<p>Process capability indices (PCIs) and acceptance sampling plans (ASPs) are crucial methodologies within statistical quality control and serve as practical tools for assessing and verifying product quality. Recently, PCI-based ASPs, combining the advantages of both methodologies, have been proposed and widely discussed. Among PCI-based ASPs, the single sampling plan (SSP) is the most fundamental and intuitive method, offering significant potential for application. However, existing studies often provide limited tables listing optimal plan designs under a restricted set of specified parameters. In practice, the requirements of buyers and sellers may not be confined to these limited parameter sets, necessitating practitioners to solve complex optimization models to derive optimal plan designs—posing considerable challenges and restricting the applicability of these plans. Therefore, we construct a cloud-computing application designed to facilitate the implementation of PCI-based SSPs for practitioners. This cloud-computing application allows users to input designated parameters to obtain the corresponding optimal plan designs. Then, practitioners can conduct sampling inspections on delivery lots based on these optimal plan designs and upload the measurement results to the application to obtain their statistical information and acceptance or rejection decisions without any computation, significantly reducing their workload. Finally, a practical case study involving microfluidic chips demonstrates the applicability of the developed tool.</p>