Mixture experiments often involve process variables, such as different chemical reactors in a laboratory or varying mixing speeds in a production line. Organizing the runs in orthogonal blocks allows the mixture model to be fitted independently of the process effects, ensuring clearer insights into the role of each mixture component. Current literature on mixture designs in orthogonal blocks ignores the order of addition of mixture components in mixture blends. This paper considers the order of addition of components in mixture and mixture-amount experiments, using the variable total amount taken into orthogonal blocks. The response depends on both the mixture proportions or the amounts of the components and the order of their addition. Mixture designs in orthogonal blocks are constructed to enable the estimation of mixture or component-amount model parameters and the order-of-addition effects. The G-efficiency criterion is used to assess how well the design supports precise and unbiased estimation of the model parameters. The fraction of the Design Space plot is used to provide a visual assessment of the prediction capabilities of a design across the entire design space.

翻译：混料实验通常涉及过程变量，例如实验室中不同的化学反应器或生产线上变化的混合速度。通过正交分块组织实验运行，可使混料模型的拟合独立于过程效应，从而更清晰地揭示各混料组分的作用。现有关于正交分块混料设计的文献忽略了混料配制中各组分的添加顺序。本文考虑混料及混料-用量实验中组分的添加顺序问题，采用可变总量方法将其纳入正交分块。响应值同时取决于混料比例（或组分用量）及其添加顺序。本文构建的正交分块混料设计能够同时估计混料（或分量-用量）模型参数与添加顺序效应。采用G-效率准则评估设计对模型参数精确无偏估计的支持程度，并利用设计空间比例图对设计在整个设计空间内的预测能力进行可视化评估。