APPLICATIONS
Investigate quality variations in your process.
Combine recorded operating conditions with manual or automated product measurements and inspections to investigate changes during manufacturing.
RECORDS FOR INVESTIGATION
Link inspection results to production.
01
Identification
Machine, product reference, mould, batch or period. Identifiers must be precise enough to retrieve the records associated with inspected parts.
02
Recorded operating conditions
Measured variables, operating states and process changes. Setpoints must be distinguished from actual measurements.
03
Quality result
Inspected characteristic, measurement method, date, quantity and classification. Conforming parts require defined product acceptance criteria.
QUALITY · KERN IoP | SMARTPRO
Quality is recorded at the machine.
SMARTPRO enables quality results to be recorded as production continues. Through the touchscreen, operators can enter counts of good and rejected parts together with defect codes when these are included in the configured form.
Operating records that support subsequent analysis.
Results can be linked to the period, machine and work order or product when those identifiers are integrated. Quality can then be examined alongside cycles, operating states and available process variables.
Once reports are saved and synchronized, the quality component of OEE can be updated during the shift. Calculating overall OEE also requires consistent times, cycles and quantities for availability and performance.
01
Reporting during the shift
Operators enter good and rejected quantities on the touchscreen at the machine.
02
Identifying defects
When defect categories or codes are available in the form, reports retain details useful for investigating variation.
03
Quality data incorporated into OEE
With synchronized quantities and the necessary availability and performance records, OEE can reflect quality reports collected during the shift.
The level of detail, defect-classification fields and update frequency are agreed according to the application and available data.
AUTOMATED QUALITY DATA · INSPECTION RESULTS
Connect product measurements with manufacturing parameters.
KERN IoP can integrate data from measuring and inspection equipment, including scales, machine-vision systems and other instruments used during production. The goal is to retain the connection between a measured product characteristic and the process that produced it.
By synchronizing weight, dimensions, visual defects and other characteristics with machine, mould, material, product, cycle and actual process measurements, engineers can investigate how a part was manufactured and what result was obtained. This relationship supports the detection of deviations during production, investigation of conditions associated with changes in quality and alerts based on process and product data sharing a common time reference.
Where the application, measurement system and control architecture permit, this information can underpin assisted process adjustment or real-time control strategies. Correlation alone does not establish causation or replace measurement-system validation; it provides a better basis for selecting variables to investigate and verifying the effects of adjustments.
UNDERSTANDING QUALITY IN DEPTH
What should a useful reject report contain?
Relating a defect to the process starts with a record identifying the result, product and production period.
Record good and rejected parts at the machine
Essential fields, timely reporting and links to OEE.
Relate quality to shift performance
How to distinguish availability losses from performance losses.
QUALITY AND MANUFACTURING CONTEXT
A recorded process curve is useful when linked to the product.
Comparisons are more meaningful when process data and inspection results refer to the same work order, batch or period. A graph alone does not establish the cause of a defect.
What monitoring contributes.
Records make it possible to reconstruct observed conditions and compare periods with different quality results. KERN can support the selection of variables and integration of quality data for the application.
A statistical relationship between two variables is not proof of a defect’s cause. Investigation may require controlled process trials, assessment of the measurement system and examination of materials or moulds.
Prepare a quality investigation
- Describe the defect or changing characteristic.
- Identify product, mould, material and period.
- Specify how the characteristic is measured and how conformity is assessed.
- Collect operating records and documented adjustments.
- Define the hypothesis to be tested.
INSPECTION AND CONTEXT
Linking quality and process requires a defined measurement method.
Part weight
If weighing equipment is integrated, readings can be recorded automatically alongside product reference and production time. For sampled measurements, retain sample identification and inspection criteria.
Critical dimensions
Dimensions may be acquired from digital instruments or vision systems when a compatible interface exists. In all cases, retain the method, identification and traceability of the inspection.
Mould and cavities
Identify the mould and cavity when investigating differences between manufacturing positions.
Material and batch
Relate material records to production to investigate resin changes or manufacturing conditions.
RELATED CONTENT
Traceability
Linking records to production.
Process analysis
Engineering investigations into process variation.
Process fundamentals: actual mould temperature
The temperature experienced by the polymer depends on heat transfer in the mould and its cooling circuits. Measuring temperature and flow provides information for investigating dimensional stability, cycle time and quality. Laura Flórez discusses these phenomena in SPE (2024).
Read “The Importance of Mold Temperature Control in Injection Molding” in Plastics Engineering ↗ · Other publications by Laura Flórez →
Request a configuration for your plant.
Tell us which equipment you wish to monitor and what information you need.
Engineering
PM Tec Engineering, through its Industry 4.0 division, KERN IoP.
Cota, Cundinamarca · Colombia.
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