Business Case
Analytics for Quality Control of Production Processes
The case of cables for the transport of energy
World leader in the production of cables for the transport of electricity, Interlem has found an ideal partner to carry out analyses aimed at quality control of production processes (Statistical Process Control).
Objectives
Carry out Statistical Process Control (SPC) analyses concerning the cable production process and in particular to study:
The behaviour of variables related to the cable production process
The exceeding of the control limits - LSL, Lower Standard Level and USL, Upper Standard Level - and the detection of potential anomalies during the production process
The analysis of variables through X-Chart and s-Chart (Control Cards)
The production of Scatter Plots and Correlation Matrices
The project has led to the creation of a reporting system that, starting from the field data, directly collected by the production machinery, allows the analysis of over 90 variables related to the production process (temperature, pressure, power, etc.)with methods of statistical process control.
The analyses carried out relate to the temperature (C° ), pressure (bar), kilograms/hour (kg/h), grams/minute (g/m) etc., detected during the insulation process of the cables. The duration of the production process for each cable goes from 10 to 14 days and the production cycle is continuous over time (24h/7 days).
Interlem’s reporting system provides a series of reports that include: Correlation Matrices, Scatter Plots, Shewhart Graphs and univariate Analysis of Production Variables. The reports allow X to understand the behavior of the data collected during the isolation phase of the cables and highlight any critical process in progress.
Benefits
- Identification of risk factors (variables) for possible cable defects and reduction of variables to be monitored
- Better assessment of the quality of the cables produced
- Timely detection of cable defects
- Reduced costs from future failures
Technologies: SAS/QC, SAS Visual Analitycs, SAS Enterprise Guide, Oracle DB Server
