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In this paper, the crystallization of PLA in PLA/thermoplastic starch (TPS) blends was investigated. The TPS was used as the minor component at a concentration varying between 0 and 42 %. The effect of interfacial area was studied by compatibilizing the blend using maleic anhydride grafted PLA. To further enhance the crystallization rate in PLA/TPS blends, the addition of talc and acetyl triethyl citrate, as nucleating agent and plasticizer respectively, was also studied. The crystallization rate was monitored using DSC analysis under both isothermal and non- isothermal conditions. The isothermal data was used to determine the crystallization half-life and to determine the optimum crystallization temperature. The crystallization half-time of PLA was decreased significantly in presence of the TPS phase and this effect was strengthened by the blends interfacial modification. By applying proper plasticization and nucleation strategy, crystallinity in excess of 50 % was achieved even at cooling rates as high as 80°C/min. Fully crystallized PLA/TPS samples were obtained by injection molding in a hot mold (80°C). Crystallized parts showed improved thermal resistance at temperatures above PLA's glass transition.

In this study, the warping mechanism was examined in terms of the difference in warpage behavior due to the presence or absence of fiber filler, using a ribbed plate. It was found that the warping mechanism due to anisotropic shrinkage is caused by the filler orientation distribution and filler form, including its size and geometry. It is seen that the sensitivity (the effect of the rib thickness on the amount of warpage) increased as the glass flake content was increased in PBT-hybrid filler. From this result, the glass flake used in this study were sufficiently small and that aspect ratio was approximately 2 compared with the glass fiber (aspect ratio: 10 ∼ 20). It can be inferred therefore that the glass flake acted like spherical filler, which contributed to reducing the anisotropic shrinkage.

In this work, the effect of processing conditions and nanoclay (NC) content on formation and various properties of polyamide 6 (PA 6) nanocomposites was studied by means of Taguchi method of experimental design. PA 6/organoclay nanocomposites were prepared by melt mixing of PA 6 at different organoclay loadings using a co-rotating twin-screw extruder. In order to investigate the effects of both processing conditions and organoclay content on silicate dispersion (exfoliation) and thermal and mechanical properties of the nanocomposites, different extrusion rates, processing temperatures and feeding rates at various NC loadings were used. X-ray diffraction (XRD) was used to characterize the formation of nanostructure and clay dispersion. The thermal properties of PA 6 nanocomposites were studied through TMA tests. XRD results revealed the formation of nanocomposite and evidenced that the samples exhibit mixed intercalated / exfoliated morphology and verified that, the extent of exfoliation increases with both clay content and extrusion rate used. The mechanical properties of PA 6 nanocomposites were studied using tensile tests. The strength and modulus of PA 6 nanocomposites were improved significantly by increasing the clay concentration and shear rate level.

The cooling system of a plastic injection mold plays a crucial role in determining both the productivity of the injection molding process and part quality. The cooling process is an important phase of injection molding, which could account for more than three-fourths of the total molding cycle time. Thus, an efficient cooling will significantly improve productivity by reducing the cooling time, and uniformity and balanced cooling can ensure part quality by preventing sink marks, different shrinkage, internal thermal residual stress and warpage. In this paper, the geometric parameters (i. e., radius and location of each cooling channel) and process parameters (i. e., inlet coolant temperature, volumetric flow rate of each cooling channel, packing time, and cooling time, etc.) are considered systematically in the cooling system design of injection molding. A two-level decomposition method for the cooling system optimization is proposed. The optimization problem is divided into two subproblems (cooling channel design and process design) on the basis of the different effects on refrigerant behaviour of different kinds of design variables. By combining the Kriging model and CAE technology, a mold cooling system for a 15-inch display was optimized. The results show that the method can efficiently improve the temperature distribution and the part quality.

Manufacturing process automation is often impeded by limitations related to automatic quality assurance. Many plastics manufacturers use univariate statistical process control (SPC) for quality control by charting the critical process states relative to defined control limits. Alternatively, principal component analysis (PCA) and projection to latent stuctures (PLS) are multivariate methods that measure the process variance by the distance to the model (DModX) and the Hotelling t-squared (T 2 ) values. A methodology for robust model development is described to perturb the manufacturing process for process characterization based on a design of experiments; best subset analysis is used to provide an optimal set of regressors for univariate SPC. Four different statistical models were derived from the same data set for a highly instrumented injection molding process. The performance of these models was then assessed with respect to fault diagnosis and defect identification when the molding process was subjected to twelve common process faults. Across two hundred molding cycles, the univariate SPC models correctly diagnosed five of the twelve process faults with one false positive, detecting only eighteen of twenty four defective products while indicating two false positives. With the same molding cycles, PCA and PLS provided nearly identical performance by correctly diagnosing ten of the twelve process faults and detecting twenty three of the twenty four defective products; PCA indicated two false positives while PLS indicated only one false positive.