Capacity Planning (Long-Term Capacity Planning) Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall. 6–1
Download
Report
Transcript Capacity Planning (Long-Term Capacity Planning) Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall. 6–1
6
Capacity Planning
(Long-Term Capacity Planning)
Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall.
6–1
Planning Management
Capacity management
Chapter 6 –
Chapter 7 –
Capacity planning
Constraint management
(long-term capacity planning)
(short-term capacity planning)
1. Economies and
diseconomies of scale
2. Capacity timing and
sizing strategies
3. Systematic approach to
capacity decisions
Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall.
Theory of constraints
Identification and
management of
bottlenecks
Product mix decisions
using bottlenecks
Managing constraints in a
line process
6–2
Capacity and Scale
Average unit cost
(dollars per patient)
best operating level = 500 beds (blue dot in the diagram)
250-bed
hospital
500-bed
hospital
Economies
of scale
750-bed
hospital
Diseconomies
of scale
Output rate (patients per week)
Figure 6.1 – Economies and Diseconomies of Scale
Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall.
6–3
A. Expansionist strategy
Forecast of capacity
required
Capacity
Planned unused
capacity
Capacity
increment
Time between
increments
Time
Figure 6.2 – Two Capacity Strategies
Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall.
6–4
B. Wait-and-see strategy
Capacity
Planned use of
short-term options
Forecast of capacity
required
Capacity
increment
Time between
increments
Time
Figure 6.2 – Two Capacity Strategies
Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall.
6–5
Output Measures
for Estimating Capacity Requirements
Output Measures are the simplest way to express
capacity.
Products produced or customers served per unit of
time
Example: Current capacity is 50 per day and demand is
expected to double in five years. Management uses a
capacity cushion of 20%.
Capacity (M) in 5 years should be:
M = 100/(1 - 0.2) = 125 customers
6–6
Input Measures
for Estimating Capacity Requirements
Input Measures are typically based on resource availability: e.g.
Availability of workers, machines, workstations, seats, etc.
For one service or product processed at one operation with a
one year time period, the capacity requirement, M, is
Processing hours required for year’s demand
Capacity
requirement = Hours available from a single capacity unit
(such as an employee or machine) per year,
after deducting desired cushion
Dp
M=
N[1 – (C/100)]
where
D = demand forecast for the year (number of customers serviced or
units of product)
p = processing time (in hours per customer served or unit produced)
N = total number of hours per year during which the process operates
C = desired capacity cushion (expressed as a percent)
Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall.
6–7
Input Measures
for Estimating Capacity Requirements
if multiple products are produced, setup
times may be required
Capacity
requirement =
M=
Processing and setup hours required for
year’s demand, summed over all services
or products
Hours available from a single capacity unit
per year, after deducting desired cushion
[Dp + (D/Q)s]product 1 + [Dp + (D/Q)s]product 1 + …
+ [Dp + (D/Q)s]product n
N[1 – (C/100)]
where
Q = number of units in each lot
s = setup time (in hours) per lot
Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall.
6–8
Decision Trees
Low demand [0.40]
$70,000
Don’t expand
$109,000
High demand [0.60]
2
$135,000
1
Low demand [0.40]
$148,000
$148,000
High demand [0.60]
$90,000
Expand
$135,000
$40,000
$220,000
Figure 6.4 – A Decision Tree for Capacity Expansion
Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall.
6–9