A Model Based on Non-linear Regressions to Predict Aluminum Injection Moulds Lifespan

Traditionally, thermoplastic injection moulds are made of steel due to its good thermal stability, high mechanical resistance and the possibility of easily obtaining the desired surface finish. Despite these advantages, steel has low thermal conductivity when compared to other materials, such as aluminium, thus requiring longer periods for the part to cool before demoulding it and, consequently, generating longer operating cycles. On the other hand, the use of aluminium in the manufacture of tools used in the injection process is still limited due to its low mechanical strength (when compared to steel), leading to distrust as to the number of parts that can be injected and, therefore, as to their lifespan. The lack of data regarding the frequency of maintenance that must be performed on the aluminium mould to ensure the quality of the injected parts corroborates this scenario of uncertainty, since this information is essential to guarantee the viability of these moulds for high production of plastic parts. This work proposes a mathematical model based on exponential regressions in order to estimate the maximum number of cycles that can be performed before the need for preventive maintenance, and to evaluate the lifespan of aluminium moulds. In order to achieve this, the model was based on the number of cycles related to preventive maintenance, as well as the mechanical strength and hardness of various mould materials.