Designing internal logistics processes for new manufacturing site

Abstract

The Boeing Company is the world's largest aerospace company and is constantly evaluating improvement opportunities to the production system. It is of ongoing interest to the company to have to tools to assess new manufacturing sites. Among the required tasks for such an effort, engineers must identify the processes and capabilities that will be needed. A critical element of this study is the system of internal logistics processes that could manage the flow of parts and material throughout a site. Planning the capacity of these processes is difficult when many of the parameters are uncertain and yet to be determined. This thesis proposes a method for estimating capacity requirements of internal logistics processes by employing the concepts of queuing theory and Little's Law. Using this methodology, a process model was developed and validated by discrete event simulation to provide process planners with an understanding of the relationship and importance of numerous parameters. This understanding allows planners and management to assess the capacity requirements of the processes in terms of projected costs and performance. Values of wait times predicted by the proposed model were in strong agreement with values observed from simulation (R-squared of 96.4%; MAPE of 14.9%) suggesting that the proposed methodology represents an easy-to-use and accurate representation of process parameters. In order to improve the applicability of capacity recommendations for Boeing, further refinement is needed of underlying process parameters as well as cost modeling of threshold parameters (k and pn_max).