1 Molecular Composition of Gases Chapter 11 Chemistry Chapter 11.
chapter 11
Transcript of chapter 11
Slack, Chambers and Johnston, Operations Management 5th Edition © Nigel Slack, Stuart Chambers, and Robert Johnston 2007
Chapter 11
Capacity planning and control
Source: Arup
Slack, Chambers and Johnston, Operations Management 5th Edition © Nigel Slack, Stuart Chambers, and Robert Johnston 2007
Capacity planning and control
Operations strategy
Improvement
Planning and control
Operations management
Capacity planning and control
The operation supplies ... the capacity to deliver products and services
The market requires … the availability of products
and servicesDesign
Slack, Chambers and Johnston, Operations Management 5th Edition © Nigel Slack, Stuart Chambers, and Robert Johnston 2007
Objective
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 …
Costs
Revenue
Working capital
Service levelSource: British Airways London Eye
Slack, Chambers and Johnston, Operations Management 5th Edition © Nigel Slack, Stuart Chambers, and Robert Johnston 2007
Objectives of capacity planning and control
Forecast demand
Time
Agg
rega
ted
outp
ut
Estimate of current capacity
Measure aggregate capacity and demand
Identify the alternative capacity plans
Choose the most appropriate capacity plan
Slack, Chambers and Johnston, Operations Management 5th Edition © Nigel Slack, Stuart Chambers, and Robert Johnston 2007
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, Chambers and Johnston, Operations Management 5th Edition © Nigel Slack, Stuart Chambers, and Robert Johnston 2007
Climatic Festive Behavioural Political Financial Social
Causes of seasonality
Construction materials
Beverages (beer, cola)
Foods (ice-cream, Christmas cake)
Clothing (swimwear, shoes)
Gardening items (seeds, fertilizer)
Fireworks
Travel services
Holidays
Tax processing
Doctors (influenza epidemic)
Sports services
Education services
Source: Alamy/Medical-on-line
Slack, Chambers and Johnston, Operations Management 5th Edition © Nigel Slack, Stuart Chambers, and Robert Johnston 2007
Demand fluctuations in four operations
Slack, Chambers and Johnston, Operations Management 5th Edition © Nigel Slack, Stuart Chambers, and Robert Johnston 2007
Good forecasts are essential for effective capacity planning …
… but 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
DE
MA
ND
TIME
Only 5% chance of demand being lower than this
DE
MA
ND
TIME
Distribution of demandOnly 5% chance of demand being higher than this
Slack, Chambers and Johnston, Operations Management 5th Edition © Nigel Slack, Stuart Chambers, and Robert Johnston 2007
Loading time
Performance rate = p= net operating time/
total operating time
Quality losses
Valuable operating
time
Quality losses
Slow-running equipment
Equipment ‘idling’Net operating time
Speed losses
Not worked (unplanned)
Breakdown failure
Set-up and changeovers
Total operating timeAvailability
losses
Quality rate = q =valuable operating time/
net operating time
Availability rate = a = total operating time/
loading time
Operating equipment effectiveness (OEE)
Slack, Chambers and Johnston, Operations Management 5th Edition © Nigel Slack, Stuart Chambers, and Robert Johnston 2007
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
Efficiency
Actual output
Effective capacity=
Utilization Actual output
Design capacity=
Slack, Chambers and Johnston, Operations Management 5th Edition © Nigel Slack, Stuart Chambers, and Robert Johnston 2007
Ways of reconciling capacity and demand
Level capacity
Demand
Capacity
Chase demand Demand management
CapacityCapacity
Demand Demand
Slack, Chambers and Johnston, Operations Management 5th Edition © Nigel Slack, Stuart Chambers, and Robert Johnston 2007
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, Chambers and Johnston, Operations Management 5th Edition © Nigel Slack, Stuart Chambers, and Robert Johnston 2007
Absorb demand
Part finishedFinished goods, orCustomer inventory
QueuesBacklogs
Have excess
capacity
Make to stock
Keep output level
Make customer
wait
Source: Madam Tussaud’s
Slack, Chambers and Johnston, Operations Management 5th Edition © Nigel Slack, Stuart Chambers, and Robert Johnston 2007
Adjust output to match demand
Hire Fire
Temporary labour Lay-off
Overtime
Subcontract
Short time
Third-party work
Source: Corbis/Photocuisine
Slack, Chambers and Johnston, Operations Management 5th Edition © Nigel Slack, Stuart Chambers, and Robert Johnston 2007
Change demand
Change pattern of demand
Develop alternative products and/or services
Source: Empics
Slack, Chambers and Johnston, Operations Management 5th Edition © Nigel Slack, Stuart Chambers, and Robert Johnston 2007
Moving a peak in demand can make capacity planning easier
Slack, Chambers and Johnston, Operations Management 5th Edition © Nigel Slack, Stuart Chambers, and Robert Johnston 2007
ShortagesQueues
InventoryActual demand
and actual capacity
Period t – 1
Outcome
How much capacity
next period?
Current capacity
estimates
Updated forecasts
Period t
Decision
How 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, Chambers and Johnston, Operations Management 5th Edition © Nigel Slack, Stuart Chambers, and Robert Johnston 2007
Demand for manufacturing operation’s output8000
For
ecas
t in
aggr
egat
ed u
nits
of
outp
ut p
er m
onth
7000
6000
5000
4000
3000
2000
1000
0J F M A M J J A S O N D
Months
Slack, Chambers and Johnston, Operations Management 5th Edition © Nigel Slack, Stuart Chambers, and Robert Johnston 2007
For capacity planning purposes, demand is best considered on a cumulative basis. This allows alternative capacity and
output plans to be evaluated for feasibility
For
ecas
t cum
ulat
ive
aggr
egat
ed
outp
ut (
thou
sand
s)
60
50
40
30
20
10
00 40 80 120 160 200 240
Cumulative operating days
Slack, Chambers and Johnston, Operations Management 5th Edition © Nigel Slack, Stuart Chambers, and Robert Johnston 2007
Cumulative representations
Cumulative demand
Time
Building stock
Unable to meet orders
Cap
acity
and
dem
and
Cumulative capacity
Slack, Chambers and Johnston, Operations Management 5th Edition © Nigel Slack, Stuart Chambers, and Robert Johnston 2007
Rejecting
Source of customers
Boundary of system
Queue or ‘waiting line’
Served customers
Balking Reneging
Server 1
Server 2
Server m
Distribution of arrival times
Distribution of processing times
Simple queuing system
Slack, Chambers and Johnston, Operations Management 5th Edition © Nigel Slack, Stuart Chambers, and Robert Johnston 2007
Time
Time
Low variability – narrow distribution of process times
High variability – wide distribution of
process times
Simple queuing system
Slack, Chambers and Johnston, Operations Management 5th Edition © Nigel Slack, Stuart Chambers, and Robert Johnston 2007
Key Terms TestCapacityThe maximum level of value-added activity that an
operation, or process, or facility, is capable of over a period of time.
Aggregated planning and controlA term used to indicate medium-term capacity planning that
aggregates different products and services together in order to get a broad view of demand and capacity.
Design capacityThe capacity of a process or facility as it is designed to be;
often greater than effective capacity.
Slack, Chambers and Johnston, Operations Management 5th Edition © Nigel Slack, Stuart Chambers, and Robert Johnston 2007
Key Terms Test
Effective capacityThe useful capacity of a process or operation after
maintenance, changeover and other stoppages and loading have been accounted for.
UtilizationThe ratio of the actual output from a process or facility to its
design capacity.
Overall equipment effectiveness (OEE)A method of judging the effectiveness of how operations
equipment is used.
Slack, Chambers and Johnston, Operations Management 5th Edition © Nigel Slack, Stuart Chambers, and Robert Johnston 2007
Key Terms TestLevel capacity planAn approach to medium-term capacity management that
attempts to keep output from an operation or its capacity constant, irrespective of demand.
Chase demand planAn approach to medium-term capacity management that
attempts to adjust output and/or capacity to reflect fluctuations in demand.
Demand managementAn approach to medium-term capacity management that
attempts to change or influence demand to fit available capacity.
Slack, Chambers and Johnston, Operations Management 5th Edition © Nigel Slack, Stuart Chambers, and Robert Johnston 2007
Key Terms TestHire and fireA (usually pejorative) term used in medium-term capacity
management to indicate varying the size of the workforce through employment policy.
SubcontractingWhen used in medium-term capacity management, a term that
indicates the temporary use of other operations to perform some tasks, or even produce whole products or services, during times of high demand.
Demand managementAn approach to medium-term capacity management that
attempts to change or influence demand to fit available capacity.
Slack, Chambers and Johnston, Operations Management 5th Edition © Nigel Slack, Stuart Chambers, and Robert Johnston 2007
Key Terms Test
Yield managementA collection of methods that can be used to ensure that an
operation (usually with a fixed capacity) maximizes its potential to generate profit.
Queuing theoryA mathematical approach that models random arrival and
processing activities in order to predict the behaviour of queuing systems (also called waiting line theory).