ISYE 6202: Increasing Efficiency at FASTENAL Distribution Center

1. ISYE 6202: Increasing Efficiency at FASTENAL Distribution Center BY NISHANT S JAIN (MS IE Georgia Tech)

2. AGENDA • Overview • My Roles & Responsibilities • Facility Layout • DC Operations • Sortation Overview • Optimal Scheduling • Lean 5S • Picking • Slotting • Replenishment • Cycle Counting • Summing It up

3. OVERVIEW • # 2 Industrial and Construction supplier in North America (#1 being W.W. Grainger) • ~$ 3 billion in sales (2010) & growing at 20% per qtr • 2400+ stores and 14 RDCs in the US • Owns 5000 Trucks, dry vans, sprinter vans • Provides Value Added Services to customers - bin- stocking programs, JIT/kanban systems, point-of-sale vending • Range of Products: • Fasteners (nuts, screws, bolts,etc..) • Chemicals, paint, liquids, office products • Tools, electrical and construction supplies • Automotive, motors, safety equipment

4. MY ROLES & RESPONSIBILITIES • Job title: DC Efficiency Analyst • Basically an internal Warehouse consultant • Also, Lean 5S responsibilities and Kaizen events • But first…….I had to prove myself ! • Started work in the Sortation department - Lean the department – Visual Aids, 5S, Optimal Scheduling - Performance Measurement system - Incentive programs • New system for Picking • Changes in cycle counting • Slotting and Replenishment improvements

5. FACILITY LAYOUT Overstock Storage (Pallet Racks + Floor Storage) Pick module (3 levels) Forward pick area Floor Storage + Rod shelving CONVEYOR SYSTEM Large Parts & Small parts Sortation. (2 levels) Packaging & Receiving ( 2 levels) Receiving & Shipping • FACILITY PROFILE • ~ 200, 000 sq. feet • Serves 250 stores + Other HUB • transfers as part of Company wide • Inventory Re-distribution • Extensive use of conveyors often • making it the bottleneck.

6. DC OPERATIONS • Receiving happens early in the morning (5 days/wk) • Sortation divided into Large Parts & Small Parts • Sorter sorts directly for cross-transfer • Sorter sorts for replenishing DC inventory (IB) • Sorter sorts customer orders (OB) • Sortation runs from early morning to late evening • Picking happens in a 6-8 hr window as most order pickers (~80%) work Part Time (hence can only work 5 hrs/day) • Shipping happens late in the night • Inventory checks happens late in the night to avoid interference • Replenishment occurs early in the morning before Picking 5 AM 10 AM 8-9 PM 1 AM RECEIVING + REPLENISHMENT SORTATION SHIPPING + CYCLE COUNT PICKING 11 AM 7 PM

7. SORTATION OVERVIEW • Small group of employees (~ 18) mostly part time ( <= 30 hrs/week) • Product damages and Quality the biggest concern • Similar HUB is better than us in production and efficiency ( they were doing more work with fewer workers hence at a lesser cost)

8. OPTIMAL SCHEDULING • Tried formulating a LP and IP. • Failed as too many constraints – worker speeds, worker times ( their schedules), part time employees hence allowance of 5 hrs, no account for buffers • INSTEAD, Excel Spreadsheet used to plan schedules based on production speed vs. demand formula • Intuitive for the manager • Changes to schedule easy • Accounts for buffer • and high variability Forecasted Load Using Moving Weighted Average

9. LEAN 5S Figure: 5S Implemented Figure: 5S Meaning Horribly disorganized and scattered. Space wastage apparent All boxes kept in a corner to save space and properly organized

10. LEAN 5S WASTESIN THE SYSTEM • Unclean environment – spills, plastic, dirt on the floor • Tough conditions ( 120 F during summer) with 6 fans cooling 50000 sq. feet • Incorrect stacking methods was causing damages to products • Conveyor belt causing huge bottlenecks • Performance Measurement based on theoretical standards. • Team based incentive was not working MEASURES TAKEN • Cleanliness became a priority – HIGH 5s incentive program. Free Lunch for Individuals keeping the area clean. • Setup 12 fans before I left • 1 employee dedicated to stacking audits & quality • Individual Performance Measurement System based on scans/hr (speed) and discrepancies (quality)

11. PICKING • PICK CHARACTERISTICS • 3 floors of the pick module (9000 SKUs) • Bottom floor for fragile and small items ( Slow pick rate) • Use of Bar Code readers • Follows ABC ranking: 30% of the SKUs contribute 65% of the picks • Pickers start from 9 AM – 7 PM; Changed it to 12 – 6 PM • ( Consolidated pick window) • Picks are downloaded every 2 hours in the system starting at 6 AM. Emergency picks up to 5 PM • Workers walk towards each other while picking starting at the ends. (zig-zag path) • Manager re-distributes workers based on work content 3 – level The GAP warehouse

12. PICKING • Disorganized picking (workers starting at will) and lack of discipline • Remember: Consolidated Picking window. i.e. orders are allowed to build before order pickers arrive • Implemented Bucket brigades • Instantly saw about 40 - 50% improvements in CF and PF. • About 10% in Shelving • But after 7 – 10 days, picking returned to almost normal though slight increase in picking ( 5-10%) • Spike was due to end of quarter (highest sales volume in the year) • Did not work due to very few downloads every 2 hours • But it instilled a team based culture, organization and competition. Figure: Bucket Brigades at work

13. SLOTTING • Workers break their backs while picking from the lowest or top most shelf of the rack (No GOLDEN ZONE) • Equal Space Allocation • Follows ABC distribution: 20% of the SKUs contribute 65% of the picks and nearly dollar sales as well. • Focus on getting the 2000 SKUs in Carton Flow and Pallet Flow • Use of Slotting software from warehousing-science.com • But Problem !! No data on Carton sizes + time of internship ending • Measured 2000 SKUs in about 30 hours in 3 levels of PF and CF ( Inventory check !!) • Use of Greenfield Approach • Considered 3 levels of storage: - PF -CF - Infinite (Shelving) • Storage in optimal quantities could potentially increase picking productivity by 20%

14. REPLENISHMENT • Current operations – 50% of Max limit triggered replenishment (1 pallet load in PF OR 6 cartons in CF triggered replenishment from Overstock) • Effects of this policy ( consider the following in Pallet Flow ) • Proposed the 14 days of supply method for replenishment • However it was unsuitable for Pallet Flow. • Suitable for Carton Flow (Few PF SKUs can be re-assigned their Min/Maxes)

15. CYCLE COUNTING • Current Method Cycle Count 35000 SKUs thrice a year @ 105,000 SKU counts + Everyday random counts - Proving to be highly ineffective - Also performed analysis of current errors ( mostly “B” items) • Improved Method – Ranked based ABC method Items responsible for the first 80% of COGS - Ranked "A" (5 times/yr) Items responsible for the next 15% of COGS- Ranked "B" (4 times/yr) Items responsible for the next 4% of COGS - Ranked "C" (3 times/yr) Items responsible for the last 1% of COGS  - Ranked "D“ (2 times/yr) - Total of 55,000 SKU counts • Savings of 50,000 SKU counts • Increased accuracy !

16. SUMMING IT UP “ A warehouse is not for the weak- hearted…. You really need to want to do this….If you do….it’s what you’ll call home !” - Manager @ Fastenal • During the last few days of the quarter when business was at its peak, we had a crises moment (workers did not show up and departmental manager left in Picking)We worked 10 AM to 1 AM …though next day treated to Beer & Pizza by the DC Manager ! • Applied warehousing-science (Global Logistics Scholar) in practice. Results were UNBELIEVABLE ! A BIG THANK YOU TO DR. BARTHOLDI and MR. PETE VIEHWEG

17. THANK YOU Contact: Nishant Jain 404.9633495 njain37@gatech.edu