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In the plastic injection industry, plastic injection molding is one of the most extensively used mass production technologies and has been continuously increasing in recent years. Cost evaluation is essential in corporate operations to increase the market share and lead in plastic part pricing. The complexity of the plastic parts and manufacturing data resulted in a long data waiting time and inaccurate cost evaluation. Therefore, the aim of this research is to apply a cost evaluation approach that combines hybrid deep learning of a tunicate swarm algorithm (TSA) with an artificial neural network (ANN) for the cost evaluation of complicated surface products in the plastic injection industry to achieve a faster convergence rate for optimal solutions and higher accuracy. The methodology entails the ANN, which applies feature-based extraction of 3D-model complicated surface products to develop a cost evaluation model. The TSA is used to construct the initial weight into the learning model of the ANN, which can generate faster-to-convergent optimal solutions and higher accuracy. The result shows that the new hybrid deep learning TSA combined with the ANN provides more accurate cost evaluation than the ANN. The prediction accuracy of cost evaluation is approximately 96.66% for part cost and 93.75% for mold cost. The contribution of this research is the development of a new hybrid deep learning model combining the TSA with the ANN that includes the calculation of the number of hidden layers specifically for complicated surface products, which are unavailable in the literature. The cost evaluation approach can be practically applied and is accurate for complicated surface products in the plastic injection industry.

In this study, the thermal analysis and numeric modelling of flow in nozzle of a real plastic injection machine with injection weight of 300 gram were conducted. The nozzle geometry was changed to optimize flow in nozzle for high-density polyethylene HDPE at temperature of 200 °C and injection pressure of 150 MPa. For numeric modelling, the ANSYS Fluent R14 was used. The analysis was made for four different geometries consisting of real system dimension r-NG and others design dimensions NG1, NG2 and NG3 . The results of the analysis showed that the most suitable flow was determined in the third NG3 design. In this geometry, for flow in the nozzle section, rounding was made in the sudden shrinking flow section to give a throat shape and so, the geometry ensuring optimized flow was obtained. As a result, with changing of nozzle geometries of plastic injection machines having different pushing capacities they were used in the industry, the positive results will be able to be obtained.

In this study, the changes in mechanical, rheological and morphological properties of glass-fiber reinforced poly(oxymethylene) composite after ageing were investigated. Samples were prepared with plastic injection molding method. Ageing process was done by waiting samples at laboratory temperature and water during 28 days. Tensile and 3 point flexural tests were done to determine the mechanical properties, melt flow index (MFI) was measured to determine the rheological property and scanning electron microscopy (SEM) was used to observe the morphological structure. From experimental results, it was seen that mechanical, rheological and morphological properties were affected by the ageing environment. It was found that mechanical properties of aged samples were lower than that of unaged sample. The most decrement in the mechanical properties was occurred at the aged in water samples. Ageing process increased MFI value.

Nanopattern replication of complex structures by plastic injection is a challenge that requires simulations to define the right processing parameters. Previous work managed to simulate replication for single cavities in 2D and 3D, showing high performance requirements of CPU to simulate periodic trenches in 2D. This paper presents two ways to approach the simulation of replication of complex 3D hydrophobic surfaces. The first approach is based on previous CFD Ansys Fluent and compared to FE based CFD Polyflow software for the analysis of laminar flows typical in polymer processing and glass forming as well as other applications. The results showed that Polyflow was able to reduce computing time from 72 h to only 5 min as desired in the project. Furthermore, simulations carried out with Polyflow showed that higher injection and mold temperature lead to better replication of hydrophobicity in agreement with the experiments. Polyflow simulations are proved to be a good tool to define process parameters such as temperature and cycle times for nanopattern replication.

Goal: Companies are increasingly concerned about the life cycle of their products in the economic and environmental perspectives. One of the processes that generates great financial returns is the injection molding process. But this process results in many impacts to the environment. The environmental concern has generated many studies involving this theme and the difficulty of measuring the impacts generated by this process. In view of the environmental concern and the injection molding process this study aims to review in the literature on eco-design tools based on the Streamlined Life Cycle Assessment of plastic injection molded products.Design / Methodology / Approach: The review of the literature was carried out by researching for complete articles published in three databases (Science Direct, Scopus and Web of Science), among the years 2013 - 2018, using combinations of keywords and Boolean operators.Results: Several studies revealed that injection molding generates many impacts, such as the high consumption of electricity caused by the emission of greenhouse gases and use of raw material.Limitations of the investigation: This paper is not free of limitations. The study analyzed the literature through three databases for a period of time and used a combination of keywords. It may be that some document has not been analyzed.Practical implications: The development of a rapid tool for the application of LCA studies will allow quick decision-making to the managers in the environmental perspective, besides reducing costs, reducing time with the application of complex studies, and assisting the designer to develop the Eco-design.Originality / Value: The study addressed the injection molding process and there are no studies in the literature that characterize this theme. Thus, a study that addresses this gap and evidences the importance of the development of an environmental tool that assists sustainable practices in the process of plastic injection molding becomes important.