Free Whitepaper
Manage quality-relevant production data end-to-end
Learn how to comprehensively capture process data in manufacturing, detect deviations early on, and archive quality-relevant information in an audit-proof manner to ensure maximum process reliability and minimize risks.

Practical tips for your practice
Ensuring Consistent Quality Data
How to make quality-related data from screwing, pressing, bonding, riveting, crimping, and testing processes centrally available.
Improving Traceability and Auditability
How to document process steps in a way that ensures long-term traceability—even over many years.
Reducing Production Risks Early On
How real-time analysis and structured worker guidance help identify errors early and prevent rework.
Significantly Reduce Archiving Costs
How long-term archiving using open formats reduces the load on your production systems and keeps costs under control.
A comprehensive software suite for your quality data management
In this whitepaper, you’ll learn how an integrated software suite captures quality-related production data throughout the entire lifecycle from data collection and analysis to long-term archiving.

Four Modules at a Glance
Integrated Process Data Management
Automatically captures process data, documents it in a history file, and issues real-time alerts in case of deviations.
Operator Guidance
Provides step-by-step guidance to operators during the assembly process and reduces errors through visual instructions.
Torque Measurement & Quality Inspection
Supports the planning, execution, and evaluation of quality-related inspections in series production.
Long-Term Archiving
Migrates inactive data to storage, keeps it available long-term, and simultaneously reduces storage and licensing costs.
Why You Should Read This Whitepaper Now
Rising recall costs, stricter product liability requirements, and increasing documentation obligations are putting pressure on production and quality management. At the same time, a shortage of skilled workers and heterogeneous system landscapes are making operational implementation more difficult.
This white paper shows you a practical way to manage your quality-relevant production data consistently, securely, and efficiently—without having to rebuild your existing infrastructure.

