EE-RM/STD-98-440- 

## 309q APPENDIX C: TECHNICAL DESCRIPTION OFTHEREVERSE ENGINEERING COST ESTIMATION METHODOLOGY
C.1 INTRODUCTION The manufacturing cost estimation methodology, or "reverse engineering", is a detailed, component focused, activity based technique for rigorously estimating the manufacturing cost of a product (direct materials, direct labor, and plant overhead costs). Arthur D. Little (ADL), a Department ofEnergy contractor, has applied its technology based cost assessment successfully to a broad range ofproducts in various stages of development from early R&D to production. This Appendix describes the technical aspects of the approach as applied to residential central air conditioners and heat pumps (CACs). Refer to Chapter 4 in the body ofthe Technical Support Document(TSD) for more information onassumptions andcontext.
C.2 TEAR-DOWNS Our first step was to perform "tear-downs" on equipment samples thatare typical oftoday's minimum efficiency air conditioners. A tear-down is a thorough disassembly of the equipment followed by a detailed inspection of the parts and subassemblies. We performed the minimum number oftear-downs required to assess all four CAC product classes. Since split and packaged equipment have different configurations, we selected one baseline (10 SEER) model from each class- -both from the same manufacturer. Since heat pumps (HPs) and cooling-only air conditioners (ACs) have similar configurations differing only by additional HP components, we selected only HPs rather than acombination ofHPs andACs.
C.2.1 SplitHeatPump Tear-down Initially, a representative 10 SEER split HP outdoor unit with a indoor fan-coil unit served as the basis for the bill-of-materials (BOM) used by both split system products (AC and HP). We disassembled the outdoor unit first and then the indoor fancoil unit. We made every attempt to perform the disassembly in reverse ofthe actual assembly process, and the BOM reflects the order of these operations. We assumed that major sub-assemblies arrive pre-assembled at the final assembly line. For example, most outdoor units feature fans and wiring that are integrated into the top cover subassembly. The model assumes that a assembly worker on the final assembly line receives the top cover assembly as a single piece, places it atop the rest ofthe completed outdoor unit, and attaches the wiring leads and screws. Sub-assemblies can also feed into other sub-assemblies before being integrated on the final assembly line. This mimics cellular manufacturingtechniques often foundintoday's state-of-the-art plants.

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# o0q9C
C.2.2 Packaged HeatPumpTear-Down We used the same processes and cost models to establish costs for 3ton packaged systems as we had for split systems. Since packaged systems have a significantly different configuration, however, we tore down a representative 10 SEER packaged HP (PHP) model. As we had done for split systems, we derived the packaged AC cost model directly from the PHP cost model by removing HP-specific parts.
C.2.3 Confirmingthe Tear-Down Results We confirmed our cost and weight predictions using a number of methods. Initially, we compared shipping weight predictions with published shipping weights. Since cost and weight tend to be highly correlated in manufactured goods, the ability to accurately predict weight is usually an important indication ofthe accuracy ofthe cost model. However, we discovered that at least one equipment manufacturer had published erroneous weight data. For example, the discrepancies at 16 and 17 SEER for evaporators are caused by inaccurate OEM submissions. Since we could notverify all the published weights, we could not place as much confidence in the weight verification as we would like. Table C.1 below shows the degree to which the equipment weights we predict differ from the weight listed by the manufacturer. Positive values denote where the model calculates weight in excess ofreported shippingweights. Table C.1 Predictedversus ListedEquipment Weight SplitAC Split HP Packaged Packaged AC HP Efficiency Outdoor Indoor Outdoor Indoor

Level Unit Unit Unit Unit (SEER)

10 3% 7% 0%/O -2% 1% 2% 

### 11 -6% 

### 8% XX X 12 6% 8% 6% -7% -2% 3% 13 -3% 18% 1% -4% 2% 14 -9% -1% -7% 4% 15 -14% -14% -22% -11% 16 -8% 1% -22% -16% 17 -8% -3%

C-2EE-RM/STD-98-440- 

### 30Oq We attributed under-predictions primarily to the weight ofnon-efficiency items such as sound blankets, cosmetic grilles, etc. found on today's high efficiency equipment that we assume would be omitted from those units once they became commodity units. Section 4.2.5 inthe TSD describes this conceptmore fully. Afterthe PHP tear-down and the quotation process, we also tore down a 12 SEER split HP outdoor unit to verify some ofour assumptions regarding higher efficiency equipment Even though different OEMs produced our 10 and 12 SEER equipment samples the physical similarities between the two models were striking. This tear-down was not meant to establish a BOM since we based the BOM solely on the 10 SEER baseline. Rather, we wanted to confirm the components used in the design and thatthe BOM model was using the correct component data. Our coil model predicted the weight ofthe 12 SEER coil within /2 pound ofits actual weight. The difference was due to the larger end-plates of the coil which, being made of galvanized cold rolled steel, do not contribute significantly to equipment cost. Furthermore, the 10 and 12 SEER defrost controllers were quite similar despitebeingmanufactured by different companies.
C.3 SELECTING ADDITIONAL EQUIPMENT SAMPLES Although we had detailed information on the three tear-down samples, we needed many more samples to span a broad range ofefficiency levels ineach ofthe fourproduct classes. That approach would provide us discrete cost points to compare against the cost curves that ARI would provide. We asked OEMs to provide us with a list ofequipment models, one model at each efficiency level, that they felt best represent baseline equipment. We then asked for detailed information on the components and physical parameters that we identified as being related to the efficiency of the product. Four OEMs responded to our request and provided data to us directly for equipment they considered to most closely represent baseline models at each efficiency level. That yielded information on 62 samples. We supplemented that data with nine more selections from ARI's UnitaryDirectoryand associated physical data from ARI's Product Attributedatabase and OEM literature.Where possible, weobtained exact specifications for purchased parts. Our subsequent cross-checking exposed a few errors in the data we had collected. We corrected all aberrations either by replacing them with correct values or by omitting the unit altogether if we determined that the entire configuration did not represent a prospective baseline system. Forexample, one 11-SEER SACunit thatwe selected was comprised ofa 10 SEER outdoor unit and a variable speed fan-coil unit. Because such combinations would be significantly more expensive than a more efficient outdoor unit coupled with a less sophisticated fancoil unit, that sample was an obvious outlier. We therefore omitted it on thepresumption that the mass market will notsustainlargeprice differences atthebaseline efficiency level.

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### EE-RM/STD-98-440- 30 d C.4 CREATING THEBILL-OF-MATERIALS We used the tear-down process to create a complete and structured bill-of-materials (BOM) for the baseline equipment. We built four separate BOMs from our two tear-downs--one for each of the four product classes. While we completely dismantled each piece ofequipment, we characterized every part according to weight, dimensions, material, quantity, and, the manufacturing processes used tofabricate and assemble it. As a simplification, we assumed that the structure ofthe BOMs we developed for the teardown samples also applied to the samples that we did not tear down. This allowed the physical parameters and parts to vary across samples, but fixed the assembly process (and the associated plant equipment) for each sample. Since a typical OEM manufacturers a wide range of products in the same plant and assembly line, we consider this a valid simplification for isolating efficiency-related changes within a product platform and within a single manufacturer. Our simplification cannot reproduce cost variability across OEMs due to differences in assembly processes or product platforms. The BOMs incorporate all materials, components, and fasteners with estimates of raw materials and purchased parts and sub-assemblies. We based our assumptions on the sourcing of parts and in-house production on our previous industry experience, recent information in trade publications, and discussions with high and low-volume original equipment manufacturers (OEMs). To reinforce our understanding of the industry's current manufacturing practices, we also visited several manufacturing plants. These visits focused on observing and characterizing current manufacturing practices. FigureC.1 illustrates a small section from astructured bill ofmaterials. Itshows: 1. Partnumber: Assigned duringdisassembly 2. Description: A description of the part. The step-like ladder approach identifies logical groupings ofparts to denote which go together where in the assembly process. Areverse indentation denotes parts that are sub-assembled onto a part prior to final assembly on the manufacturing line. 3. Category: Primarypartmaterial forrawmaterial costing and sorting purposes 4. V: This entry denotes whether apart is a purchased component or fabricated in house. Weassumed that allplasticcomponents were outsourced. 5. #:Howmanyparts areassembled in a givenassembly step. 6. OD,Length, Depth,Thickness: Physicalparameters thatdescribe the finishedpart. 7. Painted surface: Describes how many square inches ofpaint are required for each part. We assumed that any "green field" plant would rely exclusively on pre-painted steel and pricedthe paintcoatings accordingly. 8. Weight: Final weight ofpartinpounds. 9. Material cost: Final material cost ofthe part (calculated), accounting for scrap losses but excluding required assembly, painting, fabrication, orjoiningcosts. C-4EE-RM/STD-98-440- 

### 30- 10. Labor: The manual labor (in seconds) required to handle all parts or assemble them into the unit. Some parts such as fasteners also require additional tool time which is accounted for inthe latersection ofthe BOM spreadsheet.

P* T ", I I I I I I I , "" , CM, I TVI InD I Pbftd | W.lghl| I | H Wir Figure IC.1 Sample I I of I m I .aA I .ls
Tabl1.02e l

_ CB 4 4 4 lis.s these pre sses. 1.S Collarfing I ntegl 1 fast B s -MOu.01. W..tl~rap_l__ I I KM____O_ Y I 335 38.5 7 M _3 135 00 1.0 15 I Fir.Pni E Deburring Other faste - 2 1.07

. - P- 5-, Fif- p
.. T I 1F 1 r "-
- 287 - 1m .0The tear-don procs -d 2 2 5d o t s s 5prove th s 06tart ,.0 M. A-~P-1 WAS
_ TI 25 30.75 0 .a0 ON -3i o &sM ~ 1.0 a p .1a 0 and material pric, F Y 2 0p44 0.785 squ 0 amor014 t
. ,.-2- lE»WFlPfSbO8 M Y. _I 3 2.5

_ _ . 8 Li3 IEw 1DFan A ens Panl GC3

- _ __ , 0.5 0.04 7.57s81 7T38 1% 11.74 hapter 4) descibs or assu tions a nd daa sources. Ti_ s seio 0.briy s . e proc e 4 To ov _ o --- ens l 'Y '-- ' =- .BC-5 1.1 2

_ _ITO o ~ W Sos. o | s| 0 .75 0 .la | = 0.0

,. 2

- _M~c» k
_ ,, r nr Gd

_ 3725 T I 0G I 0o.08 02 no 31 T 0.82 a Figure C.1 Sample structuredbillofmaterials The BOMs also capture the major manufacturing processes required to make selected parts. Table C.2 liststheseprocesses. Table C.2 ManufacturingProcesses Capturedin theBills-of-Material
Fabrication Assembly/Joining Fixturing Adhesive bonding Stamping Spot welding Brake forming Brazing Cutting/shearing Press fitting Collaring Integral fasteners Deburring Other fasteners

C.5 ADDITIONAL PRODUCTION COST DATA The tear-down process and the development of the structured BOMs provide the starting points for estimating production costs, but we still needed information on manufacturing operations, part and material prices, wages, plant equipment amortization, and plant overhead. The TSD (Chapter 4) describes our assumptions and data sources. This section briefly describes theprocesses we usedtogather thedata andhow weusedthem.

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### EE-RM/STD-98-440- 

## 309 C.5.1 Laborand Factory Overhead Information on equipment and tooling costs, typical process cycle times, and materials used for fabrication were obtained from the ADL manufacturing databases. Plant equipment suppliers provided us with details concerning equipment capabilities and processing parameters (cycle times, scrap rates, etc.). Fabrication cycle rates are directly entered into the model and depend on part complexity and theprocessesused.
C.5.2 Depreciation Depreciation, or amortization, is the accounting process by which capital costs are allocated to production volume. Amortization occurs over aperiod oftime so that at the end ofthat time, all capital costs are accounted for in the full cost ofproducing the product over that time. For example, if a manufacturer produces 1 million air conditioners over ten years and amortizes a $10 million investment over the same ten years, each air conditioner produced during that time would include $10 inamortization charges. The methodology we used toallocate depreciation depended on whether we assumed the plant machinery to be dedicated or non-dedicated to the production ofthe sample product. Dedicated machinery is tied solely to the production ofthe sample product. During times when a piece ofdedicated machinery is not needed forthatproduct, it sits idle. The entire capital cost ofa piece of dedicated machinery is amortized across the annual volume of the sample product. Conversely, non-dedicated machinery maybe used toproduce another product when it is notneeded for the sample product. Only a fraction ofthe capital cost ofnon-dedicated machinery is allocated to the sample product based on the time the machinery was used toproduce the sampleproduct. For example, a non-dedicated press that wasused 55 percent ofthe time to produce the sample product would allocate 55 percent of its depreciation charges to the sample product and 45 percent to the other products to which it is associated. A dedicated press, on the other hand, would allocate 100 percent of its depreciation to the sample product, even if its utilization was 55 percent, since the press isnotused forany otherproduction. We assumed that all coil fabrication machinery is non-dedicated. Given the substantial equipment and space investment costs associated with coil lines, OEMs install universal, high volume machinery to achieve high production efficiencies and low costs. The total coil volume and the many configurations manufactured by OEMs ensure that no one coil type dominates the coil production centers. Thus, every type of product will only be a fraction of the total output, and amortization charges are basedon that fraction. We assumed that machinery other than coil assembly machinery is dedicated. Unlike old plant designs, new facilities usually feature several production lines under one roof that handle almost every part of fabrication and assembly. Instead ofbelonging to a functional department, all employees and equipment are dedicated to individual product lines. The industry is moving to this
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### EE-RM/STD-98-440^ 

### 309e manufacturing philosophy. Our model reflects the possibility that a piece ofproduction machinery canbe used to produce different parts for the sameproduct. That is, each product, not each part, has a setofdedicatedmachinery. All equipment and process costs are spread across the entire production volume,unlikethecoil modelwhere costs are assignedon thebasis ofutilization. We also allocated labor to operate a piece ofmachinery based on whether the machinery is dedicated ornon-dedicated. As equipment utilization rates approach 100 percent, the costs associated with dedicated vs. non-dedicated equipment costs become equal. However, few dedicated pieces of equipment ever achieve 100 percent utilization due to lack ofdemand, capacity mismatches between process steps, scheduled downtime, etc. Thus, non-dedicated equipment results in lower overall costs per part, as depreciation, maintenance, and other costs are only assessed on thebasis ofhow muchtime each part usesapiece ofequipment. As equipment samples vary, so do the manufacturing equipment and labor requirements. Depreciation charges therefore also vary across equipment samples. Figure C.2 shows how the model allocates depreciation andlaborto asampleproduct.

f_ E iB gPa4.00 1300 5.00 14. 00 16.00 11

. 00 200 1 000 1400

. I 0.00 3700

FigureC.2 Sample Fabricationand Assembly Summary Table
C.5.3 Partsand Materials Cost estimates for raw materials and purchased components were drawn from ADL's manufcturing databases and supplemented with information obtained from manu.facturer and supplier sources. We adjusted our cost estimates as appropriate to include price discounts typically seenintheindustry as theresultofhigh-volumepurchases. As purchased components make up the bulkofthe unit costs, special consideration was given to establishing accurate OEM-level price data. Through manufacturer submissions, industry literature, and active research, we were able to ascertain the exact specifications for the majority of components used in the AC and HP units under investigation. For the relatively few purchased components we couldnotidentify, wesubstitutedparts from comparable equipment

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# 9
For example, a manufacturer's technical data sheet may convey that a sample condenser uses a certain type ofcompressor supplied by a particular company, but may not state the precise size or part number. In the cases when distributors could not positively identify the part, our industry experts would compare the known attributes ofsimilar condenser units (such as coil size, compressor specs, capacities, etc.) and those ofthe equipment under question. We would then select a specific compressor sizebased onan interpolation ofthe available data. We then consulted local distributors, wholesalers, parts suppliers, and OEMs to determine high-volume pricing. We applied a discount to the prices we received from each ofthose sources based ontheir placeinthe distribution chain. These discounts were based on markup data andour previous experience in the industry. The many different data sources and the large purchased parts list also allowed for some cross-checking ofprice data and discounts. We selected those that, in our bestjudgement, most likely reflected actual prices to OEMs. The discount on each component were a function ofthe total dollar volume ofa typical OEM's account with atypical supplier. Since we are modeling high volume OEMs who deal with one supplier for each component, this results in substantial discounts relative to retail or wholesale prices.
C.5.4 Coil FabricationCosts While purchased components make up the largest part ofcosts in AC and HP units, coils, generally fabricated bythe OEM, also are important. To model the fabrication cost ofboththe indoor and outdoor coils, we constructed a second cost model for each ofthe four product classes. These costs were then fedbackintothemain costmodels.
C.6 STRUCTURE OFTHE COST MODELS Once we had collected all ofthe information required to estimate production costs for each sample, we used spreadsheet models to perform the required calculations. As stated earlier, the costs for each CAC unit are calculated withthe help oftwo cost models: the mainmodel and the coil model. Figure C.3 illustrates the structure and relationship ofthe spreadsheets that comprisethetwomodels.

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# 30

Global dta d Output and othi Cer oo working p ramafr* c rOntI i-ta Page Outpututndothr o- P |_______ working para mters Coil model Requestfor Deprecitlon Information Labor costs Indirnct materia.
dCo Mcoilol, Equipmntdedication

Component e_ Crot & d decriptions PadecrptP Purchsd compomnnt costs andweights FigureC3 Overall Model Structure

C.6.1 Main CostModel The main model serves holds data and performs the calculations that determine the production cost ofthe final assembled equipment. It contains a number ofworksheets that perform differentfunctions.
C.6.1.1 Global Controls Sheet This worksheet sets parameters such as production volume and wages while also displaying the cost results by sub-assembly. The basic parameters (e.g. days available per year) ofthe Global Controls page are linked to the coil model. A sample section ofthose controls is shown below (Figure C.4). Shaded fields are also varied inthe Monte-Carlo analysis (referto Section 4.2.9 in the TSD). The Global Controlspage also shows costs broken down by sub-assembly and cost category. The results were shown in two tables. One table (Figure C.5) featured costs by major sub-assembly and cost type by efficiency level. Another more detailed table formed the basis for the CAC Cost spreadsheets (see Appendix A inthe TSD). Cost breakdowns to this fine level allowed us to zero on the differences between equipment across efficiency levels and facilitated the calibration and industry reviewprocesses.

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A_:,11_ :400 'A '. i',' :?es~i 7 i I FigureC.4 Sample ofGlobal Controls Sheet

FigureC.5 Sample table showing majorsub-assembly andplant overhead costs
C.6.1.2 ManufacturerDataSheet The data tables in this worksheet define most equipment-specific attributes of the CAC samples. For example, coil parameters are stored here for use by the coil model and the quantity, weight, and cost results from the coil model are returned and stored for use bythe BOM and Global Controlsworksheets. The headings in Figure C.6 are taken from our questionnaire. Further data tables capture individual parameters such as cost per hairpin tube, volume of enclosure, and other physical parameters. These parameters form the basis for several calculations. For example, in the Global Controls page the total enclosed volume ofa CAC unit drives the size ofthe manufacturing facility and the assembly line. Thisreflects the assumptionthat, all else equal, aplantdedicated to producing
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# -30q larger equipment requires more storage and assembly space than a plant dedicated to producing smallerequipment

FigureC.6 Sample DataFields from ManufacturingData Sheet
C.6.13 Purchased PartsSheet Three types of data are found on the Purchased Parts page: major purchased components unique to each model; minor, common purchased components used by every model; and, raw material costsforpartsthatarefabricated in-house. 

### Q A

Major Purchase d Components
Every major purchased part has its own data table, and every sample draws its information from a line item in its table. The exact model numbers for major purchased parts are entered here along with multiple price quotations and part weights. The quotations come from multiple sources and arediscountedas appropriate. Thesetablesdetermine atleast 45 percent oftotal cost Theweight
C-11 uniue o ech ode; mnor comonpuChae-o1net1sdbyeeymde;ad a

### EE-RM/STD-98-440- J3 

# C
and minimum cost for each line item is passed on the BOM page, which queries the results by unit number. Minor, Common PurchasedComponents These include items such as connectors, wire, fasteners, boardtransformers, and other smaller parts that OEMs are likely to purchase from outside suppliers. We gathered price quotations from multiple sources (suppliers, distributors, prior experience) in quantities that are typical for OEMs. We then passedthe lowestprice on to theBOM entry which queries the table unless we had reason tobelieve thatahigherpricewas more credible. RawMaterial Costs When parts are made in-house from materials such as pre-painted sheet metal, the main model estimates the cost ofthe part from the cost ofits raw material. We obtained raw material prices from common suppliers in volumes typical for OEM requirements. The BOM scales the materialprice for each fabricated part based on the calculated weight ofthe part and its price perunit ofweight We assume that OEMs fabricate most ofthese parts themselves. One general exception is plastic parts, which require a different set of skills and facilities than typical OEMs possess. The price of a plastic part is a function of the underlying value ofthe resin, and an assumed cost to manufacture the part (including the tool) with an applied gross margin. A purchased part premium applies to any fabricated part, including a plastic part, that we assume is manufactured elsewhere. The purchased parts premium is set at 150 percent overthe underlying material cost. Given thatfew parts meet this description, this simplification has only a slight impact on the overall cost estimate forthe equipment

*'-- I xtal -renr.,-: .,;, a'.. < sI. t4w~$b £. :,-_.:: e e : g
..

FigureC.7 Sample RawMaterialDataTables and PartPriceListfrom the Purchased PartsSheet

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### EE-RM/STD-98-440 - 309e C.6.1.4 Bill-of-Materials Sheet The Bill-of-Material (as illustrated in Figure C.1 and discussed in Section C.4 of this Appendix), serves as a structured assembly tree, summarizes fabrication and assembly tool data, and calculates production costs based on the price ofthe part or material and the labor and machinery required to fabricate or assemble it. The BOM sheet also adjusts many other costs in response to changes in physical parameters. For example, the model adjusts baseline sheet metal sizes to incorporate different enclosure sizes. The size ofthe fiberglass (FG) insulation is a function ofthe sheet metal it has to cover and the efficiency level of the unit (insulation is thicker at higher efficiencies). Many fastener quantities and labor costs are also a function ofthe sheet metal walls they are to secure. The result is that every unit cost estimate is unique, using the initial BOM as a startingpoint Labor, parts, materials, and depreciation costs are aggregated by sub-assembly and linked back to the GlobalControls page.
C.6.1.5 EquipmentDataSheet This page is alist ofthe installed costs for all the plant machinery involved in theproduction ofthe CAC samples. An implicit assumption is that the plant equipment required to produce lower efficiency samples is also able to produce higher efficiency samples without any modification. The equipment data shows installed equipment costs, depreciation life, whether equipment is dedicated, labor requirements per station, and consumables costs. The installed costs include price quotations forthe equipment plusmarkups to accountforinstallationlaborandauxiliary equipment

Eauiment Cost I$/Unitl Dgonriatin 12 20 15 1 StraidtDeamciation oer piece ofEouipment/Yea r Finance Costper pieceper year 4A5L Dedicated Equipnment? N N N N Pleone orMachi 1.f5 1 00 I,,.~,.,~,~e~ t~ see B-elow I a& ~i~0 I .1I FigureC.8 Sample fromEquipmentData Sheet C.6.2 Coil Model The coil model converts each coil's physical descriptors into coil costs by calculating the number of fins, hairpin bends, U-bends, take-offs, and coil ends. The model accounts for tube diameters, spacing, material choices and thickness, rifling, and other physical characteristics that affect coil cost. It relies on a process-based cost model that accounts for every fabrication and
C-13EE-RM/STD-98-440 -fo09L assembly step. We obtained fabrication equipment costs and processing times from equipment vendors and rawmaterialprices from vendorsbasedontheir pricing at thetime.

Al Fin ,-,11- Lacing

_ Bend Oven Tesi Tine Copper |

CoilCl StoSok

EBnds Ring Machine

CSoil Ends

End Stock FigureC.9 Flow Diagram forCoil Model

Our coil flow diagram (Figure C.9) represents a state-of-the-art coil manufacturing facility sized for high-volume production. While this coil line may not be representative ofall manufacturing facilities, we assumeit toberepresentative ingeneral. The coil and main cost models work together. The equipment data sheets in the mainmodel supplied the coil parameters, and the coil cost and weight results were returned to the main model. Anyupdate ineither modelis automatically reflected inthe othermodel. Because our computational power was limited, we severed the links between the main model and the coil model during aMonte Carlo analysis. However, the effects ofthe Monte Carlo analysis on coil results were easily incorporated within the main model. For example, ifwhen labor costs varied in the main model, the labor costs components of a coil would simply vary in proportion. Thus, a large number ofMonte Carlotrials (2,500 to 3,000) couldbe accommodated over the span ofafewhours. Figure C.10 is a section ofa row header for a indoor coil unit showing fin and U-bend parameters. Weights andquantities are senttotheManufacturing Data Sheet inthemainmodel.

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Final Mass ofSingle Fin (Ib) #of Fins per Unit Annual Fin Production (K) Evap. Coil Fin Material Evap. Fin Material Scrap (%) Evap. Coil Fin Length (in) Evap. Coil Fin Width (in) Evap. Coil Fin Thckness (in)

Evap. Coil Density (fins/in) #of Large U-Bend per Unit Massper U-Bend (lb) #of U-Bends per Unit Annual Production of U-Bends (K)
FigureC.10 Coil model outputfields
The manufacturing costs for coils are also captured in a table. Figure C.11 illustrates the header ofthe table which is linked back to the Manufacturer Data Sheet. Some ofthese costs are direct costs, such as material costs used by the BOM Sheet, while others are overhead costs referenced bythe Global Controlspage. 

# Condenser Assy 1 2 3 4 5 6 7 8 9 Low Level Labor I Material Prices Direct Indirect Coil Ends Tube Fin U-Bend FigureC.11 Coil manufacturingcosts calculated inthe coil model

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