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Shape memory polymers (SMPs) are classified as smart materials owing to their inherent stimulus-induced response. SMPs are capable of recovering partially or totally to its original shape after a high degree of deformation by external stimulus. The most used stimuli are thermal, light, magnetic field and electricity. This research aims to characterize the toughness property of thermo-responsive SMP specimens fabricated by the material extrusion (ME) process and to investigate the impact of ME parameters on specimen maximum load and load-displacement curves. Moreover, to investigate the recovery efficiency based on the initial and post toughness generated by the compact tension test.

A design of experiments with three parameters (temperature, velocity and layer height) defined the ME settings to fabricate the specimens. The ME raster orientation factor was also evaluated separately. In addition, one more specimen group assisted by a clamp during the recovery process was compared with a specimen control group. After fabrication, specimens were submitted to a thermo-mechanical cycle that encompasses a compact tension test and a thermo-recovery process. Comparison studies of load-displacement, toughness and recovery efficiency of the specimens were carried out to determine the optimized fabrication parameters.

It was found that ME parameters and raster orientation impacted the test results. Samples with the clamp support during recovery returned a higher toughness than samples without support. Finally, results showed that the shape memory effect can contribute with up to 43 per cent recovery efficiency in a first recovery and up to 23 per cent in a second recovery of damaged specimens.

This paper is a reference for toughness and recovery properties of SMP parts produced by the ME fabrication process.

Shape memory polymer (SMP) is capable of recovering its original shape from a high degree of deformation by applying an external stimulus such as thermal energy. This research presents an integration of two commercial SMP materials (DiAPLEX and Tecoflex) and a material extrusion (ME) printer to fabricate SMP parts and specimens. The material properties such as Young’s modulus of the specimens was examined as a process output. Furthermore, stress-strain curve, strain recovery, instant shape-fixity ratio, long-term shape-fixity ratio and recovery ratio of SMP specimens during a thermo-mechanical cycle were investigated.

The ME fabrication settings for the SMP specimens were defined by implementing a design of experiments with temperature, velocity and layer height as process variables.

It was found, according to main effect and iteration plots, that fabrication parameters have an impact on Young’s modulus and exist minimum iteration among variables. In addition, Young’s modulus variation of DiAPLEX and Tecoflex specimens was mostly caused by velocity and layer height parameters, respectively. Moreover, results showed that SMP specimens were able to recover high levels of deformation.

This paper is a reference for process control and for rheological properties of SMP parts produced by ME fabrication process.

This paper aims to analyze the impact of transaction costs in portfolio optimization in Peru. The study aims to compare the transaction costs structure applied in Peru with respect to the ones applied in the USA, and over a few dimensions.

The paper opted for an empirical study analyzing the cost of rebalancing portfolios over a set period and dimensions. Stocks have been carefully selected using Bloomberg terminals, and portfolio designed then rebalanced using VBA programming. Over a few dimensions as type and number of stocks, holding period and trading strategy, the behavior of these different transaction costs has been compared. The analysis has been done for four different portfolios.

The paper provides empirical insights about how a retail investor actively trading in Peru can pay up to 14 times more in transaction costs than trading the same portfolio in the USA. These comparatively high transaction costs prevent retail investors to trade in the Peruvian stock market while fueling illiquidity to this market.

The paper deals with a limited amount of Peruvian stocks. Researchers are encouraged to test the proposition further, including other dimensions.

The paper includes implications for any retail investor that wants to invest in Peruvian stocks, giving an insight about how expensive it is to actively rebalance a portfolio in Peru.

This paper fulfils an identified need to study how much it costs to actively invest on the stock market in Peru.

Ti‐6Al‐4V is one of the most attractive materials being used in aerospace, automotive and medical implant industries. Electron beam melting (EBM) is one of the direct digital manufacturing methods to produce complex geometries of fully dense and near net shape parts. The EBM system provides an opportunity to built metallic objects with different processing parameter settings like beam current, scan speed, probe size on powder, etc. The purpose of this paper is to determine and understand the effect of part's thickness and variation in process parameter settings of the EBM system on surface roughness/topography of EBM fabricated Ti‐6Al‐4V metallic parts.

A mathematical model based upon response surface methodology (RSM) is developed to study the variation of surface roughness with changing process parameter settings. Surface roughness of the test slabs produced with different parameter settings and thickness has been studied under confocal microscope. Response surface methodology was used to develop a multiple regression model to correlate the effect of variation in EBM process parameters settings and thickness of parts on surface roughness of EBM produced Ti‐6Al‐4V.

It has been observed that every part produced by EBM system has detectable surface roughness. The surface roughness parameter Ra varies between 1‐20 μm for different samples depending upon the process parameter setting and thickness. The Ra value increases with increasing sample thickness and beam current, and decreases with increase in offset focus and scan speed.

Surface roughness is related to wear and friction property of the material and hence is related to the life time and performance of the part. Surface roughness is an important property of any material to be considered as biomaterial. The surface roughness of the material depends upon the manufacturing method and environment and hence it is controllable either during fabrication or by post processing. From the 1st order regression model developed in this study, it is also evident that sample thickness, scan speed and beam current have relatively more effect on roughness value then the offset focus. With the model obtained equation, a designer can subsequently select the best combination of sample thickness and process parameter values to achieve desired surface roughness.