Modified Dynamic Process Capability with Mean Shift and Variance Changes

Process capability indexes are extensively employed in the electronics industry to satisfy the rigorous quality standards required by advanced manufacturing processes. However, the reliability of these indexes can be compromised in dynamic production environments, where numerous subtle process changes often remain undetected. Although control charts are widely implemented to monitor processes and facilitate prompt corrective actions upon detecting out‐of‐control signals, their effectiveness is constrained when dealing with parameter changes due to limited sensitivity. Consequently, it becomes essential to account for undetected minor mean shifts and variance changes when evaluating process capability. This study introduces an innovative approach for calculating process capability in dynamic environments by utilizing the total detection power, which provides a robust alternative to the current conservative method. Adjustments analogous to those in conventional control charts are derived for the yield‐based process capability index across various sample sizes, and these adjustments are illustrated graphically for clarity. Numerical simulations demonstrate that the proposed method outperforms existing techniques regarding assessment accuracy. Finally, practical case studies from the assembly processes of light‐emitting diodes and wire bonding operations are presented, underscoring the applicability and effectiveness of the proposed approach.