toc conwip kanban
TRANSCRIPT
Theory of Constraints, ConWIP, Kanban
different ways for organizing a Pull
Dr. Serhiy Yevtushenko, 05 of March 2015
Content
• Introduction
• Queuing Systems – some basics
• Push vs Pull
• Different Ways of Pulling
• Relation to agile methodologies
• Comparison and Conclusions
• Further Links
Introduction
• Motivation
• Show principles, explaining the physics and fundamental reasons, why agile works
• Show connections between agile methods, production systems and supply chain management
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
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!
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!
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)
Push vs Pull
„You don‘t never make nothin‘ and send it to no place. Somebody has to come get it“
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 …)
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
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t
optimal control paramater %
Push System Pull System
Optimum
Robustness
Efficiency
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
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
Theory of Constraints – Drum-Buffer-Rope
Theory of Constraints has as well a Project Management Part
– Critical Chain Project Management
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
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
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
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
Q & A
Dr. Serhiy Yevtushenko
codecentric AG An der Welle 3 60322 Frankfurt
http://asffm.blogspot.de