Chia-Huang Wu

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.

This paper examines equilibrium mixed strategies in unobservable Markovian queues featuring a second optional service with server vacations, where arriving customers may choose to join or balk the system. All customers arriving at the system receive the essential service, and some customers opt for the second service after the first service has been completed. Once all customers in the system have been served, the server takes the first of multiple vacations. If no customers are waiting upon from the vacation, then the server takes another vacation. In unobservable queues, arriving customers cannot know the queue length; however, the information pertaining to the server state may be available. By examining unobservable queues (fully unobservable and almost unobservable cases), it is possible to formulate an equilibrium joining strategy as well as the socially optimal probability of joining a fully unobservable queue. This paper also presents numerical examples illustrating how system parameters affect mixed equilibrium and socially optimal balking strategies.

Production equipment is crucial to efficiency enhancement and product quality in the manufacturing industry. Repairman and removable standbys can be configured to support continuous production in order to minimize downtime and capacity loss associated with the malfunctioning of manufacturing equipment. Under these conditions, an idle repairman temporarily leaving the system to perform other tasks can undermine service performance. This paper presents a limited-capacity machine repair problem with standbys, two failure modes, and a working vacation policy. The steady-state system-size distribution is derived via the matrix analysis method and matrix decomposition. Based on steady-state probabilities, we derived closed-form formulations of several critical metrics for the assessment of system characteristics. Sensitivity analysis is performed to illustrate the effects of uncertainty in system parameters. Management implications are also addressed.