1. OMG 402 - Operations Management Spring 1997
OMG Spring 1997
LN 2: Process Analysis
OMG Operations Management Spring 1997
CLASS 2: PROCESS ANALYSIS
Harry Groenevelt
Bring:
- course packets
- lecture notes
- Boeing article
- Course Overview
- gray cards
- nameplates
- marker

2. Agenda Recap Capacity Bottlenecks and Congestion
OMG Spring 1997
LN 2: Process Analysis
Agenda
Recap
Capacity
Bottlenecks and Congestion
The Multi-Product Case
Types of Processes and Process Strategy
Conclusion

3. Recap Process mapping Little’s Law:
OMG Spring 1997
LN 2: Process Analysis
Recap
Process mapping
Little’s Law:
(average throughput) = (average WIP)/(average lead time)
Observing throughput is not the same as observing lead time (one is flow, the other is time).
information flow
Data
hold
add
value

4. Recap: The Toll Booth Process
OMG Spring 1997
LN 2: Process Analysis
Recap: The Toll Booth Process
3 booths
‘plaza’
entrance
line
exit
line
throughput:
# cars across entrance line / min.
stock:
# cars in plaza +
# in booth
lead time:
time to cross plaza +
time in booth (min.)

5. Recap Possible process flow diagram: toll booths = ‘workstation 2’
OMG Spring 1997
LN 2: Process Analysis
Recap
Possible process flow diagram:
Toll booth
Arrivals
Traverse plaza
toll booths =
‘workstation 2’
plaza = ‘workstation 1’

6. Recap Will Little’s Law ‘work’ if toll booth service time is variable?
OMG Spring 1997
LN 2: Process Analysis
Recap
Will Little’s Law ‘work’ if toll booth service time is variable?
Will Little’s Law work if arrivals are ‘lumpy’?
How can we predict the maximum possible throughput?

7. OMG Spring 1997
LN 2: Process Analysis
Capacity: Definition
capacity: the upper limit on the throughput of a process (or of a workstation within the process)
For even the simplest systems, capacity estimates can vary with the
time horizon
type of demand (if there are multiple products)
mix of demand (if changeovers take time)

8. Capacity Example: Toll Booth
OMG Spring 1997
LN 2: Process Analysis
Capacity Example: Toll Booth
Booths
0.2 min.
0.2 min. to process toll (raw process time), for each of 3 toll booths.
0.5 min. to cross plaza (raw process time).
Arrivals
0.5 min.
0.2 min.
0.2 min.

9. Capacity Example: Toll Booth
OMG Spring 1997
LN 2: Process Analysis
Capacity Example: Toll Booth
If items are handled one at a time, then: capacity = 1/(raw process time).
(This is just Little’s Law, applied to a server who is assumed to be always busy)
Capacity of one toll booth = ______
Capacity of three toll booths = _______
Is the capacity of the plaza 1/(0.5 min.)? Why or why not?

10. Bottlenecks and Congestion: Definitions
OMG Spring 1997
LN 2: Process Analysis
Bottlenecks and Congestion: Definitions
bottleneck: any workstation with capacity less than or equal to the demands placed on it or - the bottleneck is the limiting constraint on the entire process as demand increases. By definition, the capacity of the bottleneck determines the capacity of the entire process.

11. Bottlenecks and Congestion: Definitions
OMG Spring 1997
LN 2: Process Analysis
Bottlenecks and Congestion: Definitions
Utilization of a workstation = throughput / capacity
For random systems, congestion builds at the bottleneck as throughput approaches capacity (utilization approaches 1)….
capacity
number
in system
Throughput: Utilization:
0.2
0.4
0.6
0.8
1.0

12. Bottlenecks and Congestion: A Deterministic (Non-Random) Example
OMG Spring 1997
LN 2: Process Analysis
Bottlenecks and Congestion: A Deterministic (Non-Random) Example
Production of precision aluminum panels
Milling is continuous with capacity 12 ft2/hour
Shot-peening is done in batches in a chamber: a batch of 24 ft2 takes 2 hours
Loading of batches is essentially instantaneous
Assume both processes are deterministic (not random)
raw materials
buffer
milling
shot-peening (S-P)
- describe shot-peening…
Squares are “processes” or “activities”; triangles are storage.
This is a rudimentary “bottlneck analysis”; S-P is the bottlneck.
Hhow fast can milling go?
If S-P at 20, is nothing in the buffer? No - if S-P is a batch process.

13. Capacity: A Deterministic Example
OMG Spring 1997
LN 2: Process Analysis
Capacity: A Deterministic Example
What is the capacity of the S-P chamber?
What is the capacity of the line?
Where is the bottleneck?
What do we see in the milling/SP buffer…?
raw materials
buffer
milling
shot-peening (S-P)

14. Capacity: A Deterministic Example
OMG Spring 1997
LN 2: Process Analysis
Capacity: A Deterministic Example
inventory
in buffer
(ft2)
Find the average inventory in the buffer:
Find the avg. time spent waiting in the buffer:
What happens if batches are cut in half?
Would it help to expand milling capacity (say, to 24 ft2/hour)? 1 2 3 4
hours

15. Capacity and Bottleneck Insights
OMG Spring 1997
LN 2: Process Analysis
Capacity and Bottleneck Insights
Insight 1: Bottlenecks determine the overall capacity of a process.
Insight 2: In a system with randomness, stock and lead time explode as utilization at the bottleneck approaches 1.
Insight 3: Even in a deterministic system, large batches increase stock and extend lead times.

16. The Multi-Product Case
OMG Spring 1997
LN 2: Process Analysis
The Multi-Product Case
Things are more complicated when multiple products each have different processing times on the same machine.
For such a system, we’ll consider:
What is capacity?
What is a bottleneck?

17. Bottlenecks in the Multi-Product Case
OMG Spring 1997
LN 2: Process Analysis
Bottlenecks in the Multi-Product Case
Consider a retail bank offering two products: Home equity line Activities Resources ‘consumed’ credit check research staff rate assignment research staff line approval underwriter Home Mortgage Activities Resources ‘consumed’ credit check mortgage sales staff appraisal mortgage sales staff package design mortgage sales staff mortgage approval underwriter

18. Multiple Products: Lines and Mortgages
OMG Spring 1997
LN 2: Process Analysis
Multiple Products: Lines and Mortgages
Credit
research capacity
= 30/day
credit line:
arrival rate
=10/day
Underwriters For credit line: capacity = 30/day For mortgage: capacity = 20/day
Mortgage
research capacity
= 15/day
mortgages:
arrival rate
= 10/day

19. Multiple Products: Calculating Utilization
OMG Spring 1997
LN 2: Process Analysis
Multiple Products: Calculating Utilization
utilization of resource i
example: utilization of the underwriters = _______________________

20. Multiple Products: A Capacity Constraint
OMG Spring 1997
LN 2: Process Analysis
Multiple Products: A Capacity Constraint
Utilization of underwriters (UW) must be less than 1: 20
Underwriters constraint:
lc/50 + lM/20 < 1
when throughput mix is close
to the ‘capacity constraint’, the underwriters are a bottleneck. 15
Mortgage Thruput (lm) (jobs/day) 10 5 20 40 60
Credit Line Thruput (lc) (jobs/day)

21. Multiple Products: Capacity Constraints
OMG Spring 1997
LN 2: Process Analysis
Multiple Products: Capacity Constraints
mortgage sales 20
underwriters 15 10
Mortgage Thruput (jobs/day) 5
credit research
feasible production region 10 20 30 40 50
Credit Line Thruput (jobs/day)

22. Multiple Products: Capacity Constraints
OMG Spring 1997
LN 2: Process Analysis
Multiple Products: Capacity Constraints
Increase mortgage throughput from 10 to 15. Where is the bottleneck (the ‘binding capacity constraint’)?

23. Multiple Products: Capacity Constraints
OMG Spring 1997
LN 2: Process Analysis
Multiple Products: Capacity Constraints
mortgage sales 20
underwriters 15 10
Mortgage Thruput (jobs/day) 5
credit research
feasible production region 10 20 30 40 50
Credit Line Thruput (jobs/day)

24. Multiple Products and The Value of Capacity
OMG Spring 1997
LN 2: Process Analysis
Multiple Products and The Value of Capacity
Suppose we keep this arrival rate: throughput of credit lines = 10 jobs/day throughput of mortgages = 15 jobs/day
Consider new products: product X uses mortgage sales staff product Y uses credit research staff
Accounting measures indicate: X and Y have equal unit cost and profit contribution
Are the products equally costly?

25. Multi-Product Bottleneck Insights
OMG Spring 1997
LN 2: Process Analysis
Multi-Product Bottleneck Insights
Insight 1: bottlenecks are binding capacity constraints, resources with utilization close to 1
Insight 2: the identity of the bottleneck is determined by product mix as well as resource capacity
Insight 3: Time on a bottleneck is an opportunity cost. Time spent on the bottleneck is more expensive than time on an under-utilized resource, regardless of the ‘actual’ cost

26. Types of Processes and Process Strategy
OMG Spring 1997
LN 2: Process Analysis
Types of Processes and Process Strategy
Calculation of capacity and control of bottlenecks becomes increasingly difficult as:
product variety increases
routings through resources become more complex
arrival and process variability increase
one end of spectrum: large volume mass production
other end: small volume customized production.

27. Types of Processes Line Flow (large volume mass production)
OMG Spring 1997
LN 2: Process Analysis
Types of Processes
Line Flow (large volume mass production)
product A
product B
Batch Process (more customized, small volume)
product A A C
product B C B A A
product C B

28. Types of Processes continuous process: chemicals, oil, paper
OMG Spring 1997
LN 2: Process Analysis
Types of Processes
continuous process: chemicals, oil, paper
line flows (‘mass production’): fast food assembly, automobiles, single-use cameras,
batch process: auto parts, machine tools, tour guides, bookbinders
job shop: auto repair, health clinic, machine shop
projects: product development, consulting

29. Types of Processes where is The Goal’s factory on this graph? project,
OMG Spring 1997
LN 2: Process Analysis
Types of Processes
project,
job shop
process
focus
none
batch
flow
assembly
line
product
focus
continuous
flow
none
low volume,
high variety
one of a kind
high volume,
low variety
standardized
where is The Goal’s factory on this graph?

30. Types of Processes and Process Strategy
OMG Spring 1997
LN 2: Process Analysis
Types of Processes and Process Strategy
Process-Focused facilities typically follow a Make-to-order strategy:
produce to satisfy specific, in-hand orders.
Examples:
Product-Focused facilities typically follow a Make-to-stock strategy:
produce to replenish inventories.

31. Types of Processes and Process Strategy
OMG Spring 1997
LN 2: Process Analysis
Types of Processes and Process Strategy
Intermediate strategies:
Assemble-to-order or Finish-to-order:
use make-to-stock strategy for subassemblies
final assembly (or finishing) of these subassemblies initiated by customer orders.
Examples:

32. Types of Processes and Process Strategy
OMG Spring 1997
LN 2: Process Analysis
Types of Processes and Process Strategy
semblies
Subas-
Major
Products
Finished
Material
Raw
Major stocking point
Product A:
Make to stock FG
Product B:
Assemble-to-order SA
Width indicates the variety of items at that point in the production process
Product C:
Make to order RM
Production

33. Conclusions The realities of ‘process physics’:
OMG Spring 1997
LN 2: Process Analysis
Conclusions
The realities of ‘process physics’:
there will always be a bottleneck to limit production.
in most systems, congestion builds in front of a fully loaded bottleneck.
bottlenecks are binding capacity constraints.
Complexity of constraints varies with the type of process.
Process strategy is shaped by product complexity and strategic priorities.
Jonah’s measures most appropriate for Bob Donovan’s levels, and aligned with goals at all levels. In trouble when measures encourage ‘sub-optimization’, an individual maximizing their own measure but hurting others.
In general, most measures are inherited. But are they the best?