Inspection Detection and Emergency Flow Need Separate Denominators
Abstract
Partial wafer coverage changes which defects are observed, while emergency staffing changes a modeled patient-flow process. Their comparison should declare detected and residual outcomes separately and preserve each mechanism. Independent audits and service realizations address different gaps. A high aggregate success percentage cannot make these evidence objects interchangeable. This focused synthesis develops an empirical comparison that preserves the terminal action, observation process, and total verification cost. Its proposed tests are prospective; no new simulation run, model-training result, or intervention effect is reported.
References
- M. Qin, Z. Shi, W. Chen, S. Gao, and L. Shi, “Wafer Defect Inspection Optimization with Partial Coverage: A Numerical Approach,” IEEE Transactions on Automation Science and Engineering, vol. 18, no. 4, pp. 1916–1927, 2020.
- H. Guo, S. Gao, K. L. Tsui, and T. Niu, “Simulation Optimization for Medical Staff Configuration at Emergency Department in Hong Kong,” IEEE Transactions on Automation Science and Engineering, vol. 14, no. 4, pp. 1655–1665, 2017.
- Chick, Stephen E., and Koichiro Inoue. “New Two-Stage and Sequential Procedures for Selecting the Best Simulated System.” Operations Research, vol. 49, no. 5, 2001, pp. 732–743. https://doi.org/10.1287/opre.49.5.732.10615.
- Frazier, Peter I., Warren B. Powell, and Savas Dayanik. “A Knowledge-Gradient Policy for Sequential Information Collection.” SIAM Journal on Control and Optimization, vol. 47, no. 5, 2008, pp. 2410–2439. https://doi.org/10.1137/070693424.
- Rasmussen, Carl Edward, and Christopher K. I. Williams. Gaussian Processes for Machine Learning. MIT Press, 2006. https://gaussianprocess.org/gpml/.
- Sacks, Jerome, William J. Welch, Toby J. Mitchell, and Henry P. Wynn. “Design and Analysis of Computer Experiments.” Statistical Science, vol. 4, no. 4, 1989, pp. 409–423. https://doi.org/10.1214/ss/1177012413.
- Bertsimas, Dimitris, and Melvyn Sim. “The Price of Robustness.” Operations Research, vol. 52, no. 1, 2004, pp. 35–53. https://doi.org/10.1287/opre.1030.0065.
- Campi, Marco C., and Simone Garatti. “The Exact Feasibility of Randomized Solutions of Uncertain Convex Programs.” SIAM Journal on Optimization, vol. 19, no. 3, 2008, pp. 1211–1230. https://doi.org/10.1137/07069821X.
- Glasserman, Paul. Monte Carlo Methods in Financial Engineering. Springer, 2004. https://doi.org/10.1007/978-0-387-21617-1.
- Ankenman, Bruce, Barry L. Nelson, and Jeremy Staum. “Stochastic Kriging for Simulation Metamodeling.” Operations Research, vol. 58, no. 2, 2010, pp. 371–382. https://doi.org/10.1287/opre.1090.0754.