Capacity Planning Production Planning and Control.
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Transcript of Capacity Planning Production Planning and Control.
Capacity Planning Capacity Planning
Production Planning and Control
Capacity
The throughput, or the number of units a facility can hold, receive, store, or produce in a period of time
Determines fixed costs Determines if demand will be satisfied Used to plan overtime horizon
Modify capacity Use capacity
Planning Over a Time Horizon
Intermediate-range planning
Subcontract Add personnelAdd equipment Build or use inventory Add shifts
Short-range planning
Schedule jobsSchedule personnel Allocate machinery*
Long-range planning
Add facilitiesAdd long lead time equipment *
Design and Effective Capacity
Design capacity is the maximum theoretical output of a systemNormally expressed as a rate
Effective capacity is the capacity a firm expects to achieve given current operating constraintsOften lower than design capacity
Utilization and Efficiency
Utilization is the percent of design capacity achieved
Efficiency is the percent of effective capacity achieved
Utilization = Actual Output/Design Capacity
Efficiency = Actual Output/Effective Capacity
Bakery Example
Actual production last week = 148,000 rollsEffective capacity = 175,000 rollsDesign capacity = 1,200 rolls per hourBakery operates 7 days/week, 8 hours, 3 shifts
Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls
Bakery Example
Actual production last week = 148,000 rollsEffective capacity = 175,000 rollsDesign capacity = 1,200 rolls per hourBakery operates 7 days/week, 8 hours, 3 shifts
Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls
Utilization = 148,000/201,600 = 73.4%
Bakery Example
Actual production last week = 148,000 rollsEffective capacity = 175,000 rollsDesign capacity = 1,200 rolls per hourBakery operates 7 days/week, 8 hours, 3 shifts
Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls
Utilization = 148,000/201,600 = 73.4%
Efficiency = 148,000/175,000 = 84.6%
Bakery Example
Actual production last week = 148,000 rollsEffective capacity = 175,000 rollsDesign capacity = 1,200 rolls per hourBakery operates 7 days/week, 8 hours, 3 shifts
Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls
Utilization = 148,000/201,600 = 73.4%
Efficiency = 148,000/175,000 = 84.6%
Bakery Example
Actual production last week = 148,000 rollsEffective capacity = 175,000 rollsDesign capacity = 1,200 rolls per hourBakery operates 7 days/week, 8 hours, 3 shiftsEfficiency = 84.6%Efficiency of new line = 75%
Expected Output = (Effective Capacity)(Efficiency)
= (175,000)(.75) = 131,250 rolls
Capacity and Strategy
Capacity decisions impact all 10 decisions of operations management as well as other functional areas of the organization
Capacity decisions must be integrated into the organization’s mission and strategy
Managing Demand
Demand exceeds capacity Limit demand by raising prices, scheduling
longer lead time Long term solution is to increase capacity
Capacity exceeds demand Stimulate market Product changes
Adjusting to seasonal demands Produce products with complimentary
demand patterns
Economies and Diseconomies of Scale
Economies of scale
Diseconomies of scale
25 - Room Roadside Motel 50 - Room
Roadside Motel
75 - Room Roadside Motel
Number of Rooms25 50 75
Aver
age
unit
cost
(dol
lars
per
room
per
nig
ht)
Capacity Considerations
Forecast demand accurately Understanding the technology and
capacity increments Find the optimal operating level
(volume) Build for change
Tactics for Matching Capacity to Demand
1. Making staffing changes
2. Adjusting equipment and processes Purchasing additional machinery Selling or leasing out existing equipment
3. Improving methods to increase throughput
4. Redesigning the product to facilitate more throughput
Complementary Demand Patterns
4,000 –
3,000 –
2,000 –
1,000 –
J F M A M J J A S O N D J F M A M J J A S O N D J
Sale
s in
uni
ts
Time (months)
By combining both, the
variation is reduced
Snowmobile sales
Jet ski sales
Approaches to Capacity Expansion
(a) Leading demand with incremental expansion
Dem
and
Expected demand
New capacity
(b) Leading demand with one-step expansion
Dem
and
New capacity
Expected demand
(d) Attempts to have an average capacity with incremental expansion
Dem
and
New capacity Expected
demand
(c) Capacity lags demand with incremental expansion
Dem
and
New capacity
Expected demand
Break-Even Analysis
Technique for evaluating process and equipment alternatives
Objective is to find the point in dollars and units at which cost equals revenue
Requires estimation of fixed costs, variable costs, and revenue
Break-Even Analysis
Fixed costs are costs that continue even if no units are producedDepreciation, taxes, debt, mortgage
payments
Variable costs are costs that vary with the volume of units producedLabor, materials, portion of utilitiesContribution is the difference between
selling price and variable cost
Break-Even Analysis
Costs and revenue are linear functionsGenerally not the case in the real
world
We actually know these costsVery difficult to accomplish
There is no time value of money
Assumptions
Profit corridor
Loss
corridor
Break-Even AnalysisTotal revenue line
Total cost line
Variable cost
Fixed cost
Break-even pointTotal cost = Total revenue
–
900 –
800 –
700 –
600 –
500 –
400 –
300 –
200 –
100 –
–| | | | | | | | | | | |
0 100 200 300 400 500 600 700 800 900 10001100
Cost
in d
olla
rs
Volume (units per period)
Break-Even AnalysisBEPx =Break-even point in unitsBEP$ =Break-even point in dollarsP =Price per unit (after all discounts)
x = Number of units producedTR = Total revenue = PxF = Fixed costsV =Variable costsTC = Total costs = F + Vx
TR = TCor
Px = F + Vx
Break-even point occurs when
BEPx =F
P - V
Break-Even AnalysisBEPx =Break-even point in unitsBEP$ =Break-even point in dollarsP = Price per unit (after all discounts)
x = Number of units producedTR = Total revenue = PxF = Fixed costsV = Variable costsTC = Total costs = F + Vx
BEP$ = BEPx P
= P
=
=
F(P - V)/P
FP - V
F1 - V/P
Profit = TR - TC= Px - (F + Vx)= Px - F - Vx= (P - V)x - F
Break-Even Example
Fixed costs = $10,000 Material = $.75/unitDirect labor = $1.50/unit Selling price = $4.00 per unit
BEP$ = =F1 - (V/P)
$10,0001 - [(1.50 + .75)/(4.00)]
Break-Even Example
Fixed costs = $10,000 Material = $.75/unitDirect labor = $1.50/unit Selling price = $4.00 per unit
BEP$ = =F1 - (V/P)
$10,0001 - [(1.50 + .75)/(4.00)]
= = $22,857.14$10,000.4375
BEPx = = = 5,714FP - V
$10,0004.00 - (1.50 + .75)
Break-Even Example
50,000 –
40,000 –
30,000 –
20,000 –
10,000 –
–| | | | | |
0 2,000 4,000 6,000 8,000 10,000
Dol
lars
Units
Fixed costs
Total costs
Revenue
Break-even point
Break-Even Example
BEP$ =F
∑ 1 - x (Wi)Vi
Pi
Multiproduct Case
where V = variable cost per unitP = price per unitF = fixed costs
W = percent each product is of total dollar salesi = each product
Multiproduct Example
Annual ForecastedItem Price Cost Sales UnitsSandwich $2.95 $1.25 7,000Soft drink .80 .30 7,000Baked potato 1.55 .47 5,000Tea .75 .25 5,000Salad bar 2.85 1.00 3,000
Fixed costs = $3,500 per month
Multiproduct Example
Annual ForecastedItem Price Cost Sales UnitsSandwich $2.95 $1.25 7,000Soft drink .80 .30 7,000Baked potato 1.55 .47 5,000Tea .75 .25 5,000Salad bar 2.85 1.00 3,000
Sandwich $2.95 $1.25 .42 .58 $20,650 .446 .259Soft drink .80 .30 .38 .62 5,600 .121 .075Baked 1.55 .47 .30 .70 7,750 .167 .117 potatoTea .75 .25 .33 .67 3,750 .081 .054Salad bar 2.85 1.00 .35 .65 8,550 .185 .120
$46,300 1.000 .625
Annual WeightedSelling Variable Forecasted % of Contribution
Item (i) Price (P) Cost (V) (V/P) 1 - (V/P) Sales $ Sales (col 5 x col 7)
Fixed costs = $3,500 per month
Multiproduct Example
Annual ForecastedItem Price Cost Sales UnitsSandwich $2.95 $1.25 7,000Soft drink .80 .30 7,000Baked potato 1.55 .47 5,000Tea .75 .25 5,000Salad bar 2.85 1.00 3,000
Fixed costs = $3,500 per month
Sandwich $2.95 $1.25 .42 .58 $20,650 .446 .259Soft drink .80 .30 .38 .62 5,600 .121 .075Baked 1.55 .47 .30 .70 7,750 .167 .117 potatoTea .75 .25 .33 .67 3,750 .081 .054Salad bar 2.85 1.00 .35 .65 8,550 .185 .120
$46,300 1.000 .625
Annual WeightedSelling Variable Forecasted % of Contribution
Item (i) Price (P) Cost (V) (V/P) 1 - (V/P) Sales $ Sales (col 5 x col 7)
BEP$ =F
∑ 1 - x (Wi)Vi
Pi
= = $67,200$3,500 x 12.625
Daily sales = = $215.38$67,200
312 days
.446 x $215.38$2.95
= 32.6 33sandwiches
per day
Decision Trees and Capacity Decision
-$14,000
$13,000
$18,000
-$90,000Market unfavorable (.6)
Market favorable (.4)$100,000
Large plant
Market favorable (.4)
Market unfavorable (.6)
$60,000
-$10,000
Medium plant
Market favorable (.4)
Market unfavorable (.6)
$40,000
-$5,000
Small plant
$0
Do nothing
Strategy-Driven Investment
Operations may be responsible for return-on-investment (ROI)
Analyzing capacity alternatives should include capital investment, variable cost, cash flows, and net present value
Net Present Value (NPV)
where F = future valueP = present valuei = interest rate
N = number of years
P =F
(1 + i)N
NPV Using Factors
P = = FXF(1 + i)N
where X = a factor from Table S7.1 defined as = 1/(1 + i)N and F = future value
Year 5% 6% 7% … 10%
1 .952 .943 .935 .9092 .907 .890 .873 .8263 .864 .840 .816 .7514 .823 .792 .763 .6835 .784 .747 .713 .621
Portion of Table S7.1
Present Value of an Annuity
An annuity is an investment which generates uniform equal payments
S = RX
where X = factor from Table S7.2S = present value of a series of uniform annual receiptsR = receipts that are received every year of the life of the investment
Present Value of an Annuity
Portion of Table S7.2
Year 5% 6% 7% … 10%
1 .952 .943 .935 .9092 1.859 1.833 1.808 1.7363 2.723 2.676 2.624 2.4874 4.329 3.465 3.387 3.1705 5.076 4.212 4.100 3.791
Questions?