curs operatiuni

Introduction

Prof. Christian Terwiesch

Operations in a Restaurant


Operations in an Emergency Room


Operations from the Perspective of the Customer


Four Dimensions of Performance

Cost▪ Efficiency

Quality▪ Product quality (how good?)

▪ Process quality (as good▪ Process quality (as good as promised?)

Time▪ Responsiveness to

demand

Variety▪ Customer heterogeneity

Important for- Performance measurement- Defining a business strategy


Four Dimensions of Performance: Measurements for a Sandwich Store

Cost▪ Efficiency


▪ Process quality (as good as promised?)

Time▪ Responsiveness to demand

p )

Variety▪ Customer heterogeneity ▪ Responsiveness to demand▪ Customer heterogeneity


IntroductionEfficient Frontier


Four Dimensions of Performance: Trade-offs

Cost▪ Efficiency▪ Measured by:


=> Price▪ Process quality (as good- cost per unit

- utilization

▪ Process quality (as good as promised?)=> Defect rate

Time▪ Responsiveness to

Variety▪ Customer heterogeneity p

demand▪ Measured by:

- customer lead time- flow time

Customer heterogeneity▪ Measured by:

- number of options- flexibility / set-ups

make to order


- flow time- make-to-order

What Can Ops Management (This Course) Do to Help? Step 1: Help Making Operational Trade-Offs

ResponsivenessHigh

Very short waiting times,Comes at the expense ofFrequent operator idle time

Trade-off Long waiting times,

yet operators are almostfully utilized

Example: Call center of a large retail bank

Labor Productivity(e.g. $/call)

Low

Low laborproductivity

High laborproductivity

y

Example: Call center of a large retail bank- objective: 80% of incoming calls wait less than 20 seconds - starting point: 30% of incoming calls wait less than 20 seconds- Problem: staffing levels of call centers / impact on efficiency


OM helps: Provides tools to support strategic trade-offs

What Can Ops Management (This Course) Do to Help?Step 2: Overcome Inefficiencies

Responsiveness

HighCurrent frontier

Eliminate inefficiencies

In the industry

Competitor A

Low

Competitor C

Competitor B




Competitor B

Example:• Benchmarking shows the pattern above• Don’t just manage the current system… Change it!

Provides tools to identify and eliminate inefficiencies => Define Efficient Frontier


Types of inefficiencies:-Poor process design- Inconsistencies in activity network

What Can Ops Management (This Course) Do to Help?Step 3: Evaluate Proposed Redesigns/New Technologies

Responsiveness

HighHigh

Redesignprocess

Current frontierNew frontier

LowIn the industry

Labor Productivity( $/ )

Low labor High labor

Example:• What will happen if we develop / purchase technology X?

Better technologies are al a s (?) nice to ha e b t ill the pa ?

(e.g. $/call)productivity productivity


• Better technologies are always (?) nice to have, but will they pay?

OM helps: Evaluates system designs before they occur

Example: The US Airline Industry


IntroductionFormat of the course


Course Outline / Grading / Homework

Objective of the course: Understanding and improving business processes

Performance measuresHow-to

Mix of industries: healthcare restaurants automotive computers call centers banking etcMix of industries: healthcare, restaurants, automotive, computers, call centers, banking, etc

Course OutlineIntroduction (0.5 weeks)1. Process analysis (1.5 weeks)2. Productivity3. Product variety 4. Responsiveness 5. Quality

Requirements / Prerequisites: There are no prerequisites for the course

Some modules require statistical knowledge (standard deviation, normal distribution)

Homework assignmentsOne large assignment after each module (five assignments); 10% each

Final exam with questions from all modules; 50%


q ;

Text Book

Course book Cachon, Gerard, Christian Terwiesch, Matching Supply with Demand: An Introduction to Operations Management, 3rd edition, Irwin - McGraw Hill, 2012 (ISBN 978-0073525204, 507 pages)


Personal IntroductionMBA core course: Operations Management: Quality and Productivity

Taught ~ 60 times ~ 4000 MBA students

McKinsey Ops Practice ~ 500 new associates

Research: Operations Management, focus on Healthcare Management

Innovation tournaments and contests

Christian Terwiesch [email protected]

Andrew M. Heller Professor at the Wharton SchoolSenior Fellow Leonard Davis Institute for Health Economics

573 Jon M. Huntsman Hall


Philadelphia, PA 19104.6366

Process AnalysisI d i / Th hIntroduction / The three measures


Subway – Sitting in Front of the Store



25 Minutes later….


Processes: The Three Basic Measures

• Flow rate / throughput: number of flow units going through the process per unit of time

• Flow Time: time it takes a flow unit to go from the beginning to the end of the process

• Inventory: the number of flow units in the process at a given moment in time

• Flow Unit: Customer or SandwichFlow Unit: Customer or Sandwich


Process Analysis: The Three Measures

Immigration department Champagne MBA program Auto company

Applications

Approved or rejected cases

Processing time

Bottle of champagne

Bottles sold per year

Time in the cellar

Student

Graduating class

2 years

Car

Sales per year

60 daysProcessing time

Pending cases

Time in the cellar

Content of cellar

2 years

Total campus population

60 days

Inventory


Summary

When observing a process always aim to understand the three process measuresWhen observing a process, always aim to understand the three process measures

• Flow rate / throughput: number of flow units going through the process per unit of time

Flow Time: time it takes a flow unit to go from the beginning to the end of the process• Flow Time: time it takes a flow unit to go from the beginning to the end of the process

• Inventory: the number of flow units in the process at a given moment in time

In the next session we will discuss what drives these measuresIn the next session, we will discuss what drives these measures

We will then find out that the three measures are related to each other


Process AnalysisFinding the bottleneck


Process Analysis

In this session, we will take you INSIDE the black box

Specifically, you will learn how to:

1. Create a process flow diagram

2. Find the bottleneck of the process and determine the maximum flow rate

3 Conduct a basic process analysis3. Conduct a basic process analysis


Subway – Inside the Store


Drawing a Process Flow Diagram


Drawing a Process Flow Diagram

Customers Station 1 Station 2 Station 3

Symbols in a process flow diagram

Difference between project management and process management


Basic Process Vocabulary

• Processing times: how long does the worker spend on the task?

• Capacity=1/processing time: how many units can the worker make per unit of timeIf there are m workers at the activity: Capacity=m/activity time

• Bottleneck: process step with the lowest capacity

• Process capacity: capacity of the bottleneck

• Flow rate =Minimum{Demand rate, Process Capacity)

• Utilization =Flow Rate / Capacity

• Flow Time: The amount of time it takes a flow unit to go through the process

• Inventory: The number of flow units in the system


Inventory: The number of flow units in the system

Process AnalysisLabor productivity measures


Labor Productivity MeasuresTi

me

a2

a4

Bottleneck=Idle Time =Processing time

a1

Pro

cess

ing

a• Cycle time CT= 1/ Flow Rate

Di t L b C t t

Labor Productivity Measures

P a3 Direct Labor Content=p1+p2+p3+p4If one worker per resource:

Direct Idle Time=(CT-p1) +(CT-p2) +(CT-p3)

A l b tili ti1 2 3 4

• Capacityi =

Review of Capacity CalculationsResources ofNumber i

time idle direct content labor content labor

• Average labor utilization

Capacityi

• Process Capacity=Min{Capacityi}

• Flow Rate = Min{Demand Capacity}

iTime Processing

timeofunitperRateFlow time of unit perwages Total

• Cost of direct labor


Flow Rate Min{Demand, Capacity}

• Utilizationi=iCapacity

Rate Flow

p

Example: Assembly Line with Six Stations

3 min/unit 5 min/unit 2 min/unit 3 min/unit 6 min/unit 2 min/unit


Insert Excel analysis of Subway line here


100%

The Role of Labor Costs in Manufacturing: The Auto Industry

70%

80%

90%

100%

QualityWarrantyOverheadOther

30%

40%

50%

60%

Purchasedparts andassemblies

Parts andmaterialcosts Logistics costs

Assembly and otherLabor costs

0%

10%

20%

30%

Fi l I l di I l di R ll d

Material costs

Final Assembler’s cost

IncludingTier 1Costs

IncludingTier 2Costs

Rolled-upCosts over~ 5 Tiers

• While labor costs appear small at first, they are importantlook relative to value added- look relative to value added

- role up costs throughout the value chain

• Implications


- also hunt for pennies (e.g. line balancing) - spread operational excellence through the value chain

Source: Whitney / DaimlerChrysler

Process AnalysisLittle’s Law


Processes: The Three Key Metrics


Little’s law: It’s more powerful than you think...

What it is: Inventory (I) = Flow Rate (R) * Flow Time (T)

How to remember it: - units

Implications:• Out of the three fundamental performance measures (I,R,T), two can be chosen by

management, the other is GIVEN by nature• Hold throughput constant: Reducing inventory = reducing flow time

Given two of the three measures, you can solve for the third:• Indirect measurement of flow time: how long does it take you on average to respond to an email?

You write 60 email responses per dayYou have 240 emails in your inbox


Examples for Little’s Law Applications

In a large Philadelphia hospital, there are 10 births per day.80% of the deliveries are easy and require mother and baby to stay for 2 days20% of the cases are more complicated and require a 5 day stay

What is the average occupancy of the department?


Source: Graves and Little

Little’s law: Some remarks

Not an empirical law

Robust to variation, what happens inside the black box

Deals with averages – variations around these averages will exist

Holds for every time window

Shown by Professor Little in 1961


Process AnalysisInventory Turns / Inventory costs


Inventory Turns

Cost of Goods sold: 25,263 mill $/yearInventory: 2,003 mill $

Cost of Goods sold: 20,000 mill $/yearInventory: 391 mill $Inventory: 391 mill $

Inventory TurnsComputed as: COGSComputed as:

Based on Little’s law

Inventory COGS

Inventory turns=


Based on Little s lawCareful to use COGS, not revenues

Inventory Turns At Dell

90

100

60

70

80

40

50

60

10

20

30

0

10

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010


Inventory Turns in Retailing and Its Link to Inventory Costs

Inventory Cost Calculation

Compute per unit inventory costs as:

P it I t t = costsinventory AnnualPer unit Inventory costs=turnsInventory

y

Example:Example:

• Annual inventory costs=30%• Inventory turns=6

Per unit Inventory costs= %5year per turns 6

year per 30%


Source: Gaur, Fisher, Raman

Process AnalysisBuffer or Suffer


Simple Process Flow – A Food TruckFood Truck Every five minutes:

- You get 0, 1, or 2 orders with equal probability- You have a capacity of 0, 1, or 2 with equal probability- It is not possible to make a sandwich before the order - Customers are not willing to wait

=> How many sandwiches will you sell per five minute slot?


Variability Will Be a Key Factor in Waiting Time

Why variability does not always average itself out

Buffer-or-suffer strategy


Buffering is easier in production settings than in services (make to order vs make to stock)Preview two different models: Queue and Newsvendor

Difference Between Make-to-Order and Make-to-StockMcDonald’s

1. Make a batch of sandwiches2. Sandwiches wait for customer orders3 Customer orders can filled immediately

Subway1. Customer orders2. Customer waits for making of sandwich3 Customer orders can filled with delay3. Customer orders can filled immediately

=> Sandwich waits for customer3. Customer orders can filled with delay

=> Customer waits for sandwich

Which approach is better?Which approach is better?

Make-to-Stock advantages include:+ Scale economies in production+ Rapid fulfillment (short flow time for customer order)+ Rapid fulfillment (short flow time for customer order)

Make-to-Order advantages include:+ Fresh preparation (flow time for the sandwich)+ Allows for more customization (you can’t hold all versions+ Allows for more customization (you can t hold all versions

of a sandwich in stock)+ Produce exactly in the quantity demanded


Examples of Demand Waiting for Supply

Service Examples ER Wait Times: 58-year-old Michael Herrara of Dallas died of a heart attack

after an estimated 19 hours in the local Hospital ERSome ER’s now post expected wait times online / via Apps

It takes typically 45 days do get approval on a mortgage; Strong link between wait times and conversionW iti ti f d i th h t M D ld’ 159 d L Waiting times for drive-through at McDonald’s: 159 seconds; Long queues deter customers to join

Production ExamplesProduction Examples• Buying an Apple computer • Buying a Dell computer

=> Make-to-order vs Make-to-Stock> Make to order vs Make to Stock


http://www.minyanville.com/businessmarkets/articles/drive-thrus-emissions-fast-food-mcdonalds/5/12/2010/id/28261

Five Reasons for Inventory

Pipeline inventory: you will need some minimum inventory because of the flow time >0

Seasonal inventory: driven by seasonal variation in demand and constant capacity

Cycle inventory: economies of scale in production (purchasing drinks)

Safety inventory: buffer against demand (Mc Donald’s hamburgers)

Decoupling inventory/ buffers: buffers between several internal steps


Source: De Groote

Process AnalysisMultiple flow units


Processes with Multiple Flow Units

Contact faculty/other persons

Foreign Dep.m=2

20 min/app

3 cases per hour11 cases per hour4 cases per hour EZ form

Regular

Foreign acc.

File

Contact prioremployers Confirmation

Filem=1

3 min/app Print invoicem=1

Department 1m=3employers

Benchmarkgrades

Confirmationletter2 min/app

m 315 min/app

Department 2m=2

8 min/app8 min/app


Approach 1: Adding-up Demand Streams


Approach 2: A Generic Flow Unit (“Minute of Work”)


Steps for Basic Process Analysis with Multiple Types of Flow Units

1. For each resource, compute the number of minutes that the resource can produce

2. Create a process flow diagram, indicating how the flow units go through the processthe process

3. Create a table indicating how much workload each flow unit is consuming at each resource

4 Add up the workload of each resource across all flow units4. Add up the workload of each resource across all flow units.5. Compute the implied utilization of each resource as

The resource with the highest implied utilization is the bottleneck


Note: you can also find the bottleneck based on calculating capacity for each step and then dividing the demand at this resource by the capacity

Processes with Attrition Loss

500 ideas70/500 20/70 6/20 2/6

Where is the Bottleneck?

Pitches Scripts Pilots New Series

Showsper year

Processing time 2 days 10 days 30 days 70 days 200 daysProcessing time 2 days 10 days 30 days 70 days 200 days

Resources 5 judges 3 script writers 2 pilot teams 2 Series crews 1 Main crew(250 days per year)


ProductivityIntroduction


Productivity as a Major Challenge

“The conservation of our national resources is only preliminary to the larger question of ti l ffi i [ t b US id t]”national efficiency. [quote by a US president]”

Who is the president quoted here?

I thi d l S b + Ai liIn this module: Subway + Airlines


Introduction to Productivity

Published in 1911

Opens with a discussion of Theodore Roosevelt’s address about improving national efficiency and making more productive use of limited resources

“We can see and feel the waste of material things. Awkward, inefficient, or ill-directed movements of men, however, leave nothing visible or tangible behind”

“Employers derive their knowledge of how much of a given class of work can be done in a day from eitherEmployers derive their knowledge of how much of a given class of work can be done in a day from either their own experience, which has frequently grown hazy with age, from casual and unsystematic observation of their men, or at best from records [..]”

“This work is so crude and elementary in its nature that the writer firmly believes that it would be possible to t i i t lli t ill t b ffi i t i i h dl th b ”train an intelligent gorilla so as to become a more efficient pig-iron handler than any man can be”

Often, 3x productivity improvements were obtained through waste reduction, picking the right men/tool for the job, and setting the ride incentives


Formal Definitions

Basic definition of productivityBasic definition of productivityProductivity = Units Output produced / Input used

Example: Labor productivityL b d ti it 4 it l b h (l k l t lik i ti )Labor productivity = 4 units per labor hour (looks a lot like an processing time)

Multifactor productivityProductivity = Output / (Capital$ + Labor$ + Materials$ + Services$ + Energy$)y p ( p $ $ $ $ gy$)

Waste and InefficienciesOutput: productive time; input: total timeSome measures of productivity have natural limits (e g labor time energy)Some measures of productivity have natural limits (e.g. labor time, energy)What reduces productivity?


ProductivityEfficient Frontier


The Efficient Frontier

Responsiveness

HighCurrent frontier

Eliminate inefficiencies

In the industry

Competitor A

Low

Competitor C

Competitor B

Competitor D




Competitor B

There exists a tension between productivity and responsiveness

Efficient frontier


Example: The US Airline Industry


ProductivityThe Seven Sources of Waste


OverproductionTo produce sooner or in greater quantities than ExamplesTo produce sooner or in greater quantities than what customers demand

• Overproduced items need to be stored (inventory) and create further waste

• Bad for inventory turns

p

81.6 kg of food are trashed by the average

Bad for inventory turns• Products become obsolete / get stolen / etc

g y gGerman

61% of the trashing happens by households

Large package sizes is the main reasonLarge package sizes is the main reason

Match Supply with Demand


TransportationExamplesUnnecessary movement of parts or people pUnnecessary movement of parts or people

between processesExample: Building a dining room and kitchen at opposite ends of a house, then keeping it that way

• Result of a poor system design and/or layout• Can create handling damage and cause

production delays

Crabs fished in the North Sea

Shipped 2,500km South to Morocco

Produced in MoroccoProduced in Morocco

Shipped back to Germany

R l tRelocate processes, then introduce standard sequences for transportation


ReworkExamplesRepetition or correction of a process pRepetition or correction of a process

Example: Returning a plate to the sink after it has been poorly washed

• Rework is failure to meet the “do it right the first time” expectationtime expectation

• Can be caused by methods, materials, machines, or manpower

• Requires additional resources so that normal production is not disrupted

Readmissions to the ICU in a hospital (also called “Bounce backs”)

Readmissions to the hospital afterReadmissions to the hospital afterdischarge (major component of AffordableCare Act)

Analyze and solve rootAnalyze and solve root causes of rework=> More in quality module


Over-processingExamplesProcessing beyond what the customer requires pProcessing beyond what the customer requires

Example: Stirring a fully mixed cup of coffee

• May result from internal standards that do not reflect true customer requirements

• May be an undesirable effect of an operator’s pride inMay be an undesirable effect of an operator s pride in his work

Keeping a patient in the hospital longer than what is medically required

Provide clear, customer-driven standards for every process


MotionExamplesUnnecessary movement of parts or people within pUnnecessary movement of parts or people within

a process

Example: Locating (and keeping) a refrigerator outside the kitchen

• Result of a poor work station design/layout• Focus on ergonomics

Ergonomics

Look at great athletes

Arrange people and parts around stations with work content that has been standardized to

i i i ti


minimize motion

InventoryExamplesNumber of flow units in the system pNumber of flow units in the system

• “Product has to flow like water”• For physical products, categorized in: raw material,

WIP, or finished productsWIP, or finished products • Increases inventory costs (bad for inventory turns)• Increases wait time (see above) as well as

the customer flow time• Often times, requires substantial real estate

Loan applications at a bank

=> the BIGGEST form of waste

I d tiImprove production control system and commit to reduce unnecessary “comfort stocks”


WaitingExamplesUnderutilizing people or parts while a process pUnderutilizing people or parts while a process

completes a work cycleExample: Arriving an hour early for a meeting

Labor utilizationIdle timeIdle time

Note: - Waiting can happen at the resource (idle time)- But also at the customer level (long flow time)

Often, the time in the waiting room exceedsthe treatment time by more than 5x

Understand the drivers of waiting; more in Responsiveness module

Prof. Christian Terwiesch16

Wasteful vs LeanThe IMVP Studies

General Motors Framingham Assembly Plant Versus Toyota Takaoka Assembly Plant, 1986

GM Framingham Toyota TakaokaGross Assembly Hours per Car 40.7 18Assembly Defects per 100 Cars 130 45Assembly Space per Car 8.1 4.8Inventories of Parts (average) 2 weeks 2 hours

Gross assembly hours per car are calculated by dividing total hours of effort in the plant by the total number of cars producedDefects per car were estimated from the JD Power Initial Quality Survey for 1987Assembly Space per Car is square feet per vehicle per year, corrected for vehicle sizeInventories of Parts are a rough average for major parts


Source: Womack et al

Understand Sources of Wasted Capacity

Poor use of capacity Waste of the Resource’s time

Overproduction Transportation Over-processing MotionRework

Poor use of capacity – Waste of the Resource s time

The seven sources of waste (Muda)

Potential eighth source of waste: The waste of intellect

WaitingInventory

Not “orthogonal to each other”

Poor flow – Waste of Customer’s time

• Taichi Ohno Chief Engineer at Toyota• Taichi Ohno, Chief Engineer at Toyota• The first five sources are RESOURCE centric (and correspond to capacity): • Ask yourself: “What did I do the last 10 minutes? How much was value-add?”

Look around at the work-place (360 degree) – what percentage of people are working?• The last two sources are FLOW UNIT centric (and correspond to Flow Time and Inventory)


The last two sources are FLOW UNIT centric (and correspond to Flow Time and Inventory)• Ask yourself: “Did I really have to be here that long?”

ProductivityLink to Finance


Revisiting the Process Flow Diagram at Subway

Customers Station 1 Station 2 Station 3

Processing Time 37 sec/cust 47 sec/cust 37 sec/cust


Subway – Financial Importance of Operations


ProductivityKPI trees


Subway – EBIT tree


ProductivityOEE F k / Q ilOEE Framework / Quartile Analysis


Overall Equipment Effectiveness

100

55

100

Improve-ment potential

30

5545 > 3x

Net opera-ting time

Idlingand minorstop

Re-ducedspeed

OEEDefects Start-upAvail-able time

Break-down

Change-overs*

Total planned up-time

timestop-pages

Downtime lossesAvailability rate55 %

Speed lossesPerformance rate82 %

X X = OEE30 %

Quality lossesQuality rate67 %


55 % 82 % 30 %67 %

Source: McKinsey

OEE of an Aircraft

65*2

4h

t gat

e or

in

aint

enan

ce

3 At ma

book

ed

axi a

nd la

ndin

g

Not

bTa

Total timeIn a year

Block time Seat isIn the air

Value add(about 30%)


n

Overall People Effectiveness

Vaca

tion

Sic

k

Tim

e no

t bo

oked

Can

cela

tions

ents

that

don

’t e

to s

ee M

D

that

don

’t be

don

e by

MD

C

Pat

ieha

ve

Act

iviti

es

have

to b

Total paid time Time in practice Time booked For appointments

Time withpatients

True valueadd time

Prof. Christian Terwiesch Source: Marcus, Terwiesch, Werner

ProductivityLi b l i / iLine balancing / capacity sizing


Staffing / Capacity Sizing

So far: we started the process analysis with the process flow diagram / capacities

Often, demand can change over timeAt Subway: More customers at noon than at 3pm

Typical situation in practice – Given are:Demand (forecasts)Activities that need to be completed

Decision situation: how to build a staffing plan?

Two strategies:Production smoothing (pre-produce)Staff to demand


Line Balancing and Staffing to Demand

4545

Time46

Time

45

30

Takt45

3737

1 2 3

Operator

1 2 3

Operator

Labor content: 120 seconds / unit

3,600 sec/hourTakt: 3,600sec / 80 units=45 sec/unit

Target manpower= 120 sec/unitLabor content: 120 seconds / unitDemand: 80 units per hour

Target manpower=

= 2.67 => round up

St ff t d d t t ith th t kt ti d d i th f th

45 sec/unit


=> Staff to demand: start with the takt time and design the process from there

What Do You Do When Demand Doubles?Ideal Case Scenario

Time

22.5Takt

1 2 3

Operator

3,600 sec/hourT kt 3 600 / 160 it 22 5 / it

4 5 6

Labor content: 120 seconds / unitDemand: 160 units per hour

Takt: 3,600sec / 160 units=22.5 sec/unit

Target manpower=

= 5 33 => round up

120 sec/unit22.5 sec/unit


= 5.33 => round up

Balancing the Line

Determine Takt time

Assign tasks to resource so that total processing times < Takt time

Make sure that all tasks are assignedg

Minimize the number of people needed (maximize labor utilization)

What happens to labor utilization as demand goes up?

Difference between static and dynamic line balancing


Line Balancing and Staffing to DemandActual DemandVolume

Time

60

30

Takt time 2 minutes

Step1

Step2

Step3

Step4

Step5

Step6

Leveled DemandVolume

60 60Takt time 1 minute

S S S S S S

Takt time*Takt

30

Step1

Step2

Step3

Step4

Step5

Step6

Takt

1 1

2

Volume flexibilityAbility to adjust to changing demands

Resource planningManpower

6 6

Ability to adjust to changing demands

Often implemented with temporary workers

Keeps average labor utilization high


3

ProductivityQ il l i /Quartile analysis / Standardization


Call Center Example

Two calls to the call center of a big retail bank

Both have the same objective (to make a deposit)

Different operatorsDifferent operators

Take out a stop watch

Time what is going on in the calls.


Beyond Labor Utilization: Quartile Analysis

Bi t d ti it diff f k l d i t t k


Biggest productivity differences for knowledge intense tasks

Source: Immaneni and Terwiesch

Example: Emergency Department

Analyzed data for over 100k patients in three hospitals

80 doctors and 109 nurses

Up to 260% difference between the 10th %-tile and the 90th %-tile

=> Dramatic productivity effects


Source: McCarthy, Ding, Terwiesch, Sattarian, Hilton, Lee, Zeger

ProductivityProductivity Ratios


Basic definitions of productivity

Productivity = Output units produced / Input used

Problems:Output is hard to measure=> often times, use revenue insteadMultiple input factors (Labor, Material, Capital) => use one cost category

Example:Labor productivity at US Airways 1995: Revenue: $6.98B Labor costs: $2.87B2011: Revenue: $13.34B Labor costs: $2.41B

Labor productivity at SouthWest1995: Revenue: $2.87B Labor costs: $0.93B2011: Revenue: $13.65B Labor costs: $4.18B


Basic definitions of productivity

But WHY is one firm more productive than the other?

The ratio alone does not tell! Use the following trick:

Airline example:Revenue / labor costs = Revenue/RPM * RPM/ASM * ASM / Employee * Employees/Labor costs

Revenue/Cost= Revenue/Output * Output/Capacity * Capacity/Cost

Operational yield Transformationefficiency

1/unit cost of capacityefficiency capacity


Labor Productivity Comparison between Southwest and US Airways


Do Calculations in Excel

ProductivityReview Session


Tom and JerryTom and Jerry run an ice cream business out of their condo in Solana Beach, CA. They have purchased a fully automated ice cream making machine from Italy (at a $30k price tag) that they put in their basement. T i lli i d J t th i k Oft ti h th t f iTom is selling ice cream and Jerry operates the ice cream maker. Often times, however, they run out of ice cream and so Jerry suggested purchasing a second ice cream maker.

Tom, however, wants to first look at the usage of the current ice cream maker and suggests an Overall Equipment Effectiveness (OEE) analysis. Preliminary data suggests that:q p ( ) y y gg• Jerry is not particularly skilled at programming the machine, which needs to be done when a new

batch of ice cream gets made. Instead of spending a negligible time per set-up, he presently spends 20 minutes. A batch of ice cream takes 1h in the machine, once the machine is set-up.

• A new batch is only started if there exists sufficient time to complete the batch the same day before 7pm (including the 20 minute set up and the 1h production)7pm (including the 20 minute set-up and the 1h production)

• Since Jerry started dating a woman from the WWF, he is fascinated by energy efficiency. So he turns the machine off when he goes home at 7pm. As a result of this, the next morning, the machine has to be cooled down to its desired operating temperature, which takes from 7am to 8am.

• Jerry is also not particularly diligent at following the recipe that Tom’s aunt in Italy had sent them. So roughly one quarter of the produced ice cream has to be thrown away.

• Every other Friday, Jerry prefers to go surfing rather than showing up for work. On those days, the business has to stay closed.

TJ1: How many good batches of ice cream are produced each day Jerry comes to work?TJ1: How many good batches of ice cream are produced each day Jerry comes to work?TJ2: What is the OEE of the ice cream maker? (use 12h per day as the available time)


Preliminary data suggests that:• Jerry is not particularly skilled at programming the machine, which needs to be done when a new

batch of ice cream gets made. Instead of spending a negligible time per set-up, he presently spends 20 i t A b t h f i t k 1h i th hi th hi i t20 minutes. A batch of ice cream takes 1h in the machine, once the machine is set-up.

• A new batch is only started if there exists sufficient time to complete the batch the same day before 7pm (including the 20 minute set-up and the 1h production)

• Since Jerry started dating a woman from the WWF, he is fascinated by energy efficiency. So he turns the machine off when he goes home at 7pm. As a result of this, the next morning, the machine has to g p gbe cooled down to its desired operating temperature, which takes from 7am to 8am.

• Jerry is also not particularly diligent at following the recipe that Tom’s aunt in Italy had sent them. So roughly one quarter of the produced ice cream has to be thrown away.

• Every other Friday, Jerry prefers to go surfing rather than showing up for work. On those days, the business has to stay closedbusiness has to stay closed.

TJ1: How many good batches of ice cream are produced each day Jerry comes to work?

TJ2: What is the OEE of the ice cream maker? (use 12h per day as the available time)


Penne PestoPenne Pesto is a small restaurant in the financial district of San Francisco. Customers order from a variety of pasta dishes. The restaurant has 50 seats and is always full during the four hours in the evening. It is not possible to make reservations at Penne; most guests show up spontaneously on their way home from work. p ; g p p y yIf there is no available seat, guests simply move on to another place. On average, a guest spends 50 minutes in the restaurant, which includes 5 minutes until the guest is seated and the waiter has taken the order, an additional 10 minutes until the food is served, 30 minutes to eat, and 5 minutes to handle the check-out (including waiting for the check, paying, and leaving). It takes the restaurant another 10 minutes to clean the table and have it be ready for the next guests (of which there are always plenty) The averageclean the table and have it be ready for the next guests (of which there are always plenty). The average guest leaves $20 at Penne, including food, drink, and tip (all tips are collected by the restaurant, employees get a fixed salary).

The restaurant has 10 waiters and 10 kitchen employees, each earning $90 per evening (including any preparation, the 4 hours the restaurant is open, and clean-up). The average order costs $5.50 in materials, including $4.50 for the food and $1 for the average drink. In addition to labor costs, fixed costs for the restaurant include $500 per day of rent and $500 per day for other overhead costs.

The restaurant is open 365 days in the year and is full to the last seat even on weekends and holidaysThe restaurant is open 365 days in the year and is full to the last seat even on weekends and holidays. There is about $200,000 of capital tied up in the restaurant, largely consisting of furniture, decoration, and equipment.

Define the return on invested capital as the ratio of the profits (PER YEAR) and the invested capital. You can O C S O C “ ” fdraw an ROIC tree in the same way that we drew a KPI tree in class. Simply have the ROIC as “the root” of

the tree instead of profits. Then answer the following questions.

a. How many guests will the restaurant serve in one evening?b. What is the Return on Invested Capital (ROIC) for the owner of the restaurant?


b. What is the Return on Invested Capital (ROIC) for the owner of the restaurant? c. Assume that you could improve the productivity of the kitchen employees and free up one person who would be helping to clean up the table. This would reduce the clean-up to 5 minutes instead of 10 minutes. What would be the new ROIC?

Assign Tasks to WorkersConsider the following six tasks that must be assigned to four workers on a conveyor-paced assembly line (i.e., a machine-paced line flow). Each worker must perform at least one task.

Time to Complete Task (seconds / unit)Task 1 30Task 2 25Task 3 35Task 4 40Task 5 15Task 6 30

The current conveyor-paced assembly line configuration assigns the workers in the following way:The current conveyor paced assembly line configuration assigns the workers in the following way:• Worker 1: Task 1• Worker 2: Task 2• Worker 3: Tasks 3, 4• Worker 4: Tasks 5, 6

a. What is the capacity of the current line?b. Now assume that tasks are allocated to maximize capacity of the line, subject to the conditions that (1) a worker can only perform two adjacent operations and (2) all tasks need to be done in their numerical order. What is the capacity of this line now?p yc. Now assume that tasks are allocated to maximize capacity of the line and that tasks can be performed in any order. What is the maximum capacity that can be achieved?d. After focusing on capacity in questions a-c, you now want to factor in demand in questions d-e. Demand is 50 units per hour. What is the takt time?e What is the target manpower?


e. What is the target manpower?f. How many workers will you need?


Customer ChoiceIntroduction


Customer Choice for HP DeskJet Printers

How many HP printers are there on Amazon?

Why are there so many?

HP Deskjet printer (a look at Amazon)1000 line2000 line3000 line

3050 Printer Series3050 All-in-One3050A Wireless All-in-One

4000 line5000 line6000 line

=> A printer for every day of the year…


Customer Choice in Henry Ford’s Days

Henry Ford: “You can have any color of a car, as long as it is black”

Why did Ford not offer color?Actually, he didProduction reasons to keep the cars (a) in one color (b) black

In this module, we discuss different types of product variety; we discuss the benefits, butalso explore the costs associated with variety

End of intro lecture


Forms of Variety - Fit Based Variety

Customers differ in shirt sizes

Each customer has a unique utility maximizing shirt size

The further you go away (in either direction) from that point, the lower the utility

Hotelling’s linear city

Example: sizes, locations, arrival times

Source: Ulrich


Forms of Variety - Performance Based Variety

Each customer prefers the high end model

Customers differ in their valuation of quality (performance) and/or their ability to pay

Vertical differentiation

Example: screen resolutions, mpg, processor speeds, weight

Source: Ulrich


Forms of Variety - Taste Based Variety

Customers differ in their preferences for taste

Often times, these preferences vary over time

Rugged landscape

Example: taste for food, music, artists


Economic Motives for Variety

Heterogeneous preferences of customers Price discrimination Variety seeking by consumers Avoiding price competition in channel Channel self space Niche saturation and deterrence to market entry

Source: Ulrich


Customer ChoiceImpact on process capacity


Ordering Custom Shirts

Custom shirts ordered online

Large variety of styles

Basically infinitely many sizes

Four weeks lead time

Minimum order: 5 shirts


Cutting DepartmentThe pattern is programmed into a machine and/or a cutting template is created. This takes a certain amount of set-up time IRRESPECTIVE of how many shirts will be produced afterwards.

Sewing DepartmentSewing Section – Cut pieces of fabric are sewn together and inspected Assembly Section - Responsible for assembling shirts and measuring the size.

Finishing DepartmentResponsible for ironing shirts before folding, packaging and delivery to customers.

Custom Tailored Shirts: Production Process

Source: http://hosting.thailand.com/MWT00255/process1.htm


• Example: Cutting Machine for shirts20 minute set-up time (irrespective of the number of shirts)4 minute/unit cutting time15 Shirts in a batch

• Capacity calculation for the resource with set-up changes:

Batch SizeSet-up time + Batch-size*Time per unit

Capacity given Batch Size=

Process Analysis with Batching


Example Calculations

Cutting Section 1 Section 2 Finishing

Set-up time: 20 minutes - - -Processing time: 4 min/unit 40 min/unit 30 min/unit 3 min/unitResources: 1 machine 8 workers 5 workers 1 worker

What is the capacity of the cutting machine with a batch size of 15?


Capacity 1/p

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

10 50 90

130

170

210

250

290

330

370

410

450

490

530

570

610

650

Batch Size

Large Batches are a Form of Scale Economies


Customer ChoiceChoosing a good batch size


Production with large batches Production with small batches

CycleInventory

End ofMonth

Beginning ofMonth

CycleInventory

End ofMonth

Beginning ofMonth

Produce Sedan

Produce Station wagon


CycleInventory

End ofMonth

Beginning ofMonth

CycleInventory

End ofMonth

Beginning ofMonth

Produce Sedan



CycleInventory

End ofMonth

Beginning ofMonth

CycleInventory

End ofMonth

Beginning ofMonth

Produce Sedan



CycleInventory

End ofMonth

Beginning ofMonth

CycleInventory

End ofMonth

Beginning ofMonth

Produce Sedan


• Large batch sizes lead to more inventory in the process• This needs to be balanced with the need for capacity• Implication: look at where in the process the set-up occurs

If set-up occurs at non-bottleneck => decrease the batch sizeIf set-up occurs at the bottleneck => increase the batch size

The Downside of Large Batches


Example Calculations

Cutting Section 1 Section 2 Finishing

Set-up time: 20 minutes - - -Processing time: 4 min/unit 40 min/unit 30 min/unit 3 min/unitResources: 1 machine 8 workers 5 workers 1 worker


- one cart every 10 seconds- 2 sec boarding time per passenger- 2 sec exit time per passenger- 2 minutes to go down the elevator

Batch Size120sec + Batch-size*4sec


Batch Size120sec + Batch-size*4sec

1/10 [units/sec] =

Batch Size = 20 units

How to Set the Batch Size – An Intuitive Example


• Batching is common in low volume / high variety operations• Capacity calculation changes:

• This reflects economies of scale (similar to fix cost and variable cost)• You improve the process by:

Setting the batch size:(a) If set-up occurs at the bottleneck => Increase the batch size(b) If set-up occurs at a non-bottleneck => Reduce the batch size(c) Find the right batch size by solving equation

Process Analysis with Batching: Summary




Customer ChoiceUnderstanding the Diseconomies of Scale Extra inventory



CycleInventory

End ofMonth

Beginning ofMonth

CycleInventory

End ofMonth

Beginning ofMonth

Produce Sedan



CycleInventory

End ofMonth

Beginning ofMonth

CycleInventory

End ofMonth

Beginning ofMonth

Produce Sedan



CycleInventory

End ofMonth

Beginning ofMonth

CycleInventory

End ofMonth

Beginning ofMonth

Produce Sedan



CycleInventory

End ofMonth

Beginning ofMonth

CycleInventory

End ofMonth

Beginning ofMonth

Produce Sedan


• Large batch sizes lead to more inventory in the process• This needs to be balanced with the need for capacity

The Downside of Large Batches


General Definition of a BatchProduct A: Demand is 100 units per hourProduct B: Demand is 75 units per hour

The production line can produce 300 units per hour of either product

It takes 30 minutes to switch the production line from A to B (and from B to A)

How would you set the batch size?


Introducing a Third Product into the Product LineConsider a company that has two products, product A and product B.

Product A: Demand is 100 units per hourProduct B: Demand is 75 units per hour

The production line can produce 300 units per hour of either product (takt time: 12 sec/unit)

It takes 30 minutes to switch the production line from A to B (and from B to A)



Required Flow Rate =

Batch Size1 hour+ Batch-size/300 hour

175 units per hour =

Batch size = 420

Batch size for A= 420 * 100 / (100+75) = 240Batch size for B=420-240=180


Introducing a Third Product into the Product LineNow, the Marketing folks of the company add a third product. Total demand stays the same.

Product A1: Demand is 50 units per hourProduct A2: Demand is 50 units per hourProduct B: Demand is 75 units per hour



Introducing a Third Product into the Product LineNow, the Marketing folks of the company add a third product. Total demand stays the same (maybe they dothis because they can raise prices). Say they offer product A in two colors.

Product A1: Demand is 50 units per hourProduct A2: Demand is 50 units per hourProduct B: Demand is 75 units per hour



Required Flow Rate =

Batch Size1.5 hour+ Batch-size/300 hour

175 units per hour =

Batch size = 630

Batch size for A1= 630* 50 / (50+50+75) = 180Batch size for A2= 630* 50 / (50+50+75) = 180Batch size for B= 630* 75 / (50+50+75) = 270


Customer ChoicePooling Effects / Demand Fragmentation


Demand Fragmentation

You have 3 products (different shirt sizes)

Demand for each product could be 1, 2, or 3 with equal (1/3) probability

How good is your forecast FOR YOUR OVERALL SALES?


Customer ChoiceBuilding Flexibility: SMED / Heijunka


The 6-stage SMED approach

Source: McKinsey Ops Training Material

Before/after shutdown During shutdownStage

Measure total changeover time

1

Determine internal and external activities

2

Move external activities to before or after the shutdown

3

Improve the internal activities

4

Improve the external activities

5

ExternalInternal

Standardize procedures6

Reduce set-up so that you can change models as often as needed => Mixed model production (Heijunka)

Prof. Christian Terwiesch Source: Jordan and Graves

Full Flexibility

Prof. Christian Terwiesch Source: Jordan and Graves

Flexibility vs Chaining

Prof. Christian Terwiesch Source: Moreno and Terwiesch

Pooling vs ChainingFord’s manufacturing network Nissan’s manufacturing network

Chaining is a form of partial flexibility (“pooling” light)Does not require full flexibility, but relies on a clever product-to-plant assignment


Customer ChoiceStrategies to deal with variety / Investing in flexibility


Design for supply chain performance

Source: Ulrich


Isolate the variable elements of the product

vs.

Source: Ulrich


Customer ChoiceLimits to customization


Introduction

Design Variables Performance Specifications User Needs/ utility function

User Utility

processor

display

memory

package

XGA / SXGA / UXGA

video card

hard drive

portability

gaming performance

Informationon screen

View from distance

MS-office performance

affordability

Resolution

price

Physical dimensions

Frames per second

HD capacity

Viewable area

RAM

Instructions per second (MIPS)

Data storage potential

Integrated devices

Design Variables Performance Specifications User Needs/ utility function

User Utility

processor

display

memory

package

XGA / SXGA / UXGA

video card

hard drive

portability

gaming performance

Informationon screen

View from distance

MS-office performance

affordability

Resolution

price

Physical dimensions

Frames per second

HD capacity

Viewable area

RAM

Instructions per second (MIPS)

Data storage potential

Integrated devices

Source: Randall, Terwiesch, Ulrich


Introduction


Customer ChoiceReview Session


Window BoxesMetal window boxes are manufactured in two process steps: stamping and assembly. Each window box is made up of three pieces: a base (one part A) and two sides (two part Bs).

The parts are fabricated by a single stamping machine that requires a setup time of 120 minutes whenever switching between the two part types. Once the machine is set up, the processing time for each part A is one minute while the processing time for each part B is only 30 seconds.

Currently, the stamping machine rotates its production between one batch of 360 for part A and one batch of 720 for part B. Completed parts move from the stamping machine to the assembly only after the entire batch is complete.

At assembly, parts are assembled manually to form the finished product. One base (part A) and two sides (two part Bs), as well as a number of small purchased components, are required for each unit of final product. Each product requires 27 minutes of labor time to assemble. There are currently 12 workers in assembly. There is sufficient demand to sell every box the system can make.

a. What is the capacity of the stamping machine?

b. What is the capacity of the overall process?

c. What batch size would you recommend for the process?


(Gelato) Bruno Fruscalzo decided to set up a small production facility in Sydney to sell to local restaurants that want to offer gelato on their dessert menu. To start simple, he would offer only three flavors of gelato: fragola(strawberry), chocolato (chocolate), and bacio (chocolate with hazelnut). Demand is 10kg/hour for Fragola, 15 for chocolate, and 5 for Bacio.

Bruno first produces a batch of fragola, then a batch of chocolato, then a batch of bacio and then he repeats that sequence. After producing bacio and before producing fragola, he needs 45 minutes to set up the ice cream machine, he needs 30 minutes to change to Chocolato and 10 minutes to change to Bacio.

When running, his ice cream machine produces at the rate of 50 kg per hour no matter which flavor it is producing (and, of course, it can produce only one flavor at a time).

a. Suppose Bruno wants to minimize the amount of each flavor produced at one time while still satisfying the demand for each of the flavors. (He can choose a different quantity for each flavor.) If we define a batch to be the quantity produced in a single run of each flavor, how many kilograms should he produce in each batch?

b. Given your answer in part (a), how many kilograms of fragola should he make with each batch?


SmartPhoneApfel is a German company selling smart-phones. Presently, the company is only selling a 64GB model. The marketing department recently proposed to add a 128 GB model. Preliminary data suggests that (a) the margins for the product will increase (b) the total sales will remain the same and will be split 50:50 between the two models (c) there exists a mild positive correlation in the demand between the two models.

Consider the following statements:1. The coefficient of variation of the 64GB phone will go down2. The coefficient of variation of the 64GB phone will stay constant3. The coefficient of variation of the 64GB phone will go up4. It would be nice for the production and distribution process if the memory component, which is

the only difference between the two models, would be inserted early in the process.5. It would be nice for the production and distribution process if the memory component, which is

the only difference between the two models, would be inserted late in the process.

Which of the above statements is true?

1+41+52+42+53+43+5

Response TimeIntroduction


ExamplePhysician office

- Patients arrive, on average, every five minutes- It takes ten minutes to serve a patient- Patients are willing to wait

What is the implied utilization of the barber shop?

How long will patients have to wait?


ExamplePhysician office

- Patients arrive, on average, every five minutes- It takes four minutes to serve a patient- Patients are willing to wait

What is the utilization of the barber shop?

How long will patients have to wait?


A Somewhat Odd Service Process

Patient

ArrivalTime

ServiceTime

1 0 4

2

3

4

5

10

15

4

4

44

5

6

15

20

25

4

4

4

7

8

9

30

35

40

4

4

4

10

11

12

45

50

55

4

4

4


7:00 7:10 7:20 7:30 7:40 7:50 8:00

12 55 4

A More Realistic Service Process

Patient

ArrivalTime

ServiceTime

1 0 5

Patient 1 Patient 3 Patient 5 Patient 7 Patient 9 Patient 11

Patient 2 Patient 4 Patient 6 Patient 8 Patient 10 Patient 12

1

2

3

0

7

9

5

6

7

Time

7:10 7:20 7:30 7:40 7:50 8:007:00

4

5

6

12

18

22

6

5

2 3

7

8

9

25

30

36

4

3

4

2

case

s

9

10

11

36

45

51

4

2

20

1

Num

ber o

f


12 55 3 2 min. 3 min. 4 min. 5 min. 6 min. 7 min.

Service times

PatientArrivalTime

ServiceTime

Variability Leads to Waiting Time

Service time

Patient

1234

07912

5676

Wait time

5678

18222530

5243

7:00 7:10 7:20 7:30 7:40 7:50 8:00

89101112

3036455155

34223 7:00 7:10 7:20 7:30 7:40 7:50

5

4

8:0012 55 3

Inventory

3

2

1


y(Patients atlab) 0

7:00 7:10 7:20 7:30 7:40 7:50 8:00

The Curse of Variability - Summary

Variability hurts flowWith buffers: we see waiting times even though there exists excess capacity

Variability is BAD and it does not average itself outy g

New models are needed to understand these effects


W i i i d l ThResponse TimeWaiting time models: The need for excess capacity


Modeling Variability in Flow

OutflowN l iti l

Flow RateMinimum{Demand, Capacity} = Demand = 1/a

ProcessingBuffer

No loss, waiting onlyThis requires u<100%Outflow=Inflow

InflowDemand process is “random”

Look at the inter-arrival timesProcessingp: average processing time

a: average inter-arrival timeSt Dev(inter arrival times)

TimeIA1 IA2 IA3 IA4 Same as “activity time” and “service time”

CVp = St-Dev(processing times)

Average(processing times)

CVa =

Often Poisson distributed:CVa = 1Constant hazard rate (no memory)

St-Dev(inter-arrival times)Average(inter-arrival times) Can have many distributions:

CVp depends strongly on standardizationOften Beta or LogNormal


Exponential inter-arrivals

Difference between seasonality and variability

Average flowtime T

Flow rate

The Waiting Time Formula

Inflow Outflow

Inventorywaiting Iq

Increasing VariabilityEntry to system DepartureBegin Service

Theoretical Flow Time

Utilization 100%

Time in queue Tq Service Time p

Flow Time T=Tq+pUtilization 100%

Waiting Time Formula

22 CVCVnutilizatio

Variability factor

21

pa CVCVnutilizatio

nutilizatioTimeActivity queue in Time


Service time factor

Utilization factor

Example: Walk-in Doc

Newt Philly needs to get some medical advise. He knows that his Doc, Francoise, has a patient arrive every 30 minutes (with a standard deviation of 30 minutes). A typical consultation lasts 15 minutes (with a standard deviation of 15 minutes). The Doc has an open-access policy and does not offer appointments.

If Newt walks into Francois’s practice at 10am, when can he expect to leave the practice again?


Summary

Even though the utilization of a process might be less than 100%, it might still require long customer wait time

Variability is the root cause for this effect

As utilization approaches 100%, you will see a very steep increase in the wait time

If you want fast service, you will have to hold excess capacity


M W i i i d l /Response TimeMore on Waiting time models / Staffing to Demand


Inventory

Waiting Time Formula for Multiple, Parallel Resources

Inflow Outflow

Inventorywaiting Iq

in service Ip

Inflow OutflowFlow rate

E t t t D tB i S iEntry to system DepartureBegin Service

Time in queue Tq Service Time p

Flow Time T=Tq+p

221)1(2 m CVCVnutilizatiotimeActivity

Waiting Time Formula for Multiple (m) Servers


21pa CVCV

nutilizationutilizatio

mtimeActivityqueue in Time

Example: Online retailer

Customers send emails to a help desk of an online retailer every 2 minutes, on average, and the standard deviation of the inter-arrival timeminutes, on average, and the standard deviation of the inter arrival time is also 2 minutes. The online retailer has three employees answering emails. It takes on average 4 minutes to write a response email. The standard deviation of the service times is 2 minutes.

Estimate the average customer wait before being served.


ServerFlow unitUtilization (Note: make sure <1)

Summary of Queuing Analysis

amp

pmau 1*

1

Inventory

Utilization (Note: make sure <1)

CVCV

p

221)1(2

Inventorywaiting Iq

in service Ip

Time related measures

q

pam

q

pTT

CVCVu

umpT

21

221)1(2

Inflow Outflow

TI *1Inventory related measures (Flow rate=1/a)

qp

p

qq

III

muI

Ta

I

*

*

Entry tosystem

DepartureBeginService


qpWaiting Time Tq Service Time p

Flow Time T=Tq+p

Staffing Decision

Customers send emails to a help desk of an online retailer every 2 minutes, on average, and the standard deviation of the inter-arrival timeminutes, on average, and the standard deviation of the inter arrival time is also 2 minutes. The online retailer has three employees answering emails. It takes on average 4 minutes to write a response email. The standard deviation of the service times is 2 minutes.

How many employees would we have to add to get the average wait time reduced to x minutes?


What to Do With Seasonal DataMeasure the true demand data Apply waiting model in each sliceApply waiting model in each slice

Slice the data by the hour (30min, 15min)Slice the data by the hour (30min, 15min)

Level the demandAssume demand is “stationary” within a slice


Service Levels in Waiting Systems

0.8

1Fraction of customers who have to wait xseconds or less Waiting times for those customers

h d t t d i di t l

90% of calls had to wait 25 seconds or less

0.4

0.6

who do not get served immediately

Fraction of customers who get served

0

0.2

0.4 Fraction of customers who get served without waiting at all

00 50 100 150 200

Waiting time [seconds]

• Target Wait Time (TWT)• Service Level = Probability{Waiting TimeTWT}• Example: Big Call Center

- starting point / diagnostic: 30% of calls answered within 20 seconds


starting point / diagnostic: 30% of calls answered within 20 seconds- target: 80% of calls answered within 20 seconds

Response TimeCapacity Pooling


I d d t R

Managerial Responses to Variability: PoolingIndependent Resources

2x(m=1) Example:Processing time=4 minutesInter-arrival time=5 minutes (at each server)m=1 Cva=CVp=1m 1, Cva CVp 1

Tq =

Pooled Resources(m=2) Processing time=4 minutes

Inter-arrival time=2.5 minutesm=2, Cva=CVp=1

Tq =Tq =


Managerial Responses to Variability: Pooling

Waiting Time Tq

50.00

60.00

70.00

m=1

30.00

40.00

m=2

0.00

10.00

20.00m=5

m=10

0.0060% 65% 70% 75% 80% 85% 90% 95%

Utilization u


Pooling: Shifting the Efficient Frontier


Summary

What is a good wait time?

Fire truck or IRS?


Limitations of Pooling

Assumes flexibility

Increases complexity of work-flowIncreases complexity of work flow

Can increase the variability of service time

I t t th l ti hi ith th t / f t th tInterrupts the relationship with the customer / one-face-to-the-customer

Group clinicsGroup clinics

Electricity grid / smart grid

Flexible production plants


The Three Enemies of Operations

Additional costs due to variability in demand and activity times

Is associated with longer wait times

Use of resources beyond what is needed to meet customer requirements• Not adding value to the productIs associated with longer wait times

and / or customer loss

Requires process to hold excess capacity (idle time)

Variability

Not adding value to the product, but adding cost

• Reducing the performance of the production system

• 7 different types of waste

Waste

capacity (idle time) yp

Inflexibility

WasteWork Value-adding


C tAdditional costs incurred because of supply demand mismatches• Waiting customers or• Waiting (idle capacity)

Capacity

Customerdemand


Waiting (idle capacity)

Response TimeScheduling / Access


Managerial Responses to Variability: Priority Rules in Waiting Time Systems

• Flow units are sequenced in the waiting area (triage step)• Flow units are sequenced in the waiting area (triage step)

• Provides an opportunity for us to move some units forwards and some backwards

• First-Come-First-Serve- easy to implement- perceived fairness- lowest variance of waiting timelowest variance of waiting time

• Sequence based on importance- emergency cases

id tif i fit bl fl it- identifying profitable flow units


Managerial Responses to Variability: Priority Rules in Waiting Time Systems

Service times:A: 9 minutesB: 10 minutesB: 10 minutesC: 4 minutesD: 8 minutesA

B9 min. D

C

4 min.

D

C19 min.

23 min.

Total wait time: 9+19+23=51min

B

A12 min.

21 min.

Total wait time: 4+13+21=38 minTotal wait time: 9+19+23=51min Total wait time: 4+13+21=38 min

• Shortest Processing Time Rule - Minimizes average waiting time- Problem of having “true” processing times


Appointments

•Open Access•Open Access

• Appointment systems


Response TimeRedesign the Service PProcess


Reasons for Long Response Times (And Potential Improvement Strategies)

Insufficient capacity on a permanent basis=> Understand what keeps the capacity low

Demand fluctuation and temporal capacity shortfallsUnpredictable wait times => Extra capacity / Reduce variability in demandPredictable wait times => Staff to demand / Takt timePredictable wait times > Staff to demand / Takt time

Long wait times because of low priority=> Align priorities with customer valueg p

Many steps in the process / poor internal process flow (often driven by handoffs and rework loops)=> Redesign the service process


http://www.minyanville.com/businessmarkets/articles/drive-thrus-emissions-fast-food-mcdonalds/5/12/2010/id/28261

The Customer’s Perspective

20 minutes

How much time does a patient spend on a primary care encounter?

Driving Parking Check‐in Vitals Waiting PCP Appt. Check out Labs Drive home

20 minutes

Two types of wasted time:Auxiliary activities required to get to value add activities (result of process location / lay-out)Wait time (result of bottlenecks / insufficient capacity)

Total value add time of a unitFlow Time Efficiency (or %VAT) =


Total time a unit is in the processFlow Time Efficiency (or %VAT) =

Process Mapping / Service Blue Prints

Customer actions

Walk into the branch / talk to agent

Customer supplies more data

Customer supplies more data

Sign contracts

Line of interaction

Onstageactions

Collect basic information

Request for more data

Request for more data

Explain final documentact o s

Line of visibility

BackstagePre Approval

t

data

Pre Approval tBackstage

actions

Line of internal interaction

process; set up workflow / account responsibility

process; set up workflow / account responsibility

Supportprocesses

Run formal credit scoring model

Prof. Christian Terwiesch Source: Yves Pigneur

Process Mapping / Service Blue PrintsHow to Redesign a Service Process

Move work off the stageExample: online check-in at an airport

Reduce customer actions / rely on support processesy pp pExample: checking in at a doctor’s office

Instead of optimizing the capacity of a resource, try to eliminate the step altogetherExample: Hertz Gold – Check-in offers no value; go directly to the car

Avoid fragmentation of work due to specialization / narrow job responsibilitiesExample: Loan processing / hospital ward

If customers are likely to leave the process because of long wait times, have the wait occurlater in the process / re-sequence the activities

Example: Starbucks – Pay early, then wait for the coffee

Have the waiting occur outside of a lineExample: Restaurants in a shopping malls using buzzersExample: Restaurants in a shopping malls using buzzersExample: Appointment

Communicate the wait time with the customer (set expectations)Example: Disney


Response Time

L M d lLoss Models


Different Models of Variability

Waiting problemsUtilization has to be less than 100%Impact of variability is on Flow Time

Loss problemsDemand can be bigger than capacityImpact of variability is on Flow Rate

Pure waitingproblem, all customersare perfectly patient.

All customers enter the process,some leave due totheir impatience

Customers do notenter the process oncebuffer has reached a certain limit

Customers are lostonce all servers arebusy

Same if customers are patient Same if buffer size=0

S if b ff i i t l lSame if buffer size is extremely large

Variability is always bad – you pay through lower flow rate and/or longer flow time


Buffer or suffer: if you are willing to tolerate waiting, you don’t have to give up on flow rate

Analyzing Loss Systems Resources3 trauma bays (m=3)y ( )

Ambulances / Helicopters

Trauma center moves to diversion status once all servers are busy

Demand Process Service Processy

incoming patients are directed to other locations

One trauma case comes in every 3 hours

(a=3 hours)

Patient stays in trauma bayfor an average of 2 hours

(p=2 hours)(a 3 hours)

a is the interarrival time

Exponential interarrival times

(p 2 hours)

p is the service time

Can have any distribution


Exponential interarrival times Can have any distribution

What is Pm, the probability that all m resources are utilized?

Analyzing Loss Systems: Finding Pm(r)

• Define r = p / a1 2 3 4 5

m

• Example: r= 2 hours/ 3 hoursr=0.67

0.10 0.0909 0.0045 0.0002 0.0000 0.00000.20 0.1667 0.0164 0.0011 0.0001 0.00000.25 0.2000 0.0244 0.0020 0.0001 0.00000.30 0.2308 0.0335 0.0033 0.0003 0.00000.33 0.2500 0.0400 0.0044 0.0004 0.0000

• Recall m=3

• Use Erlang Loss Table

0.33 0.2500 0.0400 0.0044 0.0004 0.00000.40 0.2857 0.0541 0.0072 0.0007 0.00010.50 0.3333 0.0769 0.0127 0.0016 0.00020.60 0.3750 0.1011 0.0198 0.0030 0.00040.67 0.4000 0.1176 0.0255 0.0042 0.00060.70 0.4118 0.1260 0.0286 0.0050 0.0007

r = p / a

• Find that P3 (0.67)=0.02550.70 0.4118 0.1260 0.0286 0.0050 0.00070.75 0.4286 0.1385 0.0335 0.0062 0.00090.80 0.4444 0.1509 0.0387 0.0077 0.00120.90 0.4737 0.1757 0.0501 0.0111 0.00201.00 0.5000 0.2000 0.0625 0.0154 0.0031

Given Pm(r) we can compute:• Time per day that system has to deny access


Time per day that system has to deny access• Flow units lost = 1/a * Pm (r)

Implied utilization vs probability of having all servers utilized: Pooling Revisited

Probability 0.6

utilized: Pooling Revisited

Probabilitythat all serversare utilized

0.4

0.5

m=1m=2

m=5 m=100.2

0.3

m=3 m 10

m=20

0

0.1

Implied utilization0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1


Erlang Loss Tablem

1 2 3 4 5 6 7 8 9 100.10 0.0909 0.0045 0.0002 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.00000.20 0.1667 0.0164 0.0011 0.0001 0.0000 0.0000 0.0000 0.0000 0.0000 0.00000.25 0.2000 0.0244 0.0020 0.0001 0.0000 0.0000 0.0000 0.0000 0.0000 0.00000.30 0.2308 0.0335 0.0033 0.0003 0.0000 0.0000 0.0000 0.0000 0.0000 0.00000.33 0.2500 0.0400 0.0044 0.0004 0.0000 0.0000 0.0000 0.0000 0.0000 0.00000.40 0.2857 0.0541 0.0072 0.0007 0.0001 0.0000 0.0000 0.0000 0.0000 0.0000

Erlang Loss Table0.40 0.2857 0.0541 0.0072 0.0007 0.0001 0.0000 0.0000 0.0000 0.0000 0.00000.50 0.3333 0.0769 0.0127 0.0016 0.0002 0.0000 0.0000 0.0000 0.0000 0.00000.60 0.3750 0.1011 0.0198 0.0030 0.0004 0.0000 0.0000 0.0000 0.0000 0.00000.67 0.4000 0.1176 0.0255 0.0042 0.0006 0.0001 0.0000 0.0000 0.0000 0.00000.70 0.4118 0.1260 0.0286 0.0050 0.0007 0.0001 0.0000 0.0000 0.0000 0.00000.75 0.4286 0.1385 0.0335 0.0062 0.0009 0.0001 0.0000 0.0000 0.0000 0.00000.80 0.4444 0.1509 0.0387 0.0077 0.0012 0.0002 0.0000 0.0000 0.0000 0.00000.90 0.4737 0.1757 0.0501 0.0111 0.0020 0.0003 0.0000 0.0000 0.0000 0.00001.00 0.5000 0.2000 0.0625 0.0154 0.0031 0.0005 0.0001 0.0000 0.0000 0.00001 10 0 5238 0 2237 0 0758 0 0204 0 0045 0 0008 0 0001 0 0000 0 0000 0 00001.10 0.5238 0.2237 0.0758 0.0204 0.0045 0.0008 0.0001 0.0000 0.0000 0.00001.20 0.5455 0.2466 0.0898 0.0262 0.0063 0.0012 0.0002 0.0000 0.0000 0.00001.25 0.5556 0.2577 0.0970 0.0294 0.0073 0.0015 0.0003 0.0000 0.0000 0.00001.30 0.5652 0.2687 0.1043 0.0328 0.0085 0.0018 0.0003 0.0001 0.0000 0.00001.33 0.5714 0.2759 0.1092 0.0351 0.0093 0.0021 0.0004 0.0001 0.0000 0.00001.40 0.5833 0.2899 0.1192 0.0400 0.0111 0.0026 0.0005 0.0001 0.0000 0.00001.50 0.6000 0.3103 0.1343 0.0480 0.0142 0.0035 0.0008 0.0001 0.0000 0.00001.60 0.6154 0.3299 0.1496 0.0565 0.0177 0.0047 0.0011 0.0002 0.0000 0.00001.67 0.6250 0.3425 0.1598 0.0624 0.0204 0.0056 0.0013 0.0003 0.0001 0.0000 Probability{all m servers busy}= 1.70 0.6296 0.3486 0.1650 0.0655 0.0218 0.0061 0.0015 0.0003 0.0001 0.00001.75 0.6364 0.3577 0.1726 0.0702 0.0240 0.0069 0.0017 0.0004 0.0001 0.0000

r = p/a 1.80 0.6429 0.3665 0.1803 0.0750 0.0263 0.0078 0.0020 0.0005 0.0001 0.00001.90 0.6552 0.3836 0.1955 0.0850 0.0313 0.0098 0.0027 0.0006 0.0001 0.00002.00 0.6667 0.4000 0.2105 0.0952 0.0367 0.0121 0.0034 0.0009 0.0002 0.00002.10 0.6774 0.4156 0.2254 0.1058 0.0425 0.0147 0.0044 0.0011 0.0003 0.00012.20 0.6875 0.4306 0.2400 0.1166 0.0488 0.0176 0.0055 0.0015 0.0004 0.00012.25 0.6923 0.4378 0.2472 0.1221 0.0521 0.0192 0.0061 0.0017 0.0004 0.00012.30 0.6970 0.4449 0.2543 0.1276 0.0554 0.0208 0.0068 0.0019 0.0005 0.0001

y{ y}

!)( 21 rrrmr

rP m

m

m 2.30 0.6970 0.4449 0.2543 0.1276 0.0554 0.0208 0.0068 0.0019 0.0005 0.00012.33 0.7000 0.4495 0.2591 0.1313 0.0577 0.0220 0.0073 0.0021 0.0005 0.00012.40 0.7059 0.4586 0.2684 0.1387 0.0624 0.0244 0.0083 0.0025 0.0007 0.00022.50 0.7143 0.4717 0.2822 0.1499 0.0697 0.0282 0.0100 0.0031 0.0009 0.00022.60 0.7222 0.4842 0.2956 0.1612 0.0773 0.0324 0.0119 0.0039 0.0011 0.00032.67 0.7273 0.4923 0.3044 0.1687 0.0825 0.0354 0.0133 0.0044 0.0013 0.00032.70 0.7297 0.4963 0.3087 0.1725 0.0852 0.0369 0.0140 0.0047 0.0014 0.00042.75 0.7333 0.5021 0.3152 0.1781 0.0892 0.0393 0.0152 0.0052 0.0016 0.00042.80 0.7368 0.5078 0.3215 0.1837 0.0933 0.0417 0.0164 0.0057 0.0018 0.00052 90 0 7436 0 5188 0 3340 0 1949 0 1016 0 0468 0 0190 0 0068 0 0022 0 0006

!...

!2!11

mrrr

2.90 0.7436 0.5188 0.3340 0.1949 0.1016 0.0468 0.0190 0.0068 0.0022 0.00063.00 0.7500 0.5294 0.3462 0.2061 0.1101 0.0522 0.0219 0.0081 0.0027 0.00083.10 0.7561 0.5396 0.3580 0.2172 0.1187 0.0578 0.0249 0.0096 0.0033 0.00103.20 0.7619 0.5494 0.3695 0.2281 0.1274 0.0636 0.0283 0.0112 0.0040 0.00133.25 0.7647 0.5541 0.3751 0.2336 0.1318 0.0666 0.0300 0.0120 0.0043 0.00143.30 0.7674 0.5587 0.3807 0.2390 0.1362 0.0697 0.0318 0.0130 0.0047 0.00163.33 0.7692 0.5618 0.3843 0.2426 0.1392 0.0718 0.0331 0.0136 0.0050 0.00173.40 0.7727 0.5678 0.3915 0.2497 0.1452 0.0760 0.0356 0.0149 0.0056 0.00193.50 0.7778 0.5765 0.4021 0.2603 0.1541 0.0825 0.0396 0.0170 0.0066 0.0023


3.60 0.7826 0.5848 0.4124 0.2707 0.1631 0.0891 0.0438 0.0193 0.0077 0.00283.67 0.7857 0.5902 0.4191 0.2775 0.1691 0.0937 0.0468 0.0210 0.0085 0.00313.70 0.7872 0.5929 0.4224 0.2809 0.1721 0.0960 0.0483 0.0218 0.0089 0.00333.75 0.7895 0.5968 0.4273 0.2860 0.1766 0.0994 0.0506 0.0232 0.0096 0.00363.80 0.7917 0.6007 0.4321 0.2910 0.1811 0.1029 0.0529 0.0245 0.0102 0.00393.90 0.7959 0.6082 0.4415 0.3009 0.1901 0.1100 0.0577 0.0274 0.0117 0.00464.00 0.8000 0.6154 0.4507 0.3107 0.1991 0.1172 0.0627 0.0304 0.0133 0.0053

Response Time

R iReview


(My-law.com) My-law.com is a recent start-up trying to cater to customers in search of legal services online. Unlike traditional law firms, My-law.com allows for extensive interaction between lawyers and their customers via telephone and the Internet This process is used in the upfront part of the customer interaction largely consisting of answeringthe Internet. This process is used in the upfront part of the customer interaction, largely consisting of answering some basic customer questions prior to entering a formal relationship. In order to allow customers to interact with the firm’s lawyers, customers are encouraged to send e-mails to [email protected]. From there, the incoming e-mails are distributed to the lawyer who is currently “on call.” Given the broad skills of the lawyers, each lawyer can respond to each incoming request.

E-mails arrive from 8 A.M. to 6 P.M. at a rate of 10 e-mails per hour (coefficient of variationfor the arrivals is 1). At each moment in time, there is exactly one lawyer “on call,”that is, sitting at his or her desk waiting for incoming e-mails. It takes the lawyer, on average,5 minutes to write the response e-mail The standard deviation of this is 4 minutes5 minutes to write the response e mail. The standard deviation of this is 4 minutes.

a. What is the average time a customer has to wait for the response to his/her e-mail, ignoring any transmission times? Note: This includes the time it takes the lawyer to start writing the e-mail and the actual writing time.

b. How many e-mails will a lawyer have received at the end of a 10-hour day?

c. When not responding to e-mails, the lawyer on call is encouraged to actively pursuecases that potentially could lead to large settlements. How much time on a 10-hour daycan a My-law.com lawyer dedicate to this activity


Jim’s ComputerJim wants to find someone to fix his computer. PC Fixers (PF) is a local service that offers such computer repairs. A new customer walks into PF every 10 minutes (with a standard deviation of 10 minutes). PF has a staff of 5 computer technicians Service times average around 40 minutes (with a standard deviation of 40staff of 5 computer technicians. Service times average around 40 minutes (with a standard deviation of 40 minutes).

JC1. If Jim walks into PF, how long must he wait in line before he can see a technician? (Only include the waiting time, not any service time)

JC2. How many customers will, on average, be waiting for their computer to be fixed?


Real ComputeRealCompute offers real-time computing services. The company owns 4 supercomputers that can be accessed through the internet. Their customers send jobs that arrive on average every 4 minutes (inter-arrival times are exponentially distributed and, thus, the standard deviation of the inter-arrival times is 4 minutes). p y , , )

Each job takes on average 10 minutes of one of the supercomputers (during this time, the computer cannot perform any other work). Customers pay $20 for the execution of each job. Given the time-sensitive nature of the calculations, if no supercomputer is available, the job is redirected to a supercomputer of a partner company called OnComp which charges $40 per job to Real Compute (OnComp always has supercomputer capacitycalled OnComp, which charges $40 per job to Real Compute (OnComp always has supercomputer capacity available).

RC1. What is the probability with which an incoming job can be executed by one of the supercomputers owned by RealCompute?

RC2. How much does RealCompute pay on average to OnComp (in $s per hour)?


ContractorA contractor building houses and doing renovation work has currently six projects planned for the season. Below are the items, and the estimated times to complete them:

New construction at Springfield - 60 daysBathroom remodeling at Herne - 10 daysTraining time for solar roof installation - 2 daysUpdate web-site - 6 daysyRenovation of deck at Haverford - 8 daysNew kitchen at Rosemont - 20 days

Suppose the contractor starts immediately with the first project, no other projects get added to this list, and the contractor sequences them so as to minimize the average time the project waits before it gets started What willcontractor sequences them so as to minimize the average time the project waits before it gets started. What will the contractor be doing in 30 days from the start date of the first project?


Call CenterConsider a call center that has a constant staffing level. Because of increased demand in the morning, the call center has a very high utilization in the morning and a very low utilization in the afternoon. Which of the following will decrease the average waiting time in the call center?

(a) Add more servers(b) Decrease the service time coefficient of variation(c) Decrease the average service time(d) Level the demand between the morning hours and the afternoon hours(d) Level the demand between the morning hours and the afternoon hours (e) All of the above



QualityIntroduction


Quality Introduction

I said that the worst thing about healthcare would be waiting, not true; worst thing are defects

Two dimensions of quality: conformance and performance

Our focus will be on conformance quality

Motivating example: the sinking ship / swiss cheese logic


Assembly Line Defects

Assembly operations for a Lap-top

9 Steps

Each of them has a 1% probability of failure

What is the probability of a defect?


The Duke Transplant Tragedy

Source: http://www.cbsnews.com/2100-18560_162-544162.html

17 year old Jesica Santillan died following an organ transplant (heart+lung)

Mismatch in blood type between the donor and Jesica

Experienced surgeon, high reputation health system

About one dozen care givers did not notice the mismatch

The offering organization did not check, as they had contacted the surgeon with another recipient in mind

The surgeon did not check and assumed the organization offering the organ had checked

It was the middle of the night / enormous time pressure / aggressive time line

A system of redundant checks was in place

A single mistake would have been caught

But if a number of problems coincided, the outcome could be tragic


Swiss Cheese Model

Source: James Reason

Barriers

Example:

3 redundant steps

Each of them has a 1% probability of failure

What is the probability of a defect?


The Nature of Defects

Assembly line example: ONE thing goes wrong and the unit is defective

Swiss cheese situations: ALL things have to go wrong to lead to a fatal outcome

Compute overall defect probability / process yield

When improving the process, don’t just go after the bad outcomes, but also after the internal process variation (near misses)


QualityDefects / impact on flow


Impact of Defects on Flow

5 min/unit

4 min/unit50% defectScrap 6 min/unit


Impact of Defects on Flow

5 min/unit

4 min/unit30% defectRework 2 min/unit


Impact of Defects on Variability: Buffer or Suffer

Processing time of 5 min/unit at each resource (perfect balance)

With a probability of 50%, there is a defect at either resource and it takes 5 extra min/unit at the resource to rework

=> What is the expected flow rate?


The Impact of Inventory on Quality

Inventory takes pressure off the resources (they feel buffered): demonstrated behavioral effects

Expose problems instead of hiding them

Inve

ntor

y in

pro

cess

Buffer argument:“Increase inventory”

Toyota argument:“Decrease inventory”


Operations of a Kanban System: Demand Pull

• Visual way to implement a pull system• Amount of WIP is determined by

number of cards

• Kanban = Sign board • Work needs to be authorized by demandAuthorize

productionof next unit


QualitySix sigma and process capability


Gurkenverordnung:http://de.wikipedia.org/wiki/Verordnung_(EWG)_Nr._1677/88_(Gurkenverordnung)

Failure of a pharmacy

Intro: two types of variability


M&M Exercise

A bag of M&M’s should be between 48 and 52g

Measure the samples on your table:Measure x1, x2, x3, x4, x5Compute the mean (x-bar) and the standard deviationNumber of defects

All data will be compiled in master spread sheetYield = %tage of units according to specificationsHow many defects will we have in 1MM bags?


Process capability measure

• Estimate standard deviation in excel• Look at standard deviation relative to specification limits

3

Upper Specification Limit (USL)

LowerSpecificationLimit (LSL)

X-3A X-2A X-1A X X+1A X+2 X+3A

X-6B X X+6B

Process A(with st. dev A)

Process B(with st. dev B)

6LSLUSLC p

x Cp P{defect} ppm

1 0.33 0.317 317,000

2 0.67 0.0455 45,500

3 1.00 0.0027 2,700

4 1.33 0.0001 63

5 1.67 0.0000006 0,6

6 2.00 2x10-9 0,00

Measure Process Capability: Quantifying the Common Cause Variation


Not just the mean is important, but also the variance

Need to look at the distribution function

The Concept of Consistency:Who is the Better Target Shooter?


QualityTwo types of variation


Common Cause Variation (low level)

Common Cause Variation (high level)

Assignable Cause Variation

• Need to measure and reduce common cause variation• Identify assignable cause variation as soon as possible• What is common cause variation for one person might be

assignable cause to the other

Two Types of Variation


M&M Exercise

Analysis of new sample in production environment

=> Show this in Excel


Time

ProcessParameter

Upper Control Limit (UCL)

Lower Control Limit (LCL)

Center Line

• Track process parameter over time- average weight of 5 bags- control limits- different from specification limits

• Distinguish between- common cause variation

(within control limits)- assignable cause variation

(outside control limits)

Detect Abnormal Variation in the Process: Identifying Assignable Causes


Statistical Process Control

CapabilityAnalysis

ConformanceAnalysis

Investigate forAssignable Cause

EliminateAssignable Cause

Capability analysis • What is the currently "inherent" capability of my process when it is "in control"?

Conformance analysis• SPC charts identify when control has likely been lost and assignable cause

variation has occurred

Investigate for assignable cause• Find “Root Cause(s)” of Potential Loss of Statistical Control

Eliminate or replicate assignable cause• Need Corrective Action To Move Forward


QualityDetect / Stop / Alert


71

2345

68

ITAT=7*1 minute

3

1

2

4

ITAT=2*1 minute

Good unit

Defective unit

Information Turnaround Time

Inventory leads to a longer ITAT (Information turnaround time) => slow feed-back and no learning

Assume a 1 minute processing time


Cost of a Defect: Catching Defects Before the Bottleneck

What is the cost of a defect?

Defect detected before bottleneck

Defect detected after bottleneck

Bottleneck

Buy pasta / ingredients for $2 per meal

Prepare Cook ServeServe food for $20 per meal


Detecting Abnormal Variation in the Process at Toyota: Detect – Stop - Alert

Source: www.riboparts.com, www.NYtimes.com

JidokaIf equipment malfunctions / gets out of control, it shuts itself down automatically to prevent further damageRequires the following steps:

DetectAlertStop

Andon Board / Cord A way to implement Jidoka in an assembly line

Make defects visibly stand out

Once worker observes a defect, he shuts down the line by pulling the andon / cord

The station number appears on the andonboard


Detect, stop, alert

Jidoka

Andon cord

Root-cause

problem-solving

Ishikawa Diagram

Kaizen

Avoid

Poka Yoke

Build-in quality

Two (similar) Frameworks for Managing Quality

Toyota Quality System

CapabilityAnalysis

ConformanceAnalysis

Investigate forAssignable

Cause

EliminateAssignable

Cause

Six Sigma System

Some commonalities:Avoid defects by keeping variation out of the process If there is variation, create an alarm and trigger process improvement actionsThe process is never perfect – you keep on repeating these cycles


QualityProblem solve / improve


Root Cause Problem Solving

Ishikawa Diagram A brainstorming technique of what might have contributed to a problem

Shaped like a fish-bone

Easy to use

Pareto ChartMaps out the assignable causes of a problem in the categories of the Ishikawa diagram

Order root causes in decreasing order of frequency of occurrence

80-20 logic


The Power of Iterative Problem-solvingM

odel

sR

ealit

y


Root Cause Problem Solving

Ishikawa Diagram A brainstorming technique of what might have contributed to a problem

Shaped like a fish-bone

Easy to use

Pareto ChartMaps out the assignable causes of a problem in the categories of the Ishikawa diagram

Order root causes in decreasing order of frequency of occurrence

80-20 logic


ConclusionLean Operations


The Ford Production System

Influenced by Taylor; optimization of work

The moving line / big machinery => focus on utilization

Huge batches / long production runs; low variety

Produced millions of cars even before WW2

Model built around economies of scale=> Vehicles became affordable to the middle class


The Toyota Production System

Toyota started as a maker of automated looms

Started vehicle production just before WW2

No domestic market, especially following WW2

Tried to replicate the Ford model (produced about 10k vehicles)

No success due to the lack of scale

Around 1950, TPS was born and refined over the next 30 years Systematic elimination of waste Operating system built around serving demand


Introduction

19031st car

19081st Model

T

1911F.W.

Taylor

19131st

movingline

19232.1

millionvehicles/

yearCost USD/unit

19161904 1926

950

360 290Key idea of TPS: systematic elimination

of non-value-adding activities

1933Founded

1946Major strike

1950Start of

TPS

1960sSupplierdevelop-

ment

1980sTrans-plants

Mass production driven by economies of scale impossible– Low production volume (1950):

GM 3,656,000 – Toyota 11,000– Low productivity (Japan 1/9 of US)– Lack of resources

Taylorism: Standardized parts and workpatterns (time studies)

Moving line ensuring working at same paceProcess driven by huge, rapid machinery

with inflexible batch production

Source: McKinsey

Key idea of Ford: cost reduction throughcheap labor and economies of scale


Zero non-value added activities (muda)

Production flow synchronized with demand (JIT)One-unit-at-a-time flow

Mixed model production (heijunka)Match production demand based on Takt time

Pull instead of pushSupermarket / KanbanMake-to-order

Quality methods to reduce defectsFool-proofing (poka-yoke) and visual feed-backDetect-stop-alert (Jidoka)

Defects at machines (original Jidoka)Defects in assembly (Andon cord)

Flexibility

Standardization of work

Worker involvementQuality circles (Kaizen)Fishbone diagrams (Ishikawa)Skill development / X-training

Reduction of VariabilityQuartile AnalysisStandard operating procedures

Adjustment of capacity to meet takt-time

Reduce inventory to expose defects

Toyota Production System: An Overview


The Three Enemies of Operations

Is associated with longer wait times and / or customer loss

Requires process to hold excess capacity (idle time)

Buffer or suffer

Often times: quality issues

Variability

Use of resources beyond what is needed to meet customer requirements• 7 different types of waste• OEE framework• Lean: do more with less



Waste

Inflexibility

Additional costs incurred because of supply demand mismatches• Waiting customers or• Waiting (idle capacity)

Capacity

Customerdemand

Source: Reinecke / McKinsey


QualityReview Questions


Pharmacy Medication ErrorA pharmacy in a Philadelphia suburb wants to investigate the likelihood of making a medication error. There are two ways in which a patient can end up with the wrong medication:- In about 2% of the cases, the doctor fills out the prescription incorrectly. Nobody in the pharmacy catches

these errors- In about 1% of the cases, the pharmacist makes a mistake in picking the medication according to the

prescription. The pharmacy has an internal quality inspection process that catches about 97% of the errors made by the pharmacist.

Another source of quality control is the patients. The pharmacy estimates that about half of the errors made by the physician are recognized by the patient. However, the patient is only able to recognize 10% of the mistakes done at the pharmacy.

What is the likelihood that the patient is presented with a wrong medication?

What is the likelihood that the patient leaves the pharmacy with the wrong medication?


Four Step Process with Rework and Scrap Consider the following four step assembly operation with quality problems. All resources are staffed with one operator. - The first resource has a processing time of 4 minutes per unit - The second resource has a processing time of 3 minutes per unit. This process suffers from a high yield

loss and 50% of all products have to be scrapped after this step.- The third resource also suffers from quality problems. However, instead of scrapping the product, the third

resource reworks it. The processing time at the third resource is 5 minutes per unit. In the 30% of the products in which the product needs to be reworked, this extends to a total (initial processing time plus rework) processing time of 10 minutes per unit. Rework always leads to a non-defective unit.

- No quality problems exist at the first and final resource. The processing time is 2 minutes per unit.

For every unit of demand, how many units have to flow through the third step in the process?

Where in the process is the bottleneck?

What is the process capacity?


Chicken EggsA farmer focusing on the production of eco-friendly chicken eggs collects the following data about his output. In a sample of 50 eggs, the farmer finds the average egg to weigh 47 grams. The standard deviation of the egg weight is 2 grams and the distribution of weights resembles a normal distribution reasonably closely.

The farmer can sell the eggs to a local distributor. However, they have to be in the interval between 44 grams and 50 grams (i.e., the lower specification limit is 44 grams and the upper specification limit is 50 grams).

What is the capability score of the eco-friendly chicken egg operation?

What percentage of the produced eggs fall within the specification limits provided by the local distributor?

By how much would the farmer have to reduce the standard deviation of the operation if his goal were to obtain a capability score of Cp=2/3 (i.e., get 4.5% defects)?


Process capability measure

• Estimate standard deviation in excel• Look at standard deviation relative to specification limits

3

Upper Specification Limit (USL)

LowerSpecificationLimit (LSL)

X-3A X-2A X-1A X X+1A X+2 X+3A

X-6B X X+6B

Process A(with st. dev A)

Process B(with st. dev B)

6LSLUSLC p

x Cp P{defect} ppm

1 0.33 0.317 317,000

2 0.67 0.0455 45,500

3 1.00 0.0027 2,700

4 1.33 0.0001 63

5 1.67 0.0000006 0,6

6 2.00 2x10-9 0,00

Measure Process Capability: Quantifying the Common Cause Variation


Toyota Word MatchingPlease write the letter corresponding to the most appropriate example or definition from choices (a – k below) on the blank line next to each word below.a) Examples of this include: workers having to make unnecessary movements (i.e. excessive reaching or walking to get tools or parts), working on parts that are defective and idle time.b) A system that enables a line worker to signal that he or she needs assistance from his or her supervisor, for example in the case of a defect. Used to implement the Jidoka principle.c) A brainstorming technique that helps structure the process of identifying underlying causes of an (usually undesirable) outcome d) As an example of this philosophy, workers at Toyota often times make suggestions for process improvement ideas. e) A method that controls the amount of work-in-process inventory f) If an automotive assembly plant used this technique, the adjacent cars on an assembly line would be mixed models (e.g. Model A with sunroof, Model A without sunroof, Model B, Model B with sunroof), in proportions equal to customer demand.g) Making production problems visible and stopping production upon detection of defects

Please only add ONE LETTER to each of the following terms:

Kanban ____Muda ____Heijunka ____ Andon cord ____ Kaizen ____ Ishikawa ____ Jidoka ____

curs operatiuni

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