## Step 1: Quantify Your Current Quality Costs Before you can show what AI saves, you need to know what poor quality costs today. Gather the following data for the target inspection point: → Scrap cost Units scrapped due to defects that escaped inspection × cost per unit → Rework cost Labour hours spent reworking defective units × loaded labour rate → Customer returns Field returns, warranty claims, and penalties attributable to the defect type → Manual inspection labour FTEs dedicated to visual inspection at this station × annual loaded cost → Downtime from escapes Line stops caused by defective parts reaching downstream operations → Sorting & containment Cost of sorting suspect lots after a quality escape is discovered **Pro tip:** Even a rough estimate is better than nothing. Most manufacturers undercount quality costs by 40–60% because they don't track downstream impacts like line stops and sort campaigns. Ask your quality, operations, and finance teams for their numbers, the range itself is informative. ## Step 2: Model the AI Inspection Investment An AI vision inspection system typically includes hardware (cameras, lighting, edge compute) and software (AI platform, model training, integration). Here's a typical cost structure: | Cost Category | Typical Range (per station) | Notes | | --- | --- | --- | | Camera + optics | $3K–$15K | Depends on resolution and lens requirements | | Lighting | $500–$3K | Application-specific (diffuse, backlit, structured) | | Edge compute | $2K–$8K | GPU-accelerated inference node | | AI platform license | $1K–$5K/mo | Includes model training, updates, cloud analytics | | Integration & setup | $5K–$20K | PLC integration, mounting, calibration | **All-in platforms like [Overview AI](/content/product/index.html) bundle camera, compute, and software into a single system**: simplifying procurement and reducing total cost of ownership. ## Step 3: Calculate ROI Use this simplified ROI formula to get started: ROI = (Annual Quality Cost Savings − Annual AI System Cost) ÷ Annual AI System Cost × 100% Most manufacturers see 3–10× ROI within the first 12 months. Be conservative with your estimates, it's better to under-promise and over-deliver. Common savings levers include: reduced scrap (20–50% improvement), eliminated manual inspection labour (1–3 FTEs), reduced customer returns (30–70% improvement), and faster root cause analysis (days → hours). ## Step 4: Design the Pilot A well-designed pilot de-risks the investment and generates the data you need for full-scale approval. Here's the blueprint: 1. Choose one high-impact inspection point - Pick the station with the highest defect escape rate, most manual labour, or most expensive rework. One station, one defect type. 2. Define success metrics upfront - Agree on measurable targets: detection rate (>99%), false positive rate (<1%), cycle time impact, and payback period. 3. Run parallel for 2–4 weeks - Deploy AI inspection alongside existing manual or AOI inspection. Compare results side-by-side to prove accuracy before cutting over. 4. Document everything - Log every defect caught, every escape prevented, every false positive, and every hour of manual inspection eliminated. This data builds the case for scaling. ## Step 5: Align Stakeholders Different stakeholders care about different things. Tailor your message: ### CFO / Finance - ROI timeline, payback period, capital vs. opex structure, total cost of ownership ### VP Operations - Throughput impact, integration complexity, line downtime during deployment, scalability ### Quality Director - Detection accuracy, false positive rates, traceability, audit compliance, escape rate reduction ### Plant Manager - Disruption to current operations, operator training requirements, maintenance burden ## Business Case Template Outline 1. **1. Executive Summary**: One paragraph: problem, solution, expected ROI 2. **2. Current State**: Quality costs, escape rates, manual inspection limitations 3. **3. Proposed Solution**: AI visual inspection overview, hardware/software scope 4. **4. Financial Analysis**: Investment cost, annual savings, ROI, payback period 5. **5. Pilot Plan**: Station selection, timeline, success metrics, resources needed 6. **6. Risk Mitigation**: Parallel run plan, vendor support, rollback strategy 7. **7. Scale-Up Roadmap**: Path from 1 station → 10 stations → global deployment ## Need Help Building Your Business Case? Our team works with quality and operations leaders every day to build ROI models and design pilot programs. Let's build your business case together.