WATSONX INSPECT AI

Supply Chain Quality Control Automation - Business Case The Problem: Manual quality control in supply chain operations is slow, error-prone, and costly. Wrong items get shipped, damaged goods slip through, and warehouse staff spend hours on repetitive inspection tasks. The Solution: An automated quality control system that uses AI to inspect boxes and verify labels, catching errors before they reach customers. Problem 1: Wrong Items Get Shipped: What Happens: Package gets shipped to customer Customer receives wrong item Customer complains and returns item Company pays for return shipping ($25-50) Item needs to be restocked Correct item needs to be shipped again Customer satisfaction drops Manual visual check by worker Supervisor spot-checks 10% of packages Most errors caught only after customer complaint Problem 2: Damaged Goods Enter the Warehouse: What Happens: Damaged box enters warehouse Gets stored with good inventory Eventually gets shipped to customer Customer receives damaged goods Customer rejects shipment Company must replace item Original damaged item is now unsellable Receiving clerk inspects 5-10 boxes per shipment Takes 15-20 minutes per shipment Human fatigue causes missed defects No standardized criteria for "damaged" How It Works (In Simple Terms) Imagine you have a supervisor that never gets tired, never misses details, and works 24/7. That's what this system does. The System Has 4 "Specialists": The Box Inspector - Looks at every box and checks for damage The Label Checker - Reads labels and verifies they match the product The Order Validator - Checks if the order is correct in the system The Problem Solver - Handles issues and alerts supervisors How They Work Together: When a box arrives, the Box Inspector checks it automatically When a package is repacked, the Label Checker verifies the label matches If something's wrong, the Problem Solver stops the process and alerts a human Everything happens in seconds, not minutes.