A biofoundry integrates laboratory automation with Design-Build-Test-Learn (DBTL) workflows to accelerate strain development for sustainable manufacturing. Quantifying the economic efficiency of automated processes remains challenging. Here, we define the robot-assisted module (RAM) as a plug-and-play unit for constructing workflow and apply the Experiment Price Index (EPI), a standardized metric that combines time and cost per sample to evaluate and optimize synthetic biology workflows. Using EPI calculation and RAMs, we developed four workflows for strain development: guide (g)RNA cloning, genome editing, DNA assembly, and sample analysis. EPI identified workflow bottlenecks, elimination of redundancies, and assessment of techno-economic tradeoffs. We further extended the EPI framework on techno-economic assessment (TEA) by estimating return on investment (ROI) and payback periods for biofoundry operations at varying project scales. Our results demonstrate EPI for cost-effective experimental planning and scalable biofoundry deployment. Beyond strain engineering, EPI serves as a universal tool for evaluating automation efficiency across biotechnology.