Development of an open-source injection mold monitoring system

The raw data collected during the case study can be found at: https://github.com/TEPGomes/OpenMMS-T4G/blob/cfa6e23c7fc02a645e31e06d299021cb0a3ce3e7/Real_World_Test/Case_Study_Raw_Data.csv (accessed on 23 March 2023). In the highly competitive injection molding industry, the ability to effectively collect information from various sensors installed in molds and machines is of the utmost relevance, enabling the development of data-based Industry 4.0 algorithms. In this work, an alternative to commercially available monitoring systems used in the industry was developed and tested in the scope of the TOOLING 4G project. The novelty of this system is its affordability, simplicity, real-time data acquisition and display in an intuitive Graphical User Interface (GUI), while being open-source firmware and software-based. These characteristics, and their combinations have been present in previous works, but, to the authors’ knowledge, not all of them simultaneously. The system used an Arduino microcontroller-based data acquisition module that can be connected to any computer via a USB port. Software was developed, including a GUI, prepared to receive data from both the Arduino module and a second module. In the current state of development, data corresponding to a maximum of six sensors can be visualized, at a rate of 10 Hz, and recorded for later usage. These capabilities were verified under real-world conditions for monitoring an injection mold with the objective of creating the basis of a platform to deploy predictive maintenance. Mold temperature, cavity pressure, 3-axis acceleration, and extraction force data showed the system can successfully monitor the mold and allowed the clear distinction between normal and abnormal operating patterns. This work was developed in the scope of the mobilizing project TOOLING4G—Advanced Tools for Smart Manufacturing (POCI-01-0247-FEDER-024516). Further support was given through the projects with reference UIDB/00481/2020, UIDP/00481/2020, and CENTRO-01-0145-FEDER-022083, financed through FCT—Fundação para a Ciência e a Tecnologia; Programa Operacional Regional do Centro Portugal (Centro2020), in the scope of PORTUGAL2020, through the European Regional Development Fund. TG and MSC thank FCT for the scholarships with reference SFRH/BD/143429/2019 and 2020.04681.BD, respectively.