Smart quality control: Samara engineers create program that automatically detects cable defects
In cable manufacturing, there are no small details. Insulation thickness slightly below spec — and the risk of breakdown increases. Conductor resistance exceeds the limit — and the entire batch becomes questionable. But how can these parameters be monitored in real time, especially when machinery operates around the clock? Scientists at Samara Polytechnic University have found an elegant solution: they have developed a program that automatically tracks quality and raises an alarm only when truly necessary.
The concept is not new: statistical process control (SPC) methods have long been used in the automotive industry to monitor processes. However, they never gained a foothold in domestic cable production. As a result, deviations from specifications are sometimes noticed too late, after defective products have already been produced in bulk. Samara researchers, led by Doctor of Technical Sciences Vladimir Kozlovsky, set out to close this gap.
At the heart of their development lies the Shewhart control chart — a classic tool that graphically shows how process parameters change over time. But the researchers fine‑tuned it specifically for cable manufacturing needs. The program now records the characteristics of each product and analyzes trends. Importantly, it ignores normal, “healthy” fluctuations and only triggers an alert when the deviation between the reference value and the actual measurement becomes critical.
For quality specialists, this saves enormous amounts of time: there is no need to sift through mountains of data — signals are generated only when action is required. In addition, the program can work not only with actual measurements from the factory floor, but also with simulation data — modeling hypothetical processes and calculating risks in advance.
The development has already been patented and has become part of Samara’s scientific school of quality management in mechanical engineering. Cable manufacturers now have a tool that allows them not just to catch defects, but to prevent them before they occur — at the process stage.
