Operation Management Notes

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Operations Management
Session 1
Professor Arnab Bisi, PhD
1
Operations Management
Have you had an operations management class?
1. Yes
2. No
2
Operations Management
Myths
1. “The airport security line is always long; I must wait forever.”
2. “That barista at Starbucks is generally fast, and not too many customers
show up in general anyway; I should expect a short wait.”
3. “If I were to pool all the checkout lines at Safeway into a single serpentine
line, then it would be a longer line.”
4. “I can forecast demand for our brand-name shoes really well. We should
produce at the quantity of my forecast to match supply and demand.”
5. “This season’s demand is fluctuating like crazy; to err on the side of
caution, let’s keep more inventory at hand just in case.”
6. “Our friends are visiting us; the food consumption doubles, and we should
do grocery shopping twice as frequently.”
7. “I should open up all the hotel rooms for customer reservation to capture as
much demand as possible. Don’t waste any opportunity of making money!”
The purpose of the course: debunk these myths
3
Operations Management
Course Roadmap
1. Operations Strategy
The Role of Operations in Strategy
Wriston Manufacturing Case
Introduction to the Analysis of Flows
2. Process Analysis and Design
3. Managing Flows
4. Managing Variability
5. Inventory Management
6. Toyota Production System
7. Operations in a Networked World
Operations Management
Outline
Historical Perspective of Operations
~
~
~
definition of operations management
from industrial revolution to the global economy
from cost reduction to service enhancement and beyond
Operations and Performance
~
~
~
~
~
Strategic role of operations (processes support capabilities support
strategy)
Process view of operations (process flows)
Matching processes to products (product/process matrix)
Tradeoffs (efficient frontiers)
Strategic dynamics (change in technologies)
Wriston Manufacturing
5
Operations Management
Operations as Part of the Value Chain
Definition: Operations Management is the organization and
control of the fundamental business activity of providing goods
and services to customers.
Specs
New Product
Development
Transformation
Operations
Finance
Demand
Logistics
Marketing
& Sales
Distribution
Cust Support
Service
Accounting
Management of Organizations
Fundamentally, OM is about transformation processes.
6
Operations Management
Transformation Process
Inputs
Network of
Activities and Buffers
Outputs
Goods
Services
Flow units/Entities
(customers, data,
material, cash, etc.)
Resources
Labor & Capital
7
Operations Management
Historical Context of Operations
• First Industrial Revolution
(1750-1830)
~
factory system
• Second Industrial
Revolution (1850-1920)
~
~
~
mass production/
transport
rise of modern manufacturing (Carnegie, Ford,
Sloan)
scientific management
(Taylor)
• Golden Era of Big Business
(1920-1960’s)
~
~
World War II
finance, marketing, fast-track
managers, etc.
• Reinventing Manufacturing
(1970-1980’s)
~
MRP, JIT (lean), TQM (6)
• Third and Fourth Industrial
Revolution? (1990-present)
~
~
global supply chains
collaborative networks
8
Operations Management
The Strategic Role of Operations
A company’s “manufacturing” function is either a
competitive weapon or a corporate millstone.
It is seldom neutral.
–Wickham Skinner
9
Operations Management
Strategy Hierarchy
Operations Management
Strategy Hierarchy
•
Corporate strategy: defines businesses in which the corporation will
participate and specifies how key corporate resources will be acquired and
allocated to each business
•
Business strategy: defines the scope of each division or business unit in
terms of the attributes of the products that it will offer and the market
segments that it will serve
•
Operations strategy: configures and develops business processes that
best enable a firm to produce and deliver the products specified by the
business strategy
11
Operations Management
Strategy Hierarchy
Corporate Strategy
What business are you in?
Business Unit Strategy
Sales pitch used by sales
(product attributes & target segments)
CORP
BUS UNIT
OPERATIONS
OPNS STRUCTURE
Operations Strategy
What capabilities must Operations develop?
Operations Structure
How should Operations processes and resources be structured
to develop capabilities and support strategy?
12
Operations Management
Strategic Alignment
Business Performance
(Financial Metrics)
~
~
~
~
~
Operations Performance
(Operational Metrics)
~
~
~
~
~
NPV (absolute)
ROI, ROA (relative)
Cash flow (survival)
Stock price
Market share
Flow time
Throughput
Inventory
Process cost
Quality
Customer Priorities
(Order Winners)
~
~
~
~
Price
Quality
Time
Variety
13
Operations Management
Matching Capabilities to Strategy
Price (Cost) P
Quality Q
~
~
Customer service
Product quality
Time T
~
~
“order winners”
Rapid, reliable delivery
New product development
Variety V
~
Degree of customization
To deliver we need
“capabilities” as measured
by operational metrics
14
Operations Management
Dimensions of Customer Value: Product Attributes
Cost
Product price
Cost of service
Quality
Trade-off!
Product quality
Customer service
Response Time
Goods: delivery
Services: waiting
Amazon Fulfillment Center
Variety
Degree of customization
Product lines
15
Operations Management
Identifying Appropriate Capabilities
Federal Express vs. US Postal Service
• time/traceability  hub and spoke system
• price  regional post office system
General Motors vs. Ford (1930’s)
• variety  divisional structure, regular model introductions
• price  one product assembly line
Dell vs. Compaq
• variety/customization  direct marketing model
• speed/service  retail channel
16
Operations Management
Wal-Mart – Approach
Corporate Strategy
(Gain competitive advantage by) providing customers access to quality
goods, when and where needed, at competitive prices
Operations Structure
Operations Strategy
– Short flow times
– Low inventory levels
– Cross docking
– Retail Link (PoS data)
– Fast transportation system
– Focused locations
– Communication between
retail stores
17
Operations Management
Location, Location, Location: What Do You Notice?
18
Operations Management
Diffusion of Walmart
19
Operations Management
“Wal-Mart never jumped to some far off location to later fill in the
area in between. … Wal-Mart always placed new stores close to
where it already had store density.”
“When stores are packed close together, it is easier to set up a
distribution network that keeps stores close to a distribution
center.”
“When stores are close to a distribution center, Wal-Mart can save
on trucking costs. Moreover, such proximity allows Wal-Mart to
respond quickly to demand shocks. “
Holmes, T. J. (2011). The Diffusion of Wal‐Mart and Economies of
Density. Econometrica, 79(1), 253-302.
20
Operations Management
Wal-Mart – Results
• A high inventory turnover rate, even compared with other
industry leaders (e.g., Target)
• Improved targeting of products to markets
Famous example: increased stock of U.S. national flags on the
same day of 9/11
• Sales per square foot increased from $102 in
1985 to $726 in 2016 (industry average
increased from ~$100 to ~$300).
21
Operations Management
Process Architecture
Flow Efficiency
Project
Job Shop
Batch
Line Flow
Continuous Flow
Product Flexibility
22
Operations Management
Process Positioning: Product-Process Matrix
• Video
• https://www.youtube.com/watch?v=m62whN6C
WBM&t=13s
23
Operations Management
Job Shop vs. Batch vs. Flow Shop
Type of
Process
Product
Volume
Specialized
Equipment
Product
Variety
Machine
Setup
Frequency
Labor
Skills
Variable
Cost
Job Shop
low
low
high
high
high
high
Batch
med
med
med
med
med
med
Flow Shop
high
high
low
low
low
low
24
Process Positioning:
Product/Process Matrix
Operations Management
Product
Volume
Process
Flexibility
Jumbled Flow
(job shop)
Low Volume
Low Standardization
Higher Volume
Few Products
High Volume
High Standardization
Inefficient
Commercial
Printer
Disconnected
Line Flow
(batch)
Heavy
Equipment
Connected Line
Flow (assembly
batch)
Continuous
Flow
Low Volume
Multiple Products
Auto
Assembly
Infeasible
Sugar
Refinery
25
Operations Management
Product/Process Matrix – Food Industry
Product
High customization
High unit margin
Low volume
Some customization Low custom
Ave margin
Low unit margin
Med volume
High volume
Process
Job shop
Batch flow
Assembly or
Continuous flow
Cinghiale
Wolfgang Puck?
Cafeteria
Subway?
McDonalds
26
Operations Management
Representation of Strategy
Current position and
strategic directions of
movement in the
competitive product
space
Responsiveness
High
B e.g.,
A
Low
High
Price
e.g.,
Low
27
Operations Management
Strategy and Operational Effectiveness
Strategic Focus
position on efficient
frontier
Responsiveness
High
efficient
frontier
A
Operational Efficiency
distance from efficient
frontier
B
C
Low
High
Price
Low
28
Operations Management
Contrasts in Strategic Focus
High
High
Infeasible
Efficient
Frontier
Inefficient
Kia
Low
Low
High
High
Quality
Low
Infeasible
manufacturer
High
Speed
Low
Infeasible
Cost
Cost
High
Inefficient
prototype
line
Efficient
Frontier
Inefficient
Efficient
Frontier
High
Peapod
Low
Infeasible
Grainger
Cost
Cost
Rolls
Royce
grocery
Service
Low
Low
Efficient
Frontier
Inefficient
High
production
line
Variety
Low
29
Operations Management
Strategic Dynamics
Efficient frontiers do not remain static because either:
1. Technology evolves: a technology or process
improvement makes it possible to deliver higher levels of
performance (e.g., faster delivery enabled by a highly
integrated supply chain), or
2. Customers evolve: changing customer tastes or saturation
of tastes along current dimensions of competition makes
attractive a new value proposition (e.g., offering exceptional
service in addition to low cost and fast delivery)
30
Operations Management
Strategic Dynamics – Technology Change
Responsiveness
Responsiveness
High
High
Low
Low
High
Price
Low
High
Price
Low
Dynamics
• Technology (IS, OM practices, etc.) elevates efficient frontier
• Firms must continually improve to remain competitive
• Frameworks (e.g. lean, six sigma) offer guidance
31
Operations Management
Strategic Dynamics – Market Change
Responsiveness
Service Experience
High
High
Low
Low
High
Price
Low
High
Price
Low
Dynamics
• Technology stabilizes and becomes standardized
• Surviving firms offer similar performance
• Basis of competition shifts to another dimension
32
Operations Management
Implications for Competitiveness
Firms can become uncompetitive due to:
1) Operational efficiency below efficient frontier
a. K-mart dominated Sears in 1980’s but fell behind Wal-Mart in 1990’s
b. Ford/GM led industry through 1960’s but fell behind Toyota in 1980’s
c. Compaq successful in 1980’s but overtaken by Dell in 1990’s
2) Strategic focus out of step with customer needs
a. Ford dominant in the 1920’s competing on cost but fell behind GM in
1930’s by failing to compete on variety
b. Lilly ruled American insulin market (90% share) through 1980’s by
competing on purity, but lost ground to Novo-Nordisk by being late to
compete on convenience (insulin pen)
33
Operations Management
Summary: Operations Strategy
• Strategy = plan to achieve superior performance
~
~
four modes of competition: price, quality, time, variety
differentiated position in competitive product space of (P,Q,T,V)
• Operations = processes that transform inputs into outputs
~
~
~
network of activities and allocation of resources
four process attributes: cost, process quality, cycle time, flexibility
operational effectiveness = distance to the frontier
• Operations Strategy = consistency between strategy and operations
~
Evaluation: strategic operational audit
–
~
Competition: impact and dynamics
–
~
do process capabilities and strategy fit?
anticipate (offense) vs. react (defense)
Evolution: shifting basis of competition
–
capabilities must evolve to support new strategies
34
Operations Management
Wriston Manufacturing
35
Operations Management
How to Approach Operations Cases
• What does unit have to do well (mission)?
~
Look at product, service, customers and find out what they value
• What’s wrong (symptoms)?
~
Declining profits, high rework, late deliveries
• What are underlying causes of symptoms?
~
Basic analysis such as process flow, cost structure, info flow analysis
• What management levers are available?
• Perform analysis to see whether and how much changes will fix
underlying problems.
• Step back, look at side effects, interactions, and strategic
implications of changes. What could go wrong?
• Set plan of action.
36
Operations Management
Wriston Manufacturing Takeaways
• Requirement of capabilities change with market segment and product life
cycle. As a result, a firm may need to develop a wide variety of capabilities.
• Multiple focused factories, each focused on a single capability, handle
conflicting capabilities better than a single factory trying to provide all
capabilities.
• Key drivers of overhead include variety and scale. Overhead per unit
increases with variety and decrease with scale.
Rule of thumb: Overhead costs per unit drop by 15 percent for each
doubling of plant volume, and increase 25-30 percent each time the
number of product families made in the plant is doubled
37
Operations Management
BUT … Strategy is Easy; Execution is Hard
• Saying we need to create capabilities that support a
strategy is one thing. Doing it is another.
• We need to understand the links between
management levers and performance metrics.
• For that, we need to
understand PROCESS FLOW
38
Operations Management
Introduction to Process Flow
•A process flow is a collection of recurring
activities that takes one or more kinds of input and
creates an output that is of value to the customer.
39
Operations Management
Assembly is a process flow
40
Operations Management
A flight is a process flow
41
Operations Management
A hospital is a process flow
42
Operations Management
Process Flow Analysis
A flow consists of stations
and stockpoints
43
Operations Management
Performance Measures for a Flow
Throughput
(entities/hour)
Stations
1
≤ Capacity
(entities/hour)
Throughput
(entities/hour)
2
3
4
Inventory (entities)
≤ Capacity
(entities/hour)
Cycle Time
(hours)
Cycle time: Time a job spends in a process (time)
Inventory: Jobs that accumulate in a process (jobs)
Example: Work in Process (WIP); Finished Goods Inventory (FGI)
Throughput: Rate at which jobs “come and go” through the process (jobs/time)
Capacity: production rate (maximum throughput) that could be achieved if there
were no idling due to lack of work. (jobs/time)
Operations Management
Capacity Analysis: Paul’s Pizza Process
45
Operations Management
Two-server Serial System
46
Operations Management
Two-server Serial System: Starvation
Paul is the bottleneck! George is starved!
47
Operations Management
Two-server Serial System: Blockage
George is the bottleneck! Paul is blocked!
48
Operations Management
Utilization and Bottleneck
rate in
, which represents the fraction of time
capacity
a resource is busy processing entities
•
Utilization =
•
Bottleneck = station in a routing with the highest utilization
limits the capacity of the system
“A chain is only as strong as its weakest link”
Operations Management
Utilization Example
• Customers arrive at a bank every 10 minutes (i.e., at a rate of 6 per hour).
• A single teller processes each customer in 5 minutes (i.e., at a rate of 12
per hour).
customers
in system 1
0
0
• Utilization =
5
rate in
capacity
10
15
20
25
=
= 50%
6 per hour
12 per hour
30
35
40
45
50
Operations Management
Definition of Bottleneck
Why do we use highest utilization instead of slowest to
define the bottleneck?
u=
Station 2
Station 1
18 per hour
= 90%
20 per hour
18 per hour
u ( 2) =
= 75%
24 per hour
u(2)  u(1)
u(1) =
5 min
rate in =18 per hour
rate in
capacity
3 min
5 min
• Station 2 is slower than station 1, but has more machines.
• Station 2 can serve 2×12 = 24 units/hr.
• Station 1 can only serve 1×20 = 20 units per hour!
• The bottleneck is the station that limits how large “rate in” can be.
51
Operations Management
Definition of Bottleneck
Why do we use highest utilization instead of slowest to
define the bottleneck?
u=
Station 1
Station 2
75%
rate in = 10/hr
5 min
6 min
25% (yield loss)
rate in
capacity
10 per hour
= 83%
12 per hour
10 per hour  0.75
u ( 2) =
= 75%
10 per hour
u(2)  u(1)
u(1) =
• Station 2 is slower.
• But Station 1 processes more work.
• Since Station 1 is busier, it is the bottleneck.
• Again, the bottleneck determines how large “rate in” can be.
52
Operations Management
Practice Problem #1
1.
Axle housings are produced in the Wriston Detroit plant on a line
consisting of five stations, through which all housings flow. Axles arrive
to the line at a rate of 5 per hour. Assuming that the number of
machines per station and the average processing times of machines are
given below (note that we assume no detractors, such as failures, setups,
etc.), find the bottleneck of this line.
Station
No.
Resources
(Machines)
1
2
3
1
2
3
Base process
time
(without
detractors)
10 minutes
20 minutes
15 minutes
53
Operations Management
5-Step Process to Find Process Bottleneck
1. Draw the process flow diagram
2. Find the rate in to each station and write it on the diagram
3. Compute the capacity of each station (including detractors
where applicable) and write it on the diagram
4. Compute utilization for each process step
5. Identify bottleneck = highest utilization process step
54
Operations Management
Capacity Analysis
(Graphical Format): Steps 1 & 2
Flow rate
5/hr
5/hr
1
5/hr
2
5/hr
3
5/hr
4
5
55
Operations Management
Capacity Analysis
(Graphical Format): Steps 3, 4 & 5
Flow rate
(1/10)60 =
6/hr
5/hr
Station Capacity
(2/20)60 =
6/hr
5/hr
(3/15)60 =
12/hr
5/hr
1
2
5/6 = 0.83
5/6 =0.83
(1/8)60
= 7.5/hr
5/hr
3
(2/12)60
=10/hr
5/hr
4
5/12 = 0.42 5/7.5 = 0.66
5
5/10 = 0.50
Station Utilization
56
Operations Management
Capacity Analysis (Table Format)
Station No.
Natural
Resources process
time
(min)
Effective
Unit
Process
time (min)
Effective
Resource
Rate
(entities/hr)
Station
Capacity
(entities/hr)
Demand
Rate
(entities/hr)
Station
Utilization
1
1
10
10
60/10 = 6
6×1=6
5
5/6 = 0.83
2
2
20
20
60/20 = 3
3×2=6
5
5/6 = 0.83
3
3
15
15
60/15 = 4
4 × 3 = 12
5
.42
4
1
8
8
60/8 = 7.5
7.5 × 1 = 7.5
5
.66
5
2
12
12
60/12 = 5
5 × 2 = 10
5
.50
57
Operations Management
Example 2:
Capacity Calculation – Tandem Line
Single Station Calculations
28.25/hr
24.65/hr
32.12/hr
26/hr
B
1. Compute station rate for each station in line.
2. If there is no yield loss or rework, then capacity of line is equal to
minimum station capacity. This station is the bottleneck.
3. However, if there is yield loss or rework, then bottleneck is not
necessarily slowest station. For this case or any other where more
than one work flow exists, we must use the “never-fail” definition of
the bottleneck – highest utilization.
Take-away: Only in simplest cases will bottleneck be the slowest station.
To be safe, always find bottleneck via utilization!
58
Operations Management
Example 3:
Bottlenecks in Complex Systems
u = 38%
15%
u=
= 79%
71%
u
u = 76%
81%
u = 66%
u = 92%
88% u = 61%
55%
u = 58%
72%
u = 85%
94%
B
B
Note: Arrival rates may depend on product mix.
Hence, bottleneck may float.
59
Operations Management
Calculating Raw Process Time for a Line
te(1) = 6.37 min
te(2) = 12.16 min
te(3) = 1.87 min
te(4) = 2.31 min
6.37
12.16
1.87
+ 2.31
T0 = 22.71 min
Raw Process Time
1. Compute effective process time (te) at each station.
(Note that adding parallel resources at a station does NOT reduce the effective process
time, since parts are only worked on by one resource at a time)
2. Add up effective process times along the routing to get raw process
time (T0)
Operations Management
Looking Forward
• In actual systems, throughput is less than capacity
and cycle time (flow time) is greater than raw
process time.
• Why?
• Variability!!
OPS
EYES
61
Operations Management
The Operations Prism
62
Operations Management
Takeaways from Today’s Class
• How operations structure is related to corporate
strategy
• Product/Process matrix
• Efficient Frontier
• Wriston Manufacturing case
• Capacity, Utilization, Bottleneck
Takeaway question: What is the capacity of a Tandem
line or Network?
63
Operations Management
For Next Time:
• In Class 3 we will discuss National Cranberry Case
~
~
~
CT Chapters 2-3: read as case prep
National Cranberry is a group case (3/4 students)
Form your case group!
Practice problems, case instructions, hints and templates
on Blackboard
64
Operations Management
Session 2
Professor Arnab Bisi, PhD
1
Operations Management
Course Roadmap
1. Operations Strategy
2. Process Analysis and Design
3. Managing Flows
4. Managing Variability
5. Inventory Management
6. Toyota Production System
7. Operations in a Networked World
2
Operations Management
Utilization and Bottleneck
•
Utilization =
flow rate , which represents the fraction of time
capacity
a resource is busy processing entities
•
Bottleneck
limits the capacity of the system
station in a routing with the highest utilization
“A chain is only as strong as its weakest link”
Operations Management
Utilization Example
• Customers arrive at a bank every 10 minutes (i.e., at a rate of 6 per hour).
• A single teller processes each customer in 5 minutes (i.e., at a rate of 12
per hour).
Inv(t)
customers in
1
system
0
t
0
• Utilization =
5
flow rate
capacity
10
15
20
25
=
= 50%
6 per hour
12 per hour
30
35
40
45
Operations Management
Definition of Bottleneck
Why do we use highest utilization instead of slowest to define the
bottleneck?
Station 2
Station 1
rate in =18 per hour
3 min
OR
5 min
5 min
rate in
capacity
18 per hour
u(1) =
= 90%
20 per hour
18 per hour
u(2) =
= 75%
24 per hour
u(2) < u(1) u= • Station 2 is slower than station 1, but has more machines. • Station 2 can serve 2×12 = 24 units/hr. • Station 1 can only serve 1×20 = 20 units per hour! • The bottleneck is the station that limits how large "rate in" can be. 5 Operations Management Capacity Analysis Practice Problem Agents at an MVA office can process a driver's license application in four minutes. What is the capacity of a single agent? 1. 2. 3. 4. 5. 6. 4 minutes 15 minutes 30 minutes 4 per hour 15 per hour 20 per hour 6 Operations Management Capacity Analysis Practice Problem If the capacity of an individual agent is 15 per hour and the desk is staffed by 5 operators, what is the capacity of the desk? 1. 2. 3. 4. 5. 3 minutes 3 per hour 15 per hour 75 per hour none of the above 7 Operations Management Capacity Analysis Practice Problem Customers arrive at a rate of 50 per hour. All of them first go to the desk (capacity 75 per hour), but only 60% of them must also go to the photograph station (capacity 50 per hour). What is the utilization of the photograph station? 1. 2. 3. 4. 5. 50% 60% 67% 75% 100% 50 / hr 75 /hr 60% Arrival rate = 50/hr Desk Photo 40% (yield loss) 8 Operations Management Basic Process Vocabulary •Inventory: The number of flow units in the system •Activity times: how long does the worker spend on the task? •Capacity=1/activity time: how many units can the worker make per unit of time If there are m workers at the activity: Capacity=m/activity time •Throughput (Flow rate)=Minimum{Demand rate, Process Capacity} •Utilization =Flow Rate / Capacity •Bottleneck: process step with the highest utilization •Process capacity: capacity of the bottleneck •Cycle Time (Flow Time): The time it takes a flow unit to go through the process 9 Operations Management House Building Flow Diagram Production Control/Slitting Roof Press Roof Fold Base Press Base Subassembly Final Assembly Quality Control Customer 10 Supervisor Material Handler Final Assembly Roof Press Base Press Customer Production Control Roof Lot Size = 4Operations Management Base House roo Quality Control 11 Operations Management Roof Press 12 Operations Management Base Press 13 Operations Management Final Assembly 14 Operations Management Part I: Inventory Buildup Diagram 15 Operations Management A Simple Process Capacity C Demand rate, D [units/hr] [units/hr] ... ... ... ... ... • Demand Rate: rate at which materials or orders enter the system • What happens if: ~ ~ Demand Rate < Capacity : Stable system Demand Rate > Capacity : let’s see . . .
16
Operations Management
Q1: Inventory Buildup
Suppose Slitter releases bases at rate 240 per hour between 7
am and 5 pm. The capacity rate of Base Press is 200 per hour.
How many “unpressed” bases will be on the Base Presser’s desk
at 8 am?
1.
2.
3.
4.
5.
6.
240
200
150
100
40
inventory will not build up
From 7 am to 8 am, 240 bases arrived
to Base Presser’s desk, but only 200
were “pressed.”
=> 40 bases left unpressed at 8 am!!
17
Operations Management
Q2: Inventory Buildup
Suppose the (unpressed) bases buildup rate between 7 am and
5 pm is 40 per hour and the maximum amount of bases that can
be held at the desk is 400. At what time will the inventory
buffer (desk) become full?
1.
2.
3.
4.
5.
6.
7.
1 pm
2 pm
3 pm
4 pm
5 pm
6 pm
never
• total units=400 bases, build-up rate = 40 bases/hr
• 400 bases/(40 bases/hr) = 10 hr
18
Operations Management
Q3: Inventory Draw Down
Suppose the arrival rate stops at 5 pm, at which time the
inventory buffer (desk) is full with 400 bases. If the Base Press
capacity is 200 per hour, what time will the inventory buffer
become empty?
1.
2.
3.
4.
5.
6.
7.
6:00 pm
6:30 pm
7:00 pm
7:30 pm
8:00 pm
8:30 pm
never
19
Operations Management
Inventory Buildup Diagram
Inventory
Buffer
size
400
Time
7 am
5 pm
7pm
20
Operations Management
Q4: Inventory Buildup Diagram
Suppose Capacity = 100 / hr, Demand varies over time as depicted below, and there is infinite room
for holding inventory. Draw a diagram depicting inventory over time (an “inventory build-up
diagram”).
200
Demand
Rate
50
5pm
7pm
9pm
1am
7pm
9pm
1am
Time
200
Inventory
100
5pm
Time
21
Operations Management
Inventory Build-up and Throughput Rate
Inventory Build-up
– Demand Rate < Capacity » No inventory build-up – Demand Rate > Capacity
» Inventory Build-up at rate: Demand Rate – Capacity
Throughput Rate (Flow Rate):
The minimum of capacity and demand rate
22
Operations Management
Utilization and Utilization Profile
• (Implied) Utilization:
Demand rate / Capacity
• Utilization profile:
Utilization calculated for all activities,
entered on the process diagram
30%
96%
62%
28%
126%
23
Operations Management
Alternate Utilization Measure
(Actual) Utilization:
Throughput Rate/ Capacity
Note:
• Because Throughput Rate ≤ Capacity, Actual Utilization
will always be ≤ 100%
• In contrast, because Demand could exceed Capacity,
Implied Utilization can be ≥ 100%
• When making a utilization profile you can use either
Actual or Implied Utilization. To avoid ambiguity you
should not mix the two.
24
Operations Management
Part II:
Flow Time, Throughput Rate, and Inventory
(Little’s Law)
25
Operations Management
Actual Flow Time
• Actual flow time: All the time unit spends in the stage
or system (includes waiting)
• Theoretical flow time:
Minimum time if no wait
• Flow time efficiency:
Theoretical flow time / Actual flow time
26
Operations Management
Burned: Four year wait for
hospital appointment
(BBC news 1/11/2001)
• Barry Roberts has a painful lump on his neck.
• He was referred to a consultant at St James’ Hospital, Leeds.
• However, it took three months for a letter to arrive from the
hospital – and when it did, it informed him that he would have to wait
209 weeks for a meeting with a consultant plastic surgeon.
• “This is absolutely amazing, I could not believe it”
– Barry Roberts
BBC news 12/22/2004:
2006 target waiting time = 52 weeks!
27
Operations Management
Flow Time (In) Efficiency: Averages
Industry
Process
Life Insurance
Average
Flow Time
Theoretical Flow Time
Flow Time Efficiency
New Policy
Application
72 hrs.
7 min.
0.16%
Consumer
Packaging
New Graphic
Design
18 days
2 hrs.
0.14%
Commercial Bank
Consumer
Loan
24 hrs.
34 min.
2.36%
Hospital
Patient Billing
10 days
3 hrs.
3.75%
Automobile
Manufacture
Financial
Closing
11 days
5 hrs
5.60%
28
Operations Management
Little’s Law:
A Fundamental Law of Operations
T = time (in system)
I = inventory
R = rate (of throughput)
I=R×T
It may be little, but it’s the law!
29
Operations Management
Little’s Law: I = R × T
Inventory = Throughput rate × Flow time
Process
R = 2 cust/sec
T = 3 seconds
I = R x T = 2 cust/sec x 3 sec = 6 customers
30
Operations Management
Little’s Law: I = R × T
• Based on physical law: conservation of mass
• Holds for a broad range of processes
• Relates the averages of three key performance measures
• Any two parameters together determine the third
• Can’t change just 1 parameter!
…
… …
Inventory I
[units]
… …
Throughput, R
Cycle Time, T [hr]
[units/hr]
31
Operations Management
Applying Little’s Law
• Idea: Infer something difficult to measure from data that are
easier to collect
~ e.g., perhaps want (Avg.) Time spent in system, but you
only have data on (Avg.) Throughput Rate and (Avg.)
Inventory
• Applications: We will see LL examples in variety of settings
~ People, inventory, money, etc.
~ Examples are similar in spirit, but differ in terms of what is
“flowing” through system (customers, widgets, dollars)
~ To avoid trouble identifying T, I, R, explicitly write your
units (respectively time, quantity, and quantity/time)
32
Operations Management
Little’s Law Applied to a Restaurant
Customer Flow:
Customers arrive at Ouzo Bay at the average rate of 20
customers/hour. On average there are 30 customers in the
restaurant. How long does each customer spend at Ouzo Bay
on average?
Find: T
Known data: I = 30 cust, R = 20 cust/hour
I = RT
T = I/R = (30 cust)/(20 cust/hour)
= 1.5 hours
33
Operations Management
Little’s Law Applied to Professional Services
Job Flow:
A GEICO claim service center processes 10,000 claims per year. The
average processing time is 3 weeks. Assuming 50 weeks in a year,
what is the average number of claims “in process?”
R = 10,000 claims/yr, so R = 200 claims/ week
T = 3 weeks
I = 600 claims
34
Operations Management
Little’s Law Applied to Assembly Line
WIP Flow:
At the Foxconn final assembly line in Shenzhen, a new iPhone is
finished every 60 seconds. At any moment in time there are 10
iPhones on the line. How long does it take to assemble an iPhone?
R = 1 iPhone/min
I = 10 iPhones
T = I/R = 10 iPhones/(1 iPhone/min) = 10 minutes
35
Operations Management
Little’s Law Applied to Facility Assessment
Days on the lot:
A car dealership near Washington DC reports annual sales of $60 million. The
average selling price of a car is $50,000. If the picture below represents an average
snapshot of the dealership （160 cars）, how many days on average do their cars sit
before being sold?
Solution:
There are about 160 cars in the picture. I = 160.
We need to measure R in terms of cars, and the
dealer sells 60,000,000/50,000 = 1,200 cars/yr
Thus, T = I/R = 160 cars/(1,200 cars/yr) =
0.13 years (about 49 days).
36
Operations Management
Improvements Based on Little’s Law
• Usually want increased system responsiveness
• This means same or better throughput, shorter flow
time
• Shorter flow times require increased R or decreased I
• [therefore] Identify what causes inventory / flow time to
grow. What levers can we use to decrease it?
37
Operations Management
Inventory Buildup Diagram and Little’s Law
Suppose Capacity = 100 / hr, Demand varies over time as depicted below, and there is infinite room for
holding inventory. Draw a diagram depicting inventory over time (an “inventory build-up diagram”).
What is the average throughput in the 8-hour
period between 5pm and 1am?
200
Demand
Rate
Input: (50×2+200×2+50×4)/8=87.5 per hour
50
5pm
Output: (50×2+100×6)/8=87.5 per hour
7pm
9pm
1am
How long does each unit of inventory stay in the
system on average?
Little’s Law!
R=87.5 per hour,
I = AREA/T = (6×200/2)/8=75,
T= I/R=75/87.5 = 0.857 hours
≈51 minutes
200
Inventory
(or backlog)
100
5pm
Time
7pm
9pm
1am
Time
38
Operations Management
Myth
“The airport security line is always long; I must wait forever.”
I = R×T
39
Operations Management
For Next Time
• CT Chapters 2-3: read as case prep
• National Cranberry Case (group assignment):
~
~
~
~
Template on Canvas
Follow the template!
Submit on Canvas one hour before the start of Class 3
by only one of your group members
Submit as MSWord file (not as pdf file)
40
Operations Management
Session 3
Professor Arnab Bisi, PhD
Operations Management
Course Roadmap
1. Operations Strategy
2. Process Analysis and Design
3. Managing Flows
4. Managing Variability
5. Inventory Management
6. Toyota Production System
7. Operations in a Networked World
2
Operations Management
National C