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A computational weld mechanics (CWM) framework that automates multiple setups, analyses and evaluations to explore a design space for design variations defined by Design of Experiment (DOE) matrices for a given design that is described. Saving an expert-user's time to prepare several analyses and allocating CPUs for efficient use makes this framework cost and time effective for managing industrial-scale designer-driven optimization and control applications of CWM. A validation analysis is conducted to identify the CWM control vector that minimizes the difference between the computed and experimental data. Actual CWM problems with continuous and discontinuous parametric design spaces including regression modelling surrogate modelling, sensitivity analysis, and control problems to minimize weld distortion are solved in this framework using derivative-free optimization algorithms that become attractive in this framework. The study demonstrates exploration of the design space for welding structures such as aircraft, ship, automotive and heavy machinery.