This document discusses different methods for organizing pull-based production systems, including ConWIP, Kanban, and the Theory of Constraints. It covers concepts like throughput, work in progress, cycle time, and bottlenecks. Push systems are compared to pull systems, with pull systems noted as more observable, efficient, and robust. Specific pull methods like ConWIP and Drum-Buffer-Rope are described. Relationships between these production methods and agile software development methodologies like Scrum and Kanban are also discussed.

1. Theory of Constraints, ConWIP,
Kanban
different ways for organizing a Pull
Dr. Serhiy Yevtushenko, 05 of March 2015

2. Content
• Introduction
• Queuing Systems – some basics
• Push vs Pull
• Different Ways of Pulling
• Relation to agile methodologies
• Comparison and Conclusions
• Further Links

3. Introduction
• Motivation
• Show principles, explaining the physics and
fundamental reasons, why agile works
• Show connections between agile methods, production
systems and supply chain management

4. Queueing Systems - Basic Definitions
• Thoroughput – the rate, at which entities are
processed by the system
• Work in Progress – the number of entities in the
system
• Cycle Time – time it takes entity to traverse the system
• Capacity – maximal average rate at which entities can
flow through the system
The output of the system cannot equal or exceed it’s capacity
• Utilization = Rate into Station/Capacity
• Bottleneck – process with highest utilization

5. Cycle Time
• Cycle Time increases with utilization, and does so
sharply when utilization approaches 100%
• Little Law (for system in stable state)
– WIP = Throughput * Cycle Time
– Cycle Time = WIP/Throughput
Cycle Time = Delay + T (for single station)
Delay = V*U*T (case with no limits on queue)
V – a variability factor,
U –utilization factor,
T – average effective process time
Lowering WIP leads to shorter cycle times!

6. Batching
• Many operations are done in batches. Benefits
– Setup avoidance
– Better pacing
– Simultaneous processing
• Batching increases capacity, but adds wait-for-batch
and wait-in-batch times to cycle time.
• In simultaneous or sequential batching environment
– The smallest batch size that yields stable system may be
greater then one (due to large setup times)
– Delays due to batching (eventually) increase proportionally
due to batch size
One-piece Flow is not always optimal!

7. Variability and Buffering
• Variability is the fact of life. System can have
– Arrival variability
– In-process variability
• In absence of buffers between stations, variability
propagates inside system
• Variability could be buffered by some
combination of:
– Inventory (Having additional parts in buffers)
– Capacity (Having reserve machines)
– Time (Scheduling with additional time buffer)

8. Push vs Pull
„You don‘t never make nothin‘ and send it to no place.
Somebody has to come get it“

9. Push & Pull Systems
Push systems Pull systems
Doctors Practices – Scheduling
Patients
Security check in airports
Material Resource Planning Systems Supermarkets
School Timetable City Public Offices (Bürgeramt,Finanzamt …)

10. Benefits of Pull Systems
• Observability
– WIP is easy to observe
• Efficiency
– Achieve a given level of
thoroughput with a smaller
inventory
– Prevent system overload of
and overproduction
• Robustness
– Errors in setting WIP level are
less severe then errors in
setting release rate for push
systems
0
10
20
30
40
50
60
70
0 10 20 30 40 50 60 70 80 90 100 110 120 130
P
r
o
f
i
t
optimal control paramater %
Push System Pull System
Optimum
Robustness
Efficiency

11. ConWIP – Constrained Work in
Progress (Spearmann and Hopp)
Benefits:
• Easy to introduce
• Limits WIP in the system
• Suits well wenn doing a lot of custom products

12. Theory of Constraints – Five Focusing
Steps
1. Identify systems constraint
2. Decide how to exploit it
3. Subordinate everything else to the decisions made
in step 1 and 2
4. Elevate the systems constraint
5. Don’t allow inertia to be system constraint. When
constraint has been broken, go to step 1

13. Theory of Constraints – Drum-Buffer-
Rope
Theory of Constraints has as well a Project Management Part
– Critical Chain Project Management

14. Kanban
Benefits
• Works best with high-quantity low-variety parts
• Requires least amount of adjustment when demands decreases
Pecualiarity
• But if in-process variability changes, kanban system may experience
performance loss and require reconfiguration

15. Relation to Agile Methodologies
Production Planning Method Methodology
ConWIP Scrum, Extreme Programming
Drum-Buffer-Rope/Theory of Constraints Was a starting point of Kanban by D. J.
Andersen.
Drawbacks: Bottlenecks shift often in
practice in software development
It is easy to implement Critical Chain
Project Management wrong
Kanban Was used as an model, on base of which
Kanban for Software Development was
developed

16. Conclusions
 There already exist a lot of research on Production
Planning and Control System
 Mathematical part is good developed
 Simulations of different pull systems exist
 Performance of agile methods could be explained by
better robustness of pull systems
 Basing on production systems:
 Kanban suits good for high amount of low-variability tasks
 Scrum passes better for tasks with high variability in input
 Combined system could be devised as well

17. Further Links
Donald Reinertsen The Principles of Product Development Flow:
Second Generation Lean Product Development
Eliahu Goldratt, Jeff Cox The Goal: A Process of Ongoing
Improvement/Das Ziel: Ein Roman über Prozessoptimierung
Eliahu Goldratt The Race
Wallace J. Hopp, Mark L. Spearmann Factory Physics
www.factoryphysics.com
Wallace J. Hopp. Supply Chain Science
http://www.allaboutlean.com/ - site of Prof. Dr. Christoph Rosen –
covers ConWip, Kanban, Drum-Buffer-Rope and other topics,
related to lean manufacturing

18. Q & A
Dr. Serhiy Yevtushenko
codecentric AG
An der Welle 3
60322 Frankfurt
serhiy.yevtushenko@codecentric.de
http://asffm.blogspot.de