The Post began an incremental implementation of several recommendations in December 2010. 1.4 WHERE WE STARTED A second team, known as Power Wash Post (PWP), began working with the Post in January 2011 with the goal of expanding the static analysis done by the previous group. This expansion provided a dynamic simulation model of the helper component of the Post’s four work centers. The work centers are composed of primarily two labor categories: helpers and mailers. The mailers operate the collators and inserting machines (SLS machines), while the helpers move the pallets to the various machines, staging areas, and storage racks. 1.5 OUR METHOD Team PWP received a similar data set as the first team; a one-week period in February 2011. After a cleansing to remove anomalous routes, Team PWP mapped all of the remaining routes to specific helper zones within the system. Then, descriptive statistics were obtained on route times for model input to determine the best distribution and mean of the input data. From this, Team PWP determined that a significant amount of the route times received from MTC were invalid and they decided to use estimated route time data as recommended by the client instead. In addition, they collected data on markup helper schedules, arrival processes, and internal system business logic that were used to build a simulation model in Arena. 1.6 OUR TECHNICAL APPROACH Based on an in-depth study of the operational process at the warehouse of the Post and thorough discussions with the customer, Team PWP decided the best approach was to build a discrete event simulation model in Arena platform after comparing alternative options, given the nature and complexity of the problem. Certain assumptions were made in the areas of model architecture, resources, arrival processes, service time distributions, and internal business logic. Team PWP first utilized the work from the previous group and then collected new data to perform process analysis on work centers quantitatively. Followed by process analysis on routes and operations, Team PWP obtained production data then performed input data analysis on statistics related to labor, routes and arrival process. Meanwhile, the model architecture was constructed in Arena. Once the model was complete, testing, evaluation, and sensitivity analysis indicated that it did in fact accurately model the system. Team PWP then conducted output analysis that demonstrated the capabilities of the model and how its statistics could be used to inform decision makings.
The Post began an incremental implementation of several recommendations in December 2010. 1.4 WHERE WE STARTED A second team, known as Power Wash Post (PWP), began working with the Post in January 2011 with the goal of expanding the static analysis done by the previous group. This expansion provided a dynamic simulation model of the helper component of the Post’s four work centers. The work centers are composed of primarily two labor categories: helpers and mailers. The mailers operate the collators and inserting machines (SLS machines), while the helpers move the pallets to the various machines, staging areas, and storage racks. 1.5 OUR METHOD Team PWP received a similar data set as the first team; a one-week period in February 2011. After a cleansing to remove anomalous routes, Team PWP mapped all of the remaining routes to specific helper zones within the system. Then, descriptive statistics were obtained on route times for model input to determine the best distribution and mean of the input data. From this, Team PWP determined that a significant amount of the route times received from MTC were invalid and they decided to use estimated route time data as recommended by the client instead. In addition, they collected data on markup helper schedules, arrival processes, and internal system business logic that were used to build a simulation model in Arena. 1.6 OUR TECHNICAL APPROACH Based on an in-depth study of the operational process at the warehouse of the Post and thorough discussions with the customer, Team PWP decided the best approach was to build a discrete event simulation model in Arena platform after comparing alternative options, given the nature and complexity of the problem. Certain assumptions were made in the areas of model architecture, resources, arrival processes, service time distributions, and internal business logic. Team PWP first utilized the work from the previous group and then collected new data to perform process analysis on work centers quantitatively. Followed by process analysis on routes and operations, Team PWP obtained production data then performed input data analysis on statistics related to labor, routes and arrival process. Meanwhile, the model architecture was constructed in Arena. Once the model was complete, testing, evaluation, and sensitivity analysis indicated that it did in fact accurately model the system. Team PWP then conducted output analysis that demonstrated the capabilities of the model and how its statistics could be used to inform decision makings.
SYST798-OR680_Final_Report_WashingtonPost.docx