S7 - 1© 2011 Pearson Education, Inc. publishing as Prentice Hall Process Strategies ( process, repetitive, product) The objective of the process strategy

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)

S7 - 2

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


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)


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


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


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 %)


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%





Utilization = 148,000/201,600 = 73.4%


Bakery ExampleBakery Example(effective capacity & efficiency)



Utilization = 148,000/201,600 = 73.4%

Efficiency = 148,000/175,000 = 84.6%





Utilization = 148,000/201,600 = 73.4%

Efficiency = 148,000/175,000 = 84.6%



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



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



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


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)


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


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)


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


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(-)


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



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)


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!


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


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


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


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


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


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



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


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

S7 - 35

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)




-$90,000Market unfavorable (.6)

Market favorable (.4)$100,000

Large plant

Market favorable (.4)

Market unfavorable (.6)

$60,000

-$10,000

Medium plant



$40,000

-$5,000

Small plant

$0

Do nothing





Large plant



$60,000

-$10,000

Medium plant



$40,000

-$5,000

Small plant

$0

Do nothing

EMV = (.4)($100,000) + (.6)(-$90,000)

Large Plant

EMV = -$14,000





Large plant



$60,000

-$10,000

Medium plant



$40,000

-$5,000

Small plant

$0

Do nothing

-$14,000

$13,000

$18,000


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.

S7 - 40

Payback periodPayback period• New machine costs $600,000.

• Income from machine = $255,000 each year


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


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.


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:


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


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

Documents

S7 - 1© 2011 Pearson Education, Inc. publishing as Prentice Hall Process Strategies ( process, repetitive, product) The objective of the process strategy