s7 - 1© 2011 pearson education, inc. publishing as prentice hall process strategies ( process,...
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S7 - 1© 2011 Pearson Education, Inc. publishing as Prentice Hall
Process StrategiesProcess Strategies( process, repetitive, product)( process, repetitive, product)
The objective of the process strategy is to build a The objective of the process strategy is to build a production process that has capacity to meetproduction process that has capacity to meet
•customer requirements customer requirements (quality & quantity) (quality & quantity)
•product specifications product specifications (quality & cost)(quality & cost)
•within finance within finance (fixed costs = capital invested)(fixed costs = capital invested)
•other managerial constraints other managerial constraints (flexibility)(flexibility)
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Process Strategy & CapacityProcess Strategy & CapacityProcess strategy chosen has to
•Meet consumer demand (quality & quantity expectations)
– low/medium/high ?
– constant or changing ?
– predictable or unpredictable ?
•Meet Business requirements (average cost per unit)
– efficient use of existing capacity
– ability to change output (up or down) if needed
© 2011 Pearson Education, Inc. publishing as Prentice Hall
S7 - 3© 2011 Pearson Education, Inc. publishing as Prentice Hall
CapacityCapacity The number of units a facility can produce, hold,
receive, or store, in a period of time
Has a big effect on fixed costs (& therefore break even )
Determines if demand will be satisfied
Three time horizons
Long (>1yr)
Medium (3 -18 months)
Short (<3 months)
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Planning Over a Time HorizonPlanning Over a Time Horizon(relates to forecasting accuracy)(relates to forecasting accuracy)
Figure S7.1
To increase capacity To use excess capacity
Medium(3-18 month)
Subcontract Add personnelAdd equipment Build or use inventory Add shifts
Short(< 3 month)
Schedule jobsSchedule personnel Allocate machinery*
Long (> 12 month)
Add facilitiesAdd long lead time equipment *
* Difficult to adjust capacity as limited options exist
Options for Adjusting Capacity
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Capacity DefinitionsCapacity Definitions
Design capacity (measured as utilisation)
is the maximum theoretical output of a system
normally expressed as a rate (output/time)
Effective capacity (measured as efficiency)
is the actual output expects to achieve given current operating constraints (e.g. downtime for maintenance)
Often lower than design capacity
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Utilization and EfficiencyUtilization and Efficiency
Utilization is the percent of design capacity Utilization is the percent of design capacity achievedachieved
Efficiency is the percent of effective capacity Efficiency is the percent of effective capacity achievedachieved
Utilization = Actual output/Design capacity (as %)
Efficiency = Actual output/Effective capacity (as %)
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Bakery ExampleBakery Example(design capacity & utilisation)
Actual production last week = 148,000 rollsEffective capacity = 175,000 rollsDesign capacity = 1,200 rolls per hourBakery operates 7 days/week, 3 - 8 hour shifts
Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls
S7 - 8© 2011 Pearson Education, Inc. publishing as Prentice Hall
Bakery ExampleBakery Example(design capacity & utilisation)
Actual production last week = 148,000 rollsEffective capacity = 175,000 rollsDesign capacity = 1,200 rolls per hourBakery operates 7 days/week, 3 - 8 hour shifts
Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls
S7 - 9© 2011 Pearson Education, Inc. publishing as Prentice Hall
Bakery ExampleBakery Example(design capacity & utilisation)
Actual production last week = 148,000 rollsEffective capacity = 175,000 rollsDesign capacity = 1,200 rolls per hourBakery operates 7 days/week, 3 - 8 hour shifts
Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls
Utilization = 148,000/201,600 = 73.4%
S7 - 10© 2011 Pearson Education, Inc. publishing as Prentice Hall
Bakery ExampleBakery Example(design capacity & utilisation)
Actual production last week = 148,000 rollsEffective capacity = 175,000 rollsDesign capacity = 1,200 rolls per hourBakery operates 7 days/week, 3 - 8 hour shifts
Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls
Utilization = 148,000/201,600 = 73.4%
S7 - 11© 2011 Pearson Education, Inc. publishing as Prentice Hall
Bakery ExampleBakery Example(effective capacity & efficiency)
Actual production last week = 148,000 rollsEffective capacity = 175,000 rollsDesign capacity = 1,200 rolls per hourBakery operates 7 days/week, 3 - 8 hour 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%
S7 - 12© 2011 Pearson Education, Inc. publishing as Prentice Hall
Bakery ExampleBakery Example(effective capacity & efficiency)
Actual production last week = 148,000 rollsEffective capacity = 175,000 rollsDesign capacity = 1,200 rolls per hourBakery operates 7 days/week, 3 - 8 hour 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%
S7 - 13© 2011 Pearson Education, Inc. publishing as Prentice Hall
Bakery ExampleBakery Example(effective capacity & efficiency)
Actual production last week = 148,000 rollsEffective capacity = 175,000 rollsDesign capacity = 1,200 rolls per hourBakery operates 7 days/week, 3 - 8 hour shiftsEfficiency = 84.6%Efficiency of new line = 75%
Expected Output = (Effective Capacity)(Efficiency)
= (175,000)(.75) = 131,250 rolls
S7 - 14© 2011 Pearson Education, Inc. publishing as Prentice Hall
Bakery ExampleBakery Example(effective capacity & efficiency)
Actual production last week = 148,000 rollsEffective capacity = 175,000 rollsDesign capacity = 1,200 rolls per hourBakery operates 7 days/week, 3 - 8 hour shiftsEfficiency = 84.6%Efficiency of new line = 75%
Expected Output = (Effective Capacity)(Efficiency)
= (175,000)(.75) = 131,250 rolls
S7 - 15© 2011 Pearson Education, Inc. publishing as Prentice Hall
S7 - 16© 2011 Pearson Education, Inc. publishing as Prentice Hall
Capacity and StrategyCapacity 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
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Capacity ConsiderationsCapacity Considerations
1. Forecast demand accurately(marketing department do this)
2. Understand the technology and capacity increments
3. Find the optimum operating level (volume)
4. Build for change(flexibility is desirable)
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Economies and Economies and Diseconomies of ScaleDiseconomies 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
Av
era
ge
un
it c
os
t(d
olla
rs p
er
roo
m p
er n
igh
t)
Figure S7.2
S7 - 19© 2011 Pearson Education, Inc. publishing as Prentice Hall
Managing DemandManaging Demand Demand exceeds capacity
reduce demand by raising prices, scheduling longer lead time
Long term solution is to increase capacity
Capacity exceeds demand Stimulate market (advertising, price cuts, etc)
Product changes (diversify, make to stock)
Adjusting to seasonal demands Produce products with opposite demand
patterns (surf wear / snow wear)
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Complementary Demand Complementary Demand PatternsPatterns
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
Sal
es i
n u
nit
s
Time (months)
Combining both demand patterns reduces the variation
Snowmobile motor sales
Jet ski engine sales
Figure S7.3
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Tactics for Matching Tactics for Matching Capacity to DemandCapacity to Demand
1. Making staffing changes (extra shifts(+), reduce hours (-))
2. Adjusting equipment Purchasing additional machinery(+)
Selling or leasing out existing equipment(-)
3. Improving processes to increase throughput (+)
4. Redesigning products to facilitate more throughput(+)
5. Adding process flexibility to meet changing product preferences (+/-)
6. Closing facilities(-)
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Demand & Capacity Management Demand & Capacity Management in Servicesin Services
Demand management Appointment, reservations, FCFS rule
Capacity management Staffing levels & scheduling
full-time
part-time
Temporary/casual
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S7 - 24© 2011 Pearson Education, Inc. publishing as Prentice Hall
Capacity Analysis & Theory of ConstraintsCapacity Analysis & Theory of Constraints
Each workstation (within a system) can have its own unique capacity
Some work areas will be faster ( higher output) and some will be slower (lower output) than others.
Capacity analysis measures the output capacity of workstations in a system
A bottleneck is the workstation with the lowest effective capacity in the system and it will be the limiting factor or constraint for that system.
(Chains as strong as weakest link / a column marches as fast as the slowest marcher)
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Process Times for Stations, Process Times for Stations, Systems, and CyclesSystems, and Cycles
Process time of a stationProcess time of a station time to produce one unit at that single workstation
inverse of capacity for that workstation
Process time of a systemrocess time of a system the longest process time in the system … the bottleneck
Process cycle timeProcess cycle time time a product takes to go through the production
process with no waitingThese two
might be quite different!
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Process Times for Stations, Process Times for Stations, Systems, and CyclesSystems, and Cycles
System process timeSystem process time
•Is the process time of the bottleneck after dividing by the number of parallel operations
System capacitySystem capacity
•is the inverse of the system process time
Process cycle timeProcess cycle time
•is the total time through the longest path in the system
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Capacity AnalysisCapacity Analysis Two identical sandwich lines
Lines have two workers and three operations
All completed sandwiches are wrapped
Wrap
37.5 sec/sandwich
Order
30 sec/sandwich
Bread Fill Toast
15 sec/sandwich 20 sec/sandwich 40 sec/sandwich
Bread Fill Toast
15 sec/sandwich 20 sec/sandwich 40 sec/sandwich
S7 - 28© 2011 Pearson Education, Inc. publishing as Prentice Hall
Capacity Capacity AnalysisAnalysis Wrap
37.5 sec
Order
30 sec
Bread Fill Toast
15 sec 20 sec 40 sec
Bread Fill Toast
15 sec 20 sec 40 sec
Toast work station has the longest processing time – 40 seconds
The two lines each deliver a sandwich every 40 seconds so the process time of the combined lines is 40/2 = 20 seconds
At 37.5 seconds, wrapping and delivery has the longest processing time and is the bottleneck
Capacity per hour is 3,600 seconds/37.5 seconds/sandwich = 96 sandwiches per hour
Process cycle time is 30 + 15 + 20 + 40 + 37.5 = 142.5 seconds
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Capacity Capacity AnalysisAnalysis All possible paths must be compared
Cleaning path is 2 + 2 + 4 + 24 + 8 + 6 = 46 minutes
X-ray exam path is 2 + 2 + 4 + 5 + 8 + 6 = 27 minutes
Longest path involves the hygienist cleaning the teeth
Bottleneck is the hygienist at 24 minutes
Hourly capacity is 60/24 = 2.5 patients
Patient should be complete in 46 minutes
Checkout
6 min/unit
Check in
2 min/unit
DevelopsX-ray
4 min/unit 8 min/unit
DentistTakesX-ray
2 min/unit
5 min/unit
X-rayexam
Cleaning
24 min/unit
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Theory of ConstraintsTheory of Constraints
Five-step process for recognizing and managing constraints/ bottlenecks
Step 1:Step 1: Identify the constraint
Step 2:Step 2: Develop a plan for overcoming the constraints
Step 3:Step 3: Focus resources on accomplishing Step 2
Step 4:Step 4: Reduce the effects of constraints by offloading work or expanding capability
Step 5:Step 5: Once overcome, go back to Step 1 and find new constraints
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Bottleneck ManagementBottleneck Management
1. Release work orders to the system at the pace of set by the bottleneck
2. Inspect products before the bottleneck
3. Lost time at the bottleneck represents lost time for the whole system
4. Increasing the capacity of a non-bottleneck station is a mirage
5. Increasing the capacity of a bottleneck increases the capacity of the whole system
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S7 - 33© 2011 Pearson Education, Inc. publishing as Prentice Hall
Decision making about Decision making about Capacity ChangesCapacity Changes
(a) Leading demand with incremental expansion
Dem
and
Expected demand
New capacity
(c) Attempts to have an average capacity with incremental expansion
Dem
and
New capacity Expected
demand
(b) Capacity lags demand with incremental expansion
Dem
and
New capacity
Expected demand
Figure S7.6
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Expected Monetary Value Expected Monetary Value (EMV) and Capacity Decisions(EMV) and Capacity Decisions
Forecast probable Future demand
Market favorability
Analyse using decision trees and expected value Hospital supply company
Four alternatives
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Decision TreesDecision Trees(used for comparing options)(used for comparing options)
Square = decision being considered.
Circle = probability of some ‘state of nature’
(e.g. market response
being favourable 0.7
being unfavourable 0.3)
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Expected Monetary Value Expected Monetary Value (EMV) and Capacity Decisions(EMV) and Capacity Decisions
-$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
S7 - 37© 2011 Pearson Education, Inc. publishing as Prentice Hall
Expected Monetary Value Expected Monetary Value (EMV) and Capacity Decisions(EMV) and Capacity Decisions
-$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
EMV = (.4)($100,000) + (.6)(-$90,000)
Large Plant
EMV = -$14,000
S7 - 38© 2011 Pearson Education, Inc. publishing as Prentice Hall
Expected Monetary Value Expected Monetary Value (EMV) and Capacity Decisions(EMV) and Capacity Decisions
-$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
-$14,000
$13,000
$18,000
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Investment Appraisal for Capacity InvestmentInvestment Appraisal for Capacity Investment
Operations may be responsible for investment appraisal of capacity decisions.
Methods include
Payback period – comparing cash returns from investment to cash invested until balance is zero. (No discounting used – but useful if debt used to invest)
Net Present Value – finding the cash value of the investment (in today’s dollars) before investing by applying discount rate to future earnings.
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Payback periodPayback period• New machine costs $600,000.
• Income from machine = $255,000 each year
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investment returns Net position
Year 0 ($600,000) (600,000)
Year 1 $255,000 (345,000)
Year 2 $255,000 (90,000)
Year 3 $255,000 $165,000 (So payback is sometime in year 3.)
To find the month : =(cash needed / annual cash flow) *12= (90,000/255,000)*12= 0.352*12= 4.2 (first week of April)
Payback period = 2 yrs 4.2 months
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Net Present Value (NPV)Net Present Value (NPV)NPV discounts the future value of cash due to •uncertainty •loss of earnings compared to having it now.
Key decision is the discount rate to use to reduce the value of future cash flows.
High rate – future is heavily discounted / lower valueLow rate – future is lightly discounted / higher value
Usual choice is the interest rate on bank deposits.
If i= 10% then investing $100.00 today is worth $110.00 in one year – so - $100.00 is worth more than $100.00 received in one year from now.
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Net Present Value (NPV)Net Present Value (NPV)
where F = future valueP = present valuei = interest rate
N = number of years
P =F
(1 + i)N
F = P(1 + i)N
In general:
Solving for P:
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NPV Using FactorsNPV 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
Portion of Table S7.1
Year 6% 8% 10% 12% 14%
1 .943 .926 .909 .893 .8772 .890 .857 .826 .797 .7693 .840 .794 .751 .712 .6754 .792 .735 .683 .636 .5925 .747 .681 .621 .567 .519
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LimitationsLimitations
1. Investments with the same NPV may have different projected lives and salvage values
2. Investments with the same NPV may have different cash flows
3. Assumes we know future interest rates
4. Payments are not always made at the end of a period