Order-of-addition experiments for sequential adjacency relationship problems.

Area of Science:

• Experimental design
• Chemical engineering
• Industrial chemistry

Background:

• Order-of-addition (OofA) experiments are crucial in industry and pharmacy.
• Existing models (pairwise, component-position) do not address responses dependent solely on component adjacency.
• Sequential adjacency relationship (AR) problems have limited research.

Purpose of the Study:

• Introduce OofAM, a novel method for solving sequential AR problems using OofA experiments.
• Develop a new model and analytical techniques for inferring optimal component orders.
• Provide an information-efficient approach for sequential AR problems.

Main Methods:

• Developed a novel model tailored for sequential AR problems within the OofA framework.
• Designed experiments with specific theoretical properties for optimal order inference.
• Employed analytical techniques for inferring optimal component sequences.

Main Results:

• OofAM is a straightforward and information-efficient method for sequential AR problems.
• Case studies show OofAM outperforms existing methods.
• Demonstrated superior efficiency, particularly for large-scale problems.

Conclusions:

• OofAM represents a significant advancement in applying OofA experiments to sequential AR problems.
• The proposed method offers a practical and efficient solution for determining optimal component orders.
• OofAM is a valuable tool for optimizing processes where component adjacency is key.