enhancing complex system performance using discrete-event simulation
In this paper, we utilize discrete-event simulation (DES) merged with human factors analysis to provide the venue within which the separation and deconfliction of the system/human operating principles can occur. A concrete example is presented to illustrate the performance enhancement gains for an aviation cargo flow and security inspection system achieved through the development and use of a process DES. The overall performance of the system is computed, analyzed, and optimized for the different system dynamics. Various performance measures are considered such as system capacity, residual capacity, and total number of pallets waiting for inspection in the queue. These metrics are performance indicators of the system's ability to service current needs and respond to additional requests. We studied and analyzed different scenarios by changing various model parameters such as the number of pieces per pallet ratio, number of inspectors and cargo handling personnel, number of forklifts, number and types of detection systems, inspection modality distribution, alarm rate, and cargo closeout time. The increased physical understanding resulting from execution of the queuing model utilizing these vetted performance measures identified effective ways to meet inspection requirements while maintaining or reducing overall operational cost and eliminating any shipping delays associated with any proposed changes in inspection requirements. With this understanding effective operational strategies can be developed to optimally use personnel while still maintaining plant efficiency, reducing process interruptions, and holding or reducing costs.
queuing model discrete event simulation potential capacity