Effective, Strategic Planning Using Cost Modeling written by:
John E. Lenz, CMS Research, Inc.
Ray Neitzel, Mid-States Aluminum
Factory modeling (which includes capacity planning, queuing models, and computer simulation) has provided decision support to a variety of factory design and operating questions. Some of these include: "How many machines are needed?", "How many operators are needed?", "How should the operators be assigned to the stations?", "What is a minimum work-in-process level?", "Where and what size of queues are needed?", "How many vehicles are needed for transportation?"
The solution to each of these questions implies an absolute answer that consists of one number--or set of numbers. In order to reach the observation of this number, factory performance measures are used.
The factory model establishes a relationship between each solution and a set of factory performance measures. These performance measures include: production rate, station utilization, inventory levels, queue sizes, labor utilization, and flow time. Some criteria is established to rank these measures and results are identified from the configuration which yields the "best" measures.
For example, a model is used to determine the appropriate inventory level and queue size for a production cell. The process and layout data are entered into the model and the model is evaluated at different inventory levels. The inventory that produces the highest production rate is identified as the solution. This evaluation is suitable for optimization of a few production variables, but has limited applications when comparing strategic alternatives.
Strategic alternatives affect all production variables and it is not possible to identify one single performance measure in order to rank these alternatives. For example, consider the decision to determine the degree of automation for a machining cell. One alternative is a fully-automated, material handling system with pallet delivery monitored by supervisory computer control and the other is one where operators load/unload all of the machines. Both alternatives use the same process and number of machines. When both of these alternatives are modeled, the model results indicate the same production rates and same machine efficiency. The manual alternative requires more operators and the automated cell requires automated handling, computer control, and possibly more pallets. Traditional performance measures alone can not indicate which of these is the best alternative.
Table 1 contains a list of traditional performance measures describing the limitations in providing a measure of the efficiency of a production system.

TABLE 1
TRADITIONAL PERFORMANCE MEASURES

PRODUCTION RATE: production mix influences results

STATION UTILIZATION: difficult to interpret when bottleneck moves during operation.

INVENTORY LEVEL: more does not always mean higher efficiency

LABOR UTILIZATION: useful only in labor-limited production

QUEUE SIZES: identifies an imbalance in the process

FLOW TIME: overall system measure--but little detail
From these limitations, no single performance measure provides a means to compare one production alternative against another alternative. Conditional interpretations are needed to weigh one measure's importance over another. For example, when a machine fails, it might become the bottleneck for a period of time. This, in turn, can affect the production mix which will change the observed production rates. To make an accurate interpretation of the efficiency of the production system, both station's utilization and production rate results would need to be taken into consideration. This type of performance evaluation is much more complicated than comparing one production rate against another.
A method for comparing one production system configuration to another is needed for these dynamic situations. Also, a method for comparing alternatives which produces the same values for performance measures is needed, such as in the case of comparing alternatives--in such situations--is the purpose of cost modeling.
TABLE 2
COST AS A PERFORMANCE MEASURE

TRADITIONAL MEASURES
1.
Component Oriented
2.
Optimize Operation

COST MEASURE
1.
System Oriented
2.
Compare Strategic Alternatives & Optimize the Operation
COST MODELING
Cost Modeling is an extension of factory modeling. When factory modeling provides results for the traditional performance measures, cost modeling is oriented towards measuring the entire production

system. Table 2 contains a list of contracts between cost as a performance measure and traditional measures. Not only does cost provide a system of measure, but it also provides a means to compare strategic alternatives such as degree of automation.
TABLE 3
FACTORY MODEL + COST EQUATION = COST MODELING PERFORMANCE MEASURES
Cost modeling utilizes the traditional performance measures which are produced by factory models and a cost equation as shown above. Cost modeling can be viewed as a single measure which uses relative cost as a weighty factor for each performance measure. It does this by applying cost to the components of the production system through a cost equation.
Cost Equation . The cost equation assigns cost all of the factory performance measures. In the application of using factory modeling to optimize one production variable, only one or two performance measures are used to compare alternatives. However, with the use of a cost equation, all performance measures are included in the equation. The influence or importance of each component is measured by its actual cost. These costs are distributed to the production system based on its activity.
The integration of factory performance into a single measure is done with the cost equation. The cost equation (see Table 4) consists of eight components.
TABLE 4
COST EQUATION = STATION COST
+ LABOR COST
+ SETUP COST
+ INVENTORY COST
+ AUTOMATION COST
+ CAPACITY COST
+ MATERIAL COST
+ OVERHEAD COST
The cost formula consists of eight (8) major components. These include: a) station cost; b) labor cost; c) setup cost; d) inventory cost; e) automation cost; f) capacity cost, g) material cost; and h) overhead or indirect cost.
The Station cost includes the capital expense of the machining and the consumable expenses of electricity, tooling, fluids, etc.
The Labor cost includes the cost of labor and is based upon a rate applied to actual use.

Setup cost includes the cost due to lost efficiency during product change over and is associated with a production schedule.
Inventory costs include the carrying cost of work-in-process inventory and includes the post-cell strategic inventory.
Automation cost includes the cost of the material handling system and automation including all computer control which is distributed to actual use.
Capacity cost includes the costs associated with early and late delivery of the parts and not setting the capacity to match production requirements.
Material cost includes the actual cost of the material.
Overhead cost is the cost of indirect and management support such as supervisory, engineering, maintenance, insurance, etc.
The performance variables are used in the cost equation with the actual cost of each component providing the relative weight (importance) as a means for evaluation. A wide variety of alternatives can be modeled, and using the cost equation, they can be compared to one another.
Case Study-An Application of Cost Modeling
At Mercury Marine cost modeling was applied to determine the best practice for the machining of gearcases. Several processes were developed and a palletized conveyor system using sequential processing was selected for further review. Sequential processing would require a component to go into several machines before it was completed. The system was simulated using the MAST Simulation Software. The simulation determined the number of operators required, the equipment needed at a predetermined volume, utilization for both machines and operators needed in process inventory, and downtime. After reviewing the data from the simulation, we determined that the sequential processing of a part in the low-inventory, palletized system resulted in poor utilization of the equipment. Also, the needed equipment increased to compensate for the poor utilization. When the costs for the system were compared to the savings, the sequential process was unacceptable.
The simulation showed us that sequential processing on a conveyor line was not practical.
However, non-sequential processing may be acceptable. A process to machine a complete component on one CNC was developed and simulated--and the results were favorable.
Before, when we would justify projects, if the payback met the requirements of the company, the project was a go. But the assignment of this team was to determine the best process to machine a gearcase

that exceeds six sigma quality requirements at the lowest possible cost. So our job was not complete until all the viable processes were reviewed.
To do this in an objective, unbiased manner, we used the Cost Model. The Cost Model is a method to cost a component as it goes through a computer-simulated, manufacturing process. Wherever the component comes in contact with a manufacturing cost, the appropriate amount of cost is allocated to that component. An example would be the loading of a component into a fixture. The labor and fixture cost to load that component would be attached to it. This is similar to actual costing, process costing, or activitybased costing, but it does have several important differences that we will discuss later.
The team determined that the Cost Model should address three issues:
1.
Should the line be an FMS, utilized automated material handling system or should it be a cell of CNC equipment where the machines would be manually loaded and unloaded?
2.
What would be the cost effect of three shifts over two shifts?
3.
What is the cost of special processes in the line?
To address these issues the team determined the cost of our current process. We used these costs as a benchmark for comparing alternate processes.
The next step would be building the costs of the process under review. For this step, we used a spreadsheet that would accommodate frequent changes. In this study, we broke down our costs into three categories: labor cost, station cost, and overhead cost.
The simulation determined what our equipment requirements were and the team member went to the machine suppliers for estimates. These estimates were loaded into the spreadsheet. (Table 7). The number of years we use for depreciation were added and the per year depreciation cost per machine was calculated. Depreciation is a station cost so it is completely allocated to the station cost. See Table 7 on the following page.

OPERATION DESCRIPTION
Operation Specific Capital
Load Line/Machine
Transporter
Work Station
Transporter Track
Control System
Load Areas
Machine Gearcase
CNC Machines
Pallets
Fixtures
Tooling Expense
Tooling
Coolant System
Unload Line/Machine
Tranporter
Work Station
Transporter Track
Control System
Load Areas
Gage Gearcase
CMM
Gage Stations
Special Drill
Special Drill Machine
Leaktest Gearcase
Leaktest Stations
Wash Gearcase
Washers
COST/
MACHINE
$30,000.00
$30,000.00
$30,000.00
$80,000.00
$37,500.00
$538,462
$5,000.00
$30,000.00
$8,200.00
$32,800.00
$184,000.00
$30,000.00
$30,000.00
$30,000.00
$80,000.00
$37,500.00
$0
$0
$83,333
$25,000.00
$60,000.00
Subtotal
CAPITAL
REQUIRED
$0
$0
$83,333
$25,000.00
$100,000.00
$2,994,487.00
$455,789
$8,200.00
$32,800.00
$184,000
$30,000.00
$30,000.00
$30,000.00
$80,000.00
$37,500.00
$30,000.00
$30,000.00
$30,000.00
$80,000.00
$37,500.00
$1,616,385
$75,000.00
1
1
1
1
1
15
1
1
1
# OF
MACHINES
REQUIRED
1
1
1
1
1
3
15
1
2
0
0
1
Op. Total
Op. Total
Op. Total
Opn Total
Opn Total
Opn Total
Opn Total
# OF YRS. DEP DEP/YEAR
10
10
10
7
10
3
1
3
10
10
7
10
10
10
7
10
10
10
7
5
10
$3,000.00
$3,000.00
$3,000.00
$11,428.60
$8,750.00
$230,769.20
$7,500.00
$141,823.10
$8,200.00
$10,933.30
$18,400.00
$3,000.00
$3,000.00
$3,000.00
$11,425.60
$3,750.00
$0.00
$0.00
$8,333.30
$24,179
$0
$2,500.00
$10,000
$8,333
$2,500
$10,000
$496,916
$427,726
$24,179

Several of the implementation costs would stay the same or were not station or labor specific so we treated them as overhead costs. See Table 8.
TABLE 8
Capital Costs Allocated to the Cost Center
Will not be machine specific, but will be included in fixed O/H
Staging Conveyors
Conveyors
Turnkey
$25,000
$152,000
1
1
$25,000
$152,000
Installation $75,000
Subtotal
1 $75,000
$252,000
Total $3,246.467
10
10
10
$2,500
$15,200
$7,500
$25,200
The most interesting part of the allocation process was the burden allocation. (See Table 9 on the following page). The team listed every remaining cost associated with the manufacturing process, the quantity of that cost required, the percent allocated to the machine station, and the percent allocated to labor. Under basic machining, the team determined that a manufacturing engineer would spend half of his/her time in this machining process of which 75% of the time would be on machines and 25% of the time spent with labor. Every cost issue was addressed. The team spent approximately three hours in the allocating process.

BURDEN ALLOCATIONS
Salary Quantity Allocated % Mach Alloc $ Mach Alloc % Labor Alloc $ Labor Alloc
Basic Machining
Mfg. Engineering
Quality Engineering
$35,000
$35,000
0.5
0.25
$17,500
$8,750
75%
75%
$13,125
$6,563
25%
25%
$4,375
$2,188
Foreman/Tech
Area Manager
Tech Services
Industrial Engineering
Quality
Layout Inspection
$25,000
$40,000
$30,000
$32,500
Cost
$0
0.5
0.1
0.2
0.1
$12,500
$4,000
$6,000
$3,250
Subtotal $52,000
25%
15%
95%
20%
$3,125
$600
$5,700
$650
$28,763
75%
85%
5%
80%
$9,375
$3,400
$300
$2,600
$22,238
Quantity Allocated % Mach Alloc $Mach Alloc % Labor Alloc $ Labor Alloc
1
Subtotal
$0
$0
90% $0
$0
10% $0
$0
Maintenance
Maintenance
Tooling
Tool/Gage Crib
Cutter Grinder/Pre
Tool Room
Tool Design
Safety House Keeping
Asset Utilization
Material Handling 611
Material Handling 614
Material Handling 616
Material Handling 634
General Mfg.
Ind. Relations
$100,000
$1,500
$1,500
$1,500
$3,500
$100,000
$2,500
$3,200
$3,200
$3,500
$45,000
$2,600
1 $100,000
Subtotal $100,000
1
1
$1,500
$1,500
1
1
Subtotal
$1,500
$3,500
$6,000
1 $100,000
Subtotal $100,.000
1
1
1
$2,500
$3,200
$3,200
1
1
$3,500
$45,000
1 $2,600
Subtotal $60,000
90%
90%
90%
90%
80%
80%
100%
100%
100%
100%
5%
0%
$90,000
$90,000
$1,350
$1,350
$1,050
$2,800
$6,850
$80,000
$80,000
$2,500
$3,200
$3,200
$3,500
$2,250
$0
$14,650
10%
20%
20%
0%
0%
0%
0%
95%
100%
10%
10%
10%
$10,000
$10,000
$150
$150
$150
$700
$1,150
$20,000
$20,000
$0
$0
$0
$0
$42,750
$2,600
$45,350
Direct Expense
(Varies With Volume)
Perishable Tooling
Shop Supplies
Coolant
Defective Material
Maintenance
Misc. (Training)
Yearly Allocation
$5,000
$2,300
$2,750
$1,550
$62,300
$30,000
1
1
1
1
1
$6,000
$2,300
$2,750
$1,550
$62,300
1 $30,000
Subtotal $104,900
Total $424,900
90%
20%
100%
50%
80%
$6,400
$460
$2,750
$775
$49,840
50% $15,000
$74,225
Machine $295,488
10%
80%
0%
50%
20%
50%
Labor
$600
$1,840
$0
$775
$12,460
$15,000
$30,675
$129,413

With the labor/machine allocation process complete, we could now determine what our labor costs are.
The spreadsheet totaled up the labor allocation per year and the simulation determined how many operators were required. With these two numbers, we calculated the hourly allocations and added them to the wage rate plus fringe benefits. (See Table 10).
TABLE 10
Alloc Per Hour No. of Oprs.
1
Direct Labor/Hr.
Wages
Total
Fringes
Allocations
$12.00
$6.62
$32.35
$50.97
No. of 8 Hr. Shift Days/Year
2 250
Total Hr/Yr.
4000
$ Per Hour
$32.35
Fixed Overhead $0
And the last step was that the team took the machine allocation and applied them to the individual stations.
(See Table 11 on the following page). Under basic machining the team determined the Manufacturing Engineer would spend 10% of his/her time at the load/unload station, 60% at the CNC’s, 10% at the washers, 10% at the gage stations, 5% at the leaktest, and 5% at the special machining stations. This part of the process took less than an hour.

BURDEN ALLOCATIONS
BASIC MACHINING
Mfg. Engineering
Quality Engineering
Foreman/Tech
Area Manager
Tech Services
Industrial Engineering
QUALITY
Layout Inspection
MAINTENANCE
Maintenance
TOOLING
Tool/Gage Crib
Cutter Grinder/Pre
Tool Room
Tool Design
SAFETY HOUSE KEEP
Buildings & Grounds
ASSET UTILIZATION
Material Handling 611
Material Handling 614
Material Handling 616
Material Handling 634
General Mfg.
Ind. Relations
DIRECT EXPENSE
(Varies With Volume)
Perishable Tooling
Shop Supplies
Coolant
Defective Material
Maintenance
Misc. (Training)
Depreciation
(Manual Dep. Schedule)
COST LOAD/UNLOAD
% $
$0 10% $0
$0 5% $0
$0 20% $0
$0 20% $0
$0 20% $0
$0 50% $0
$0 10% $0
$0 20% $0
CNC
% $
WASH
% $
GAGE LEAKTEST
% $ % $
60% $0 10% $0 10% $0 5% $0
55% $0 5% $0 30% $0 3% $0
50% $0 10% $0 10% $0 5% $0
50% $0 5% $0 10% $0 3% $0
50% $0 10% $0 10% $0 5% $0
20% $0 10% $0 10% $0 5% $0
50% $0 10% $0 10% $0 5% $0
50% $0 5% $0 5% $0 5% $0
SPECIAL TOTAL %
% $ % $
5% $0 100% $0
3% $0 100% $0
5% $0 100% $0
3% $0 100% $0
5% $0 100% $0
5% $0 100% $0
5% $0 100% $0
15% $0 100% $0
$0 10% $0
$0 10% $0
$0 10% $0
$0 10% $0
$0
$0 20% $0
$0 17% $0
$0 17% $0
$0 17% $0
$0 17% $0
$0 17% $0
$0 17% $0
$0 20% $0
$0 20% $0
60% $0 5% $0 5% $0 5% $0
60% $0 5% $0 5% $0 5% $0
60% $0 5% $0 5% $0 5% $0
60% $0 5% $0 5% $0 5% $0
50% $0 10% $0 10% $0 5% $0
17% $0 17% $0 17% $0 17% $0
17% $0
17% $0
17% $0
17% $0
17% $0
17% $0
17% $0
17% $0
17% $0
17% $0
17% $0
17% $0
17% $0
17% $0
17% $0 17% $0 17% $0
17% $0 17% $0 17% $0
60% $0 0% $0
50% $0 10% $0
0% $0
10% $0
0% $0
5% $0
15% $0
15% $0
15% $0
15% $0
17% $0
17% $0
17% $0
100% $0
100% $0
100% $0
100% $0
5% $0 100% $0
17% $0 100% $0
100% $0
100% $0
100% $0
17% $0 100% $0
17% $0 100% $0
20% $0 100% $0
5% $0 100% $0
$0 20% $0
$0 20% $0
60% $0 0% $0
60% $0 5% $0
0% $0 0% $0
0% $0 0% $0
20% $0 100% $0
20% $0 100% $0
$0 20% $0
$0 20% $0
$48,357
$48,357
50% $0 10% $0
50% $0 0% $0
$427,726
$427,726
$10,000
$10,000
10% $0 5% $0
10% $0 5% $0
$0
$0
$2,500
$2,500
10% $0 100% $0
5% $0 100% $0
$8,333 $496,916
$8,333 Total Machine Allocation
Now that we have the labor costs, overhead costs, and stations costs we loaded them into the MAST simulation and it calculated our per piece cost. The new process results in a cost savings, but as we mentioned earlier, the team’s assignment was to identify the best manufacturing practice. So we addressed the three issues mentioned earlier.

1.
Should the line be an FMS or should it be a cell of CNC equipment that would be manually loaded and unloaded?
In the first simulation we simulated a manual line. The next simulation was an automated line. With the second simulation, all of the costs were revisited with the automated process in mind. By now we were veterans at the allocation process and it went quickly. As a result, the manual line was more cost effective that the FMS. However, when the processes were modeled at a higher volume, the FMS was more cost effective.
The team’s suggestion was to layout the manual cell so that it can be automated when higher volumes were achieved.
2.
What would be the cost effect of three shifts over two shifts?
When the team resimulated and reallocated for three shifts, we were able to save over two million dollars in equipment. The savings in capital and the increase in machine utilization was more than the increase in supervisions required for the third shift.
The team’s suggestion was to operate with three shifts, while maintaining a strict preventative maintenance schedule.
3.
What is the cost of a special process in the line?
Currently, we use the standard cost system. With the standard cost system the cost of a special process is spread across the entire cost center and then allocated to the component as a burden percentage attached to direct labor. This dilutes the standard cost of the special process and the component cost is often understated. The Cost Model allocated directly to the special process. As a result, the special drill operation costed five times more than the standard costs. It is now justifiable to use engineering resources to eliminate the need for the special processing.
Our goal is to eliminate the special processing before capital is spent.
CONCLUSION
When the best practice was presented to upper management, the scope of the project was increased and even more alternatives were now available. With the Cost Model we are now evaluating the various alternatives with current and future costs. We can determine how well we utilize our resources with the simulation and the team better understands what drives costs.
That is where the differences are between Cost Modeling and actual costing, process costing, or activity-based costing. Decisions are based on future costs versus historical costs. You can determine how well a process will utilize your resources--not how well it utilized them. It also helps people understand how a decision drives the cost of a part.