Case Studies on the Use of Software to Implement Lean in High-Mix Manufacturing Industries

Transcription

1 Case Studies on the Use of Software to Implement Lean in High-Mix Manufacturing Industries Tom Knight Founder & Chief Strategy Officer North American Plant-to-Enterprise Conference September 21-23, Orlando, FL

2 The following Strategic Initiatives of MESA International are associated with this presentation: Lean Manufacturing 2

3 Agenda The Business Case for Lean Lean in High-Mix Industries & The Role of IT Case Studies & Best Practices 3

4 Manufacturing Challenges Fierce offshore competition Shorter product life cycles More product variants and SKUs Standardizing best practices across plants Complex global supply networks Heightened regulatory compliance 4

5 Why Are Companies Pursuing Lean? Companies with relatively mature lean processes have recorded 68% faster revenue growth over the past 20 quarters than non-lean companies. Lean manufacturers enjoyed net profit margins that averaged 26% higher than profit margins reported by manufacturers that haven t pursued lean practices. Manufacturing Insights Global Performance Index

6 Lean ROI is often >300%, with payback in < 1Year Four Main Benefits: 1. Increase Throughput 10-20% 2. Improve Customer Service 2-5% fewer late orders 5-10% better on-time delivery 3. Reduce Cycle Times 20-75% 4. Reduce Inventory 20-80% Return on Investment Analysis ($US millions) Fortune 100 Company Company: Date of Financials: 12/31/2006 Basic Financial Metrics current projected Annual Revenue $ 5,000 $ 5,000 Annual COGS $ 3,000 $ 3,000 Annual Net Income After Tax $ 500 $ 500 Inventory $ 400 $ 240 Cost of Capital 12% Storage/Handling/Obsolescence (as 10% Additional Financial Metrics current projected Fixed Assets (prop/plant/equip) $ 5,000 $ 5,000 Current Assets $ 3,500 $ 3,340 Total Assets $ 12,000 $ 11,840 Current Liabilities $ 2,500 $ 2,500 Net operating income 10.0% 10.0% Return on Total Assets 4.2% 4.2% Return on Net Assets 8.3% 8.6% Cycle Time Metrics current projected Inventory Turns Cycle Time [days] Value of 1 Day ($US millions) $ 8 $ 8 Invistics Return on Investment Investment first 12 months $ (12.90) Return first 12 months $ ROI first 12 months 520% ROI over 5 years 870% 5 Year Net Present Value (NPV) $ 121 6

7 Four Case Studies: Company Results Increased throughput while reducing inventory by millions and cycle times 35+% Increased throughput, productivity, and customer service, while tripling inventory turns. Plant went from potential shutdown to Team of the Year in its industry Increased throughput and customer service while reducing inventory by millions Increased throughout while maintaining perfect customer service levels and cutting inventory by $10 million 7

8 Agenda The Business Case for Lean Lean in High-Mix Industries & The Role of IT Case Studies & Best Practices 8

9 Product Proliferation Hitting Every Industry Increased demands by customers: Consumer Products adding 20% more SKUs each year Chemicals experiencing 60% volatility in some SKUs 9

10 Every Industry Is Changing Then Now Long runs High utilization Dedicated equipment Repetitive Stable demand Short runs Faster changeovers Shared equipment Responsiveness Highly variable demand High-volume High-mix 10

11 Beware of automotive lean tools in your high-mix plants 11

12 What is Different in High-Mix Industries? [High-mix industries] lag in the adoption of Lean practices across the board primarily because the Lean techniques popularized by the Toyota Production System (TPS) can be difficult to implement in the shared equipment, high product mix, and highly volatile demand scenarios they face. AMR Research Demand-Driven Manufacturing: The Potential Rise of Lean, June

13 Example: Traditional High-Volume Kanban Kanban Card Part Number: Quantity: 10 Stage: Fin Goods Kanban Card Part Number: Quantity: 10 Stage: Fin Goods Machine 1 Kanban Card Part Number: Quantity: 10 Stage: Machine Machine 2 Kanban Card Part Number: Quantity: 10 Stage: Machine Machine 3 Kanban Card Part Number: Quantity: 10 Stage: Fin Goods Raw Materials Kanban Card Part Number: Quantity: 10 Stage: Machine Kanban Card Part Number: Quantity: 10 Stage: Machine Kanban Card Part Number: Quantity: 10 Stage: Fin Goods Fin. Goods Kanban Card Part Number: Quantity: 10 Stage: Machine 2 13

14 Will Traditional Kanban Work for High-Mix? Part Specific cards: Requires inventory to be held for every part every day, even if the parts are -Low volume -Make-to-order, or -Beginning or End of product life-cycle One piece flow: Requires either very fast set-up times or dedicated equipment. Paper-based signals: Requires paper (or similar substitute) to physically move upstream. 14

15 4 Flavors of Pull for High-Mix 1. Part-specific Kanban Best option for repetitive parts Best for High- Volume No Software Required 2. Part-generic Kanban 3. Drum Buffer Rope 4. Constant Work in Process (CONWIP) Better fit for uncommon parts Best when bottleneck is known & fixed Broadly applicable/ most flexible Best for High-Mix or Maketo-Order Software Required 15

16 Extending Lean to High-Mix Industries using Lean Software #1 Value Streams #2 Organization #3 Performance Measures #4 Bottlenecks and Capacity Planning #5 Inventory Optimization #6 Lot Sizing #7 Pull Toyota Dedicated cells for similar products Dedicated people for each cell Visual line of sight metrics like Heijunka boards Fixed bottlenecks & Rules of thumb to dedicate capacity Rules of thumb to slowly lower water levels Rules of thumb like EPEI Part-specific Kanban High-Mix Flow Paths through shared equipment Focused factories aligned to flow paths Flow Path metrics leveraging enterprise software Shifting Bottlenecks & Optimization of capacity buffers Optimization of inventory buffers using operations research Optimization of lot sizes/campaign sizes/rhythm wheels Part-generic techniques like CONWIP 16

17 The Lean Journey & The Role of Lean Software Define Build Business Case Map Value Streams & Design Pull Leverage Data Assets Measure Analyze Improve Measure Performance vs. Goal Optimize Inventory & Capacity Reduce Waste & Variability Lean Software is Necessary for - High-Mix - Scalability - Sustainability Improve Flow & Visibility Implement Pull 17

18 Lean Software Extends ERP & MES for Lean Corporate Business Systems like ERP (level 4) Business Planning & Logistics Plant-Level Automation Systems like MES (level 3) Lean Software: Measures Lean Business Case Analyzes Variability & Optimize Inventory Models & Selects Kaizen Improvements s Flow & Implements Pull Manufacturing Operations & Machine Monitoring & Supervision like HMI (level 2) Sensors & Process lers like PLCs (levels 1,0) Batch Continuous Discrete (Hierarchy from ISA standard for Enterprise/Manufacturing Integration) 18

19 Agenda The Business Case for Lean Lean in High-Mix Industries & The Role of IT Case Studies & Best Practices 19

20 4 Case Studies on How IT Supports Lean Define Measure Analyze Improve 20

21 Value Stream Mapping for High-Mix RM 21 WIP FG Post Treatments CBM Dilution H2O Dil. Mash Weigh Sterilization Seed Tank Mash Weigh & Make Up Sterilization Fermentation Beer Wells Precipitation 2 De Water 2 Press 2 Shake Flask All Other 12 Liter L2 Pasteurization Drying 2 Milling 2 Post Treatment Post Treatments Gellan 12 Liter KOH Addition Gellan Pasteurization Filter / ph adjustment Precipitation 3 De Water Press 3 Drying 3 Milling 3 Extruder Recon. System Blend 2 Gly. Trmnt Bld 2 Blending 2, 3, 4 Blending 8 Fine Milling 4, J10 Specialty Blend 4,5,10,11,12, 13 Fine Milling J10 FG Packaging Specialty Blend 10, 5 Fine Milling 4 Specialty Blend 5, 11, 12, 13 Blend 4 IP IP 3 3 Q C IP IP IP IP Q C 1 Q C Q C Q C Q C GelRite Gellan Xanthan 3 / NAWX Diutan Rhamsan Dispersable Xthn Xanthan 2 Xanthan 1 L1 Pasteurization Precipitation 1 Press 1 Dry 1 Mill 1 Blend 1,6,7 2 IP IP Define Measure Analyze Improve

22 Pull Design for High-Mix Define Measure Analyze Improve Pull Design for SKUs using 2 Loop Replenishment Inboxes Sorted by Product Wheel CDL Inbox Pete CDL Loop Pull signasl from WIP Reblend Inbox Pete Reblend Loop Pull signals For Reblend Pull signals from Remote DCs Pull signals from San Diego DC Lyman sets targets Pull signals For CDL Pack to WIP Quality 2-14 days Reblend Re-pack WIP DC2 Hodges 20 SKUs 60% Buy Raw Material CDL Ferment ation Recover y Bledning 40% Pack to FG Quality Q.I. DC1 San Diego Direct Ship Ship to Customer Raw Material 22 DC 3 Columbus 4 SKUs DC4 Antwerp 6 SKUs

23 Used Data in ERP/MES to deliver Lean Business Case Define Measure Analyze Improve ERP Planning ERP/MES Execution ERP APS 23

24 Measure: Establish Scalable, Sustainable Lean Metrics De-emphasize traditional metrics like equipment utilization or department budgets Define Measure Analyze Improve Focus on measures that track the movement of materials to the customer through each value stream Cycle time elapsed time from receipt of raw materials to shipment of finished products Throughput - production rate of sales Customer Service - ability to meet customer commitments Utilize data already in ERP or MES systems so the metrics are scalable and sustainable 24

25 Used Lean Metrics to Reduce Cycle Times Define Measure Analyze Improve Before: No cycle time metrics Large piles of WIP Long cycle times After: Cycle time metrics using existing ERP/MES data on easy to use web pages Incentives for reductions 50% faster cycle times 25

26 26 e m e a q t u m u c c t U V + + ) (1 2 CT 1 1) 2( 2 2 Understanding Variability Define Analyze Improve Measure

27 Using Software to Manage Variability Define Measure Analyze You must understand variability and flow to improve inventory, cycle time, throughput, and customer service Reliability Process Quality Wait time Setup Forecast Error Lead Time New Products 27 Improve

28 Optimized Inventory & Customer Service using Lean Software Define Measure Analyze Improve 28

29 Optimized Lot/Batch Sizes using Lean Software Define Measure Analyze Improve Cycle Time (hrs) Cut Setup Times 20% Optimum Lot Size drops from: 8 to 5 Units Batch Size (jobs/batch) Lot Size [units] No Lot Splitting 29

30 Selected Best Kaizen Improvement Projects using Lean Software Define Measure Analyze Improve Production team identified 25 possible Kaizen improvement projects, and thought 6 of these should be implemented Team used Lean Software to evaluate all 25 projects, and found that a different 6 projects showed an ROI 375% greater than possible with initial 6 projects. Team implemented 6 projects selected by Lean Software: Cut Cycle Times by 33% Increased throughput by 10%, which was worth millions. 30

31 Improved Visibility Using Lean Software & ERP/MES Data Define Measure Analyze Improve Before: Many reports but little visibility 90 minute daily meetings Poor customer service After: 5 minute daily meetings 100% customer service (no late orders for 28 months) 31

32 Used Pull to Lower the Water Used Lean to Remove Rocks Define Measure Analyze Improve Raw Material Finished product to the customer Sea of Inventory Raw Material Low First Pass Success Cycle Time Schedule Sequence Restrictions Equipment Cycle Time Large Production Campaigns Long Changeover Times 32 QC / QA Cycle Time Poor Lead Time Management Uncontrolled Scheduling Forecast Accuracy Demand variability

33 Implemented Pull Using Lean Software & ERP/MES Data Define Measure Analyze Improve Raw Material Low First Pass Success Cycle Time Schedule Sequence Restrictions Equipment Cycle Time Large Production Campaigns 33 Long Changeover Times QC / QA Cycle Time Poor Lead Time Managemen t Uncontrolled Scheduling Forecast Accuracy Demand variability

34 Used Pull to Reduce Inventory by $10 Million Define Measure Analyze Improve Kilos [1000s] WIP vs. Inventory CONWIP vs. Target Pull Target during During Pilot Pilot Project 1st CONWIP Target: WIP Dropped & Stabilized (Target Removed: WIP Grew again) 2nd CONWIP Target: WIP Dropped & Stabilized 8/23 9/22 10/22 11/21 12/21 1/20 34

35 Thank You! Questions (800)