Process Improvement Through Design of Experiments
topic
Full factorial, fractional factorial, and response surface designs systematically vary process factors including dye concentration, temperature, pH, time, and auxiliaries across planned experiments while measuring multiple quality responses, using analysis of variance and regression to identify significant factors, two-factor interactions, and optimum operating conditions within the experimental region.
Role
Replaces inefficient one-factor-at-a-time process development in textile dyeing, finishing, and chemical formulation with statistically efficient experimental designs that identify factor interactions invisible to sequential experimentation, reducing the number of experiments needed to optimise complex multi-variable textile processes while improving model reliability.