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Microfluidics is proposed as a technique for efficient sperm sorting, to achieve the ultimate goal of resolving infertility problems in livestock industry. Our study aimed to design a microfluidic sperm-sorting device (SSD) through a high-efficacy and cost- and time-effective fabrication process, by using COMSOL Multiphysics simulation and modeling software, and the design of experiment (DOE) method. The eight factors affecting SSD performance were established. The simulation was then run, and statistically significant factors were analyzed. Minitab16 was used to optimize the design modulus factor. By setting the statistical significance at p < 0.05, the factors affecting experimental structure were analyzed. At a desirability of 97.99, the optimal parameters for the microfluidic chip were: angle between sperm and medium inlet chambers (A = 43°), sperm inlet flow rate (B = 0.24 µL min−1), medium inlet flow rate (C = 0.34 µL min−1), and inlet and outlet chamber lengths (D = 5000 µm). These optima were then applied to microfluidics device construction. The device was produced using soft lithographic microfabrication techniques and tested on Holstein–Friesian bull sperm. The highest bull sperm-sorting performance for this microfluidic device prototype was 96%. The error between the simulation and the actual microfluidic device was 2.72%. Fluid viscosity ranges analysis-based simulations revealed acceptable fluid viscosity tolerances for the SSD. The simulation results revealed that the acceptable tolerance range for fluid viscosity was 0.00001–0.003 kg m−1 s−1. This optimally designed microfluidic chip-based SSD may be integrated into sperm x/y separation micro devices.

International audienceThis paper proposes an integrated framework to analyse Business-to-Business relationships using data mining techniques such as K-Means based on particle swarm intelligence (PSO) and Association Rule (AR). It constructs relationship rules of holistic performance enhancement road map. The data set of relationships between enterprise and its direct customers was used for demonstration. The results of the case study in France show, how domain managers powerfully use the graphical analysis results to provide the holistic performance improvement and weakness resolution relationship rules. In the long run, Supply Chain managers are able to use this framework to design and adjust their units to meet the customer needs. This paper introduces and explains a new idea of measuring performance along the supply chain from a collaborative perspective. The extended model is adapted from our previous model and from a Balanced Score Card (BSC) model. It provides a tool to measure tangible and intangible values between partners

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