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OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin [email protected]
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OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin [email protected].

Dec 31, 2015

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Page 1: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

OPSM 501: Operations Management

Week 4:

Process analysis

Kristen’s Cookie

Koç University Graduate School of BusinessMBA Program

Zeynep [email protected]

Page 2: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Mark your calendars: Plant visit to Mercedes Benz in Hadimkoy on 19/12

9:30-12:00 at plant

Departure very early from campus with pick-up stop from Ataturk Oto Sanayi

Page 3: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Process Architecture is defined and represented by a process flow chart:

Process = network of activities performed by resources

1. Process Boundaries:– input– output

2. Flow unit: the unit of analysis

3. Network of Activities & Storage/Buffers– activities with activity times– routes: precedence relationships (solid lines)

4. Resources & Allocation

5. Information Structure & flow (dashed lines)

Page 4: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Flowchart Symbols

Tasks or operations

Examples: Giving an admission ticket to a customer, installing an engine in a car, etc.

Decision Points

Examples: How much change should be given to a customer, which wrench should be used, etc.

Page 5: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Flowchart Symbols

Storage areas or queues

Examples: Lines of people or cars waiting for a service, parts waiting for assembly etc.

Flows of materials or customers

Examples: Customers moving to a seat, mechanic getting a tool, etc.

Page 6: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.
Page 7: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Recall:Terminology

Flow Time (T)The flow time (also called variously throughput time, cycle time) of a given routing is the average time from release of a job at the beginning of the routing until it reaches an inventory point at the end of the routing.

1 2 3 4

Flow time

Page 8: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Flow time in the House Game process?

Production Control(color sheets, log sheets, scissors)

(scissors)

Base Cut(scissors)

Final Assembly(tape)

Base Weld(stapler)

Quality Control

Customer

Roof Base Form

Page 9: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Critical Path & Critical Activities

Critical Path: A path with the longest total cycle time.

Critical Activity: An activity on the critical path.

A B

C

D

Page 10: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Operational Measure: Flow TimeDriver: Activity Times, Critical Activity

(Theoretical) Flow Time

Critical Activity

Flow Time efficiency = TimeFlowAverage

TimeFlowlTheoretica

Page 11: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

X-Ray Service Process

1. Patient walks to x-ray lab 2. X-ray request travels to lab by messenger 3. X-ray technician fills out standard form based on info. From

physician 4. Receptionist receives insurance information, prepares and signs

form, sends to insurer 5. Patient undresses in preparation of x-ray 6. Lab technician takes x-ray 7. Darkroom technician develops x-ray 8. Lab technician checks for clarity-rework if necessary 9. Patient puts on clothes, gets ready to leave lab 10. Patient walks back to physicians office 11. X-rays transferred to physician by messenger

Page 12: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Example

32

1

4 765

11

109

start end

25%

75%7

20 6

5 3

6 12 2

20

3 7

transport

support

Value added

decisionMeasured actual flow time: 154 minutes

8

Page 13: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Consider all possible paths

Path1: 1-4-5-6-7-8-9-10 50 Path 2: 2-3-4-5-6-7-8-9-10 69 Path 3: 1-4-5-6-7-8-11 60 Path 4: 2-3-4-5-6-7-8-11 79

Page 14: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Levers for Reducing Flow Time

Decrease the work content of critical activities

– work smarter

– work faster

– do it right the first time

– change product mix

Move work content from critical to non-critical activities

– to non-critical path or to ``outer loop’’

Reduce waiting time.

Page 15: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Industry Process AverageFlow Time

TheoreticalFlow Time

Flow TimeEfficiency

Life Insurance New PolicyApplication

72 hrs. 7 min. 0.16%

ConsumerPackaging

New GraphicDesign

18 days 2 hrs. 0.14%

Commercial Bank ConsumerLoan

24 hrs. 34 min. 2.36%

Hospital Patient Billing 10 days 3 hrs. 3.75%

AutomobileManufacture

FinancialClosing

11 days 5 hrs 5.60%

Most time inefficiency comes from waiting: E.g.: Flow Times in White Collar Processes

Page 16: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Flow rate (capacity) in the House Game process?

Production Control(color sheets, log sheets, scissors)

(scissors)

Base Cut(scissors)

Final Assembly(tape)

Base Weld(stapler)

Quality Control

Customer

Roof Base Form

Page 17: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Tools: Gantt Chart

Gantt charts show the time at which different activities are performed, as well as the sequence of activities

Res

ourc

es

1

2

3

4

time

activities

Page 18: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Example of a two-stage production line

A B

5 min 2 min

Page 19: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Gantt Chart

A A A A

B B B B

5 10 15 20

7 12 17 22

Page 20: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Example of a two-stage production line

A1

B

2 minA2

5 min

5 min

Page 21: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Gantt Chart

A1 A1 A1 A1

B

5 10 15 20

7 12 17 22

A2A2A2A2

5 12 17 22

B

9

B B

14

B B

19

B B

24

Page 22: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Example of a two-stage production line

A1

B

2 minA2

5 min

5 min

Page 23: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Gantt Chart

A1 A1 A1 A1

B

5 10 15 20

7 12 17 22

A2A2A2A2

5 20

B

9

B B

14

B B

19

B B

24

10 15

Page 24: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Theoretical Capacity

Theoretical capacity: The capacity (throughput rate) of a process under ideal conditions (units / time)

Effective capacity: The capacity that one expects of a process under normal working conditions (units/time)

Effective capacity < Theoretical capacity

Page 25: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Effective Capacity (scheduled availability)

Effective capacity depends on the following– Number of shifts– Product variety– Maintenance – Idleness

Page 26: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Realized Capacity (net availability)

Actual production or realized throughput rate– Usually lower than effective capacity.

• Machine and equipment failures

• Quality problems

• Workforce losses

• Other uncertainties

Page 27: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Operational Measure: CapacityDrivers: Resource Loads

(Theoretical) Capacity of a Resource

Bottleneck Resource

(Theoretical) Capacity of the Process

Capacity Utilization of a Resource/Process = Realized throughput [units/hr]

Theoretical capacity [units/hr]

Page 28: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

X-ray revisited

32

1

4 765

11

109

start end

25%

75%7

20 6

5 3

6 12 2

20

3 7

transport

support

Value added

decisionMeasured actual flow time: 154 minutes

8

Page 29: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

X-Ray revisitedResource Pool

Res. Unit Load

Load Batch

Theoretical Capacity of Res. unit

No of units in pool

Theoretical capacity of pool

Messenger 20+20 min/patient

1 60/40=1.5 patients/hr

6 1.5(6)=9 Patient/hr

Receptionist 5 1 60/5=12 1 12

X-ray technician

6+7.5+2.5 1 60/16=3.75 4 15

X-ray lab 6+0.25(6)=7.5

1 60/7.5=8 2 16

Darkroom technician

12+0.25(12)=15

1 60/15=4 3 12

Darkroom 12+0.25(12)=15

1 60/15=4 2 8

Changing room

3+3 1 60/6=10 2 20

Page 30: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Utilizations given an observed throughput of 5.5 patients/hr

Resource pool Theoretical capacity

Patients/hr

Capacity utilization

Messenger 9 61.11

Receptionist 12 45.83

X-ray technician 15 36.67

X-ray lab 16 34.38

Darkroom technician 12 45.83

Darkroom 8 68.75

Changing room 20 27.50

Page 31: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

A Recipe for Capacity Measurements

Resource Unit Load Resource Capacity Process Resource

(time/job) Unit Capacity # of units Total Capacity Utilization*

* assuming system is processing at full capacity

Page 32: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Effect of Product Mix- Example

Resource pool

Unit Load (Physician)

Unit Load (Hospital)

Unit Load (60%-40% mix)

Mailroom clerk

0.6 1.0 0.76

Data-entry clerk

4.2 5.2 4.60

Claims processor

6.6 7.5 6.96

Claims supervisor

2.2 3.2 2.60

Page 33: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Theoretical capacity for hospital claims

Resource Sch. availability

Unit Load min/claim

Th. Capacity resource

Number in pool

Th. Capacity pool

Mailroom clerk

450 1.0 450/1=450 1 450

Data entry clerk

450 5.2 450/5.2=86.5 8 692

Claims processor

360 7.5 360/7.5=48 12 576

Claims supervisor

240 3.2 240/3.2=75 5 375

Page 34: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Theoretical capacity for 60%-40% mix

Resource Sch. availability

Unit Load min/claim

Th. Capacity resource

Number in pool

Th. Capacity pool

Mailroom clerk

450 0.76 592 1 592

Data entry clerk

450 4.60 98 8 784

Claims processor

360 6.96 51.7 12 621

Claims supervisor

240 2.60 92 5 460

Page 35: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

In summary

Throughput Process Capacity Effective Capacity Theoretical Capacity

Page 36: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Levers for Increasing Process Capacity

Decrease the work content of bottleneck activities– work smarter– work faster– do it right the first time– change product mix

Move work content from bottlenecks to non-bottlenecks– to non-critical resource or to third party

Increase Net Availability– work longer– increase scale (invest)– increase size of load batches– eliminate availability waste

Page 37: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Example

10 min/unit2 min/unit 6 min/unit

•Flow time T = 2+10+6 = 18 min.

•System cycle time 1/R= 10 min.

•Throughput rate R= 6 units / hour

•Utilizations: R1: 2/10=20%

R2=100% (bottleneck)

R3=6/10=60%

R1 R2 R3

Page 38: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Tools: Gantt Chart

Gantt charts show the time at which different activities are performed, as well as the sequence of activities

Res

ourc

es

1

2

3

4

time

activities

Page 39: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

R2

10 min/unitR1

2 min/unitR3

6 min/unit

R1

R2

R3

10 20 30 40 50 60

1 2 3 4 5

1 2 3 4 5

1 2 3 4 5

Three Workers

W1 W2 W3

Page 40: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

R1

R2

R3

10 20 30 40 50 60

1 2 3 4 5

1 2 3 4 5

1 2 3 4 5

Three Workers

Throughput time for an order of 5 units

System cycle time

Throughput time for a rush order of 1 unit

Page 41: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

R1

R2

R3

10 20 30 40 50 60

1 2 3 4 5

1 2 3 4 5

1 2 3 4 5

W1

W2

Two Workers

1 2 3 4 5

Page 42: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

More on multi-products and product-mix

Page 43: OPSM 501: Operations Management Week 4: Process analysis Kristen’s Cookie Koç University Graduate School of Business MBA Program Zeynep Aksin zaksin@ku.edu.tr.

Announcement

Assignment 2: Individual problem solving– Will encourage you to read the Chapters– Will prepare you for the exam– Will help you review the process analysis module– There are simple solved questions which you can look at

first

If after serious attempts you are unable to solve, come to my office for hints and pointers.

Assigned problems: 2.5, 2.10, 3.5, 4.3 Due: Session 6-same due date as The Goal Can do first two this week