International Journal of Experimental Design and Process Optimisation (3 papers in press)

Regular Issues

• 3D printing parameters' adjustment of elastomer TPU material using the Box-Behnken design of experiments  
  by Foteini Vakouftsi, John D. Kechagias, Stefanos P. Zaoutsos 
  Abstract: The filament material extrusion (MEX) process is a widespread additive manufacturing (AM) process that requires parameter adjustments for zero-defect parts, although it is flexible and simple. The MEX process can use many pure, composite, or blended materials in filament form to fabricate functional customised parts layer-by-layer. Due to its flexural and elongation properties, the elastomer thermoplastic polyurethane (TPU) is used in 3D printing elastic and wearable electronics or medical applications. This work aims to assess the layer thickness (LT), nozzle temperature (NT), and bed temperature (BT) on the flexural strength (sb) and elasticity modulus (E) of TPU parts produced through 3D printing. The Box-Behnken design (BBD) of experiments and the response surface methodology (RSM) are adopted. Second-order mathematical models were fitted, and the residuals were tested for normality. The results were analysed by main effect plots (MEP), contour, and surface plots. The optimisation plot showed that the 0.24 mm LT, 235 ℃ NT, and 60 ℃ BT optimise the process performance.
  Keywords: filament material extrusion; thermoplastic polyurethane; Box-Behnken design; BBD; response surface methodology; flexural strength; main effect plots; MEP.
  DOI: 10.1504/IJEDPO.2025.10068801
   
  
• Constructing D-optimal designs for mixture-process variable experiments with binary responses  
  by Mona Khoddam, Hossein Tohidi, Douglas C. Montgomery 
  Abstract: Mixture experiments are widely applied in various fields to analyse responses influenced by component proportions that sum to a constant. While classical mixture experiments focus solely on these proportions, mixture-process variable (MPV) experiments also incorporate additional non-mixture factors. Introducing process variables into the model significantly increases the complexity of the experimental design. Additionally, binary responses pose further challenges, as traditional designs for continuous responses under normal-theory linear models often fail to perform adequately in such scenarios. This research proposes an exchange algorithm to generate D-optimal designs for MPV experiments with binary responses. The algorithm effectively addresses key challenges, including the nonlinear nature of the D-optimality criterion, the interaction between mixture and process variables, and the need for prior parameter estimates. The method demonstrates robustness and efficiency by producing stable designs across varying sizes while achieving high D-optimality scores. By bridging the gap in experimental design for binary responses, this work enhances the applicability of MPV experiments in industrial and scientific research. The findings highlight the importance of tailored approaches for binary responses and lay the foundation for future advancements in experimental design methodologies spanning diverse applications.
  Keywords: mixture-process variable experiments; binary responses; logistic regression; D-optimality; coordinate exchange algorithm.
  DOI: 10.1504/IJEDPO.2025.10070461
   
  
• Immersion system oil filtration improvement under cyclic pumping  
  by Maher Shehadi 
  Abstract: Efficient oil filtration in immersion systems is essential for preserving equipment integrity and coating longevity. However, many systems operate without dynamic filtration control, permitting contaminant buildup and performance degradation. This study evaluates the influence of cyclic pumping on filtration efficiency in an oil-based rust prevention immersion system, aiming to optimise ON/OFF intervals for improved particulate capture and reduced maintenance. A controlled experimental setup introduced ISO dust particles into the system, with oil samples collected downstream of the filter during various pump cycles. Filtration performance was quantified via particle size distribution and pressure differential analysis across the filter. Shorter cycles enhanced removal of particles >10 μm, lowered pressure drop, and extended filter life. In contrast, longer cycles facilitated bypass of <10 μm particles, accelerating clogging and reducing efficiency. Findings demonstrate that optimising pump cycling frequency significantly influences filtration dynamics. Future research will address adaptive control, real-time diagnostics, and long-term system sustainability.
  Keywords: immersion system; oil filtration; filter efficiency; intermittent pumping; particle size detection; corrosion resistance; surface preparation; coating.
  DOI: 10.1504/IJEDPO.2025.10071007