Simulation Using ProModel

ProModel is a powerful, yet easy-to-use, commercial simulation package that is designed to effectively model any discrete-event processing system. It also has continuous modeling capabilities for modeling flow in and out of tanks and other vessels. The online tutorial in ProModel describes the building, running, and output analysis of simulation models. A brief overview of how ProModel works is presented here. The labs in this book provide a more detailed, hands-on approach for actually building and running simulations using ProModel.

4.6.1 Building a Model

A model is defined in ProModel using simple graphical tools, data entry tables, and fill-in-the-blank dialog boxes. In ProModel, a model consists of entities (the items being processed), locations (the places where processing occurs), resources (agents used to process and move entities), and paths (aisles and pathways along which entities and resources traverse). Dialogs are associated with each of these modeling elements for defining operational behavior such as entity arrivals and processing logic. Schedules, downtimes, and other attributes can also be defined for entities, resources, and locations.

Most of the system elements are defined graphically in ProModel (see Figure 4.8). A graphic representing a location, for example, is placed on the layout to create a new location in the model (see Figure 4.9). Information about this location can then be entered such as its name, capacity, and so on.

Default values are provided to help simplify this process. Defining objects graphically provides a highly intuitive and visual approach to model building.

The use of graphics is optional, and a model can even be defined without using any graphics. In addition to graphic objects provided by the modeling software, import capability is avail- able to bring in graphics from other packages. This includes complete facility layouts created using CAD software such as AutoCAD.

4.6.2 Running the Simulation

When running a model created in ProModel, the model database is translated or compiled to create the simulation database. The animation in ProModel is displayed concurrently with the simulation. Animation graphics are classified as either static or dynamic. Static graphics include walls, aisles, machines, screen text, and others. Static graphics provide the background against which the animation

FIGURE 4.8 Sample of ProModel graphic objects.

FIGURE 4.9

ProModel animation provides useful feedback.

takes place. This background might be a CAD layout imported into the model.

The dynamic animation objects that move around on the background during the simu- lation include entities (parts, customers, and so on) and resources (people, fork trucks, and so forth). Animation also includes dynamically updated counters, indicators, gauges, and graphs that display count, status, and statistical information (see Figure 4.9).

4.6.3 Output Analysis

The output processor in ProModel provides both summary and detailed statistics on key performance measures. Simulation results are presented in the form of re- ports, plots, histograms, pie charts, and others. Output data analysis capabilities such as confidence interval estimation are provided for more precise analysis. Outputs from multiple replications and multiple scenarios can also be summa- rized and compared. Averaging performance across replications and showing multiple scenario output side-by-side make the results much easier to interpret.

Summary Reports

Summary reports show totals, averages, and other overall values of interest.

Figure 4.10 shows an output report summary generated from a ProModel simula- tion run.

FIGURE 4.10

Summary report of simulation activity.

---General Report

Output from C:\ProMod4\models\demos\Mfg_cost.mod [Manufacturing Costing Optimization]

Date: Feb/27/2003 Time: 06:50:05 PM

---Scenario : Model Parameters

Replication : 1 of 1 Warmup Time : 5 hr Simulation Time : 15 hr

---LOCATIONS

Average

Location Scheduled Total Minutes Average Maximum Current

Name Hours Capacity Entries Per Entry Contents Contents Contents

--- --- --- --- --- --- ---

---Receive 10 2 21 57.1428 2 2 2

NC Lathe 1 10 1 57 10.1164 0.961065 1 1

NC Lathe 2 10 1 57 9.8918 0.939725 1 1

Degrease 10 2 114 10.1889 1.9359 2 2

Inspect 10 1 113 4.6900 0.883293 1 1

Bearing Que 10 100 90 34.5174 5.17762 13 11

Loc1 10 5 117 25.6410 5 5 5

RESOURCES

Average Average Average Number Minutes Minutes Minutes

Resource Scheduled Of Times Per Travel Travel % Blocked

Name Units Hours Used Usage To Use To Park In Travel % Util

--- --- --- --- --- --- --- ---

---CellOp.1 1 10 122 2.7376 0.1038 0.0000 0.00 57.76

CellOp.2 1 10 118 2.7265 0.1062 0.0000 0.00 55.71

CellOp.3 1 10 115 2.5416 0.1020 0.0000 0.00 50.67

CellOp 3 30 355 2.6704 0.1040 0.0000 0.00 54.71

ENTITY ACTIVITY

Average Average Average Average Average

Current Minutes Minutes Minutes Minutes Minutes

Entity Total Quantity In Moving Wait for In Blocked

Name Exits In System System Res, etc. Operation

--- --- --- --- --- --- ---

---Pallet 19 2 63.1657 0.0000 31.6055 1.0000 30.5602

Blank 0 7 - - - -

-Cog 79 3 52.5925 0.8492 3.2269 33.5332 14.9831

Reject 33 0 49.5600 0.8536 2.4885 33.0656 13.1522

Bearing 78 12 42.1855 0.0500 35.5899 0.0000 6.5455

FIGURE 4.11 Time-series graph showing changes in queue size over time.

FIGURE 4.12 Histogram of queue contents.

Time Series Plots and Histograms

Sometimes a summary report is too general to capture the information being sought. Fluctuations in model behavior over time can be viewed using a time series report. In ProModel, time series output data are displayed graphically so that patterns can be identified easily. Time series plots can show how inventory levels fluctuate throughout the simulation or how changes in workload affect re-source utilization. Figure 4.11 is a time series graph showing how the length of a queue fluctuates over time.

Once collected, time series data can be grouped in different ways to show pat- terns or trends. One common way of showing patterns is using a histogram. The histogram in Figure 4.12 breaks down contents in a queue to show the percentage of time different quantities were in that queue.

As depicted in Figure 4.12, over 95 percent of the time, there were fewer than 12 items in the queue. This is more meaningful than simply knowing what the average length of the queue was.