Time Studies and Simulation Modeling
Discrete-event simulation (DES) models emulate processes by modeling all the steps of a process throughout time (Allen et al., 2015; Gittins et al., 2020; Schriber et al., 2013). Logic rules can also be applied to make simulations accurately reflect “real world” processes (Schriber et al., 2013). A process flow diagram provides the basic structure of a DES model. Data collected via time studies are inserted into each step in the model to simulate the amount of time required to complete the process. The resources that are used (labor, costs, supplies) in the process can also be inserted into the model (Allen et al., 2015). By using DES models, users can capture the complexity of commercial-scale, production systems and inform decisions made about those systems (Gittins et al., 2020).
To construct a DES model, the process in question must be defined and outlined, which can be accomplished as described above with a process flow diagram. The process diagram is recreated in DES modeling software, such as Simio (Simio LLC, Sewickley, PA), to form the basis of the model. Next, data on the time required for each step in the process must be collected and inputted into the model. It is common for data to be collected through repeated time studies where an operator performs the process and an observer records how long it takes to complete each step. In addition, costs, such as labor, supplies, and equipment, would be inputted into the model. After all relevant data has been inserted, models can be used to calculate the amount of time and resources (e.g., number of operators, amount of supplies, and equipment options) necessary to process a specific number of samples of a certain quality. Simulation models used in Bodenstein et al., (2022) can be downloaded below. Discrete-event simulation modeling has already been applied to the field of aquatic species cryopreservation to assist in facility planning and repository development (Hu et al., 2015). Thus, process flow diagrams and simulation modeling are valuable tools that can facilitate development of high-throughput cryopreservation pathways that are operated within germplasm repositories (Figure 3) and be used to facilitate interactions with their communities.
Figure 3. A video of a discrete-event simulation model, simulating oyster cryopreservation, running in Simio software. Grey rectangles are called “servers” and represent steps in the cryopreservation pathway. Arrows indicate the direction of flow of oyster germplasm through the model. When servers light up green this indicates that oysters are being processed. “Sinks” at the end of the model keep track of how many oysters have been processed. The model was run at x40 speed. This simulation model is based off the process flow diagram in Figure 2. This model created from data collected in Bodenstein et al., 2022.
Simulation models used in Bodenstein et al., (2022) can be downloaded here. Models can only be opened using Simio software (simio.com). Simio offers a free version of their software with limited capability. Researchers or educators can apply for an academic grant to gain full access to the software, commercial work is prohibited (Academic Grant Application).
01.oyster_model_original_website.spfx
02.oyster_model_funnel_website.spfx
03.oyster_model_CASA_website.spfx
04.oyster_model_funnelCASA_website.spfx
A variety of online tools exist to learn Simio, including an Introduction to Simio Document and Simio Quickstart Guide. In addition, Simio offers a textbook (Access to Simio Book) and courses (Simio University Online) upon request.