Slide 1: An application of Little's Law in Micron's supply chain
An application of Little's Law in Micron’s supply chain Reviewed 2025 © 2020-2025 Micron Technology, Inc. All rights reserved. Information, products, and/or specifications are subject to change without notice. All information is provided on an “AS IS” basis without warranties of any kind. Statements
Slide 2: Copyright guidelines
Copyright guidelines By using any content provided by the Micron Educator Hub, you acknowledge that Micron Technology, Inc. (“Micron”) is the sole owner of the content and agree that any use of the content provided by the Micron Educator Hub must comply with applicable laws and require strict compli
Slide 3: How to cite sources from the Micron Educator Hub
How to cite sources from the Micron Educator Hub • Micron is committed to collaborate with Use case How to cite sources educators to make semiconductor memory Whole slide deck or whole No additional citation required education resources available through the document Micron Educator Hub Description:
Slide 4: Table of contents
Table of contents 1 Goals, objectives and target audience 2 Little’s Law 3 Mapping to production 4 Application examples 5 Glossary 4
Slide 5: Little's Law – goal and objectives
Little’s Law – goal and objectives Goal Objectives • Participants will be able to understand basic • Understand Little’s Law as a fundamental theory in concepts of Little’s Law and how it applies to the supply chain management manufacturing industry at large, and specifically to • Explain how Little
Slide 6: Little's Law – target audience
Little’s Law – target audience • Individuals interested in a career in supply chain and interested in how data driven supply chain works. Pro tip • Interns, NCGs (New College Grads), and new employees in supply chain Everyone interviewing at Micron roles need to understand these concepts can use thi
Slide 7: Data disclaimer
Data disclaimer The data presented in this document has been solely generated for educational purposes and does not represent real Micron data. 7
Slide 8: Little's Law
Little’s Law 8
Slide 9: John goes to a coffee shop
Little’s Law John goes to a coffee shop Input variables John’s position in the queue • Service rate – 30 seconds per customer (2 customers per minute) • Population – Infinite 9th 08:00:00 • Arrival rate – 2 customers per minute (for demonstration purpose) 8 7 6 5 4 3 2 1 9
Slide 10: John goes to a coffee shop
Little’s Law John goes to a coffee shop John’s position in the queue 8th 08:00:30 9 7 6 5 4 3 2 1 10
Slide 11: John goes to a coffee shop
Little’s Law John goes to a coffee shop John’s position in the queue 7th 08:01:00 9 8 6 5 4 3 2 1 11
Slide 12: John goes to a coffee shop
Little’s Law John goes to a coffee shop John’s position in the queue 6th 08:01:30 9 8 7 5 4 3 2 1 12
Slide 13: John goes to a coffee shop
Little’s Law John goes to a coffee shop John’s position in the queue 5th 08:02:00 9 8 7 6 4 3 2 1 13
Slide 14: John goes to a coffee shop
Little’s Law John goes to a coffee shop John’s position in the queue 4th 08:02:30 9 8 7 6 5 3 2 1 14
Slide 15: John goes to a coffee shop
Little’s Law John goes to a coffee shop John’s position in the queue 3rd 08:03:00 9 8 7 6 5 4 2 1 15
Slide 16: John goes to a coffee shop
Little’s Law John goes to a coffee shop John’s position in the queue 2nd 08:03:30 9 8 7 6 5 4 3 1 16
Slide 17: Little's Law: John goes to a coffee shop
Little’s Law John goes to a coffee shop John is currently being served 08:04:00 9 8 7 6 5 4 3 2 17
Slide 18: Little's Law: John goes to a coffee shop
Little’s Law John goes to a coffee shop John exits the system 08:04:30 9 8 7 6 5 4 3 2 1 18
Slide 19: Little's Law: John goes to a coffee shop
Little’s Law John goes to a coffee shop John exits the Metrics system • Average queue length – 9 customers 08:04:30 • Time taken by John in the system – 4 minutes 30 seconds • Service rate – 30 seconds per customer (2 customers per minute) Relationship drawn Average queue length (9 customers) = Time
Slide 20: Little's Law
Little’s Law • Little's Law is a fundamental principle in queuing theory and inventory management • Here is how the Little’s law equation can be applied in the service industry as derived from the coffee shop scenario Average queue Average Service rate length time in queue 20
Slide 21: Mapping to production
Mapping to production 21
Slide 22: Little's Law application at Micron
Little’s Law application at Micron • Throughput time = 10 weeks • Throughput rate = 7,000 wafers per week What is the expected WIP inventory? 𝑤𝑎𝑓𝑒𝑟𝑠 𝑊𝐼𝑃 = 10 𝑤𝑒𝑒𝑘𝑠 × 7,000 = 70,000 𝑤𝑎𝑓𝑒𝑟𝑠 𝑤𝑒𝑒𝑘 Coffee shop scenario Micron application Queue length WIP Inventory Time in queue…
Slide 23: Factors that affect time in queue or throughput time
Factors that affect time in queue or throughput time Service Industry Service Industry Strategies Queue length Improve service rate by • 9 people takes 4:30 minutes • Increasing the number of servers to reduce the wait time • 20 people takes 10 minutes • Giving training to the servers • 100 people t
Slide 24: Little's Law applications
Little’s Law applications 1) Management strategy and control 2) Inventory Management Only two out of the three of the following determine a strategy. The third is implicitly determined. Turnover Ratio 𝐿= average inventory 𝑊= throughput time 𝜆= throughput rate Inventory 1 = 𝜆 (WIP) 𝑊 𝐿 𝐿 𝐿=…
Slide 25: Graphical representation of a service industry example
Graphical representation of a service industry example 𝑁 customers are served by the system during a cycle. A customer is represented by a rectangle of unit height, whose length equals the time the customer spends in the system. Representation of each customer arrival and their respective service…
Slide 26: Little's Law: Service vs. Semiconductor Industry
Little’s Law: Service vs. Semiconductor Industry Average queue Average Service rate length time in queue Average Average Inventory time a product is in Rate of production (WIP) the system WIP – Work in progress 26
Slide 27: Little's Law: Mapping to the production context
Little’s Law Mapping to the production context Therefore, the resultant relationship is For production scenario Average queue length ≡ average inventory (WIP) Average time in the system ≡ throughput time (time Little’s Law spent by a product within the system) Average inventory (WIP) = Service rate
Slide 28: Semiconductor memory manufacturing stages of production
Semiconductor memory manufacturing stages of production Stages of Production Start Material: Silicon is purified and formed into wafers (outside Micron). Wafer-Level Fabrication: Electronic devices (transistors, resistors, capacitors, etc.) are fabricated on the silicon wafers, and are then 1. Front
Slide 29: Types of inventory
Types of inventory Inventory Level (WOS) A typical semiconductor company accumulates inventory in three stages: Finished Goods Finished Safety Stock and • Finished Goods Goods Allowances Finished Goods Cycle Stock • Back End manufacturing Back End Safety Stock and Allowances • Front End (Wafer / Die
Slide 30: Types of inventory
Types of inventory Inventory Level (WOS) Finished Goods Finished Safety Stock and Goods Allowances Finished Goods Cycle Stock Little’s Law typically is applicable to Back End Safety Stock and Allowances the cycle stock (WIP occurring during production process) Back End Back End Cycle Stock Front End
Slide 31: Study of cycle stock
Study of cycle stock Product group X aggregated cycle stock Product group X comprises of products A, B, C, D, and E 3 Production Sites: Site 1, 2, and 3 Purpose of analysis: identify expected directional changes in product group X Site 3 Site 2 • Is overall product group inventory increasing Site 1
Slide 32: Application examples
Application examples 32
Slide 33: Translating throughput time to WIP targets
Translating throughput time to WIP targets Little’s Law Little’s Law Formula Utilized to determine target WIP levels 𝑊𝐼𝑃 = 𝑇ℎ𝑟𝑜𝑢𝑔𝑝𝑢𝑡 𝑡𝑖𝑚𝑒 𝑥 𝑇ℎ𝑟𝑜𝑢𝑔ℎ𝑝𝑢𝑡 𝑟𝑎𝑡𝑒 Targets • How much WIP should we have in our fab? – What should be the target throughput time? – What should be the…
Slide 34: Semiconductor scenario use for Little's Law
Semiconductor scenario use for Little’s Law • The business quarterly demand is 13,000 wafers • Each wafer has 700 steps to complete • Note: A business quarter is 13 weeks • Production time for each wafer is 10 weeks 700 Steps Total Week M T W Th F Sa Su ✓ 1 1 Step 1 ✓ 2 2 ✓ 3 3 ✓ … 4 ✓ … 5 ✓ … 7 ✓ 6
Slide 35: What is the expected target WIP?
What is the expected target WIP? Quarterly Demand = Steps per wafer = Production time (Throughput Time) = 13,000 wafers 700 steps 10 weeks per wafer 700 Steps ✓ 1 ✓ 2 ✓ 3 ✓ … Business quarter = 13 weeks What is the expected target WIP? 𝑇𝑎𝑟𝑔𝑒𝑡 𝑡ℎ𝑟𝑜𝑢𝑔ℎ𝑝𝑢𝑡 𝑟𝑎𝑡𝑒 𝑝𝑒𝑟 𝑤𝑒𝑒𝑘 =…
Slide 36: Is the target throughput rate being met?
Is the target throughput rate being met? Tuesday: 70,000 steps were completed. week M T W Th F Sa Su Target Throughput 70,000 rate= 1,000 Steps wafers/week What is the Weekly Throughput for Tuesday? 70,000 𝑠𝑡𝑒𝑝𝑠/𝑑𝑎𝑦 𝑇ℎ𝑟𝑜𝑢𝑔ℎ𝑝𝑢𝑡 𝑟𝑎𝑡𝑒 𝑑𝑎𝑦 = = 100 𝑤𝑎𝑓𝑒𝑟𝑠/𝑑𝑎𝑦 700…
Slide 37: Is the target throughput rate being met?
Is the target throughput rate being met? Tuesday: 70,000 steps were completed. week M T W Th F Sa Su Target Throughput 70,000 rate= 1,000 Steps wafers/week Is Tuesday’s pace ahead or behind the target? (assume each step has equal contribution to wafer processing and WIP is evenly distributed) 700…
Slide 38: Little's Law
Little’s Law 𝑊𝐼𝑃 𝑊𝐼𝑃 𝑊𝐼𝑃 𝑇ℎ𝑟𝑜𝑢𝑔ℎ𝑝𝑢𝑡 𝑇𝑖𝑚𝑒 = = = 𝑇ℎ𝑟𝑜𝑢𝑔ℎ𝑝𝑢𝑡 𝑅𝑎𝑡𝑒 𝑃𝑎𝑐𝑒 𝑀𝑜𝑣𝑒𝑠 / 𝑆𝑡𝑒𝑝 𝑄𝑇𝑌 • Constant: Step quantity Other expressions for throughput time • Dynamic: Moves and WIP 𝑆𝑡𝑒𝑝 𝑄𝑇𝑌 𝑆𝑡𝑒𝑝 𝑄𝑇𝑌 𝑜𝑟 - More moves and less WIP = lower…
Slide 39: Cumulative pace delta
Pace plot for visualizing performance Pace plot shows actual pace performance Pace plot vs. target pace 1200 200 Target pace 100 1100 • Calculation is based on demand and step QTY 0 Cumulative pace delta 1000 -100 Actual pace -200 Pace 900 • Actual pace based on actual number of steps performed -300
Slide 40: Glossary
Glossary 40
Slide 41: Glossary
Glossary Term or acronym Definition/description Cycle stock Inventory that is used during the production process Safety stock Inventory kept to prevent stockouts due to variability in demand or supply Throughput time The average time a product spends within the system from the start until it is comp
Slide 42: © 2022-2025 Micron Technology, Inc. All rights reserved. Information, products, and/or specifications are subject
© 2022-2025 Micron Technology, Inc. All rights reserved. Information, products, and/or specifications are subject to change without notice. All information is provided on an “AS IS” basis without warranties of any kind. Statements regarding products, including statements regarding product features,