LECTURE 29
LSM733-PRODUCTION
OPERATIONS MANAGEMENT
By: OSMAN BIN SAIF
1
Summary of last Session
 Characteristics of a Waiting-Line System
 Arrival Characteristics
 Waiting-Line Characteristics
 Service Characteristics
 Measuring a Queue’s Performance
 Queuing Costs
2
Summary of last Session (Contd.)
 The Variety of Queuing Models
 Model A(M/M/1): Single-Channel Queuing
Model with Poisson Arrivals and Exponential
Service Times
 Model B(M/M/S): Multiple-Channel Queuing
Model
 Model C(M/D/1): Constant-Service-Time
Model
 Model D: Limited-Population Model
3
Summary of last Session (Contd.)
 Other Queuing Approaches
4
Agenda for this Session
 Capacity
 Design and Effective Capacity
 Capacity and Strategy
 Capacity Considerations
 Managing Demand
 Demand and Capacity Management in
the Service Sector
5
Agenda for this Session (Contd.)
 Bottleneck Analysis and Theory of
Constraints
 Process Times for Stations, Systems, and
Cycles
 Theory of Constraints
 Bottleneck Management
 Break-Even Analysis
 Single-Product Case
6
Agenda for this Session (Contd.)
 Applying Expected Monetary Value to
Capacity Decisions
7
ADDITIONAL CHAPTER:
CAPACITY AND CONSTRAINT
MANAGEMENT
8
Capacity
 The throughput, or the number of units a
facility can hold, receive, store, or
produce in a period of time
 Determines
fixed costs
 Determines if
demand will
be satisfied
 If facilities remain idle
9
Planning Over a Time Horizon
Options for Adjusting Capacity
Long-range
planning
Add facilities
Add long lead time equipment
Intermediaterange planning
Subcontract
Add equipment
Add shifts
Short-range
planning
*
Add personnel
Build or use inventory
*
Modify capacity
Schedule jobs
Schedule personnel
Allocate machinery
Use capacity
* Difficult to adjust capacity as limited options exist
Figure S7.1
10
Design and Effective Capacity
 Design capacity is the maximum
theoretical output of a system
 Normally expressed as a rate
 Effective capacity is the capacity a firm
expects to achieve given current operating
constraints
 Often lower than design capacity
11
Utilization and Efficiency
Utilization is the percent of design capacity
actually achieved
Utilization = Actual output/Design capacity
Efficiency is the percent of effective capacity
actually achieved
Efficiency = Actual output/Effective capacity
12
Bakery Example
Actual production last week = 148,000 rolls
Effective capacity = 175,000 rolls
Design capacity = 1,200 rolls per hour
Bakery operates 7 days/week, 3 - 8 hour shifts
Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls
Bakery Example
Actual production last week = 148,000 rolls
Effective capacity = 175,000 rolls
Design capacity = 1,200 rolls per hour
Bakery operates 7 days/week, 3 - 8 hour shifts
Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls
Bakery Example
Actual production last week = 148,000 rolls
Effective capacity = 175,000 rolls
Design capacity = 1,200 rolls per hour
Bakery 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%
Bakery Example
Actual production last week = 148,000 rolls
Effective capacity = 175,000 rolls
Design capacity = 1,200 rolls per hour
Bakery 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%
Bakery Example
Actual production last week = 148,000 rolls
Effective capacity = 175,000 rolls
Design capacity = 1,200 rolls per hour
Bakery 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%
Bakery Example
Actual production last week = 148,000 rolls
Effective capacity = 175,000 rolls
Design capacity = 1,200 rolls per hour
Bakery 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%
Bakery Example: Estimating Output of a New
Facility
They are considering adding a second production line
and they plan to hire new employees and train them to
operate this new line
Effective capacity on this new line = 175,000 rolls which
is the same on the first line
However, due to new hires they expect that efficiency of this new line will be 75%
rather than 84.6%
Expected Output = (Effective Capacity)(Efficiency)
= (175,000)(.75) = 131,250 rolls
Capacity 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
Important Issues in Capacity
Planning
1. Forecast demand accurately
2. Understand the technology and
capacity increments
3. Find the optimum
operating level
(volume)
4. Build for change
21
Average unit cost
(dollars per room per night)
Economies and Diseconomies of
Scale
25 - room
roadside motel
50 - room
roadside motel
Economies of
scale
25
75 - room
roadside motel
Diseconomies of
scale
50
Number of Rooms
75
Figure S7.2
22
Managing Demand
 Demand exceeds capacity

Curtail demand by raising prices, scheduling longer lead time

Long term solution is to increase capacity
 Capacity exceeds demand

Stimulate demand through price reductions

Product changes
 Adjusting to seasonal demands

Produce products with complementary demand patterns
23
Complementary Demand Patterns
Sales in units
4,000 –
3,000 –
2,000 –
1,000 –
JFMAMJJASONDJFMAMJJASONDJ
Time (months)
Jet ski
engine
sales
Figure S7.3
24
Complementary Demand Patterns
Sales in units
4,000 –
3,000 –
Snowmobile
motor sales
2,000 –
1,000 –
JFMAMJJASONDJFMAMJJASONDJ
Time (months)
Jet ski
engine
sales
Figure S7.3
25
Complementary Demand Patterns
Sales in units
4,000 –
3,000 –
Combining both
demand patterns
reduces the
variation
Snowmobile
motor sales
2,000 –
1,000 –
JFMAMJJASONDJFMAMJJASONDJ
Time (months)
Jet ski
engine
sales
Figure S7.3
26
Tactics for Matching Capacity to
Demand
1.
Increasing/decreasing employees and shifts
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
27
Demand and Capacity
Management in the Service Sector
 Demand management (scheduling customers)
 Appointment, reservations, FCFS rule
 Capacity
management
(scheduling workforce)
 Full time,
temporary,
part-time
staff
28
Bottleneck Analysis and Theory of
Constraints
 Capacity analysis determines the throughput
capacity of workstations in a system
 A bottleneck has the lowest effective capacity in
a system
 A bottleneck is a limiting factor or constraint
29
Theory of Constraints
 Five-step process for recognizing and managing
limitations
Step 1:
Identify the constraint
Step 2:
Develop a plan for overcoming the constraints
Step 3:
Focus resources on accomplishing Step 2
Step 4:
Reduce the effects of constraints by offloading work or expanding
capability
Step 5:
Once overcome, go back to Step 1 and find new constraints
30
Bottleneck Management
1. Release work orders to the system at the pace of
set by the bottleneck
2. Lost time at the bottleneck represents lost time
for the whole system
3. Increasing the capacity of a non-bottleneck
station is a mirage
4. Increasing the capacity of a bottleneck increases
the capacity of the whole system
31
Process Times for Stations, Systems,
and Cycles
 The process time of a station is the time to
produce a unit at that single workstation
 The process time of a system is the time of
the longest process in the system … the
bottleneck
 The system capacity is the inverse of the
system process time
 The process cycle time is the total time
through the longest path in the system
32
A Three-Station Assembly Line
Process time of stations: 2, 4 and 3 min/unit
Process time for the system: 4 min/unit
Process Cycle Time= 2 + 4 + 3 = 9 min/unit
System Capacity = ¼*60(min)= 15 units/hour
A
B
C
2 min/unit
4 min/unit
3 min/unit
Figure S7.4
33
Capacity Analysis
EXAMPLE
 Two identical sandwich lines
 Lines have two workers and three operations
 All completed sandwiches are wrapped
Bread
15 sec/sandwich
Fill
20 sec/sandwich
Toast
40 sec/sandwich
Order
Wrap
30 sec/sandwich
37.5 sec/sandwich
Bread
15 sec/sandwich
Fill
20 sec/sandwich
Toast
40 sec/sandwich
34
Capacity
Analysis
Bread
Order
30 sec
15 sec
Bread
15 sec
Fill
Toast
20 sec
40 sec
Fill
Toast
20 sec
40 sec
Wrap
37.5 sec
 It seems that the toast work station has the longest processing time
– 40 seconds, but the two lines work in parallel and each deliver a
sandwich every 40 seconds so the process time of the toast work
station is 40/2 = 20 seconds. So process time of five stations are 30,
15, 20, 40 and 37.5 sec., respectively.
 With 37.5 seconds, wrapping station has the longest processing time
and it is the bottleneck. So process time of the system is 37.5 sec.
 System capacity per hour is (1/37.5)*3,600 seconds = 96 sandwiches
per hour
 Process cycle time is 30 + 15 + 20 + 40 + 37.5 = 142.5 seconds
35
Capacity Analysis
Example
 Standard process for cleaning teeth
 Cleaning and examining X-rays can happen
simultaneously
Hygienist
Cleans
the teeth
Customer
Checks in
A Lab Ass.
Takes
X-ray
A Lab Ass
Develops
X-ray
2 min/unit
2 min/unit
4 min/unit
24 min/unit
Dentist
re-processes
Dentist
Examines
X-ray and
processes
8 min/unit
Customer
pays
6 min/unit
5 min/unit
36
Capacity
Analysis
Cleaning
Check
in
Takes
X-ray
Develops
X-ray
24 min/unit
2 min/unit
2 min/unit
4 min/unit
X-ray
exam
Dentist
Check
out
8 min/unit
6 min/unit
5 min/unit
 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, so
the process cycle time is 46 min. The patient will be out
of door after 46 min.
 Bottleneck is the hygienist at 24 minutes which is the
process time of the system
 System capacity is (1/24)*60 min = 2.5 patients/per hour
37
Break-Even Analysis
 Technique for evaluating process and
equipment alternatives
 Objective is to find the break-even
point in dollars and in units at which
cost equals revenue
 Requires estimation of fixed costs,
variable costs, and revenue
38
Break-Even Analysis
 Fixed costs are costs that continue even if
no units are produced
 Depreciation, taxes, debt, mortgage
payments
 Variable costs are costs that vary with the
volume of units produced
 Labor, materials, portion of utilities
 Contribution is the difference between
selling price and variable cost
39
Break-Even Analysis
Assumptions
 Costs and revenue are linear
functions
 Generally not the case in the real
world
 We actually know these costs
 Very difficult to verify
 Time value of money is often
ignored
40
Break-Even Analysis
–
Total revenue line
900 –
800 –
700 –
Cost in dollars
Total cost line
Break-even point
Total cost = Total revenue
600 –
500 –
Variable cost
400 –
300 –
200 –
100 –
–
0
|
Figure S7.5
Fixed cost
|
|
|
|
|
|
|
|
|
|
|
100 200 300 400 500 600 700 800 900 1000 1100
Volume (units per period)
41
Break-Even Analysis
BEPx = break-even point in units
BEP$ = break-even point in
dollars
P = price per unit (after all
discounts)
x = number of units produced
TR
F
V
TC
=
=
=
=
total revenue = Px
fixed costs
variable cost per unit
total costs = F + Vx
Break-even point occurs when
TR = TC
or
Px = F + Vx
BEPx =
F
P-V
42
Break-Even Analysis
BEPx = break-even point in units
BEP$ = break-even point in
dollars
P = price per unit (after all
discounts)
BEP$ = BEPx P
F
=
P
P-V
F
=
(P - V)/P
F
=
1 - V/P
x = number of units produced
TR
F
V
TC
=
=
=
=
total revenue = Px
fixed costs
variable cost per unit
total costs = F + Vx
Profit = TR - TC
= Px - (F + Vx)
= Px - F - Vx
= (P - V)x - F
43
Break-Even
Example
Fixed costs = $10,000
Direct labor = $1.50/unit
BEP$ =
Material = $.75/unit
Selling price = $4.00 per unit
F
1 - (V/P)
=
$10,000
1 - [(1.50 + .75)/(4.00)]
44
Break-Even Example
Fixed costs = $10,000
Direct labor = $1.50/unit
F
1 - (V/P)
BEP$ =
=
BEPx =
Material = $.75/unit
Selling price = $4.00 per unit
=
$10,000
.4375
F
P-V
$10,000
1 - [(1.50 + .75)/(4.00)]
= $22,857.14
=
$10,000
4.00 - (1.50 + .75)
= 5,714
45
Break-Even Example
50,000 –
Revenue
40,000 –
Break-even
point
Dollars
30,000 –
Total
costs
20,000 –
Fixed costs
10,000 –
|–
|
|
|
|
|
0
2,000
4,000
6,000
8,000
10,000
Units
46
Expected Monetary Value (EMV) and
Capacity Decisions
 Determine states of nature
 Future demand
 Market favorability
 Analyzed using decision trees
 Hospital supply company
 Four alternatives for capacity
expansion
47
Expected Monetary Value (EMV) and
Capacity Decisions
Market favorable (.4)
Market unfavorable (.6)
Market favorable (.4)
Medium plant
Market unfavorable (.6)
Market favorable (.4)
Market unfavorable (.6)
$100,000
-$90,000
$60,000
-$10,000
$40,000
-$5,000
$0
48
Expected Monetary Value (EMV) and
Capacity Decisions
Market favorable (.4)
Market unfavorable (.6)
Market favorable (.4)
Medium plant
Large Plant
EMV =
(.4)($100,000)
+ (.6)(-$90,000)
EMV = -$14,000
Market unfavorable (.6)
Market favorable (.4)
Market unfavorable (.6)
$100,000
-$90,000
$60,000
-$10,000
$40,000
-$5,000
$0
49
Expected Monetary Value (EMV) and
Capacity Decisions
-$14,000
Market favorable (.4)
Market unfavorable (.6)
$100,000
-$90,000
$18,000
Market favorable (.4)
Medium plant
Market unfavorable (.6)
$60,000
-$10,000
$13,000
Market favorable (.4)
Market unfavorable (.6)
$40,000
-$5,000
$0
50
Summary of the Session
 Capacity
 Design and Effective Capacity
 Capacity and Strategy
 Capacity Considerations
 Managing Demand
 Demand and Capacity Management in
the Service Sector
51
Summary of the Session(Contd.)
 Bottleneck Analysis and Theory of
Constraints
 Process Times for Stations, Systems, and
Cycles
 Theory of Constraints
 Bottleneck Management
 Break-Even Analysis
 Single-Product Case
52
Summary of the Session (Contd.)
 Applying Expected Monetary Value to
Capacity Decisions
53
THANK YOU
54