%0 Generic %A Smith, Zachary Brooks %D 2019 %T DIGITAL TWIN: FACTORY DISCRETE EVENT SIMULATION %U https://hammer.purdue.edu/articles/educational_resource/DIGITAL_TWIN_FACTORY_DISCRETE_EVENT_SIMULATION/10148141 %R 10.25394/PGS.10148141.v1 %2 https://hammer.purdue.edu/ndownloader/files/18289409 %K 3dx %K delmia %K dassault systemes %K discrete event simulation %K des %K industry 4.0 %K plm %K product life cycle %K enterprise system %K enterprise systems %K information systems %K operations %K industrial engineering %K model based %K model based engineering %K MBSE %K MBE %K factory %K factory simulation %K factory flow %K process planning %K digital twin %K digital thread %K digital transformation %K digital manufacturing %K digital factory %K modeling %K modeling and simulation %K simulation %K Science, Technology and Engineering Curriculum and Pedagogy %K Business Information Management (incl. Records, Knowledge and Information Management, and Intelligence) %K Information Systems Management %K Information Systems %K Technology not elsewhere classified %X Industrial revolutions bring dynamic change to industry through major technological advances (Freeman & Louca, 2002). People and companies must take advantage of industrial revolutions in order to reap its benefits (Bruland & Smith, 2013). Currently, the 4th industrial revolution, industry is transforming advanced manufacturing and engineering capabilities through digital transformation. Company X’s production system was investigated in the research. Detailed evaluation the production process revealed bottlenecks and inefficiency (Melton, 2005). Using the Digital Twin and Discrete Event Factory Simulation, the researcher gathered factory and production input data to simulate the process and provide a system level, holistic view of Company X’s production system to show how factory simulation enables process improvement. The National Academy of Engineering supports Discrete Event Factory Simulation as advancing Personalized Learning through its ability to meet the unique problem solving needs of engineering and manufacturing process through advanced simulation technology (National Academy of Engineering, 2018). The directed project applied two process optimization experiments to the production system through the simulation tool, 3DExperience wiht the DELMIA application from Dassualt Systemes (Dassault, 2018). The experiment resulted in a 10% improvement in production time and a 10% reduction in labor costs due to the optimization %I Purdue University Graduate School