Introduction to LEAN SIMULATION MODELS 2/1/2008 1
Contents 1. Overview of Models 2. Highlights of the Lean Manufacturing Model 3. Background on Enclosures Documentation & Setup Guides for each Model 2/1/2008 2
1. Models Lean Manufacturing Demand driven Scheduling options Validation, changeover & cleanout rules Optional Integration In-process tests Raw materials tests & inventory Laboratory Test profiles Lab skills Equipment planning Clinical Trials Strategic Planning Patient recruitment R&D & Quality processes Clinical supply chain Plant capacity Supply chain flows & inventory Tax, royalty, plant cost & incremental investment Established & developmental products 2/1/2008 3
1. s Models Are Essential Tools for Lean Programs To Test Alternative Solutions Before Implementing Them To analyze plant capacity to trade-off volume & mix (variety) of products To analyze service levels to balance demand and supply Make-to-Stock inventory, typical in commercial environments Make-to-Order lead times, typical during clinical trials and pilot plant operations There can be a multiple sites across a supply chain to be analyzed - from chemical to finishing and packaging operations. Simulation models take variability (in processing, cleanouts and downtime) into account which is not possible to do with an equation. 2/1/2008 4
2. Highlights of Lean Model Spreadsheets Start rules Provide timing, sequence, campaign lengths, etc. Arrays Provide process times, valid equipment, etc. Run parameters Switches to activate functions Configured for any product/process type Summary Reports in Spreadsheets 2/1/2008 5 Graphs Lot detail in Reporting Spreadsheet
2. Lean Model Folder spreadsheet capable Master workbooks are inputs automatically read in at the start of a run Operations-Equip for Notebook is a reference information-only spreadsheet Report workbooks are outputs updated automatically at the end of a run Setup Checklist is a reference spreadsheet 2/1/2008 6
2. Lean Model Overview Panel Hierarchy Top level of model Start rules Each operation contains Operation Panel These panels and the spreadsheets contain inputs & outputs 2/1/2008 7
2. Parameters & Results for each operation Within each operation, Takt Time & OEE is calculated for each set of equipment Within each operation, there is also logic for processing each lot through quality lab or release processes after the manufacturing process completes 2/1/2008 8
2. Scheduling & Replenishment Design 6 7 Rhythm Wheels, CONWIP, Kanban Options: - Schedules (including rhythm wheels) & campaign lengths can be evaluated - Kanban triggers & sizes integrated - Takt rates from actual demand. Materials flow from operation Trigger starts processing The Start Signal determines how the trigger is created 2/1/2008 9 Product/equipment validation matrix drives the choice of path used with the scheduling rules.
2. Details of Cleanouts/Changeovers for all Production & Shared Equipment Cleaning Rules Include types of cleans required: Between lots or campaigns Between product groups Between colors (lighter to darker, darker to lighter) Between strengths After a number of lots After a time period Shared tanks, bins, carts also included 2/1/2008 10 Variability Uses probabilistic processing for: Processing times Full & Back-to-Back Cleanouts Quality lab & Release times Late materials Scrap rates Absentee rates in labor crews Hold & Equilibration times If there are sufficient data, STAT::FIT distribution-fitting software is used to create statistical distributions. Alternatively, minimum, maximum and most likely values may be used to populate triangular distributions.
2. All Types of BioPharma Operations Solids Products Liquids Products Mixing Hold Tanks Packaging Granulation Compression Coating Gel Dipping Printing Packaging 7 Gran units (6 Forms) 11 Comp units (16 Forms) Bins between Granulation & Compression WIP measured across entire process 11 Coating Pans 19 Total 8 Total Totes across remaining steps 11 Lines (95 FG SKUs) Cycle time of every batch recorded Demand Seasonality Bottle Size Mix Production Campaign History Hours 150 6 Mix tanks Wait times recorded for all batches Time Waiting for Packaging 12 Hold tanks CIP systems Value 1 10 Lines Bottles (125 FG SKUs) Utilizations of all resources computed vs. scheduled time Monthly Average Line1 Utiization Occurrences 1200 Avg Batches in WIP Hours 400 Cycle TIme 131.25 112.5 0.875 0.75 1050 350 93.75 0.625 900 300 75 0.5 750 600 450 300 150 0 0 5 10 15 20 Number of Batches AvgBatchesInWIP Shared Resources Utilization & Backlogs 250 200 150 100 50 0 0 2190 4380 6570 8760 Time Cycle Time Mean 56.25 37.5 18.75 0 0 1460 2920 4380 5840 7300 8760 Time Pkg Line 1 Pkg Line 2 Pkg Line 3 Pkg Line 4 0.375 0.25 0.125 0 0 1460 2920 4380 5840 7300 8760 Time Util By Month Cum Utilization Detailed Analysis of Manufacturing Lines e.g., Sterile Products with Lyophilization Units Re source Type Number Utiliza tion (95% confidence int) CleaningUnits Resourc e Pool 2 0.2431±0.04727 TotalCrewsAvail Labor 5 0.4347±0.02713 Value 1 Formulation (cart decontamination in parallel) Filling & Load Other batches starting in formulation suite using different lyophilization units Lyo Vials Filling & Capping Status Unload & Capping Y2 2 0.75 1.5 Value 2 CIP System Backlog 0.5 0.25 1 0.5 1.75 1.5 0 0 56 72.16667 88.33333 104.5 120.6667 136.8333 153 169.1667 185.3333 201.5 217.6667 233.8333 250 Time VialFormStat VialFillStat VialCap Y2 FilCapCartClean 1.25 1 0.75 Changeover & Cleanup Lines & Cart 0.5 0.25 0 0 1460 2920 4380 5840 7300 8760 Time Batches Waiting 2/1/2008 11 In this example, the 5 day freeze-dry cycle ends, but the cart is being cleaned; start of unload & capping is delayed
2. QC / QA Release Included As a Process Manufacturing Packaging Resource utilization & impacts in QC across multiple manufacturing centers can be tracked 2/1/2008 12
3. Some Background Operations improvement consulting since 1987 Strategic to operational level Physical and IT expertise Improvement methodology Simulation and optimization modeling www..com has some other examples & information Founded by Jim Curry Led large IT and operational process development organizations, including 10 years in wine and spirits industry (Seagram) Educational background in Operations Research Teaches simulation as a tool in lean manufacturing and supply chain design in graduate program at Fairfield University 2/1/2008 13
3. Some Client Examples Supply Chain Improvement & Simulation Modeling Rohm and Haas Arco Chemical Honeywell 3Com Blue Circle Cement J&J Sanofi-Aventis Aventis-Behring Parke-Davis Pfizer IT Planning / Architecture Hewlett-Packard UPS Gillette Nestle Logistics Arkema Minerals Technologies 2/1/2008 14
3. s Value Added VISION Integrated Pipeline Skills TOOLS & METHODOLOGIES Models Road maps PRODUCT Best Practices *Lean Simulation Models Integrated Supply Chain Info IMPLEMENTATION 2/1/2008 15