Statistical Process Control: SPC as the Key to Production Planning

Traditional quality inspections only react once deviations have been detected. SPC takes another approach: instead of checking the different results, it monitors the process itself. This also involves distinguishing between normal fluctuations and systematic changes. Action is taken when actual disruptions occur and not with every minor deviation. Unnecessary corrections are avoided and the process is protected from destabilizing "oversteering".

• Early detection of deviations: Problems are identified before they lead to scrap or rework.
• Consistent process control: Interventions only in case of actual faults — not with normal fluctuations.
• Less unnecessary intervention: No more over-regulation due to hectic reactions to random deviations.
• Lower failure costs: Less scrap, less rework, less complaints
• More transparency: The process is continuously monitored, not only selectively.
• Better decisions: Clear data supports structured decision-making and provides a reliable basis for quality and efficiency.

• Automotive manufacturers and suppliers: Where the highest demands are placed on process capability, SPC provides the evidence that customers and auditors expect.
• Pharmaceutical companies: Strict regulatory requirements and quality limits ask for reliable processes.
• Electronics manufacturing: Sensitive components and tight tolerances require early detection of even the smallest deviations.
• Food industry: SPC ensures hygiene, traceability, and consistent product quality on a permanent basis.
• Producers with series or large-scale manufacturing: If failures are costly and manufacturing processes must continue, SPC helps to avoid them rather than correct them.
• Organizations with audit requirements or certification specifications: SPC helps document process statuses in a traceable manner and ensures structured tracking for auditors.

• Measuring systems are not reliable: If calibration or precision is missing, the data does not provide an accurate picture.
• The data basis is insufficient: Small or distorted samples lead to incorrect conclusions.
• Processes fluctuate constantly: If processes are largely manual or unstable, a comparison is not possible.
• Responsibilities are not clearly defined: If personnel, responsibilities, and QM processes are not defined, SPC has no practical effect.
• The technical infrastructure is missing: Without digital data collection and suitable software, SPC cannot be implemented.

• Suitable measuring systems: An MSA (measurement system analysis) checks whether measured values are reliable. The Shewhart principles provide the basis for correctly classifying deviations and responding in a targeted manner.
• Reliable samples: The data basis must be sufficient, unbiased, and meaningful.
• Consistent process flow: Only stable processes allow for reliable evaluation.
• Clear inspection planning: Inspection characteristics, frequency, and method must match the relevant process parameters.
• SPC expertise in the team: Training and clear responsibilities promote continuous optimization.

• Control charts show the process development and reveal whether measured values are always more or less close to the mean value or violate the warning limits.
• Process capability (Cp and Cpk) is based on process stability and standard deviation and shows whether tolerances are reliably respected.
• Machine capability (Cm and Cmk) evaluates the short-term performance of a machine under similar conditions.
• Long-term capability (Pp and Ppk) describes how efficient a process actually is over a longer period of time.
• Additional KPIs:The calculation of FPY or OEE provides important information about process quality and plant efficiency.

Not every deviation from the target value requires immediate action. The decisive factor is whether the control chart shows certain patterns. For example, a prolonged upward or downward trend, a noticeable accumulation of points on one side of the mean value line, or regularly recurring fluctuations. Such signals indicate that the process is no longer showing random variation but is deliberately going off course. Only then is action taken — in a targeted, justified manner and with a view to achieving long-term process stabilization.

The benefits of SPC are not reflected in impressive figures, but in clear improvements: stable processes, less waste, and greater planning reliability. If warning and intervention limits are clearly defined and targeted action is taken in case of deviations, failure sources can be significantly reduced. Companies benefit in several ways — through lower failure costs, traceable process improvements, and consistent product quality assurance. No reactive correction, but proactive action.

SPC can have a big impact, but only if it is incorporated into everyday work. For this to happen, a real change is needed: processes must be transparent, data must be presented in an understandable way, and everyone in the team must be involved. Training courses help, responsibilities provide structure, and digital tools ensure that you can act quickly if something goes wrong.

We support you with our mApp In-Production Inspection, which integrates inspections during production into the MES. The mApp Quality Analysis & Statistics adds to this with graphic evaluations of inspection data, control charts, and the calculation of statistical key figures such as Cp and Cpk. Both applications are part of our MES HYDRA and ensure that quality data does not remain isolated but is integrated into your processes.
As Technology Leader in the area of MES (SPARK Matrix 2025), we know what really counts — not only technically, but also on a human level. With over 500 employees worldwide and clear values, we are committed to long-term partnerships rather than short-term promises.

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