FlexSim is a discrete-event simulation software package developed by FlexSim Software Products, Inc. The FlexSim product family currently includes the general purpose FlexSim product and healthcare systems modeling environment (FlexSim HC).
History
FlexSim development began in late-2001 as an unnamed development project of F&H Simulations, Inc., a U.S. distributor of F&H Holland's Taylor II and Taylor ED products. Development was initially led by Dr. Eamonn Lavery, with lead developer Anthony Johnson joining in April 2002. Before the end of 2002, the development project was renamed FlexSim, which coincided with F&H Simulations, Inc. changing its name to FlexSim Software Products, Inc.[1] FlexSim was acquired by Autodesk, Inc. in 2023.[2]
FlexSim 1.0 was released in February 2003. FlexSim used a major.minor.build software versioning scheme until version 7.7.4; beginning with version 16.0.0 on March 14, 2016, FlexSim transitioned to a year.update.bugfix versioning scheme.[3]
FlexSim has been used in a variety of simulation projects involving both standard and flexible manufacturing systems.[6] Some examples include studies to determine optimal buffer sizes,[citation needed] optimizing blend components in feed production,[7] rescheduling problems in mixed-line production planning,[8] optimizing electronics assembly lines,[9] and steel production scheduling.[10]
Industry 4.0
FlexSim has been used to automate simulation model development for more than a decade; a 2008 study described a FlexSim-based solution that communicates with Product Lifecycle Management (PLM) software to generate simulation models.[11] With the ongoing trend of Industry 4.0 pushing manufacturers toward automation and improved communication, FlexSim has been used to develop computer simulation models for these applications.[12]
FlexSim can be extended through C++, which allows the software to be integrated into systems involving real-time data communication.[13] The software has been used for nearly real-time production planning, which improves upon the Master Schedule approach (which can get out of date and miss on-site changes).[14] In one study, FlexSim was integrated into a dynamic data-driven application system to automatically generate simulation models via the XML language.[15]
Robotics and Crane
FlexSim's standard object library contains a 6-axis robot object capable that contains both pre-built motion logic and the ability to create customized motion paths.[16] FlexSim has been used to model and analyze robotic cells in manufacturing environments, including dynamic scheduling and control of a robotic assembly cell.[17]
The standard object library also contains a crane object, "designed to simulate rail-guided cranes such as gantry, overhead, or jib cranes."[18] FlexSim, through the use of the crane object, has been used to evaluate solutions to crane scheduling in a shipbuilding environment.[19]
Healthcare
In April 2009, FlexSim Software Products, Inc. released a standalone healthcare simulation product named FlexSim HC. It was developed as simulation package focused on modeling patient flows and other healthcare processes.[20] The final release in original FlexSim HC development path was version 5.3.10 on February 19, 2019; beginning with FlexSim version 19.1.0 on April 29, 2019, FlexSim HC functionality was merged into the core FlexSim development and became a modeling environment within the software.[21]
In practice, the FlexSim HC environment is used by healthcare organizations to evaluate different scenarios in their healthcare processes and validate the scenarios before they are implemented.[22] The environment has been used in various patient care improvement initiatives, including studies to understand different treatment options in Labor & Delivery,[23] deploying advanced practice nurses in treating non-urgent patients,[24] and demonstrating simulation-based design of a breast-screening facility as both a process improvement tool and as a management training tool.[25]
During the COVID-19 pandemic, FlexSim HC was used to analyze vaccination rollout efforts and improve patient flow at vaccination sites.[26] Outside of the traditional healthcare setting, FlexSim has been used to dynamically calculate and visualize radiation exposure.[27]
As general purpose simulation software, FlexSim is used in a number of fields:
Material handling: Conveyor systems, AGV, packaging, warehousing
Logistics and distribution:[28] Container terminal operation, supply chain design, distribution center work flow, service and storage layout, etc.
Transportation:[29] Highway system traffic flow, transit station pedestrian flow, maritime vessel coordination, custom traffic congestion, etc.
Others: Oil field or mining processes, networking data flow,[30] etc.
Main features
Robust standard objects
FlexSim includes a standard object library, with each object containing pre-built logic and task execution to mimic the resources found in real-world operations. FlexSim objects[31] are defined and programmed in four classes: fixed resource class, task executer class, node class and visual object class. FlexSim uses an object-oriented design.
Logic building tools
The logic for a FlexSim model can be built using very little or no computer code. Most standard objects contain an array of drop-down lists, properties windows, and triggers that allow the user to customize the logic required for an accurate model of the system. FlexSim also includes a flowcharting tool to create the logic for a model using pre-built activity blocks.
Drag-and-drop controls
Users can build the model by dragging and dropping predefined 3D objects into a "model view" to layout and link the model. Experienced users also have the option to specify and modify object parameters and behaviors using FlexScript and C++ programming languages.[32]
^Tikasz, Laszlo G.; McCulloch, Robert I.; Pentiah, Scheale Duvah; Baxter, Robert F. (2012). "Simulation Tools to Complement Cast House Design and Daily Operation". Light Metals 2012. pp. 993–997. doi:10.1007/978-3-319-48179-1_173. ISBN978-3-319-48570-6.
^Kaczmar, Ireneusz (2015). "Cost optimization of blend preparation with the use of the FlexSim environment". Agricultural Engineering. 4 (156): 51–60. doi:10.14654/ir.2015.156.151. ISSN2083-1587.
^Huang, Hsiang-Hsi; Pei, Wen; Wu, Horng-Huei; May, Ming-Der (2013). "A research on problems of mixed-line production and the re-scheduling". Robotics and Computer-Integrated Manufacturing. 29 (3): 64–72. doi:10.1016/j.rcim.2012.04.014. ISSN0736-5845.
^Yao, Liufang; Zhu, Weifeng (2010). Visual simulation framework of iron and steel production scheduling based on Flexsim. 2010 IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA). Changsha: IEEE. pp. 54–58. doi:10.1109/BICTA.2010.5645359.
^Burnett, Gabriel A.; Medeiros, D. J.; Finke, Daniel A.; Traband, Mark T. (2008). "Automating the development of Shipyard manufacturing models". 2008 Winter Simulation Conference. pp. 1761–1767. doi:10.1109/WSC.2008.4736264. ISBN978-1-4244-2707-9. S2CID3107244.
^Fan, Shu-hai; Zhou, Zhi; Shen, Qian (2009). "A Virtual MCQA Information System Based on Flexsim". 2009 Second International Symposium on Knowledge Acquisition and Modeling. pp. 111–113. doi:10.1109/KAM.2009.50. ISBN978-0-7695-3888-4. S2CID9348862.
^Mihoubi, B; Gaham, M; Bouzouia, B; Bekrar, A (2015). "A rule-based harmony search simulation-optimization approach for intelligent control of a robotic assembly cell". 2015 3rd International Conference on Control, Engineering & Information Technology (CEIT). pp. 1–6. doi:10.1109/CEIT.2015.7233172. ISBN978-1-4799-8212-7. S2CID16851230.
^Wen, Charlie; Ekşioğlu, Sandra Duni; Greenwood, Allen; Zhang, Shu (2010). "Crane scheduling in a shipbuilding environment". International Journal of Production Economics. 124 (1): 40–50. doi:10.1016/j.ijpe.2009.09.006. ISSN0925-5273.
^Macleod, Kenny; Moody, Robert (March 14, 2017). "Chapter 31: Simulation modelling and analysis to test health systems". In Nestel, Debra; Kelly, Michelle; Jolly, Brian; Watson, Marcus (eds.). Healthcare Simulation Education: Evidence, Theory and Practice. John Wiley & Sons. pp. 209–213. doi:10.1002/9781119061656. ISBN978-1-119-06159-5.
^Tompkins, G.H.; Kornreich, D.E.; Parker, R.Y.; Koehler, A.C.; Gonzales-Lujan, J.M.; Burnside, R.J. (2004). "Dynamic Radiation Dose Visualization in Discrete-Event Nuclear Facility Simulation Models". Proceedings of the 2004 Winter Simulation Conference, 2004. Vol. 2. pp. 472–478. doi:10.1109/WSC.2004.1371496. ISBN0-7803-8786-4. S2CID9961278.
^Liu, Miaomiao; Dong, Mingwang (2008). "The Simulation Technology of Port Container Logistics System Based on Flexsim". Logistics. pp. 2547–2552. doi:10.1061/40996(330)376. ISBN9780784409961.
^Wang Weiping, Zhao Wen, Zhu Yifan and Hua Xueqian, "Survey on the Object oriented Simulation Method", Journal of National University of Defense Technology, 1999-01.
^
Pierre G. Paulin, Faraydon Karim and Paul Bromley, "Network Processors: A Perspective on Market Requirements, Processor Architectures and Embedded S/W Tools", Design, Automation and Test in Europe Conference and Exhibition, p. 0420, 2001.
^William B. Nordgren. "Flexible simulation (Flexsim) software: Flexsim simulation environment", Proceedings of the 35th conference on Winter simulation: driving innovation, 2003.
Further reading
Beaverstock, Malcolm; Greenwood, Allen; Nordgren, William (2017). Applied Simulation: Modeling and Analysis Using FlexSim (5th ed.). Orem, UT: FlexSim Software Products, Inc. ISBN978-0-9832319-5-0.
Pawlewski, Pawel; Greenwood, Allen, eds. (2014). Process Simulation and Optimization in Sustainable Logistics and Manufacturing. Springer. ISBN978-3-319-07347-7.
Qin, Tianbao (2013). Zhou, Xiangyang (ed.). 实用系统仿真建模与分析—使用Flexsim [Practical System Simulation Modeling and Analysis with Flexsim] (in Chinese). Beijing, China: Tsinghua University Press. ISBN978-7-302-31322-9.
Kim, Jun Woo (2019). 3D 팩토리 시뮬레이션을 이용한 생산 시스템 모델링 Handbook (FlexSim 소프트웨어 활용법 - 입문편) [Handbook of Production System Modeling using 3D Factory Simulation (FlexSim Software for Beginners)] (in Korean). Seoul, South Korea: Chungsol. ISBN978-89-94364-67-4.
Law, Averill M. (2006). Simulation Modeling and Analysis (4th ed.). McGraw-Hill Science. ISBN978-0-07-329441-4.