A high degree of uncertainty is incurred during the early product design and process planning stages of a bicycle. Consequently, this research presents an optimization procedure for the design of critical components of a bicycle frame and planning of their corresponding processes using simulation and fuzzy goal programming (FGP). For this frame, the reliability, dependability, mass, and fatigue factor were the main quality responses. Initially, the critical bicycle’s frame components with their corresponding design parameters and tolerances were identified via technical knowledge. Designed experimentation based on the Taguchi’s array was conducted by simulation with twenty replicates for various combinations of design parameters and tolerances of the key frame components. Then, satisfactory regression models were formulated to relate each quality response with design parameters and tolerances and then inserted in the optimization model. The design parameters and tolerances and processes' means and tolerances were expressed in terms of fuzzy membership functions and their relevant goals and constraints were included in the optimization model. Finally, the objective functions were minimizing the negative and positive deviation from desired goals and maximizing process capability indices. Results showed that the FGP optimization procedure effectively achieved the desired targets of the bicycle’s quality responses and process capability indices. In conclusion, the proposed procedure can be used for optimal concurrent product and process design in a wide range of industrial applications. Manuscript profile