DOI: 10.61931/2224-9028.1667 ISSN: 2224-9028

A Mold Mating Surface Temperature Monitoring System for Injection Molding Using Infrared Thermography and Mahalanobis Distance

Yoshio FUKUSHIMA, Makoto FUKUSHIMA, Sho SHIBUYA, Keigo KUDO, Yuta ABE

In plastic injection molding, minimizing defects is crucial for sustainable and stable manufacturing because resin behavior and molding conditions fluctuate due to variations in material lots, seasonal shifts, and factory environmental factors such as temperature and humidity. Among various process parameters, mold temperature - specifically the mold mating surface temperature immediately after part ejection-  plays a critical role in mitigating these variations and maintaining consistent product quality. However, embedding conventional sensors into the mating surface is structurally difficult. While non-contact infrared thermography is an effective alternative, shiny metallic mold surfaces suffer from low emissivity, leading to inaccurate readings. Furthermore, high-end thermal cameras are often cost-prohibitive for small and medium-sized enterprises (SMEs). To address these challenges, this study proposes a low-cost remote temperature monitoring system. Small counterbores were machined outside the mold cavity and coated with a high-emissivity black body paint, resolving the emissivity problem without affecting product quality. Molding experiments were conducted by intentionally inducing short-shot defects using resins with different flow properties to simulate process variations. The temperature variations were captured using both high-end and low-cost infrared thermometers, and analyzed using the Mahalanobis distance (MD value). The results demonstrated that the proposed system could successfully detect short shots on a cycle-by-cycle basis. Notably, the low-cost thermometer provided adequate monitoring accuracy when measured from the front, comparable to the high-end camera. This system offers a cost-effective, easily  implementable solution for remote process monitoring, significantly contributing to the digital transformation (DX) and smart factory realization in SMEs.