Hndt Mba s4 Shouldice

8/12/2019 Hndt Mba s4 Shouldice

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DISCLAIMER: Use of any portion of these materials toaid in the preparation of a case write-up for this, or anyother class; current or future, or sharing any portion ofthese materials with anyone who mustor might somedayhave toprepare a case write-up for this case constitutes a

serious violation of the Olin School Honor Code .

Session 4 HandoutPart 1

1

Cycle Time Management

Session 4

2OMM 5704 Session 4 Handout 1 of 14


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CYCLE TIME

C A P A C I T Y

INVENTORY

T HR O U GHP UT

THE OPS QUADRANGLE

3

OMM Chayet

Capacity Makespan, INV, !

Capacity Investment Capacity Constraints Product-Mix Decisions Levers for Increasing Capacity

Capacity and Bottlenecks



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OMM Chayet

Make Sure not Wasting Bottleneck Capacity Idle during lunch breaks Bottleneck not making parts for nished goods inventory! Quality Control prior to Bottleneck

The Goal

BN QC

defects

pass

BNQC

defects

pass

5

OMM Chayet

Ofoad Must all parts ow through the BN? Sub-Contract?

Heat Treatment Across Town Price? Shadow Prices: (NCC, Merton)

The Goal



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CYCLE TIME

C A P A C I T Y

INVENTORY

T HR O U GHP UT

THE OPS QUADRANGLE

7

OMM Chayet

Search for Clarity

Drive

Critical Paths Cycle Time

Bottlenecks Capacity

Drivedifferent paths ! critical path cycle time

throughput ! bottleneck capacity



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OMM Chayet

Of Bottlenecks and Critical Paths

A B

C

D

E

F G

H

I

13 15

6

5

4 9

5

19 16

10 11

5

4

3 7

3

12 11

max = ?

Critical Path ?

9



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OMM Chayet

Of Bottlenecks and Critical Paths

A B

C

D

E

F G

H

I

13 15

6

5

4 9

5

19 16

10 11

5

4

3 7

3

12 11

Critical Path Length = 53 min

11

OMM Chayet

Are Bottlenecks Always on the Critical Path?



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Washington University Olin Business School

OMM 5704 Operations Management

Chayet

Bottlenecks and Critical Paths: An Example

1

1 2

W a i

t

1

0

1

2

3

4

5

6

7

8

T 1

T 2

T 3

B

I n B W O u t

1 t

1 t

1 t 2 t

2 t

2 t 3 t

3 t 3 t 4 t

4 t

1 b

2 b

3 b

4 b

1 b

T 1

T 2

T 3

2 b

3 t

1

2

3

4

1

2

3

1 b

1 t

2 b

2 t

3 b

3 t

4 b

4 t

C u t

OMM 5704 Session 4 Handout 7 of 14


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OMM Chayet


Top 1 Top 2 Top 3

Bottom

1 11

2

Wait

13

OMM Chayet


InTop 1Top 2Top 3

BottomWaitOut

0 1 2 3 4 5 6 7 8

1t

1t

1t

1b

1b

2t

2t

2t

2b

2b

3t

3t

3t

3b

3b

4t

4t

4b

1 2 3 4

2 3

=

CT =

1

2 min

I V =

m n

+ 1

2=

3

2

1



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OMM Chayet

CT: Key Facts

Includes Waiting Times It is an Average

Determined by Critical Path

15

OMM Chayet

Customers Should Only See Value-Add!

Process Value-Add Non-Value-Add

Fire ghting Spraying water Testing the sirenProduct development Designing to meet specs Perfecting a new technology

Retail ordering Ordering hot-selling items Ordering slow-moving itemsHome mortgage approval Processing application Deciding lending policy

Order fulllment Assembly Credit checkingComplaint processing Phoning customer Management study



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OMM Chayet

Focus promotes rapid learningand smooth ow (variance reduction)

through simplicity and repetition.

Focus

17

OMM Chayet

Riding the Learning Curve

time/cost

quality

Experience

P e r f o r m a n c e



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DISCLAIMER: Use of any portion of these materials toaid in the preparation of a case write-up for this, or anyother class; current or future, or sharing any portion ofthese materials with anyone who mustor might somedayhave toprepare a case write-up for this case constitutes a

serious violation of the Olin School Honor Code .

Session 4 HandoutPart 2

19

OMM 5704 Session 4 Handout 11 of 14


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Washington University Olin Business SchoolOMM 5704 Operations ManagementChayet

Session 41. Assignment: Merton Truck Company Exercise II

Testing Constraint:12

X 101 + 14

X 102 1100

Or equivalently:2 X 101 + X 102 4400

The new decision variable graph:

0 500 1000 1500 2000 2500 30000

500

1000

1500

2000

2500

3000

3 0 0 0 X 1 0 1 + 5 0 0 0 X

1 0 2 = 5 , 0 0 0 , 0 0 0 X

101

X 102

M e t a l S t a m p i n g

E n g i n e As s e m b l y

Constraints Graph

T e s t i n g

The optimal solution is encircled. Using Excel Solver we conrm:

X 101 = 1600

X 102 = 1200

Contribution = $10 .8M .



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2. Assignment: Shouldice Hospital Limited

Annual net prot

Hospital: $111 1patient day

(4 day)(6850 patient) $2.8M = $241, 400.

Clinic: ($450 + $60 + (0 .2) $75) 1patient (6850 patient) $2M = $1 , 596, 250.

Average number of beds occupied according to Littles Law

INV = CT = 6850/ year50wk/ year

4 day7 day/ wk

= 78.29.

Recall that there are 89 regular and 14 hostel beds for a total of 103, well above 78.29.Although not part of the assignment, notice that if beds were the only limitation,Shouldices capacity would be max = 1034 / 7wk = 180.25/ wk.

Please see the posted spreadsheet

Some available options and their associated costs:

Conguration Schedule Capacity I NV Revenue IncrementSu M T W Th F S (#/wk) (per wk) (per year)

Current 34 37 15 14 37 0 0 78.3 $132,753 CT=4 37 37 15 14 37 0 0 140 80.0 $135,660 $145,350CT=3 37 37 29 37 37 0 0 177 75.9 $151,866 $955,650S CT=4 35 33 21 14 35 33 0 171 97.7 $165,699 $1,647,300

S Su CT=4 26 26 26 25 26 26 25 180 102.9 $174,420 $2,083,35045 bed wing CT=4 37 37 37 37 37 0 0 185 105.7 $179,265 $2,325,600S,No W CT=4 37 37 0 29 37 23 0 163 93.1 $157,947 $1,259,700



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Washington UniversityOlin Business SchoolOMM 5704 Operations ManagementFall B 2013, Chayet

Session 4: Lessons

1. Critical Path:

We learned that the critical path is the sequence of steps through which all jobs must pass,

having the longest total time, including wait time. If you want to reduce cycle-time, you

must focus on the critical path.

2. Bottlenecks and Critical Paths:

Using a simple example we saw how the critical path doesnt always include the bottleneck.

We used a Gantt chart to illustrate the progress of jobs through the system.

3. Focus Strategy:

By focusing, rm can reduce variability, simplify processes, and increase the rate of learning

through repetition. The effect is to more quickly ride the learning curve of improving Time,

Price, and Quality. We discussed in detail how Shouldice creates value through focus, as

well as other examples.

4. Revenue as a Function of the Operations Quadrangle:

We can use the Operations Quadrangle to understand how a rm makes money. In an INV-

business, such as the hospital side of Shouldice, customers pay more as their cycle-time, i.e.

length of stay, increases. In a -business customers pay for participation, such as the clinic

side of Shouldice where customers pay per operation. Viewed on the whole, Shouldice is

a mixture of both. We saw that because inventory is tightly held, i.e. INV INV max ,

Shouldice can increase revenue by reducing cycle-time to increase , which follows from

Littles Law. Shouldice can also increase INV max by adding a 45-bed wing, or increase

the weekly effective capacity by scheduling operations on Saturday.

5. Scheduling Constraints:

Unlike all other situations we have faced so far, assessing the capacity of Shouldice cannotbe done by looking at each resource pool in isolation. There are constraints that depend

on time, i.e. patients cannot be admitted on Friday or Saturday, which interact with

inventory constraints on the number of beds. We saw how Excel Solver can be used to

obtain a schedule that maximizes weekly throughput, i.e. yields weekly effective capacity.

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Hndt Mba s4 Shouldice

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