Energy Efficiency Optimization for Machining of Wood Plastic Composite

Compressive Properties of Polyurethane Fiber Mattress Filling Material

There is an inevitable trend toward exploring new, environmentally friendly fibers that can be used as raw material for mattresses with moderate hardness and air-permeable characteristics. Ethylene-propylene side by side (ES), high-shrinkage fibers, and thermoplastic polyester elastomer (TPEE) chips were introduced into polyethylene glycol terephthalate (PET)/polybutylene terephthalate (PBT) chip by melt blending to modify PET/PBT fiber. The modified PET/PBT (hereinafter referred to as PLON) is more suitable for mattress filling material than PET/PBT. To explore the compressive properties of PLON cushion made of PLON fiber and expand the scope of the PLON cushion’s application, a layered hardness test, hardness classification test and variance analysis were used to comprehensively evaluate the surface hardness, core hardness, bottom hardness and hardness classification of the mattress made of PLON cushion. The conclusions are: (1) The materials of the support layer have a significant effect on the hardness grade S. The hardness of the mattress with PLON as the support layer is between the spring and the coir; (2) when PLON is used as the material of the support layer, it possesses higher supporting force than coir and the characteristics of light weight and high resilience, which coir does not have; it is also softer than a spring mattress. As cushion material, it provides higher support for mattresses than foam. Practical applications, densities and structure were clarified through the above research, with implications for broader applications for PLON blocks in mattress products.

Modeling and Predicting the Machined Surface Roughness and Milling Power in Scot’s Pine Helical Milling Process

Helical milling with the advantages of stable machining process, a well-machined surface quality, etc., is an interest of researchers and producers. Machined surface roughness (arithmetic mean deviation (Ra) and maximum height of the assessed profile (Rz)) and milling power consumption as two main machining characteristic parameters were studied and chosen as response factors to evaluate the machinability of Scots pine helical milling. Input variables included helical angle of milling cutter, rotation speed of main shaft, and depth of milling. Response surface methodology was applied for the design of experiments, data processing and analysis, and optimization of the processing parameters. The results showed that Ra and Rz decreased with an increase in helical angle and rotation speed of main shaft, though increased with an increase in depth of milling. Milling power increased when the helical angle and depth of milling increased and showed a slight downward trend as the rotational speed increased. The quadratic models were applied to predict the values of Ra, Rz, and milling power due to the high values of R2 of 0.9895, 0.9905, and 0.9885, respectively. The plot of predicted and actual values also indicated that the created models had good predictability. The optimized combination of helical angle, rotation speed, and depth of milling are 64°, 7500 r/min, and 0.5 mm, respectively. The effects of input variables and the quantitative relation between input variables and response variables were revealed clearly. These achievements will be useful for guiding the selection of helical milling parameters to achieve the purposes of improving processed surface quality and saving the processing power consumption.