Analysis of Cycle Time and Shot Count in the Injection Moulding Process Using eMoldino Sensor.

Abstract

The injection moulding process requires proper control of cycle time and shot count to maintain production efficiency and mould service life. This study aims to analyze cycle time and shot count using the eMoldino sensor as an Internet of Things (IoT)-based production monitoring system. Data were collected through an eight-week monitoring period and analyzed using the Failure Mode and Effects Analysis (FMEA) method to identify potential failures and determine improvement priorities within the production process. The results indicate that several factors contributed to production instability, including an inefficient mould cooling system, excessive use of regrind material, prolonged barrel charging time, inappropriate cooling time settings, and delays in cycle time data acquisition by the eMoldino sensor. The implementation of improvement actions successfully reduced the Risk Priority Number (RPN) values of the prioritized failure factors, resulting in improved process stability. Monitoring results after the implementation of improvements showed an average actual cycle time of 29.07 seconds, with an average deviation of 1.59% from the approved cycle time of 28.62 seconds. In addition, the total shot count recorded during the observation period reached 1,949,046 shots, with an average of 243,631 shots per week or 34,804 shots per day. These findings demonstrate that the use of the eMoldino sensor combined with the FMEA approach is effective in supporting production monitoring, cycle time evaluation, shot count control, and the implementation of improvement actions in the injection moulding process.