Optimizing Radiation Safety Protocols in Industrial Radiography Using Linear Programming and Simulation

Abstract

Industrial radiography puts non-destructive testing (NDT) technicians at risk of high photon dose rates during inspection activities. Old methods of scheduling and assigning tasks are based on guesses and do not provide equal distribution of doses, leading to inefficient means of operation and avoidable exposures. In this article, an integrated operations research (OR) framework has been offered to optimize radiation safety measures in industrial radiography, based on linear programming (LP) and the Monte Carlo simulation. The model will reduce the collective dose and enhance the efficiency of the workflow in realistic field conditions. In the case study of ten radiographic jobs and three technicians, the optimized schedule has resulted in a total collective dose that is less by 25 %, the highest dose that is less by 34 %, and an improvement in operational time by 15 %. Monte Carlo simulation ensures the ability to resist variation of dose rates and the length of the job. These results demonstrate opportunities for the OR-based decision support systems to optimize the ALARA implementation and increase the safety performance of the industrial radiography practice.