Hydrogen, recognized as a critical energy source, requires green production methods, such as proton exchange membrane water electrolysis (PEMWE) powered by renewable energy. This is a key step toward sustainable development, with economic analysis playing an essential role. Life cycle costing (LCC) is commonly used to evaluate economic feasibility, but traditional LCC analyses often provide a single cost outcome, which limits their applicability across diverse regional contexts. To address these challenges, a Python-based tool is developed in this paper, integrating a bottom-up approach with net present value (NPV) calculations and Monte Carlo simulations. The tool allows users to manage uncertainty by intervening in the input data, producing a range of outcomes rather than a single deterministic result, thus offering greater flexibility in decision-making. Applying the tool to a 5 MW PEMWE plant in Germany, the total cost of ownership (TCO) is estimated to range between €52 million and €82.5 million, with hydrogen production costs between 5.5 and 11.4 €/kg H₂. There is a 95% probability that actual costs fall within this range. Sensitivity analysis reveals that energy prices are the key contributors to LCC, accounting for 95% of the variance in LCC, while iridium, membrane materials, and power electronics contribute to 75% of the variation in construction-phase costs. These findings underscore the importance of renewable energy integration and circular economy strategies in reducing LCC.

When a service encounter goes south, customers expect empathy. Hearing an employee say, “I share your frustration,” can calm tensions and rebuild trust. But new research from the University of South Florida suggests that when a chatbot tries the same tactic, it can backfire.