# Cobot Factory Operations_ Payback Analysis & Labor Market Impact ## Slide 1 STRATEGIC ASSESSMENT 2026 Cobot Factory Operations Payback Analysis & Labor Market Impact Chinese cobot clusters, CNC automation economics, and the urgency of building IE reconfiguration capability Philippine Manufacturing Operations June 2026 ## Slide 2 EXEC UTIVE OVER VIEW 01 The CNC Cost Revolution 02 Chinese Cobot & AMR Benchmark 03 Payback Period Analysis 04 Labor Market Impact 05 Construction: 3-Year Horizon 06 Implementation Roadmap 07 Staff Templates & Placeholders ## Slide 3 01 The CNC Cost Revolution Why automation economics suddenly work — the 10x cost collapse in machining centers and the shift to utilization maximization ## Slide 4 CNC machine prices collapsed 6-10x in a decade — idle spindle time is now the dominant cost Cost Factor | 2015 (Imported CNC) | 2025 (Chinese Domestic) | Change Entry-level 3-axis VMC | $80K - $120K | $8K - $20K | ~6-10x cheaper Mid-range VMC (0.01mm) | $120K - $200K | $25K - $50K | ~4-5x cheaper Cost per machine-hour | $8 - $15/hr | $2 - $4/hr | ~3-4x cheaper Machines per floor (typical) | 10 - 30 units | 80 - 200 units | ~5-7x more Utilization target | 50-60% (1 shift) | 80-95% (2-3 shifts) | +30-35 pp KEY STRATEGIC INSIGHT At $15K-35K per machine, a material handler earning PHP 260K/year represents a meaningful fraction of hourly operating cost. Cobot automation becomes rational not as luxury — but as competitive necessity. Chinese shops achieve 80-90% utilization via multi-shift cobot tending. Philippine shops at 50-65% utilization on single-shift manual operation cannot compete on cost-per-part. 10x PRICE REDUCTION (Entry-level VMC, 10yr) 85-95% TARGET UTILIZATION (With cobot tending, 3 shifts) Source: Chinese domestic VMC market analysis, Dongguan/Ningbo machine shop surveys, 2024-2025 ## Slide 5 Four Chinese cobot brands deliver comparable specs at 40-60% below Western prices Brand | Flagship Series | Payload | Reach | Repeatability | Price (USD) | Best For Elite Robots | CS Series | 3-30 kg | 624-1800mm | 0.03 mm | $12K-$35K | Machine tending JAKA Robotics | Zu Series | 3-18 kg | 327-1327mm | 0.03 mm | $12K-$36K | Compact cells AUBO Robotics | i-Series | 3-20 kg | 500-1350mm | 0.02 mm | $14K-$38K | Precision assembly Dobot | CR Series | 5-20 kg | 400-1700mm | 0.05 mm | $18K-$55K | Heavy payload Universal Robots | e-Series | 3-30 kg | 500-1750mm | 0.03 mm | $28K-$75K | Ecosystem leader FANUC (Ref) | CR/CRX | 4-35 kg | 550-1800mm | 0.01 mm | $35K-$90K | Precision leader All four Chinese brands carry CE marking and meet ISO 13849 safety standards. The gap vs. Universal Robots is not hardware capability — it's ecosystem maturity (UR+ marketplace has 400+ certified peripherals), global support density (24 offices, 1,100+ integrators), and long-term field data (17+ years vs. 5-8 years). For Philippine manufacturers with internal technical staff capable of handling integration, Chinese brands offer comparable specifications at roughly half the hardware cost. Source: Vendor datasheets, RobotShop pricing, cobot market analysis 2025-2026 ## Slide 6 Chinese AMRs complete the automation stack at $30K-$60K with 1-2 year payback AMR Category | Payload | Navigation | Price (USD) | Payback | Use Case Tote/case handling | 50-200 kg | LiDAR + camera | $30K-$60K | 1-2 years | Line-side feeding Pallet-moving | 1,000-1,500 kg | SLAM + vision | $50K-$95K | 1.5-3 years | Bulk material Forklift AMR | 2,000+ kg | LiDAR + 3D vision | $80K-$150K | 2-3 years | Heavy pallets LEADING CHINESE AMR VENDORS Geek+ — 40,000+ units deployed globally, warehouse & manufacturing Hikrobot — Machine vision + AMR integrated platform Quicktron / Hai Robotics — ASRS + AMR hybrid solutions AMRs complement cobots: Cobots = load/unload. AMRs = material flow. Payback: 1-2 years for tote AMRs. [STAFF: Insert AMR cost-per-tote-move comparison chart] vs. manual forklift + operator labor cost Key advantage: Chinese AMR peers benefit from well-developed domestic robotics component ecosystems, providing cost advantages resulting in typical paybacks of 1-3 years vs. 3-5+ years for European or American AMR vendors. For a CNC tending cell, the relevant category is tote/case handling — moving bins of raw parts and finished components between the cell and inventory stations. Source: Geek+, Hikrobot, Quicktron vendor pricing; Interact Analysis AMR market report 2025 ## Slide 7 A complete cobot+AMR cell costs $84K-$124K installed and serves 4-6 CNC machines Component | Specification | Qty | Subtotal (USD) Cobot arm | Elite CS612 / JAKA Zu 12 | 2 | $30K-$36K End effector / gripper | Pneumatic or electric | 2 | $6K-$12K AMR (tote handling) | 100 kg, LiDAR nav | 1 | $35K-$50K Safety peripherals | Light curtains, e-stops | 1 set | $2K-$5K Integration & programming | Commissioning, training | 1 | $8K-$15K Mobile workstation | Adjustable, locking | 2 | $3K-$6K Total Installed Cost | | | $84K-$124K Total (PHP @ 59:1) | | | P4.96M - P7.32M DEPLOYMENT SCENARIOS Conservative: 1 cobot + 1 AMR, 2 CNCs ~$45K-$60K installed Moderate: 2 cobots + 1 AMR, 4 CNCs ~$72K-$85K installed Aggressive: 3 cobots + 2 AMRs, 6 CNCs ~$105K-$140K installed Critical insight: These costs are front-loaded and fixed, while labor costs displaced are recurring and escalating at ~5% annually (minimum wage adjustments). The investment is significant but dwarfed by the P15M-P25M in 5-year cost avoidance it generates at aggressive deployment scale. P4.96M MODERATE CELL COST (PHP) 4-6 CNC MACHINES SERVED P15M-P25M 5-YEAR COST AVOIDANCE Source: Vendor quotes, integration estimates, PHP/USD 59:1 ## Slide 8 02 Payback Period Analysis Financial modeling for the Philippine wage context PHP 260K labor vs. automated cobot+AMR cells ## Slide 9 Aggressive cluster deployment achieves 16.9-month payback — validating the 2-year target Scenario | Cell Cost | Workers Displaced | Shifts | CNCs | Annual Savings (PHP) | Payback (Months) Conservative | P2.66M | 3 | 2 | 2 | P975K | 32.7 Moderate | P4.25M | 6 | 2 | 4 | P1.95M | 26.1 Aggressive | P6.20M | 13.5 | 3 | 6 | P4.39M | 16.9 PAYBACK FORMULA Payback = Cost / (Savings x 1.25) 1.25x = throughput gain + scrap reduction + lights-out [STAFF: Insert payback period bar chart — conservative / moderate / aggressive] Include 24-month target line for visual reference Key validation: Only the aggressive deployment achieves the ~2-year payback target. A single cobot on one shift takes 10+ years to pay back — cluster deployment across multiple machines and shifts is the correct strategy. The same fixed cell cost is amortized over more labor-hours eliminated per additional shift. Source: Modeled from vendor quotes, PHP 260K labor, 59:1 exchange rate, 25% throughput uplift ## Slide 10 Automated cells break even at Year 3 and generate P1.5M-P2M net savings by Year 5 [STAFF: Insert 5-year cumulative cost chart] Manual labor (red) vs. Cobot cell + supervisors (green) — show crossover point at Year 3 5-YEAR CUMULATIVE (MODERATE SCENARIO) Manual Labor: 6 handlers x P260K x 2 shifts Wage escalation: 5% annually 5-year total: ~P8.5M Cobot Cell: Upfront: P4.25M (cell cost) Ongoing: 2 supervisors + 3% maintenance 5-year total: ~P6.8M Net savings by Year 5: P1.7M THE COMPOUNDING PHASE From Year 3 onward, every additional year generates approximately P1M-P1.5M in cost avoidance. The fixed capital cost has been recovered; ongoing savings accrue directly to margin. This is when automation transitions from "cost project" to "profit driver." Year 3 CROSSOVER POINT P1.7M NET SAVINGS BY YEAR 5 Source: Financial model, moderate scenario, 5% annual wage escalation ## Slide 11 Every additional shift operated is the single biggest lever on payback time Variable Change | Base Case | Optimistic (+20%) | Impact on Payback Labor cost per worker | P260K/yr | P312K/yr | -2.8 months Throughput/quality gain | +25% | +40% | -2.1 months Cell cost (volume discount) | P6.20M | P5.31M | -2.5 months Shifts operated (+overtime avoid) | 3 shifts | 3 + no overtime | -1.5 months Combined optimistic | 16.9 mo | ~11.0 mo | -5.9 months total MOST POWERFUL LEVER Shift count is the #1 lever: 1. Same fixed cost, more labor-hours eliminated 2. More workers displaced per shift added 3. No extra capital — just scheduling 4. Avoids overtime premiums Plan for 3 shifts from Day 1. Pessimistic: Single-shift, low throughput = 30+ months. Conservative (1-cobot) not recommended. Mitigation: Start moderate (2 cobots, 2 shifts), expand after payback validates. [STAFF: Insert tornado/sensitivity diagram showing variable impact on payback] Range: labor cost, cell cost, throughput gain, shift count, maintenance % Source: Sensitivity analysis on aggressive scenario base case (16.9 months) ## Slide 12 03 Labor Market Impact Who gets displaced, when, and what new roles emerge in manufacturing and construction ## Slide 13 Philippine manufacturing shed 150K-424K jobs in 2025 as automation accelerates [STAFF: Insert S-curve displacement chart] % of at-risk material handling jobs automated, 2025-2035 2025 PSA EMPLOYMENT DATA Manufacturing: 49.26M employed (Nov 2025) Down from 49.54M (Nov 2024) Decline: 150K-424K jobs year-on-year Manufacturing subsector: 64,000 positions lost (Oct-Nov 2025 alone) At-risk roles: Routine, physically repetitive tasks requiring minimal cognitive judgment — CNC material handlers, part loaders, bin movers DISPLACEMENT TIMELINE (S-CURVE) 2025-2027 (Pilot): Early adopters deploy pilot cells — small % displaced 2027-2030 (Scale): Internal competency builds, acceleration phase 2030-2035 (Mature): Cobot tending becomes standard practice — 55% penetration NEW ROLES EMERGING Cobot Cell Operator: P400K-500K/yr (vs. P260K handler) Cobot Maintenance Technician: P450K-600K/yr Industrial Engineer (Cell Optimization): P500K-800K/yr Cobot Programmer / Integrator: P400K-700K/yr Polarization: Demand grows for cobot technicians. Demand shrinks for material movers. WEF: 85M jobs displaced, 97M created — transition favors higher-skill roles. Source: Philippine Statistics Authority 2025; WEF Future of Jobs Report 2020 ## Slide 14 Construction automation follows a 3-year lag as heat stress claims 19% of working hours by 2030 HEAT STRESS IMPACT (ILO PROJECTIONS) Construction share of global working hours lost to heat stress: 1995: 6% | 2030: 19% (3x increase) Philippine construction: 9.8% of total workforce (Nov 2025) Ambient temps: 35-40C, heat index: 50C+ High voluntary attrition as workers leave for indoor jobs CONSTRUCTION ROBOTICS MARKET 2025: $1.53 billion 2034 (projected): $6.27 billion CAGR: 15.2% Key categories already commercial: Autonomous earthmoving (Built Robotics) Rebar tying robots (TyBOT) Layout robots (Dusty Robotics) [STAFF: Insert construction robotics maturity timeline — 2026-2031] Show phases: R&D (now) -> Pilot (2027-2028) -> Commercial Scale (2029-2031) -> Mature (2032+) Map to specific robot categories: earthmoving, rebar, layout, demolition, exoskeletons The 3-year lag thesis: The same Chinese ecosystem that cut CNC/cobot costs now targets construction. Sany, XCMG, Zoomlion integrate autonomy into export machines. Costs follow the same 40-60% discount pattern. Implication: Cobot/IE competency built today directly transfers to construction robotics in 2028-2030. 3-year LAG VS. MANUFACTURING 15.2% MARKET CAGR Source: ILO Working on a Warmer Planet 2019; Grand View Research 2025; PSA 2025 ## Slide 15 The IE function is the competitive moat — not the hardware HARDWARE = COMMODITY Any competitor can buy the same: Elite CS612 from the same distributor JAKA Zu 12 at the same price Geek+ AMR from the same vendor Hardware advantage: Zero Sustainable differentiation: None IE CAPABILITY = COMPETITIVE MOAT Your IE can deliver: 15-minute changeover (drag-to-teach + job library) vs. competitor's 4+ hours of specialist programming Cell reconfiguration for new products: Minutes Optimized layouts for max throughput: Custom Changeover playbooks: Documented & trained WHAT YOUR IE DOES THAT COMPETITORS CANNOT COPY: 1. Cell Layout: Groups machines by cycle time, part family, changeover frequency. Optimal ratio: 2-3 CNCs per cobot. 2. Changeover: Playbooks for gripper swap, program select, fixture adjust, QA check. Target <15 min. 3. Cycle Balancing: No machine waits idle. Optimal service schedules. 4. Training: Internal capability for diagnostics, reprogramming, PM without vendor dependency. Wage comparison: Material Handler: P260K/yr | Cobot Cell Supervisor: P400K-600K/yr Industrial Engineer: P500K-800K/yr The wage premium reflects skill scarcity — and creates worker incentive to upskill. Source: Internal capability assessment framework; cobot vendor training data ## Slide 16 04 Implementation Roadmap 42-month phased deployment plan Urgency assessment and risk mitigation ## Slide 17 Three converging pressures make the next 12-18 months critical 1. COMPETITIVE DYNAMICS Chinese machine shops run 120+ CNCs at 80-90% utilization via cobot tending. Can deliver parts at 30-50% lower cost-per-part than manually operated PH shops. As Chinese CNC gets cheaper, this gap widens. Vietnam and Indonesia are already deploying at scale. 2. LABOR SUPPLY CONSTRAINTS PH manufacturing shed 424K workers in Dec 2025. Remaining workers seek higher-skill, higher-wage roles. Pool for repetitive handling at P260K/yr is shrinking. Automation = operational continuity necessity. 3. TECHNOLOGY COST CURVES Cobot prices declining ~6% annually (2023-2025). Waiting 2-3 years saves marginal hardware cost. But 12-18 month learning curve means late starters begin at zero when competitors scale. Competency is the asset — not the hardware. THE COMPETENCY WINDOW: 12-18 MONTHS TO BUILD INTERNAL CAPABILITY Learning curve: Vendor select (2-3 mo) IE hire + train (3-6 mo) Pilot + debug (3-4 mo) Cost of delay: P200K-P400K/month + Lost contracts + Shrinking pool 12-18 mo COMPETENCY BUILDING WINDOW 6% ANNUAL COBOT PRICE DECLINE 424K PH MANUFACTURING JOBS LOST (DEC 2025) Source: PSA employment data; cobot market price tracking; competitive analysis ## Slide 18 Four-phase roadmap: 42 months, P10M-P15.5M investment, 15-20 positions displaced Phase | Timeline | Actions | Investment (PHP) | Milestone 1. Foundation | Months 1-6 | Hire IE; send 2 techs to China for training; pilot 1 cobot on 1 CNC | P1.5M - P2.5M | Single cell operational, operators trained 2. Scale | Months 7-18 | Deploy 2-cobot cell + AMR; document changeover; evaluate 3rd shift | P3.0M - P4.5M | 4-6 CNCs automated, payback data validated 3. Optimize | Months 19-30 | Expand to 3 cobots + 2 AMRs; predictive maintenance; lights-out runs | P2.5M - P3.5M | 6+ CNCs on 3 shifts, >85% utilization 4. Expand | Months 31-42 | Replicate across product lines; in-house programming; construction R&D | P3.0M - P5.0M | Multiple cells, construction robotics pilot TOTAL: P10.0M - P15.5M | 15-20 POSITIONS DISPLACED | ANNUAL COST AVOIDANCE: P5M+ FROM YEAR 3 [STAFF: Insert Gantt chart or timeline visualization showing 4 phases across 42 months] Include key milestones, investment tranches, and headcount transition points Source: Internal financial model, vendor quotes, integration estimates ## Slide 19 Six risk categories with concrete mitigation strategies Risk Category | Specific Risk | Likelihood | Impact | Mitigation Technology | Vendor support delays (Chinese brands have thinner global networks) | Medium | High | Spare parts inventory; select vendor with SE Asia distributor; train internal techs for Tier 1 repairs Technology | Integration complexity (CNC door interlocks, spindle signals, error handling) | High | Medium | Budget 30-80 hrs integration engineering; hire experienced IE; contract integrator for first cell Workforce | Resistance to automation from remaining staff | Medium | Medium | Upskill-vs-exit policy; retrain handlers as operators (P260K to P400-500K); phase over 12-18 months Workforce | Skill gap — no internal cobot experience exists | High | High | Vendor training program; pilot cell as learning platform; hire 1 experienced IE as anchor Financial | Payback period exceeds 24-month target | Medium | High | Conservative modeling; commit to 3-shift operation; track OEE weekly; exit gate at Month 6 if pilot fails Market | Competitor automates faster and captures contracts | High | High | Fast-follower strategy; 12-month pilot-to-scale target; build IE capability as defensible moat [STAFF: Insert risk probability-impact matrix heat map] Plot each risk on Likelihood x Impact grid; color-code by mitigation status RISK SUMMARY Highest: Market + Skill gap Action: Hire IE, lock vendor, upskill Source: Internal risk assessment framework; vendor due diligence ## Slide 20 STAFF TEMPLATE — FILL IN YOUR DATA Your CNC Machine Inventory & Specifications Instructions: List every CNC machine in your facility. This data drives cobot cell grouping decisions. Prioritize machines with highest spindle hours and most repetitive part families for automation first. Machine ID | Model | Brand | Year | Spindle Hrs/Day | Utilization % | Parts/Shift | Priority (1-5) | Notes [CNC-001] | [e.g., VMC-850] | [e.g., Syntec] | [2022] | [16] | [65%] | [120] | [1] | [Add notes] [CNC-002] | [...] | [...] | [...] | [...] | [...] | [...] | [...] | [...] [CNC-003] | [...] | [...] | [...] | [...] | [...] | [...] | [...] | [...] [CNC-004] | [...] | [...] | [...] | [...] | [...] | [...] | [...] | [...] [CNC-005] | [...] | [...] | [...] | [...] | [...] | [...] | [...] | [...] [CNC-006] | [...] | [...] | [...] | [...] | [...] | [...] | [...] | [...] [CNC-007] | [...] | [...] | [...] | [...] | [...] | [...] | [...] | [...] [CNC-008] | [...] | [...] | [...] | [...] | [...] | [...] | [...] | [...] Next step: Share with IE to identify part family groups. Priority 1-2 machines = aggressive cell targets. Tip: Photograph nameplates for unclear model data. ## Slide 21 STAFF TEMPLATE — FILL IN YOUR DATA Your Cobot Cell Layout Design Instructions: IE to sketch actual cell configurations. Use grid paper or CAD. Show machine positions, cobot reach envelopes, AMR paths, safety zones, and part staging. Start with your Priority 1-2 machines from the inventory. [DRAW OR INSERT FLOOR PLAN HERE] Scale: 1 grid square = 1 meter Legend: CNC = machine, C = cobot base, A = AMR station, S = staging, Z = safety zone LAYOUT CHECKLIST [ ] CNCs by part family [ ] Cobot reach covers chucks [ ] AMR aisle 1.2m [ ] Staging near machines [ ] Light curtains [ ] E-stop within 2m [ ] Cables safe [ ] Maintenance access [ ] Exit path [ ] Material entry Dimensions: [ ] Reach: _____ mm [ ] Spacing: _____ m [ ] Ceiling: _____ m [ ] Floor: _____ kg/m2 ## Slide 22 STAFF TEMPLATE — FILL IN YOUR DATA Your Product Line Mapping to Cells Instructions: Map each product family to a proposed cobot cell. This determines changeover frequency, gripper requirements, and which machines can be grouped. Products with similar cycle times and part sizes are best grouped together. Product Family | Part Wt/Size | Cycle Time | Current CNC | Proposed Cell | Changeover (now) | Target (<15min) | Parts/Month [e.g., Bracket-A] | [2kg / 150mm] | [8 min] | [CNC-001] | [Cell-1] | [45 min] | [10 min] | [3,000] [...] | [...] | [...] | [...] | [...] | [...] | [...] | [...] [...] | [...] | [...] | [...] | [...] | [...] | [...] | [...] [...] | [...] | [...] | [...] | [...] | [...] | [...] | [...] [...] | [...] | [...] | [...] | [...] | [...] | [...] | [...] [...] | [...] | [...] | [...] | [...] | [...] | [...] | [...] Analysis guidance: Products with cycle times within 20% of each other and part weights within the same cobot payload range should be grouped. The changeover time target of <15 minutes requires: (1) stored job programs in the cobot library, (2) quick-change grippers, (3) standardized fixtures, and (4) a documented step-by-step procedure. After completion: Sort by "Proposed Cell" to see which products share cells. Verify that total cycle time per cell does not exceed cobot service capacity. ## Slide 23 STAFF TEMPLATE — FILL IN YOUR DATA Your IE Changeover Procedure Template Instructions: Document the step-by-step changeover process for each product family transition. This becomes the standard operating procedure that any trained operator can follow. Target: <15 minutes total changeover time. Step | Action | Details / Parameters | Tools Needed | Safety Check | Time (min) | Done 1 | [Stop current program] | [E-stop, confirm spindle stop] | [None] | [Chuck clear] | [0.5] | [ ] 2 | [Remove finished part] | [Place in finished bin] | [Gloves] | [Part cool] | [1.0] | [ ] 3 | [Swap gripper] | [Quick-connect fitting] | [Wrench] | [Air off] | [2.0] | [ ] 4 | [Select new job program] | [From stored library] | [Teach pendant] | [Verify program ID] | [1.5] | [ ] 5 | [Adjust fixture / offsets] | [Per product spec sheet] | [Dial gauge] | [Zero confirmed] | [3.0] | [ ] 6 | [Load first blank] | [Cobot auto-loads] | [Staging bin] | [Material correct] | [2.0] | [ ] 7 | [QA first-piece check] | [Dimension + surface] | [Calipers] | [In spec] | [3.0] | [ ] TARGET: _____ min Procedure notes: Each product family transition needs its own changeover sheet. Common transitions (frequent product switches) should be optimized first. Store all job programs in the cobot's internal library with clear naming: [PRODUCT]-[MACHINE]-[GRIPPER]-v[X] After completion: Time each step with a stopwatch during actual changeover. Identify bottlenecks and iterate. Post the finalized procedure at each cell. ## Slide 24 STAFF TEMPLATE — FILL IN YOUR DATA Your Staff Training & Transition Plan Instructions: Map each affected worker to a transition path. The upskill-vs-exit policy should prioritize retraining existing staff over hiring externally. Document training modules, providers, costs, and completion targets. Current Role | Target Role | Trainee | Training Module | Duration | Provider | Cost (PHP) | Complete By Material Handler | Cell Operator | [Name] | [Cobot basics + safety] | [2 weeks] | [Vendor / In-house] | [P25K] | [Month 3] Material Handler | Cell Operator | [Name] | [...] | [...] | [...] | [...] | [...] [Machinist] | [Maint. Tech] | [Name] | [Cobot diagnostics + PM] | [4 weeks] | [Vendor cert.] | [P50K] | [Month 6] [New Hire] | [IE - Cell Opt.] | [Name] | [Cobot programming + layout] | [8 weeks] | [Vendor + abroad] | [P120K] | [Month 4] [...] | [...] | [...] | [...] | [...] | [...] | [...] | [...] [...] | [...] | [...] | [...] | [...] | [...] | [...] | [...] POLICY 1. Retrain staff 2. Hire for IE only 3. Attrition absorbs loss BUDGET Trainees: _____ Total: P_____ Avg: P_____ After completion: Share with HR for budget approval and scheduling. Coordinate with vendor training calendars. Book travel for abroad training 2 months in advance. ## Slide 25 STAFF TEMPLATE — FILL IN YOUR DATA Your Custom Financial Projection Model Instructions: Replace bracketed values with your actual shop data. This model auto-calculates payback based on your specific labor costs, shift structure, and cell configuration. Adjust variables to test different scenarios. INPUT VARIABLES | YOUR VALUE Number of cells planned | [e.g., 2] Cobots per cell | [e.g., 2] AMRs per cell | [e.g., 1] CNC machines served per cell | [e.g., 4] Shifts operated | [e.g., 2] Workers displaced per cell | [e.g., 6] Annual labor cost per worker (PHP) | [e.g., 260,000] Cell cost per unit (PHP) | [e.g., 4,250,000] AUTO-CALCULATED | RESULT Total cobots | [= Cells x Cobots] Total AMRs | [= Cells x AMRs] Total workers displaced | [= Cells x Workers] Annual labor savings (PHP) | [= Workers x Labor Cost x 1.25] Total cell investment (PHP) | [= Cells x Cell Cost] Annual maintenance (3%) | [= Investment x 0.03] Net annual benefit (PHP) | [= Savings - Maint.] PAYBACK (months) | [= Investment / Net Benefit x 12] Test one variable at a time. Top levers: (1) Shifts 2->3, (2) More CNCs per cell, (3) Volume discount on 2+ cells. Save conservative/moderate/aggressive versions. Include 5% annual wage escalation. ## Slide 26 STAFF TEMPLATE — FILL IN YOUR DATA Your Vendor Evaluation Scorecard Instructions: Evaluate 3-4 cobot vendors using weighted scoring. Rate each 1-5 on each criterion. Multiply by weight to get weighted score. Total possible: 100 points. Weight reflects your priorities — adjust weights if needed. Evaluation Criteria | Weight | Vendor A [Name] | Vendor B [Name] | Vendor C [Name] | Vendor D [Name] | Notes Price (per cobot) | 20% | [Score x 20] | [Score x 20] | [Score x 20] | [Score x 20] | [Include quote ref] Payload / reach fit | 15% | [...] | [...] | [...] | [...] | [Match to your parts] Support in Philippines | 15% | [...] | [...] | [...] | [...] | [Local office? Distributor?] Spare parts availability | 10% | [...] | [...] | [...] | [...] | [Stock in SE Asia?] Training program offered | 10% | [...] | [...] | [...] | [...] | [Onsite? Abroad? Cost?] Warranty & service terms | 10% | [...] | [...] | [...] | [...] | [Years? Response time?] TOTAL WEIGHTED SCORE | 100% | [Total] | [Total] | [Total] | [Total] | [Winner: _____] Evaluate: Elite, JAKA, AUBO (+ Dobot for heavy). Request: quote, SE Asia contact, training outline, reference customer. Top 2 proceed to on-site demo with actual parts/CNCs. ## Slide 27 The Imperative is Now The 12-18 month window closes. Competitors deploy today. Hardware is commodity. Capability is moat. Start one pilot. Build IE. Scale with conviction. 1. Hire IE within 30 days 2. Issue RFP to 3 cobot vendors within 60 days 3. Deploy pilot cell within 6 months 16.9 MONTH PAYBACK P5M+ ANNUAL SAVINGS YR 3 13.5 WORKERS DISPLACED/CELL June 2026 | Strategic Operations Assessment