Date of Submission
Spring 2018
Project Type
Senior Design
Department
Department of Systems and Industrial Engineering
Committee Chair/First Advisor
Dr. Adeel Khalid
Abstract
Siemens Energy offers world-class products and solutions for power generation. They help their clients worldwide to successfully operate conventional power plants by renting out their toolkits. Clients can work on anything from gas or steam turbines, generators, turbines, or even hybrid power and storage. One of Siemens’ more profitable toolkits would be the A-Set, or as the floor assemblers refer to as ‘the majors,’ which consists of two large conex containers filled with thousands of tools ready for any type of operation at power plants. By looking at how long it takes floor assemblers at the Siemens Facility in Suwanee, GA to unload, degut, perform inventory, etc. on A-Sets coming in from use, our teams goal is to optimize the process and cut down on time to reduce the turnover rate. From time studies performed at the facility, the collection of logbooks kept since early 2016, and interviews taken from leads in involved departments, it was found that the average turnover rate of an A-Set is roughly 12 days, from start to finish. Given the processes involved with ensuring that the A-Set is ready to be “white -tagged” or ready to be sent out again to a new client, our team used tools such as Arena ® Simulation Software, DMAIC, statistical analysis, and process mapping to assess the system to be able to cut down on time. Through the analysis of the data and simulations run from Arena ®, the Mechanical Jack process was found to be the bottleneck in which the entire process would be waiting on. Following the acknowledgement of the bottleneck, the implementation of a solution involving an additional floor assembler and a priority system set to allow the Mechanical Jack process to begin faster, we were able to reduce the turnover time from 12 days to 8.55 days, while also increasing the revenue flow by increasing the amount of A-Sets Siemens could theoretically turn out in the same period of time with the reduction in time per turnover. With the turnover time being reduced, it is important to note that while in our calculations we accounted for additional A-Sets being turned out, that the Siemens facility in Suwanee could use the extra time shaved off per cycle in whatever which way they prefer. Initial recommendations would be to use the extra time to turnover more A-Sets, but another option could be to cross train their workers to circumvent any other slow processes that they may come up against through the reallocation of their workers from process to process as their priority levels increase. Regardless of what the facility decides to do with the reduction of turnover time, our team was successful in our endeavors and the following report will delve into what each process consisted of, as well as the direction our team chose to assess the system and give a formal recommendation to Siemens Energy.