative also uses kit-to-order, but the components are semiautomatically (light-directed method) inserted. The third alternative automatically inserts standard DIPs (dualin line packages), axials and radials that are Kan-
(17)
In Eqs. (18) and (19), SUT is the setup time, IT is the insertion time, DR is the defect rate, DRT is the defect repair time, TEC is the total equipment cost, I
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Journal of Manufacturing Systems Volume 8/No. 4
Table2 ]3jpiealValuesfor each Method of Insertions ..... j.
32.0 Individual
Equipment
Setup
Insertion
Defect
Equipment
Cap~clty
Method of
Time
Time
Rmte
Cost
(Nmaberof
Insertion
(lin)
(seconds) (per 1000)3 ($I000)
colD/day)
Manual
I-I0
20
1.8
fi
Seli-Autolu~tie
I-I0
12.5
1.2
452
4320
Semi-Automatic
1-10
3.5
1.0
70
15400
15-4,5
1.5
.6
4851
36000
Automatic
24.0 Cost/ Board (elba) le.o
2700
Z
3 8.0
1000
10000
100000
Total Annual Board Volume
1 Total costs for one DIP, one ~xi&l ~ d one r a d i a l insertion machine
2 Includes a storage system for 700 components 3 Source: (RtmsullSr)
Figure 6 Component Control and Insertion Cost per Board ($)/bd) vs. TABVfor Various Methods of Component Control and Insertion and N = 10 Years
banned and manually inserts the odd-form components that use the kit-to-order form of component control. The fourth alternative also automatically inserts the standard components, but it semiautomatically (light-directed) inserts the odd-form components that are also Kanbanned. The four alternatives are compared for various board volumes (TABV), component values (CV), and equipment lifetimes (N). Some of the values used in the comparisons are shown in Tables 1-3 (the middle of each range is used where applicable) and the other values are DRT = 3600 seconds and I = 15%. For alternatives 3 and 4, NDCws = 300 for the automatically inserted standard components, and NDCws = 700 for the semiautomatically inserted nonstandard components. For alternatives 1 and 2, NPN = 100, and for alternatives 3 and 4 NPN--- 20 (here fewer components are manually inserted). Two values of CV are used in each case because DIPs are much more expensive than other components, and they are typically inserted automatically. The results are shown in Figures 6 and 7, where Figure 6 assumes N = 10 years and CV = $1.00 for the
32.0
24.0 Cost/ Board ($/bd)
8.0
NOC
NOC
(automatiC)
o
1
250
0
2
0
250
o
3
5O
0
20o
4
0
50
200
1 light
directed
100000
standard components, and CV = $.20 for the nonstandard components. Figure 6 shows that alternative 4 is the least costly method of assembly for TABV > 10,000 boards. Likewise, alternative 2 proves the least expensive method of assembly for 500 < TABV < 10,000 boards. Figure 7 shows that alternative 4 is the most economical method of assembly for TABV > 20,000, and alternative 2 is the least costly method of assembly for 1500 < TABV < 20,000 boards. This figure assumes N = 3 years and CV = $5.00 for the standard components and CV = $1.00 for the nonstandard components. The changes in CV had little effect, however, because alternative 3 (manual insertion of nonstandard components using kit-to-order) is still more expensive than alternative 4 for all board volumes shown in the figure.
NOC
(seml-auto)l
10000 Total Annusl Board Voluse
Figure 7
Table 3
(manual)
1000
Component Control and Insertion Cost per Board ($/bd) vs. TABVfor Various Methods of Component Control and Insertion and N = 3 Years
The Number of Components (NOC) Inserted for Each Method of Insertion in Each Alternative
Alternative
16.0
method
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Journal of ManuJacturing Systems Volume 8/No. 4
Although the full costing rate used for offshore assembly accounts for the overhead personnel in the offshore plant, it does not account for the additional overhead costs incurred in the U.S. operation due to manufacturing offshore. Some of these costs are attributed to carrying additional inventory in the total assembly system. Offshore assembly causes these inventory costs to increase because each plant in a JIT-PCB assembly system must store most of the PCBs and components that are assembled in the system (see Figure 1). These expenses include the cost of money and the additional personnel needed in the U.S. plant to handle and transact the inventory. It is assumed that these costs are "captured" in the inventory carrying rate. Other costs, such as communication, travel, and quality control--which increase in the U.S. operation due to manufacturing offshore-are not considered here due to lack of data. Therefore, this analysis underestimates the cost of offshore assembly. Five Different Systems. Five different manufacturing systems are compared. Four of these are shown in Figure 8, and all five are summarized in Table 4. In the first and second systems, the PCBs are completely assembled in a U.S. location. The first uses the same methods of component control and insertion as the second alternative described earlier--semiautomatic insertion (light-directed) using kit-to-order. The second system uses the same methods of component control and insertion as the fourth alternative named in the previous section-automatic insertion of standard components and semiautomatic (light-directed) insertion of the oddform components and all of the components; all of the components are Kanbanned between the supermarket and mini-markets. In both systems, components and unpopulated PCBs are stored in the supermarkets. Although some actual systems might also store populated PCBs in the product assembly line's mini-market, these instances are not considered here. This paper assumes that since the response time between the PCB and product assembly lines can be very smail (that is, one day), a specific PCB is assembled only when a product is ordered that uses the specific PCB. As a result, it is not necessary to store PCBs in the product assembly line's minimarket. In the third system, the U.S. location purchases the unpopulated PCBs, the PCBs are manually assembled (kit-to-order) and tested in an offshore
Economic Models The lower labor costs that exist in many underdeveloped countries have made "offshore assembly" an extremely attractive option. However, few companies have analyzed the effect of offshore assembly on manufacturing overhead costs, which--as pointed out earlier--have become much larger than direct labor costs. Additionally, offshore assembly increases manufacturing overhead costs in both U.S. and offshore locations. Much of the increased manufacturing overhead costs are related to the increased inventory that results from offshore assembly (refer to the first paragraph in this paper for actual percentages), since parts and assemblies must now be stored in a greater number of supermarkets, mini-markets and work centers. 6 Further, offshore assembly also increases noninventory associated manufacturing overhead costs such as travel, communication, plant and equipment (duplication of equipment), maintenance (duplication of equipment and less access to equipment suppliers), management (duplication of personnel), and quality control (more incoming inspection and increased time for quality feedback). Offshore plants also typically have higher start-up costs, and they take longer to reach accepted quality levels than do U.S. plants. 7 Offshore and U.S. assemblies are compared here both by using the "full costing rate" for offshore assembly (DLoyy),and the "marginal costing rate" for U.S. assembly (DL, s) and by developing and applying models of board and component inventory carrying cost, test labor cost, and shipping cost. The full costing rate includes the direct labor rate and all of the overhead expenses in the offshore plant. This overhead primarily represents personnel who are not needed if the additional assembly is performed in the U.S., since these personnel duplicate those in the U.S. operation. The marginal costing rate only includes the additional costs that would be incurred if the assembly is performed in the U.S. plant. This includes direct labor, benefits, lost time, inspection and hand tools used in manual assembly. Westinghouse factories have found that the other overhead costs do not typically decrease when assembly has been moved offshore. Therefore, these overhead costs are not expected to increase if the assembly operations are moved back to the U.S. plant and the "full costing rate" is not used for assembly in the U.S. plants.
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Journal of Manufacturing Systems Volume 8/No. 4
F i r s t and second systems
I
Third system
i
Jq
Suppl lore
U.S, Location
d
Un,o,u. d PCB Storage
-
,roduct
Assembly
/
Asmembly
-i Cu.,o.r
i
A
[
U.S. Location
q
Suppl lerm
Unpopulsted
]Storage of-
PCB Storage
Itemted PCBs
1
1~
Product
Customer
Assembly
t Offshore Locab|on
Unpopulited --
PCB Storage
I1_ ~ PCB I Assembly l
U.$. Location Fourth mnd fifth systems
[
I
Suppl lets
--~PCB Assembly
IStorag. 0¢Itembed PCBx
I~Product I Allembly
Customer
t Offshore Location UnpopulstedPCB Storage
I- ~
PCB Assembly
Figure 8 A D i a g r a m o f F i v e P C B A s s e m b l y Systems
Table 4 A Summary of the Five Systems
STstem 1 2 S 4~i
Standard Coiponents MO_~I CCM Location Semi-Auto. ICf0 U.S. Auto. Kanban U.S. Manual k'ro Offshore Auto. l~nban U.S.
mini-market in the U.S. plant. In the fourth system, the PCBs are assembled both in the U.S. and abroad. The U.S. location purchases the unpopulated PCBs and automatically inserts the standard components using Kanban. The odd-form components are manually inserted using kit-to-store, and the boards are tested--both in the same offshore location. Therefore, components and unpopulated PCBs are stored in the U.S. plant supermarket, components and populated PCBs are stored in the offshore location supermarket, and assembled and tested PCBs are stored at the product assembly line mini-market in the U.S. In the fifth system, the PCBs are assembled in both an American plant and two offshore locations (the second offshore location is not shown in Figure 8). This manufacturing system is the same as the
Odd-Form Components MO_.II CCll Location Seai-Auto KTO Semi-Auto Kanban Manual KTO Manual KTO
U.S. U.S. Offshore O~fshore
HOI: method of insertionj CCii: component control method, KTO: kit to order
plant, and the PCBs are assembled into the final product in a U.S. location. Therefore, components and unpopulated PCBs are stored in both the U.S. and offshore location supermarkets and assembled and tested PCBs are stored at the product assembly line
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Journal of Manufiwturing Systems Volume 8/No. 4
fourth one, except that the populated PCBs are tested at a second offshore location before the PCBs are assembled into the final product. Therefore, populated PCBs must also be stored at the second offshore location in addition to the three other board storage locations described for the fourth system. Cost Models. The five systems just described are compared using Eq. (1), where CCC, CILC and ECPB are developed in the previous sections. The component inventory costs in the U.S. supermarket-part of the component control costs (CCC)--are not considered since each system has the same cost. Systems that use offshore assembly, however, require that components be stored in an offshore supermarket, so these systems are considered using Eq.
weight, CPP is the shipping cost per pound, and NOT is the number of trips. Cost Comparison B e t w e e n Systems. The five systems are compared for various values of average component cost (CV), offshore costing rate (DL) and the inventory carrying rate (ICR). The offshore costing rates can range between $5/hr. and $15/hr. depending on the country's wages, the number of overhead personnel in the factory, and the capability of and turnover in the factory's workforce. The inventory carrying rate can range between 15% and 25% depending on the amount of inventory that is damaged or becomes obsolete each year, the "complexity" of the production system, and the amount of automation in the production system. Component costs can range between $.01 and $150 although DIPs (one category of standard components) are more expensive (typically between $.20 and $1.00) than other components (usually between $.01 and $.50). Two values of CV are used--one for automatically inserted components and one for nonstandard components--since these components are added to the boards at different times in the offshore assembly systems. Since DIPs are typically inserted automatically, the high value of CV represents those components which are automatically inserted and the low value of CV represents the other components. As for the other variables, the same values are used in these comparisons that are defined in previous sections (Tables I, 2, and 3). The life of the equipment is assumed to be three years and an interest rate of 15% is used. The distribution of annual board volumes for individual boards is shown in Table 5. These volumes are for actual boards assembled in a particular factory. The test time is assumed to be 20 minutes, the average board weight is assumed to be 1.4 pounds (actual weight of a multilayer board containing 250 components), and the initial board cost (typical multilayer board) is assumed to be $75. Since the previous section showed that semiautomatic and manual insertion are the lower cost methods for TABV <20,000, and automatic insertion is the lowest cost method for TABV >20,000, systems 1 and 3 are compared for TABV = 10,000 and systems 2, 4, and 5 are compared for TABV = 50,000. Response time and shipping cost between locations depend on the offshore assembly location. Since Caribbean countries are popular with many U.S. electronics companies, typical values are taken for ship-
(5). BICC, or board inventory carrying costs per
board, can be estimated using the same equations developed earlier for component inventory costs. The board inventory carrying costs are summed over each board and each location as shown in Eq. (21): BICC = ZEBVot*ICR*NOBLot*BLS/ABV o (21)
where: BVot is the value or cost of board b at storage location 1, NOBLbt is the number of lots stored for board b in storage location 1, and BLS is the typical lot size. The board value increases as components are added and the board is tested, as shown in Eq. (22): B V n = BC o + CC*NOC + RLC b + CLC o + CILCo + TLC o
(22)
where: BC is the initial board cost, CV*NOC is the raw material component cost and RLC, CLC, CILC and TLC are the retrieval, counting, insertion and test labor costs respectively for board b. As shown in Eq. (23), NOBL o depends on the response time (RSTt) to location I in terms of days, the board's annual volume (ABVo), and the board lot size. Since the raw-board inventory carrying costs in the U.S. location are the same for each system, they are not considered in the analysis: NOBL b = RSTi*ABVb/(BLS*250)
(23)
TLC, or test labor costs, and shipping costs SC, are represented by Eqs. (24) and (25), respectively: TLC = T I * D L
(24)
SC = W*CPP*NOT
(25)
where: Tit is the test time per board, B W is the board
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Journal of Manufacturing ,~vstems Volume 8/No. 4
Figures 9, 10, and 11 show total assembly costs (TAC) for systems 1-5 as a function of direct labor-
Table 5 The Annual Board V o l u m e s for E a c h Board Group Used to Compare the Five Systems Board St~le
Board Croup
l
1 2 1 2 3 1 2
B C
D
1
2 3 4 5
6 E
F
1
Board
Board
Stile
Croup
1132 102 57 47 693 618 18 1096
C
1 2 3 4 5 6 1
494 568 372 10 54 149
I
2
351
1
492 1227 317 9 47
2 3 4 5
H
J
AB__VV 1259 68 17 26 4 4 lgl
2 1 2 i
4114 200
2
1995
1899 16
3
357
4
2165 380 91 3
5 1 2 3
K
L
rate, component value, and inventory carrying rate using a 2-level, 3-factor experiment. The trials with a lower offshore labor rate are shown on the left side of each cube, and the trials with a larger offshore labor rate are shown on the right sides of the cubes. Similarly, low and high inventory carrying rates are shown on the fronts and backs of the cubes respectively, and low and high component values are shown on the bottoms and tops.
564 859
1 2
4OO
1. 0
ping between the eastern United States and the Caribbean. The response time between locations is assumed to be 10 days, and the shipping cost per pound is assumed to be $1.50. Asian and South American countries have longer response times and higher shipping costs. An example calculation for specific values of CV, ICK DLoff and TABV is shown in Table 6. As expected, the board and component inventory and shipping costs are higher for the offshore assembly systems (3-5) than for those in the United States. The labor costs for each are similar in this example, however, because DLo// = $15 (includes all overhead costs), DL,~ = $20 (includes only some overhead costs), and the U.S. systems are assumed to have a more automated method of component insertion than those offshore.
Component I Value($)I
.25
i
Inventory
Carrying Rate
.01
.025 5
15
Direct Laborof f ($)
Figure 9 Assembly Costs per Board ($) for System 1 (Top Value in E a c h Box) a n d 3 (Bottom Value in E a c h Box) and a Total Annual Board Volume of 10,000
l.Op
Table 6 Example Calculation of Assembly System Costs Per B o a r d 2
Component "I
Value($)~ S]fste.
TABV (bds/yr)
CICC ~1)
LC ~
ECPB (I)
BICC _~
SC ~.~
TAC ($)
1 2 3 4 5
10,000 50,000 I0,000 50,000 50,000
0.00 0.20 2.80 0.40 0.40
28.90 14.90 30.80 14.40 14.40
4.80 4.60 .20 4.30 4.30
0.00 0.00 5.00 7.70 11.70
0.00 0.00 4.20 4.20 6.30
33.50 19.70 43.00 31.00 37.10
1: LC = CILC + RLC + CLC +
.25ventory
.025 54
Direct Laborof f
t~16
($)
Figure I0 Assembly Costs per Board ($) for System 2 (Top Value in E a c h Box) a n d 4 (Bottom Value in E a c h Box) and a Total Annual Board Volume of 50,000
TIC
2:CV=$1.O0 (standard components) and 1.20 (non-standard components, ICR=25~ and DLoff= $15.oo/hour (includes overhead COSTS)
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~l
nent insertion and both U.S. and offshore assembly systems. Using typical values from a particular factory, it is determined that the "Kanban" method is the lowest cost method of component control except for a combination of high average component cost (>$.50), a large number of components stored at each workstation (>700), and a low number of different part numbers per board (<50). Under these circumstances, the kit-to-order method is the least expensive method of component control. The paper also concludes that a combination of automatic insertion of standard components and semiautomatic insertion of nonstandard components that are "Kanbanned" proves a lower cost method of component control and insertion than does more manual alternatives for volumes greater than 20,000 boards per year. These results are combined with board inventory carrying cost, test labor cost, and shipping cost models to compare five U.S. and offshore assembly systems in both high volume (50,000 boards/year) and low volume (10,000 boards/year) situations. Due to its higher shipping and inventory costs, offshore assembly is found to be more expensive than U.S. assembly in a number of situations. For a low volume system, U.S. assembly is the lower cost operation when the offshore "costing rate" (includes overhead costs) is greater than about $12/hour. For a high volume system, U.S. assembly is less costly when the offshore "costing rate" is greater than about $7/hour. Since typical offshore costing rates vary between $5/hour and $15/hour, depending on the country and other factors, offshore assembly can be more expensive than U.S. assembly in some cases. Although this analysis is done for PCB assembly, the models and concepts are applicable to any assembly system. The relative values of labor and inventory carrying costs and thus U.S. vs. offshore assembly costs will differ due to different assembly processes and material costs. For example, since wire assembly typically has a lower ratio of material-tolabor costs--and thus inventory-to-labor costs--than PCB assembly, offshore wire assembly is more economical than offshore PCB assembly. Mechanical assembly can have a lower or higher ratio of material-to-labor cost, depending on whether the parts require complex (e.g., casting and forging) or simple (such as screws and nuts) fabrication operations•
m
YalueC°mP°nent(8)
~v 119.41
iz0.4
Figure II Assembly Costs per Board ($) for System 2 (Top Value in Each Box) and 5 (Bottom Value in Each Box) and a Total Annual Board Volume of 50,000
In Figure 9 system 1 is the top value, and system 3 is the bottom value. As shown, system 1 (U.S. assembly) is a lower cost method of assembly than system 3 (offshore assembly) for DL = $15.00/hour. The reverse is true for DL = $5.00/hour0 The crossover points for the direct labor rate are DL = $13.23 for CV = $. 1 (standard components) and $.025 (nonstandard components) and ICR = 15% and DL = $9.95 for CV = $1.0 and $.20 and ICR = 25%. Figures 10 and 11 show total assembly cost for systems 2 (top values in each box), 4 (bottom values in each box of Figure 10), and 5 (top values in each box of Figure 11) as a function of the same variables as indicated in Figure 9. System 2 (U.S. assembly) is always a lower cost assembly system than system 5 (two offshore assembly locations) for the values shown in Figure 11. System 2 is also a lower cost method of assembly than system 4 (one offshore location), except when DL = $5.00/hour and CV = $.10 and $.025. The crossover points for the direct labor rate are DL = $6.51 for CV = $.10 and $.025 and ICR = .25 and DL = $8.11 for CV = $,10 and $.025 and ICR = 15%.
Concluding Remarks This paper develops and uses economic models of labor and inventory carrying costs to compare various methods of component control and compo-
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Journal oi"Manufacturing Systems Volume 8/No. 4
CLS== = [(RTs= *NOC*DL* TABVmm)/ (NDCmm.CV.ICR) ].5
Appendix Optimal Component Lot Size The optimal component lot size balances the retrieval labor cost and the component inventory carrying cost. Two cases are considered: 1) When DCV*RST/CLS <1, NOCL = 1, since a minimum of one lot must be carried in inventory; 2) When DCV*RST/CLS > 1, component lot size has little effect on component inventory costs 6 so the largest possible lot size that satisfies this condition (that is, NOCL = 1) is the optimal lot size--since this will minimize retrieval labor costs. Therefore, the optimal lot size for deliveries between a supermarket and a minimarket (CLSm.) using the kit-to-store method can be represented by Eq. (26), by setting Eq. (8) equal to the first half of Eq. (7) when NOCL = 1. The optimal lot size for deliveries between a supermarket and a workstation (CLSws) can be represented by Eq. (27), by setting Eq. (12) equal to Eq. (13). The optimal lot size for deliveries from a mini-market to a kit CLSk,) can be represented by Eq. (28), by setting Eq. (10) equal to the second half of Eq. (7).
CLSws = [(RT~m*NOC*DL*TABVwJ NDCw~*CV*ICR) ].s
(26) (27)
CLSki t = [(RTmm*NOC*DL*TABVmm / NPN*NDB*CV*ICR)] "s (28)
References 1. J. Miller, T. Vollmann."The Hidden Factory",Harvard Business Review,November-December,1985. 2. G. Boothroyd."Economicsof AssemblySystems",Journalof ManufacturingSystems, Vol.l/No.l, 1982,pp. 111-127. 3. M. Carter,P. Carter."TheCost of InsertingOdd-FormComponents -Manual vs. Robotic Placement",Connection Technology, September 1987, p. 19. 4. R. Gustavson. "Choosing ManufacturingSystemsBased on Unit Cost", 13thlSIR/Robots 7 Conference,April 1983. 5. R. Schonberger."WorldClass Manufacturing",New York."The Free Press, 1986. 6. J. Funk."A Comparisonof InventoryCost ReductionStrategiesin a JIT ManufacturingSystem", InternationalJournal of Production Research, Vol.27/No. 7, 1989,pp. 1065-1080. 7. H. Shaiken."HighTechGoesThirdWorld",TechnologyReview,January 1988. 8. G.A. Russell, G. Boothroyd,P. Dewhurst."Printed Circuit Board Designfor Assembly,Report#5, Departmentof Industrialand ManufacturingEngineering,Universityof RhodeIsland,Kingston,RhodeIsland.
Author Biography Jeffrey L. Funk is a Senior Engineer at the Westinghouse Science and Technology Center in Pittsburgh, Pennsylvania. He earned his BS degree in Physics from California Polytechnic State University, and both his MS degree in Mechanical Engineering/Engineering and Public Policy, and his PhD degree in Engineering and Public Policy from Carnegie-Mellon University. His research interests are in the economics and management of manufacturing systems, design for manufacturing, and computer integrated manufacturing. Dr. Funk is currently working on the implementation of automated semiconductor processes as a Westinghouse-Mitsubishi Exchange Engineer in Fukuoka, Japan.
287
needed to repair the problem (for example, replacing a defective or incorrectly inserted component). Inventory related costs can be divided into four categories: the personnel needed to handle (for example, indirect labor and stock room, shipping, and receiving personnel) and transact (for example, production, planning and control, inventory control, and accounting) inventory; the space to store inventory; the cost of money; and the financial losses from inventory that becomes obsolete each year due to changes in market demand or in engineering strategy. This paper describes economic models that address the concerns of manufacturing overhead costs and that can be used to compare both diverse methods of component control/component insertion and various U.S./offshore assembly systems for PCBs. These models represent nonequipment overhead costs for retrieval and kitting labor costs of individual components; inventory costs of boards and components; rework costs for various methods of component control/component insertion; and for the number of plants in the assembly system. The methods of component control include "kit-to-order," "kit-tostore," and "total Kanban". In addition to having different retrieval and kitting labor costs as well as different inventory costs, each method can affect component insertion labor costs: The inventory related expenses are included in the inventory carrying rate that seems to range between 12% and 25%, depending on both the overhead costs included in the rate and the efficiency of the manufacturing system. The lower bound includes
Abstract Although nonequipment overhead costs typically represent greater than 80% of manufacturing costs, few models of these costs have been developed and therefore, such expenditures are usually not explicitly considered when choosing a manufacturing system. This paper develops and uses models of retrieval and kitting labor costs along with component and board inventory costs--which together represent a large percentage of manufacturing overhead expenses--to compare U.S. and offshore assembly systems. Due to its higher inventory, other overhead, and shipping costs, offshore assembly is found to be less economically advantageous than previously believed.
Keywords: Assembly, Economics, Offshore, Kitting, Inventory, PCBs.
Introduction Manufacturing overhead costs have steadily risen in electronic industries and now exceed 80% of the value-added in most of these businesses. ~Further, although most economic models of electronic and mechanical assembly systems emphasize direct labor and equipment costs,2-a more than 80% of manufacturing overhead costs are for nonequipment costs. ~A large percentage of these costs in printed circuit board (PCB) assembly can be attributed to retrieval and kitting of electronic components, rework-related costs, and the storage of components and boards (that is, inventory). Rework costs include the time 274
Journal of Manufacturing Systems
Volume 8/No. 4
only the cost of money, while the upper bound includes all of the inventory related costs mentioned for an "inefficient" manufacturing system*. Because a just-in-time (JIT) "pull" system is becoming the standard production system within the commercial part of many manufacturing companies, the inventory models are developed for this type of production system. The pull system, originally developed in Japan, has become popular with a number of U.S. firms due to its low operating cost (for example, it requires fewer production, planning, and control personnel) and its positive effect on delivery times and inventory costs/ The diverse methods of component control/ insertion and of various U.S./offshore assembly systems are compared using Eq. (1):
Economic Models A generic PCB assembly system that uses a "pull" system for material control is outlined in Figure 1. The assembly system can have multiple plants (typically 1-3) with each plant having one "supermarket" and multiple "mini-markets." The supermarkets are used to store PCBs and components, while the mini-markets are used to store kits and components. Suppliers deliver unpopulated PCBs and electronic components to the first plant where they are stored in the plant's "supermarket." When a populated board is requested by a product assembly line or a partially populated board is requested by a second plant in the PCB assembly system, the supermarket releases the unpopulated PCBs and/or kits to a station in the assembly system. The supermarket also delivers electronic components to each minimarket when it requests them. A Kanban card or signal (electronic) is generally used to request either a particular PCB or electronic component from a supermarket. The components can be delivered from a supermarket to workstations in three ways and typically multiple methods are used in one factory as shown in Figure 2. Kit-to-Order. With the first method, "kits" can be made that contain the exact number of components needed to assemble one lot of a particular board type. This method is called "kit-to-order." When the product assembly line or a second plant in the PCB assembly system requests a specific board type, the components are retrieved from the supermarket, then counted into a kit, and the board is assembled. This method of component control is commonly used for very low-volume factories that use expensive and/or nonstandard components because it does not require components or kits to be stored at a mini-market. The component control cost per board (CCCkt o) for the kit-to-order method is represented by Eq. (2):
TA C = CCC + CILC + ECPB + TLC + BICC + SC (1)
where: TAC is the total assembly cost per board, CCC is the component control cost per board, CILC is the component insertion labor cost per board, ECPB is the equipment cost per board, TLC is the test labor cost per board, BICC is the board inventory carrying cost per board, and SC is the shipping cost. Component control costs are develo/ged in the section on economic models of component control, and they are represented by Eqs. (2), (7), and (12). Models of component insertion labor cost and equipment cost per board are developed in a later section, these are represented by Eqs. (18) and (19) respectively. Board inventory carrying, test labor, and shipping cost models are likewise developed in the subsequent section and are represented by Eqs. (21) through (25) respectively. In the first section of this paper, component control cost models are developed to compare three methods of component control. These include retrieval and kitting labor and component inventory carrying cost models. The next section combines these with component insertion labor and equipment cost per board models in order to compare four component control and insertion alternatives. The third section develops board inventory carrying, test labor, and shipping cost models and combines these with the other models to compare two U.S. and three offshore assembly systems.
C C C k t o = e z c k , o + C t C + ClCCsra
(2)
where: retrieval (RLCkt o) and counting labor costs (CLC) and component inventory carrying cost per board in the supermarket (CICCsm) are repres-
* The author is presentlydevelopingmodelsthat explicitlyrepresentthe inventoryrelated overheadcosts as a functionof parameters such as the type of production system (that is, push vs. pull), the amount of continous-flowmanufacturing,and the amount of standardization in the product. These modelswouldprovide a more accurate representationof the discussedissues.
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PCB and ComponentSuppliers [
Superaarket
I I
Plant ~I
#1
Boards ] Components
[ Comp. Insertion [
Kittlag
I
[ICo-ponentl
i,, 0o-oo, 1,,_
]
"Kit
to Order"
'Kit
to
Store'
I
IMini-aarket #I.I [
Minl-m~rket #1.M[ Coap. Insertlon[ "'" [ Comp. Insertion I Insertion Board Test
Components
]
WComplete Kanban'
Figure 2
An Outline of Three Component DeliveryMethods (TABVsI) that uses the supermarket. With respect to retrieval and counting labor costs, RTsI is the time for one retrieval from a supermarket, NPN is the number of part numbers that must be retrieved for a typical board, DL is the direct labor rate - including benefits, BLS is the board lot size, ABV is the annual board volume for a typical board, CT is the time to count one component, and NOC is the number of components that must be counted for a typical board. The component inventory carrying costs are represented by Eqs. (5) and (6), where the inventory costs are summed over each type of component stored in the supermarket. In Eq. (5), NDCsm is the number of different components stored in the supermarket, CV i is the component value or cost for component i, ICR is the inventory carrying rate, LSM i is the number of lots stored in the supermarket for component type i and CLS,p is the component lot size delivered by the supplier.
Plant ~N
Supermarket #N Boards [ Components
[ Comp. Insertion [
Kitting
I
Iilini-aarket #N. 11 [Minl-market #N.i/ Comp. Insertion[ "'" [ Comp. Insertion I
Storage
]
Assembly
Figure 1
Outline of a Generic PCB AssemblySystem ented by Eqs. (3), (4), and (5) respectively.
LSM i =
CICCsm
=
RLCkt o = RT, m*NPN*DL/BLS
(3)
CLC = CT*NOC*DL
(4)
DCV i CRSTst, / CLSsp
(6)
Equation 6, which estimates LSM i, is based on the number of Kanban cards/containers needed to transport component type i between each supplier and the plant, where the safety factor is assumed to be zero for simplicity. DCV i is the daily component volume for component type i, and CRST~p is the response time between the supplier and the supermarket.** The effect of each of these variables on carrying cost per part can be found in Funk ' 8 9 . 6
~ c'n CVi*ICR*LSMi*CLSstj/TABVsm (5)
i=1
The retrieval and counting labor costs are estimated for a "typical" board, while the component inventory costs are estimated for the plant and then amortized over the total annual board volume
** Although the component lot sizes and response times for deliveries between suppliers, supermarkets, and mini-markets vary among components, these equations assume that they are the same for simplicity's sake.
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Journal of ManuJacturingSystems Volume 8/No. 4
NDCmm (number of different components in the minimarket), CLS~p with CLSmm, RSTsp with RSTs, (response time between the supermarket and a minimarket), TABVsm with TABVmm (total annual board volume handled by the mini-market), and LSM with LMM (number of lots stored in the mini-market for component type z). The kit inventory carrying cost (KICCmm) can be developed from Eq. (9) by summing the inventory costs over each type of component in a kit (NPN), as opposed to each component in the mini-market, (NDCmm) and by multiplying Eq. (9) by the number of different kits/boards (NDB) that are assembled using the kit-to-store method, as shown in Eq. (11). Further, the product of LMMi and CLSm,. is replaced by CLSkit,which is the number of components stored in each component bin of the kit.
Kit-to-Store. Kits produced by the second method can be stored in a mini-market in which each kit contains a large, nonfixed number of components for each type of component in a particular board type. This approach is called "kit-to-store." When the product assembly line or a second plant requests a specific board type, a kit is sent from the minimarket to a workstation served by that mini-market, and then the board is assembled. Before the kit is sent to the workstation, a "handful" of components are added to each component bin that is nearly empty in the kit. Components are delivered between the supermarket and mini-markets as they are requested by the mini-market via Kanban, as shown in Figure 2. Kit-to-store is typically used for inexpensive and nonstandard components. Although it requires the storage of kits and components at each minimarket, components do not have to be counted into a kit for each lot, and this method only requires component retrieval operations when components are needed either by a mini-market or to fill one component bin in a kit. The component control costs per board (CCCkt~) for the kit-to-store method are represented by Eq. (7):
NPN K1CCmm =
The retrieval labor costs per board (RLCkt~) from the supermarket and the mini-market can be represented by Eq. (8): RLCki t = RTsm * NOC* DL/ CLSIm + (8)
CLSm,. is the component lot size used in delivering components from the supermarket to a minimarket via Kanban. RTm,. is the time for one retrieval from a mini-market, and CLSki t is the component lot size used for filling a component bin in a kit from a mini-market. The component inventory carrying cost per board in the supermarket (CICC,,,) and mini-market (CICCmm)are represented by Eqs. (5), (9), and (10): ClCCmm = N~Cmra CV i*ICR~LMMiCLSmra/TABVmI (9) i=1
L M M i = D C V i * RSTsm / CLSmm
i=1
CVi*ICR*CLSkit/TABVmm (1 1)
Complete Kanban. Using a third method called complete Kanban, each workstation can be made a mini-market in which it stores each component used by that workstation. The components are delivered from the supermarket to a mini-market as requested by that mini-market via Kanban. This method is typically used in medium- to high-volume operations because although it requires very few retrievals and no counting of components into kits, it requires components to be stored at each workstation. The component control costs for this method (CCCka.) can be represented by Eq. (12). The retrieval labor costs (RLCka.) can be developed from Eq. (8) by replacing CLS,, m with CLSws(lot size for delivering components from the supermarket to a workstation), as shown in Eq. (13). The component inventory cost in the supermarket is represented by Eq. (5), and the component inventory cost at the workstation (CICCws) can be represented by Eqs. (14) and (15). Equations (14) and (15) are developed from Eqs. (9) and (10) by replacing TABVmm with TABVws (total annual board volume at the workstation), NDCmra by NDCw~(number of different components stored at the workstation), LMM with LWS (number of lots stored at a workstation for component type t), and CLS,, m with CLSw~.
CCCkts = RLCkit 4- CICCsm + CICCm m + KJCCmm (7)
RTmm*NOC*DL/CLSki t
NDB* ~
( 1O)
where: the inventory costs are summed over each type of component stored in the supermarket and mini-markets. Equations (9) and (10) are developed from Eqs. (5) and (6) by replacing NDC~,n with
277
CCCka~ = RLC~,, + CICC~,. + CICCw~
(12)
RLCka. = RTka,*NOC*DL/CLSw~
(13)
Journal of ManuJacturing Systems Volume 8/No. 4
CICCws =
~
Lws
i=1
Table I List of Component Control Cost Variables and theirDefault Values
CVi*ICR*LWSi* CLSws/ TABVws (14)
LWS i =
DCV~*RSTsm/CLSws
(15)
CateKor ~
Although most of the variables used in Eqs. (2) through (15) are independent, some of them are not. The component volumes (DCVi) used to estimate component inventory costs in a supermarket, minimarket, or workstation should match the product of the average number of components in each board (NOC) and the board volumes handled by the supermarket, mini-market, and workstation (TABV). Therefore, daily component volume (DCVi), the number of components/board (NOC), total annual board volume (TABV), and the number of different components (NDC) are related by Eq. (15), where (TABV) and (NDC) are for a supermarket, mini-market, or workstation. Each side of Eq. (15), which assumes that there are 240 working days in a year, represents the total number of components that are used by a supermarket, mini-market, or workstation.
Time
E i=1
DCVi
Definition
Board and
Value
CT
Time to count one component
RSTsm
Response time between the supermarket
1.2 see. .5 days
mad mini-market
RTsm NDCmm
R e t r i e v a l time from the supermarket Average number of d i f f e r e n t
NPN
Number of different part
Component
30 see. 1000
components per mini-mLrket
Diversity
I00
numbers per board
Volume
NCC
Number of components per board
250
TABYmm T o t a l ~nnuml board volume s e r v e d by a mini-market
13,500
TABVws Total annuml board volume of a
4,320
workstation Cost
DL
Direct Labor rate
ICR
Inventory carrying rate
$20/hr 25~
semiautomatic workstation, and the value for TABVmm assumes ten manual workstations working at full capacity for one shift. The results are shown in Figures 3-5 using a 2-level, 3-factor experiment. Each figure shows the effect of three variables on one method of component control. For example, the trials with a lower board lot size are shown on the left side of the cube in Figure 3, and the trials with a larger board lot size are shown on the right side of the cube. Similarly, low- and high-retrieval times are shown on the front and back of the cube respectively, while low and high values for NPN are shown on the bottom and top of the cube.
NDL
TABV*NOC/240=
¥ariable
(16)
Equations (5), (9), (11), (14), and (16) can be simplified using average component values in place of summing over the values for each component type. For example, the summation in Eq. (5) can be eliminated by multiplying the equation by the number of different components (NDCsI) and replacing CVi and NOCi with CV and NOC. Similarly, the summations in Eqs. (9), (11), (14), and (16) can be eliminated by multiplying Eq. (9) by NDCmm, Eq. (1 1) by NDCmm, Eq. (14) by NDCws, and the righthand side of Eq. (16) by NDC. Cost Comparison Between Methods. The three methods of component control are compared using Eqs. (2) through (16) for various values of BLS, NPN, RTsm , NDB, CV, RTmm and NDCw,. Since the component inventory carrying costs in the supermarket (CCC,m) are the same for each method of component control, Eqs. (5) and (6) are not considered in this section. The optimal lot sizes (CLSsm, CLSmm , and CLSws) are calculated in the Appendix by minimizing the sum of inventory carrying and retrieval labor costs. DCV is calculated for the mini-markets and workstations using Eq. (15). The values for the other variables are shown in Table 1 and are for a typical high-volume, high-mix factory. For example, the value for TABVw~assumes a two-shift, full capacity,
NP
35
Ts= (sec) 50
lO ~
D 2o BLS
Figure 3 Component Control Cost per Board ($) vs. BLS, RTsrn and NPN for the Kit-to-Order Method
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Journal of Manufacturing Systems Volume 8/No. 4
Figures 3-5 show that the Kanban procedure is
lo I .o5 I .1<1 cv
(s)
Figure 4 Component Control Cost per Board ($) vs. CV, RT=_ and NDB for the Kit-to-Store Method where ~PN = 100 and RTsm = 30 see.
NDCws
3~S mCsee)
I00
831 25 cv
(s)
D.5
the least costly method of component control, except for a combination of high values of CV (>$.50) and NDCws(>700) and low values of NPN (<50). In this case, kit-to-order is the lowest cost method of component control. The kit-to-store method is never the least costly method of component control. It is always the most expensive means, except when a low diversity of boards (NDB) is assembled and/or there are low component values (CV). In this case, the kitto-order method proves the most expensive. The method of component control used can also affect component insertion labor cost, however, "kit-to-order" and "kit-to-store" can increase the setup time for nonmanual insertion, while "complete Kanban", can increase manual insertion time. Setup time is increased when using kit-to-store or kit-toorder, because each component tube or reel must be loaded onto the automatic insertion equipment or each component bin must be filled with components for each individual lot. Manual insertion time is increased when using the complete Kanban method of component control because it may take longer to locate the correct component in the mini-market than in the kit. Therefore, kit-to-order and kit-tostore are typically used only with manual and one method of semiautomatic insertion because kitting only has a small effect on setup time. Likewise, complete Kanban is used only with semiautomatic, automatic, or robotic insertion because the equipment automatically delivers the components to either the insertion head or operator with these insertion methods. Described in the next section are some economic models and results for typical combinations of methods of component control and component insertion.
Economic
Figure 5 Component Control Cost per Board ($) vs. CV, RTsm and NDC for the Kanban Method
Models
Components can be manually, semiautomatically, automatically, or robotically inserted. Manual insertion requires an operator to read the process instructions and typically the operator verifies that all of the parts are in the kit or in the mini-market before insertion begins. The operator then acquires each component from the kit or mini-market, forms it if necessary (axial components), inserts it and cuts and clinches the leads. Semiautomatic equipment can be "light-directed" or "auto-place". The light-directed type of
Different variables are shown in each figure because most of the variables only have an effect on one method of component control. For example, NDB and RTmmonly affect the kit-to-store method. Similarly, NDCwsonly affects the Kanban method, and BLS only affects the kit-to-order method. The default values of these variables when they are not shown in Figures 3-5, are also shown in Table 1.
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semiautomatic insertion equipment uses a program to step the operator through a specific board. The operator loads a program, and the equipment presents or lights up the correct component bin or tube. The equipment also lights up the correct component insertion location for the operator who acquires the component and then inserts it. The auto-place type of semiautomatic insertion equipment requires the operator to move the board underneath the insertion head and the equipment automatically inserts the component. The component bins or tubes that apply to a particular board type may have to be loaded onto both types of semiautomatic equipment before insertion can begin. This is required when the components are "kitted", or when a component is inserted that does not have a dedicated location on the equipment when the components are "Kanbanned." Automatic insertion equipment independently performs all of the necessary operations. However, it still requires an operator to load and unload boards and to fix jams. The component tubes or reels may also have to be changed before insertion can begin. Even without these changes, the setup time is often long because the PCB must be adjusted within the board fixture before insertion can be performed correctly. Robotic insertion is slower than automatic insertion equipment, but its setup times are typically shorter and it can be used to insert nonstandard components. However, because special grippers and part feeders are needed for these nonstandard components, robotic insertion is applicable only for highvolume nonstandard components 3 For this reason, it is not considered further in this paper. Cost Models. Component insertion costs (CIC) per board can be represented by Eq. (17) where component insertion labor costs per board (CILC) and equipment costs per board (ECPB) can be represented by Eqs. (18) and (19) respectively. Component insertion costs are summed over each method of insertion (4 methods) since multiple methods are typically used to assemble a board. Equipment costs are annualized and then amortized over the annual board volume. CIC = CILC + ECPB
is the interest rate and N is the life of the equipment. 4
CILC = ~, (SUT)moi/BLS + ITmoi*NOCraoi + moi=l NOCmo i *oRmo i* DRT)* DL
ECPB =
TEC*I*(I+ 1)N TBV*[(I+ I )N-1]
(18) (19)
Total equipment costs can be represented by summing over each type of insertion equipment used in the system as shown in Eq. (20), where IEC is the individual equipment cost, ECP is the equipment's capacity in components per day, and TABV is total annual board volume. The value of TBV*NOC/ECP in Eq. (20) must be an integer because it represents the number of each type of equipment needed to handle the board volume. 4
TEC = raoiffil ~ IECmoi*TABV*NOC,~oi/ (ECPmoi*250X20)
Typical values of setup time, insertion time, defect rate, equipment cost and equipment capacity are shown for each method of insertion in Table 2. These values, particularly the defect rate, depend on the factory in question. The defect rates shown in Table 2 represent an average of a few manufacturing facilities. Since the typical defect repair time (to identify, remove, and replace the component) in one factory is 3600 seconds, the defect repair time per component can sometimes be greater than the insertion time per component. For example, the average defect time per component is 3.65 seconds for semiautomatic insertion (3600 seconds per component × 1 defect per 1000 components), and the average semiautomatic insertion time is 3.5 seconds. This simple numerical calculation supports the recent realization that quality should receive greater emphasis in American manufacturing. Cost Comparison Between Alternatives. Since standard components are typically inserted using more automated methods than nonstandard components, this section compares alternatives that contain multiple methods of insertion. The first alternative uses manual insertion and the kit-to-order method of component control. The second alternative also uses kit-to-order, but the components are semiautomatically (light-directed method) inserted. The third alternative automatically inserts standard DIPs (dualin line packages), axials and radials that are Kan-
(17)
In Eqs. (18) and (19), SUT is the setup time, IT is the insertion time, DR is the defect rate, DRT is the defect repair time, TEC is the total equipment cost, I
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Journal of Manufacturing Systems Volume 8/No. 4
Table2 ]3jpiealValuesfor each Method of Insertions ..... j.
32.0 Individual
Equipment
Setup
Insertion
Defect
Equipment
Cap~clty
Method of
Time
Time
Rmte
Cost
(Nmaberof
Insertion
(lin)
(seconds) (per 1000)3 ($I000)
colD/day)
Manual
I-I0
20
1.8
fi
Seli-Autolu~tie
I-I0
12.5
1.2
452
4320
Semi-Automatic
1-10
3.5
1.0
70
15400
15-4,5
1.5
.6
4851
36000
Automatic
24.0 Cost/ Board (elba) le.o
2700
Z
3 8.0
1000
10000
100000
Total Annual Board Volume
1 Total costs for one DIP, one ~xi&l ~ d one r a d i a l insertion machine
2 Includes a storage system for 700 components 3 Source: (RtmsullSr)
Figure 6 Component Control and Insertion Cost per Board ($)/bd) vs. TABVfor Various Methods of Component Control and Insertion and N = 10 Years
banned and manually inserts the odd-form components that use the kit-to-order form of component control. The fourth alternative also automatically inserts the standard components, but it semiautomatically (light-directed) inserts the odd-form components that are also Kanbanned. The four alternatives are compared for various board volumes (TABV), component values (CV), and equipment lifetimes (N). Some of the values used in the comparisons are shown in Tables 1-3 (the middle of each range is used where applicable) and the other values are DRT = 3600 seconds and I = 15%. For alternatives 3 and 4, NDCws = 300 for the automatically inserted standard components, and NDCws = 700 for the semiautomatically inserted nonstandard components. For alternatives 1 and 2, NPN = 100, and for alternatives 3 and 4 NPN--- 20 (here fewer components are manually inserted). Two values of CV are used in each case because DIPs are much more expensive than other components, and they are typically inserted automatically. The results are shown in Figures 6 and 7, where Figure 6 assumes N = 10 years and CV = $1.00 for the
32.0
24.0 Cost/ Board ($/bd)
8.0
NOC
NOC
(automatiC)
o
1
250
0
2
0
250
o
3
5O
0
20o
4
0
50
200
1 light
directed
100000
standard components, and CV = $.20 for the nonstandard components. Figure 6 shows that alternative 4 is the least costly method of assembly for TABV > 10,000 boards. Likewise, alternative 2 proves the least expensive method of assembly for 500 < TABV < 10,000 boards. Figure 7 shows that alternative 4 is the most economical method of assembly for TABV > 20,000, and alternative 2 is the least costly method of assembly for 1500 < TABV < 20,000 boards. This figure assumes N = 3 years and CV = $5.00 for the standard components and CV = $1.00 for the nonstandard components. The changes in CV had little effect, however, because alternative 3 (manual insertion of nonstandard components using kit-to-order) is still more expensive than alternative 4 for all board volumes shown in the figure.
NOC
(seml-auto)l
10000 Total Annusl Board Voluse
Figure 7
Table 3
(manual)
1000
Component Control and Insertion Cost per Board ($/bd) vs. TABVfor Various Methods of Component Control and Insertion and N = 3 Years
The Number of Components (NOC) Inserted for Each Method of Insertion in Each Alternative
Alternative
16.0
method
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Journal of ManuJacturing Systems Volume 8/No. 4
Although the full costing rate used for offshore assembly accounts for the overhead personnel in the offshore plant, it does not account for the additional overhead costs incurred in the U.S. operation due to manufacturing offshore. Some of these costs are attributed to carrying additional inventory in the total assembly system. Offshore assembly causes these inventory costs to increase because each plant in a JIT-PCB assembly system must store most of the PCBs and components that are assembled in the system (see Figure 1). These expenses include the cost of money and the additional personnel needed in the U.S. plant to handle and transact the inventory. It is assumed that these costs are "captured" in the inventory carrying rate. Other costs, such as communication, travel, and quality control--which increase in the U.S. operation due to manufacturing offshore-are not considered here due to lack of data. Therefore, this analysis underestimates the cost of offshore assembly. Five Different Systems. Five different manufacturing systems are compared. Four of these are shown in Figure 8, and all five are summarized in Table 4. In the first and second systems, the PCBs are completely assembled in a U.S. location. The first uses the same methods of component control and insertion as the second alternative described earlier--semiautomatic insertion (light-directed) using kit-to-order. The second system uses the same methods of component control and insertion as the fourth alternative named in the previous section-automatic insertion of standard components and semiautomatic (light-directed) insertion of the oddform components and all of the components; all of the components are Kanbanned between the supermarket and mini-markets. In both systems, components and unpopulated PCBs are stored in the supermarkets. Although some actual systems might also store populated PCBs in the product assembly line's mini-market, these instances are not considered here. This paper assumes that since the response time between the PCB and product assembly lines can be very smail (that is, one day), a specific PCB is assembled only when a product is ordered that uses the specific PCB. As a result, it is not necessary to store PCBs in the product assembly line's minimarket. In the third system, the U.S. location purchases the unpopulated PCBs, the PCBs are manually assembled (kit-to-order) and tested in an offshore
Economic Models The lower labor costs that exist in many underdeveloped countries have made "offshore assembly" an extremely attractive option. However, few companies have analyzed the effect of offshore assembly on manufacturing overhead costs, which--as pointed out earlier--have become much larger than direct labor costs. Additionally, offshore assembly increases manufacturing overhead costs in both U.S. and offshore locations. Much of the increased manufacturing overhead costs are related to the increased inventory that results from offshore assembly (refer to the first paragraph in this paper for actual percentages), since parts and assemblies must now be stored in a greater number of supermarkets, mini-markets and work centers. 6 Further, offshore assembly also increases noninventory associated manufacturing overhead costs such as travel, communication, plant and equipment (duplication of equipment), maintenance (duplication of equipment and less access to equipment suppliers), management (duplication of personnel), and quality control (more incoming inspection and increased time for quality feedback). Offshore plants also typically have higher start-up costs, and they take longer to reach accepted quality levels than do U.S. plants. 7 Offshore and U.S. assemblies are compared here both by using the "full costing rate" for offshore assembly (DLoyy),and the "marginal costing rate" for U.S. assembly (DL, s) and by developing and applying models of board and component inventory carrying cost, test labor cost, and shipping cost. The full costing rate includes the direct labor rate and all of the overhead expenses in the offshore plant. This overhead primarily represents personnel who are not needed if the additional assembly is performed in the U.S., since these personnel duplicate those in the U.S. operation. The marginal costing rate only includes the additional costs that would be incurred if the assembly is performed in the U.S. plant. This includes direct labor, benefits, lost time, inspection and hand tools used in manual assembly. Westinghouse factories have found that the other overhead costs do not typically decrease when assembly has been moved offshore. Therefore, these overhead costs are not expected to increase if the assembly operations are moved back to the U.S. plant and the "full costing rate" is not used for assembly in the U.S. plants.
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Journal of Manufacturing Systems Volume 8/No. 4
F i r s t and second systems
I
Third system
i
Jq
Suppl lore
U.S, Location
d
Un,o,u. d PCB Storage
-
,roduct
Assembly
/
Asmembly
-i Cu.,o.r
i
A
[
U.S. Location
q
Suppl lerm
Unpopulsted
]Storage of-
PCB Storage
Itemted PCBs
1
1~
Product
Customer
Assembly
t Offshore Locab|on
Unpopulited --
PCB Storage
I1_ ~ PCB I Assembly l
U.$. Location Fourth mnd fifth systems
[
I
Suppl lets
--~PCB Assembly
IStorag. 0¢Itembed PCBx
I~Product I Allembly
Customer
t Offshore Location UnpopulstedPCB Storage
I- ~
PCB Assembly
Figure 8 A D i a g r a m o f F i v e P C B A s s e m b l y Systems
Table 4 A Summary of the Five Systems
STstem 1 2 S 4~i
Standard Coiponents MO_~I CCM Location Semi-Auto. ICf0 U.S. Auto. Kanban U.S. Manual k'ro Offshore Auto. l~nban U.S.
mini-market in the U.S. plant. In the fourth system, the PCBs are assembled both in the U.S. and abroad. The U.S. location purchases the unpopulated PCBs and automatically inserts the standard components using Kanban. The odd-form components are manually inserted using kit-to-store, and the boards are tested--both in the same offshore location. Therefore, components and unpopulated PCBs are stored in the U.S. plant supermarket, components and populated PCBs are stored in the offshore location supermarket, and assembled and tested PCBs are stored at the product assembly line mini-market in the U.S. In the fifth system, the PCBs are assembled in both an American plant and two offshore locations (the second offshore location is not shown in Figure 8). This manufacturing system is the same as the
Odd-Form Components MO_.II CCll Location Seai-Auto KTO Semi-Auto Kanban Manual KTO Manual KTO
U.S. U.S. Offshore O~fshore
HOI: method of insertionj CCii: component control method, KTO: kit to order
plant, and the PCBs are assembled into the final product in a U.S. location. Therefore, components and unpopulated PCBs are stored in both the U.S. and offshore location supermarkets and assembled and tested PCBs are stored at the product assembly line
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Journal of Manufiwturing Systems Volume 8/No. 4
fourth one, except that the populated PCBs are tested at a second offshore location before the PCBs are assembled into the final product. Therefore, populated PCBs must also be stored at the second offshore location in addition to the three other board storage locations described for the fourth system. Cost Models. The five systems just described are compared using Eq. (1), where CCC, CILC and ECPB are developed in the previous sections. The component inventory costs in the U.S. supermarket-part of the component control costs (CCC)--are not considered since each system has the same cost. Systems that use offshore assembly, however, require that components be stored in an offshore supermarket, so these systems are considered using Eq.
weight, CPP is the shipping cost per pound, and NOT is the number of trips. Cost Comparison B e t w e e n Systems. The five systems are compared for various values of average component cost (CV), offshore costing rate (DL) and the inventory carrying rate (ICR). The offshore costing rates can range between $5/hr. and $15/hr. depending on the country's wages, the number of overhead personnel in the factory, and the capability of and turnover in the factory's workforce. The inventory carrying rate can range between 15% and 25% depending on the amount of inventory that is damaged or becomes obsolete each year, the "complexity" of the production system, and the amount of automation in the production system. Component costs can range between $.01 and $150 although DIPs (one category of standard components) are more expensive (typically between $.20 and $1.00) than other components (usually between $.01 and $.50). Two values of CV are used--one for automatically inserted components and one for nonstandard components--since these components are added to the boards at different times in the offshore assembly systems. Since DIPs are typically inserted automatically, the high value of CV represents those components which are automatically inserted and the low value of CV represents the other components. As for the other variables, the same values are used in these comparisons that are defined in previous sections (Tables I, 2, and 3). The life of the equipment is assumed to be three years and an interest rate of 15% is used. The distribution of annual board volumes for individual boards is shown in Table 5. These volumes are for actual boards assembled in a particular factory. The test time is assumed to be 20 minutes, the average board weight is assumed to be 1.4 pounds (actual weight of a multilayer board containing 250 components), and the initial board cost (typical multilayer board) is assumed to be $75. Since the previous section showed that semiautomatic and manual insertion are the lower cost methods for TABV <20,000, and automatic insertion is the lowest cost method for TABV >20,000, systems 1 and 3 are compared for TABV = 10,000 and systems 2, 4, and 5 are compared for TABV = 50,000. Response time and shipping cost between locations depend on the offshore assembly location. Since Caribbean countries are popular with many U.S. electronics companies, typical values are taken for ship-
(5). BICC, or board inventory carrying costs per
board, can be estimated using the same equations developed earlier for component inventory costs. The board inventory carrying costs are summed over each board and each location as shown in Eq. (21): BICC = ZEBVot*ICR*NOBLot*BLS/ABV o (21)
where: BVot is the value or cost of board b at storage location 1, NOBLbt is the number of lots stored for board b in storage location 1, and BLS is the typical lot size. The board value increases as components are added and the board is tested, as shown in Eq. (22): B V n = BC o + CC*NOC + RLC b + CLC o + CILCo + TLC o
(22)
where: BC is the initial board cost, CV*NOC is the raw material component cost and RLC, CLC, CILC and TLC are the retrieval, counting, insertion and test labor costs respectively for board b. As shown in Eq. (23), NOBL o depends on the response time (RSTt) to location I in terms of days, the board's annual volume (ABVo), and the board lot size. Since the raw-board inventory carrying costs in the U.S. location are the same for each system, they are not considered in the analysis: NOBL b = RSTi*ABVb/(BLS*250)
(23)
TLC, or test labor costs, and shipping costs SC, are represented by Eqs. (24) and (25), respectively: TLC = T I * D L
(24)
SC = W*CPP*NOT
(25)
where: Tit is the test time per board, B W is the board
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Journal of Manufacturing ,~vstems Volume 8/No. 4
Figures 9, 10, and 11 show total assembly costs (TAC) for systems 1-5 as a function of direct labor-
Table 5 The Annual Board V o l u m e s for E a c h Board Group Used to Compare the Five Systems Board St~le
Board Croup
l
1 2 1 2 3 1 2
B C
D
1
2 3 4 5
6 E
F
1
Board
Board
Stile
Croup
1132 102 57 47 693 618 18 1096
C
1 2 3 4 5 6 1
494 568 372 10 54 149
I
2
351
1
492 1227 317 9 47
2 3 4 5
H
J
AB__VV 1259 68 17 26 4 4 lgl
2 1 2 i
4114 200
2
1995
1899 16
3
357
4
2165 380 91 3
5 1 2 3
K
L
rate, component value, and inventory carrying rate using a 2-level, 3-factor experiment. The trials with a lower offshore labor rate are shown on the left side of each cube, and the trials with a larger offshore labor rate are shown on the right sides of the cubes. Similarly, low and high inventory carrying rates are shown on the fronts and backs of the cubes respectively, and low and high component values are shown on the bottoms and tops.
564 859
1 2
4OO
1. 0
ping between the eastern United States and the Caribbean. The response time between locations is assumed to be 10 days, and the shipping cost per pound is assumed to be $1.50. Asian and South American countries have longer response times and higher shipping costs. An example calculation for specific values of CV, ICK DLoff and TABV is shown in Table 6. As expected, the board and component inventory and shipping costs are higher for the offshore assembly systems (3-5) than for those in the United States. The labor costs for each are similar in this example, however, because DLo// = $15 (includes all overhead costs), DL,~ = $20 (includes only some overhead costs), and the U.S. systems are assumed to have a more automated method of component insertion than those offshore.
Component I Value($)I
.25
i
Inventory
Carrying Rate
.01
.025 5
15
Direct Laborof f ($)
Figure 9 Assembly Costs per Board ($) for System 1 (Top Value in E a c h Box) a n d 3 (Bottom Value in E a c h Box) and a Total Annual Board Volume of 10,000
l.Op
Table 6 Example Calculation of Assembly System Costs Per B o a r d 2
Component "I
Value($)~ S]fste.
TABV (bds/yr)
CICC ~1)
LC ~
ECPB (I)
BICC _~
SC ~.~
TAC ($)
1 2 3 4 5
10,000 50,000 I0,000 50,000 50,000
0.00 0.20 2.80 0.40 0.40
28.90 14.90 30.80 14.40 14.40
4.80 4.60 .20 4.30 4.30
0.00 0.00 5.00 7.70 11.70
0.00 0.00 4.20 4.20 6.30
33.50 19.70 43.00 31.00 37.10
1: LC = CILC + RLC + CLC +
.25ventory
.025 54
Direct Laborof f
t~16
($)
Figure I0 Assembly Costs per Board ($) for System 2 (Top Value in E a c h Box) a n d 4 (Bottom Value in E a c h Box) and a Total Annual Board Volume of 50,000
TIC
2:CV=$1.O0 (standard components) and 1.20 (non-standard components, ICR=25~ and DLoff= $15.oo/hour (includes overhead COSTS)
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~l
nent insertion and both U.S. and offshore assembly systems. Using typical values from a particular factory, it is determined that the "Kanban" method is the lowest cost method of component control except for a combination of high average component cost (>$.50), a large number of components stored at each workstation (>700), and a low number of different part numbers per board (<50). Under these circumstances, the kit-to-order method is the least expensive method of component control. The paper also concludes that a combination of automatic insertion of standard components and semiautomatic insertion of nonstandard components that are "Kanbanned" proves a lower cost method of component control and insertion than does more manual alternatives for volumes greater than 20,000 boards per year. These results are combined with board inventory carrying cost, test labor cost, and shipping cost models to compare five U.S. and offshore assembly systems in both high volume (50,000 boards/year) and low volume (10,000 boards/year) situations. Due to its higher shipping and inventory costs, offshore assembly is found to be more expensive than U.S. assembly in a number of situations. For a low volume system, U.S. assembly is the lower cost operation when the offshore "costing rate" (includes overhead costs) is greater than about $12/hour. For a high volume system, U.S. assembly is less costly when the offshore "costing rate" is greater than about $7/hour. Since typical offshore costing rates vary between $5/hour and $15/hour, depending on the country and other factors, offshore assembly can be more expensive than U.S. assembly in some cases. Although this analysis is done for PCB assembly, the models and concepts are applicable to any assembly system. The relative values of labor and inventory carrying costs and thus U.S. vs. offshore assembly costs will differ due to different assembly processes and material costs. For example, since wire assembly typically has a lower ratio of material-tolabor costs--and thus inventory-to-labor costs--than PCB assembly, offshore wire assembly is more economical than offshore PCB assembly. Mechanical assembly can have a lower or higher ratio of material-to-labor cost, depending on whether the parts require complex (e.g., casting and forging) or simple (such as screws and nuts) fabrication operations•
m
YalueC°mP°nent(8)
~v 119.41
iz0.4
Figure II Assembly Costs per Board ($) for System 2 (Top Value in Each Box) and 5 (Bottom Value in Each Box) and a Total Annual Board Volume of 50,000
In Figure 9 system 1 is the top value, and system 3 is the bottom value. As shown, system 1 (U.S. assembly) is a lower cost method of assembly than system 3 (offshore assembly) for DL = $15.00/hour. The reverse is true for DL = $5.00/hour0 The crossover points for the direct labor rate are DL = $13.23 for CV = $. 1 (standard components) and $.025 (nonstandard components) and ICR = 15% and DL = $9.95 for CV = $1.0 and $.20 and ICR = 25%. Figures 10 and 11 show total assembly cost for systems 2 (top values in each box), 4 (bottom values in each box of Figure 10), and 5 (top values in each box of Figure 11) as a function of the same variables as indicated in Figure 9. System 2 (U.S. assembly) is always a lower cost assembly system than system 5 (two offshore assembly locations) for the values shown in Figure 11. System 2 is also a lower cost method of assembly than system 4 (one offshore location), except when DL = $5.00/hour and CV = $.10 and $.025. The crossover points for the direct labor rate are DL = $6.51 for CV = $.10 and $.025 and ICR = .25 and DL = $8.11 for CV = $,10 and $.025 and ICR = 15%.
Concluding Remarks This paper develops and uses economic models of labor and inventory carrying costs to compare various methods of component control and compo-
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CLS== = [(RTs= *NOC*DL* TABVmm)/ (NDCmm.CV.ICR) ].5
Appendix Optimal Component Lot Size The optimal component lot size balances the retrieval labor cost and the component inventory carrying cost. Two cases are considered: 1) When DCV*RST/CLS <1, NOCL = 1, since a minimum of one lot must be carried in inventory; 2) When DCV*RST/CLS > 1, component lot size has little effect on component inventory costs 6 so the largest possible lot size that satisfies this condition (that is, NOCL = 1) is the optimal lot size--since this will minimize retrieval labor costs. Therefore, the optimal lot size for deliveries between a supermarket and a minimarket (CLSm.) using the kit-to-store method can be represented by Eq. (26), by setting Eq. (8) equal to the first half of Eq. (7) when NOCL = 1. The optimal lot size for deliveries between a supermarket and a workstation (CLSws) can be represented by Eq. (27), by setting Eq. (12) equal to Eq. (13). The optimal lot size for deliveries from a mini-market to a kit CLSk,) can be represented by Eq. (28), by setting Eq. (10) equal to the second half of Eq. (7).
CLSws = [(RT~m*NOC*DL*TABVwJ NDCw~*CV*ICR) ].s
(26) (27)
CLSki t = [(RTmm*NOC*DL*TABVmm / NPN*NDB*CV*ICR)] "s (28)
References 1. J. Miller, T. Vollmann."The Hidden Factory",Harvard Business Review,November-December,1985. 2. G. Boothroyd."Economicsof AssemblySystems",Journalof ManufacturingSystems, Vol.l/No.l, 1982,pp. 111-127. 3. M. Carter,P. Carter."TheCost of InsertingOdd-FormComponents -Manual vs. Robotic Placement",Connection Technology, September 1987, p. 19. 4. R. Gustavson. "Choosing ManufacturingSystemsBased on Unit Cost", 13thlSIR/Robots 7 Conference,April 1983. 5. R. Schonberger."WorldClass Manufacturing",New York."The Free Press, 1986. 6. J. Funk."A Comparisonof InventoryCost ReductionStrategiesin a JIT ManufacturingSystem", InternationalJournal of Production Research, Vol.27/No. 7, 1989,pp. 1065-1080. 7. H. Shaiken."HighTechGoesThirdWorld",TechnologyReview,January 1988. 8. G.A. Russell, G. Boothroyd,P. Dewhurst."Printed Circuit Board Designfor Assembly,Report#5, Departmentof Industrialand ManufacturingEngineering,Universityof RhodeIsland,Kingston,RhodeIsland.
Author Biography Jeffrey L. Funk is a Senior Engineer at the Westinghouse Science and Technology Center in Pittsburgh, Pennsylvania. He earned his BS degree in Physics from California Polytechnic State University, and both his MS degree in Mechanical Engineering/Engineering and Public Policy, and his PhD degree in Engineering and Public Policy from Carnegie-Mellon University. His research interests are in the economics and management of manufacturing systems, design for manufacturing, and computer integrated manufacturing. Dr. Funk is currently working on the implementation of automated semiconductor processes as a Westinghouse-Mitsubishi Exchange Engineer in Fukuoka, Japan.
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