Probabilistic predictive modeling in the critical human-in-the-loop (HITL) ergonomics engineering problems

Abstract: Improvements in ergonomics engineering can be achieved through better work environment and other traditional efforts that directly affect human behaviors and performance. There is also a significant potential, however, for the improvement in ergonomics engineering tasks and problems through better understanding the role that various uncertainties play in the planner’s and operator’s worlds of work, when never-perfect human, never failure-free equipment and instrumentation, never hundred-percent-predictable response of the object of control (such as, say, car, train, or air- and spacecraft), and uncertain-and-often-harsh environments that contribute jointly to the never-zero likelihood of a mishap. By employing quantifiable and measurable ways of assessing the role and significance of such uncertainties and treating a human-in-the-loop (HITL) as a part, often the most crucial part, of a complex man-instrumentation-object-of-control system, one could improve dramatically the state-of-the-art in assuring success and safety of an ergonomics system. This can be done by predicting, quantifying and, if necessary, even specifying an adequate probability of a possible mishap. Nothing and nobody are perfect, of course, and the difference between a highly reliable ergonomics object, product, performance or a mission and an insufficiently reliable one is “merely” in the level of the never-zero probability of failure. Application of the probabilistic predictive modeling (PPM) concept provides a natural and an effective means for reduction failures. This is not the current practice though. The application of the PPM concept can improve the state-of-the-art in understanding and accounting for the human performance in a particular ergonomics undertaking. While the traditional statistical human-factor-oriented approaches are typically based on experimentations followed by statistical analyses, the PPM concept is based on, and starts with, physically meaningful and flexible probabilistic predictive modelling followed by highly focused and highly cost-effective experimentations geared to the chosen governing model(s). The PPT concept enables quantifying, on the probabilistic basis, the outcome of a particular HITL related ergonomics effort, situation or a mission. If the predicted outcome, in terms of the most likely probability of the operational failure, is not favorable enough, then an appropriate sensitivity analysis (SA) based on the developed and available algorithms can be effectively conducted to improve the situation. There are quite a few publications of the authors on the theme of the suggested presentation.The Systemic Structural Activity Theory (SSAT) is another tool that allows to analyze human performance and predict the probability of successful outcome not by just analyzing the existing software or equipment but to do it at the design stage. Application of SSAT improves efficiency and productivity and saves resources by making the design flows apparent at the early stages of the process.

Keywords: human, in, the, loop, probabilistic predictive modeling, sensitivity analysis, Systemic Structural Activity Theory, human errors, efficiency, productiviti

DOI: 10.54941/ahfe1003002

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