RESUMEN
Four-dimensional (4D) printing combines stimulus-responsive materials with additive manufacturing (AM) technologies. This new concept of printing three-dimensional (3D) objects opens the possibility for solving processing issues, through the production of complex geometries that can undergo programmed temporal changes in response to external stimuli. However, as 4D technology emerges from AM, various challenges still need to be explored, such as the controlled morphing effect. Understanding the aspects related to this behavior, both at the macroscopic level of the structure and at the microscopic level of the polymeric chain, is fundamental. Focused on thermoplastic poly(lactic acid) (PLA) printed by fused deposition modeling, this review addressed the influence of molecular weight, polymeric chain modifications, and 3D printing parameters on the shape change effect of a PLA-based material. The glass transition temperature proved to be a highly important parameter, which can be modified by molecular weight changes. Nozzle temperature, fill density, print patterns, and raster angle are 3D printing parameters that influence the material shape change. Shape recovery is highly dependent on the recovery temperature. Potential applications for shape memory structures are also addressed in this review.
RESUMEN
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.
