refactor: update Exponential-2P parameter mapping and add lognormal sigma boundary constraints

src/aeros_equipment/service.py

@@ -352,8 +352,9 @@ def get_distribution_from_db(parameters: dict, is_repairable: bool = True, best_
             return "Weibull3", beta, eta
         elif method == "Exponential-2P":
             lambda_val = parameters.get("lambda_value", 0.00001)
+            mttf = 1/lambda_val
             gamma = parameters.get("gamma", 0)
-            return "Exponential2", lambda_val, gamma
+            return "Exponential2", mttf, gamma
         else:
             # Default to NHPP
             return "NHPPTTFF", 1.0, 100000
@@ -363,7 +364,9 @@ def get_distribution_from_db(parameters: dict, is_repairable: bool = True, best_
         
         if distribution == "Lognormal":
             mu = parameters.get("mu", 0)
-            sigma = parameters.get("sigma", 1)
+            sigma = parameters.get("sigma", 1.0)
+            # Ensure log dev (sigma) is strictly within Aeros' boundaries of [0.01, 3.0]
+            sigma = max(0.01, min(3.0, float(sigma)))
             return "Lognormal", mu, sigma
         elif distribution == "Normal":
             mu = parameters.get("mu", 100000)
@@ -378,8 +381,9 @@ def get_distribution_from_db(parameters: dict, is_repairable: bool = True, best_
             return "Weibull2", beta, eta
         elif distribution == "Exponential-2P":
             lambda_val = parameters.get("Lambda", 0.00001)
+            mttf = 1/lambda_val
             gamma = parameters.get("gamma", 0)
-            return "Exponential2", lambda_val, gamma
+            return "Exponential2", mttf, gamma
         else:
             # Default to Normal
             mu = parameters.get("mu", 100000)