Challenges in practice
Internal deviations in manufacturing, assembly, or logistics are often the root cause of subsequent customer or supplier complaints. Yet, in many companies, they are not systematically recorded and analyzed. Errors are addressed locally, root causes are not thoroughly analyzed, and insights remain hidden within specific departments.
Especially on the shop floor, suitable data capture options are frequently lacking: PCs at every production station are expensive, not universally available, and impractical in daily production. As a result, errors are documented late, incompletely, or not at all – valuable information is lost.
In addition, measurement data from inspections is often manually transferred or evaluated separately, which is time-consuming and prone to errors.
A lack of transparency regarding error frequencies, causes, and costs makes it difficult to prioritize improvements. Measures get lost in the daily grind, effectiveness checks are neglected, and recurring errors occur.
Without integration into FMEAs, controlling, and ERP processes, valuable optimization potential remains untapped.
Solution QS1
QS1 offers comprehensive internal deviation and CAPA management across all processes, production stages, and plants – right down to the shop floor.
Deviations can be easily, quickly, and remotely recorded directly at the point of action using a tablet or smartphone – a cost-effective alternative to desktop PCs. With a "flying tablet," shop floor employees can intuitively document errors without needing in-depth quality assurance knowledge or operating complex systems.
Measuring machines can be directly connected to QS1, allowing measurement data to be automatically transferred to inspection orders and deviations to be detected immediately. Manual data entry is eliminated, inspection processes are accelerated, and data quality is improved.
- Freely configurable process for recording internal deviations and errors
- Mobile error recording via smartphone or tablet directly in production and assembly
- Graphically guided error coding for a standardized internal error description
- Automatic generation of deviations from testing and quality processes
- Workflow-based internal corrective action and CAPA management
- Root cause analysis with Ishikawa diagrams, 5 Whys, and AI support
- Failure chain analysis across the batch network to identify causes and dependencies
- Transparent recording of scrap, rework, and error costs
- Feedback of internal deviations into FMEAs and improvement processes
- Collective scrap and scrap management for batch and quantity deviations
- Integration into ERP, production, and controlling systems
Does this sound familiar?
- Internal deviations in manufacturing, assembly, or logistics are "resolved" locally, but not systematically recorded and analyzed, and later resurface as customer complaints.
- Practical data collection methods are lacking on the shop floor: PCs at every station are expensive or impractical, so errors are documented late, incompletely, or not at all. Valuable information is thus lost.
- Measurement values and test results are transferred manually or analyzed separately: This is time-consuming, error-prone, and leads to trends and process drift becoming apparent too late.
- Transparency regarding frequencies, causes, and costs is lacking: Improvements are not prioritized, measures get bogged down in day-to-day operations, and effectiveness checks are neglected. This results in recurring errors.
- Without integration into ERP, controlling, and FMEA, the feedback loop remains open: Error costs are not properly recorded, and insights are not systematically fed back into risk and prevention efforts.
This should be achieved through a robust process
- Low-threshold, standardized data collection directly at the point of action: mobile, fast, uniformly coded, and without media breaks.
- Automatic derivation from testing and quality processes: Deviations must occur where measurements/tests indicate them, not retrospectively.
- Guided analysis instead of free text: Root cause analysis (e.g., Ishikawa, 5 Whys) and CAPA logic must be structured, comparable, and documented in an audit-proof manner.
- Workflow-based control of corrective actions: Responsibilities, deadlines, escalations, status, and effectiveness checks must be reliably mapped, including a comprehensive overview of all open issues.
- End-to-end traceability and cost logic: Deviation <=> Order/Material/Batch <=> Scrap/Rework/Costs, including feedback in FMEA and data-driven evaluations.
Coverage in QS1
- Enables freely configurable recording of internal complaints and deviations – directly on the shop floor via tablet or smartphone, including graphically guided error coding for standardized error descriptions.
- Automatically captures deviations from inspection and quality processes, as well as through direct connection to measuring instruments, so that measurement data flows into inspection orders and deviations are immediately detected and recorded as errors.
- Intelligently manages processing via workflow: automatic routing to responsible roles (e.g., shift supervisor, quality assurance, process owners), clear status logic, and transparent task and deadline management.
- Supports root cause analysis and CAPA management (Ishikawa, 5 Whys, optional AI support) and translates findings directly into corrective actions, including effectiveness verification, to ensure the sustainable elimination of root causes.
- Making error chains visible across the batch network, linking deviations to ERP and cost data (scrap, rework, internal error costs), and automatically feeding results back into FMEA and BI/dashboards for true real-time transparency.
The result: Early detection and clear documentation of internal errors, less waste and rework, binding measures with proof of effectiveness, transparent error costs and a closed control loop extending to FMEA and controlling, before the error reaches the customer.
Your advantages
- Early detection and systematic handling of internal deviations
- Simple, mobile error recording via tablet or smartphone without additional PCs at production stations
- Sustainable elimination of root causes instead of merely treating symptoms
- Clear responsibilities and structured action tracking
- Transparency regarding error frequencies, causes, and costs
- Reduction of scrap, rework, and internal error costs
- Stronger integration of quality, production, and controlling
- Continuous improvement through data-driven decisions
- Prevention of consequential errors in customer processes
