AI-Based Recovered Paper Inspection System

Product Introduction

The AI-Based Recovered Paper Inspection System combines material preparation, AI vision inspection, selected contaminant detection, microwave moisture measurement and digital quality evaluation.
Designed for paper mills and recovered-paper receiving facilities, the modular system improves incoming-material visibility, inspection consistency and quality-data traceability.

Core Information

Detection Target	Typical Applications
Paper Grade · Visible Off-Grade Materials · Selected Contaminants · Moisture	Incoming Material Inspection · Supplier Quality Evaluation · Procurement Inspection · Receiving Quality Control

AI-Based Recovered Paper Inspection System image

Product Overview

Overview

Recovered-paper quality cannot always be evaluated using a single measurement parameter.
Paper grade, visible contaminants, moisture and material weight can all affect procurement evaluation and production suitability.
The MOSYE system combines selected inspection components in one configurable platform. Inspection results can be connected with supplier, batch and weighing information to support receiving quality control and procurement management.
Final system configuration depends on the paper mill’s recovered-paper grades, purchasing standards, receiving process and inspection objectives.

Application Scope

The system can be configured to evaluate:
Recovered-paper grades
Visible off-grade materials and contaminants
Selected sensor-detectable foreign materials
Truckload or individual-bale moisture
Weight, supplier and batch data can also be integrated.

Detection Principles

Recovered paper is prepared and conveyed through the inspection line. Industrial cameras capture material images, and application-specific AI models identify configured paper grades and visible off-grade materials. Additional components can measure moisture or detect selected contaminants. The system combines inspection results with weight, supplier and batch information to generate digital quality records. AI vision evaluates only materials visible to the cameras. Hidden or covered materials may require bale opening, material separation or additional inspection methods. Final acceptance and settlement decisions remain subject to the paper mill’s approved inspection procedures.

Key Advantages

Multi‑Parameter Inspection Combines AI vision, contaminant inspection, moisture measurement and production data to provide broader incoming‑material quality information.

Configurable System Design System components can be selected according to recovered‑paper grades, inspection targets, receiving workflow and project requirements.

Consistent Quality Evaluation Configured recognition categories and quality rules help apply more consistent inspection criteria across suppliers and incoming batches.

Digital Quality Data Inspection results can be connected with weighing, receiving, quality‑management, ERP or procurement systems.

Product Parameters

Parameter	Specification
Material-Preparation Module	Opens selected bales and distributes recovered paper for inspection
AI Vision Inspection Module	Identifies configured paper grades and visible off-grade materials
Camera and Lighting Module	Provides controlled image acquisition
Contaminant Detection Module	Detects selected foreign materials using the configured sensor technology
Microwave Moisture Measurement	Provides whole-truck or individual-bale moisture information
Weight Data Interface	Connects weighing data with inspection results
Industrial Control System	Coordinates conveying, inspection and system interlocks
Data Management Platform	Displays, records and transmits inspection information

Optional Configuration

01 — AI Vision Inspection Configuration

AI vision configuration for identifying selected recovered-paper grades, visible off-grade materials and configured contaminants.

02 — AI Inspection with Material Preparation

Combines bale opening, material distribution and AI vision inspection to provide more consistent image-acquisition and inspection conditions.

03 — Integrated Multi-Parameter Inspection

Combines material preparation, AI vision, selected contaminant detection, moisture measurement and quality-data management.

Moisture measurement can be configured with:

MS-X590: representative whole-truck moisture evaluation before unloading

MS-590L-1: individual-bale moisture measurement after unloading

Final configuration depends on the receiving workflow, inspection targets and project requirements.

Application Engineering

Evaluate the MS-204 for Your Process

Share your material characteristics, moisture range, process conditions and installation requirements with MOSYE application engineers. We will evaluate the appropriate probe, process connection and measurement configuration for your application.

Request Application Evaluation