Slack, Brandon-Jones and Johnston, Essentials of Operations Management, 1st Edition, © Slack, Brandon-Jones and Johnston, 2011
Chapter 8
Capacity management
Slack, Brandon-Jones and Johnston, Essentials of Operations Management, 1st Edition, © Slack, Brandon-Jones and Johnston, 2011
Slack et al’s model of operations management
Design
Deliver
Direct
Develop
Operations Management
Lean synchronis-
ation
Planning and control
Capacity manag-ement
Supply network
management
Inventory management
Slack, Brandon-Jones and Johnston, Essentials of Operations Management, 1st Edition, © Slack, Brandon-Jones and Johnston, 2011
In Chapter 8 - Capacity planning and control – Slack et. al. identify the following key questions…….
What is capacity management?
How are demand and capacity measured?
What are the alternative ways of coping with demand
fluctuation?
How can operations plan their capacity level?
How can queuing theory be used to plan capacity?
Key operations questions
Slack, Brandon-Jones and Johnston, Essentials of Operations Management, 1st Edition, © Slack, Brandon-Jones and Johnston, 2011
Capacity is in the static, physical sense means the scale of an operation,
What is capacity?
But this may not reflect the operation’s processing capability
So we must incorporate a time dimension appropriate to the use of assets.
For example 24 000 litres per day.
10,000 calls per day
57 patients per session
Etc.
Slack, Brandon-Jones and Johnston, Essentials of Operations Management, 1st Edition, © Slack, Brandon-Jones and Johnston, 2011
The objectives of capacity planning and control
To provide an “appropriate” amount of capacity at any point in time.
The “appropriateness” of capacity planning in any part of the operation can be judged by its effect on…...
CostsRevenue
Working Capital
Service Level
Slack, Brandon-Jones and Johnston, Essentials of Operations Management, 1st Edition, © Slack, Brandon-Jones and Johnston, 2011
Objectives of capacity planning and control
Forecast demand
Time
Aggr
egat
ed o
utpu
t
Estimate of current capacity
Measure aggregate capacity and demand
Identify the alternative capacity plansChoose the most appropriate capacity plan
Slack, Brandon-Jones and Johnston, Essentials of Operations Management, 1st Edition, © Slack, Brandon-Jones and Johnston, 2011
The nature of aggregate capacity
- rooms per night;
- ignores the numbers of guests in each room.
- tonnes per month;
- ignores types of alloy, gauge and batch variations.
Aggregate capacity of a hotel:
Aggregate capacity of an aluminium producer:
Slack, Brandon-Jones and Johnston, Essentials of Operations Management, 1st Edition, © Slack, Brandon-Jones and Johnston, 2011
Climatic Festive Behavioural Political Financial Social
Causes of seasonality
Construction materialsBeverages (beer, cola)Foods (ice-cream)Clothing (swimwear, shoes)Gardening items (seeds)Fireworks
Travel servicesHolidaysTax processingDoctors (influenza epidemic)Sports servicesEducation services
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Demand fluctuations in four operations
Slack, Brandon-Jones and Johnston, Essentials of Operations Management, 1st Edition, © Slack, Brandon-Jones and Johnston, 2011
Good forecasts essential for effective capacity planningBut so is an understanding of demand uncertainty because it allows you to judge the risks to service level.
When demand uncertainty is high the risks to service level of under provision of capacity are high.
Dem
and
Time
Only 5% chance of demand being lower than this
Dem
and
Time
Distribution of demandOnly 5% chance of demand being higher than this
Slack, Brandon-Jones and Johnston, Essentials of Operations Management, 1st Edition, © Slack, Brandon-Jones and Johnston, 2011
Loading time
Equipment “idling”
Speed losses
Slow running equipment
Net operating time
Not worked (unplanned)
Breakdown failure
Set-up and change-overs
Total operating time
Availability losses
Operating equipment effectiveness (OEE)
Availability rate = a = total operating time
loading time
Performance rate = p= net operating time
total operating time
Quality rate = q= valuable operating time
net operating timeQuality losses
Valuable operating
time
Quality losses
Slack, Brandon-Jones and Johnston, Essentials of Operations Management, 1st Edition, © Slack, Brandon-Jones and Johnston, 2011
How capacity and demand are measured
Design capacity
168 hours per week
Effective capacity
109 hours per week
Planned loss of 59 hours
Actual output –51 hours per
week
Avoidable loss –58 hours per
week
EfficiencyActual output
Effective capacity=
Utilization Actual outputDesign capacity=
Slack, Brandon-Jones and Johnston, Essentials of Operations Management, 1st Edition, © Slack, Brandon-Jones and Johnston, 2011
Ways of reconciling capacity and demand
Level capacity
Demand
Capacity
Chase demand Demand management
CapacityCapacity
Demand Demand
Slack, Brandon-Jones and Johnston, Essentials of Operations Management, 1st Edition, © Slack, Brandon-Jones and Johnston, 2011
How do you cope with fluctuations in demand?
Absorb Demand
Change demand
Adjust output to match demand
Level capacity
Chase demand
Demand management
Ways of reconciling capacity and demand
Slack, Brandon-Jones and Johnston, Essentials of Operations Management, 1st Edition, © Slack, Brandon-Jones and Johnston, 2011
Absorb demand
Part finishedFinished goods, orCustomer Inventory
QueuesBacklogs
Have excess capacity
Make to stock
Keep output level
Make customer
wait
Absorb demand
Slack, Brandon-Jones and Johnston, Essentials of Operations Management, 1st Edition, © Slack, Brandon-Jones and Johnston, 2011
Adjust output to match demand
Hire Fire
Temporary labour Lay-off
Overtime
Subcontract
Short time
3rd party work
Adjust output to match demand
Slack, Brandon-Jones and Johnston, Essentials of Operations Management, 1st Edition, © Slack, Brandon-Jones and Johnston, 2011
Change demand
Change pattern of demand
Develop alternative products and/or services
Change demand
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Moving a peak in demand can make capacity planning easier
Slack, Brandon-Jones and Johnston, Essentials of Operations Management, 1st Edition, © Slack, Brandon-Jones and Johnston, 2011
ShortagesQueues
InventoryActual demand
and actual capacity
Period t - 1
OutcomeHow much capacity
next period?
Current capacity
estimatesUpdated forecasts
Period t
DecisionHow much capacity
next period?
Current capacity
estimatesUpdated forecasts
Period t + 1
DecisionCapacity level
ShortagesQueues
Inventory
CostsRevenues
Working capitalCustomer satisfaction
etc
Actual demand
and actual capacity?
CostsRevenues
Working capitalCustomer satisfaction
etc
Outcome
Capacity planning and control as a dynamic sequence of decisions
Slack, Brandon-Jones and Johnston, Essentials of Operations Management, 1st Edition, © Slack, Brandon-Jones and Johnston, 2011
Demand for a manufacturing operation’s output
8000
Fore
cast
in a
ggre
gate
d un
its
of o
utpu
t per
mon
th
7000
6000
5000
4000
3000
2000
1000
0J F M A M J J A S O N D
Months
Slack, Brandon-Jones and Johnston, Essentials of Operations Management, 1st Edition, © Slack, Brandon-Jones and Johnston, 2011
For capacity planning purposes demand is best considered on a cumulative basis. This allows alternative capacity and output plans to be evaluated for feasibility.
Fore
cast
cum
ulat
ive
aggr
egat
ed
outp
ut (t
hous
ands
)
60
50
40
30
20
10
00 40 80 120 160 200 240
Cumulative operating days
But will not satisfy demand at all points throughout the year
Producing at average demand
Producing at average demand allows inventory to be accumulated
Slack, Brandon-Jones and Johnston, Essentials of Operations Management, 1st Edition, © Slack, Brandon-Jones and Johnston, 2011
Cumulative representations
Cumulative demand
Time
Building stock
Unable to meet orders
Cap
acity
and
Dem
and
Cumulative capacity
Slack, Brandon-Jones and Johnston, Essentials of Operations Management, 1st Edition, © Slack, Brandon-Jones and Johnston, 2011
Time
Time
Low variability -narrow distribution of process times
High variability -wide distribution of
process times
Simple queuing system
Slack, Brandon-Jones and Johnston, Essentials of Operations Management, 1st Edition, © Slack, Brandon-Jones and Johnston, 2011
Boundary of system
Queue or “waiting line”
Served customers
Rejecting Balking Reneging
Server 1
Server 2
Server m
Distribution of arrival times
Distribution of processing times
Simple queuing system
Source of customers