Included in the process flow diagram for each step are the duration times by product and resources needed at each step, and product routes. Also needed at this time are business rules governing the process such as working hours, safety envelopes, quality control, queueing rules, and many others. Capturing this complex interrelated system begins by visiting the process and talking with the process owner and operators. Drawing the diagram and listing other information is a good second step, but actually building and operating the process is when a person truly understands the process and its complexities. Of course many of the processes we want to improve are already built and are in use. In most cases, students will not be able to do either of these. However, building a verified and validated simulation model is a good proxy for doing the real thing, as the model will never validate against the actual process output unless all of the complexity is included or represented in the model.

1. Promodel Simulation Examples Free
2. Witness Simulation

In the ‘Systems and Simulation’ course at the University of Idaho students first learn fundamentals of process management including lean terms and tools. Then they are given the opportunity to visit a company in the third week of class as a member of a team to conduct a process improvement project. In this visit students meet the process owner and operators.

• The same as Model 2 but several (Bernoulli) conditional probability distribution is constructed for various queue lengths (see the Example). • On arrival, a maximum tolerable length of queue is determined from a discrete probability distribution for each entity. The maximum number is then compared with the queue length at the moment of arrival to determine whether or not the entity balks. The first three approaches model the underlying tolerance for waiting implicitly. Model 4 allows tolerance variation among customers to be modeled explicitly.

Assume a 10% significance level. Comment on your results. Digit (bin) 0 1 2 3 4 5 6 7 8 9 Expected count 10 10 10 10 10 10 10 10 10 10 Actual count 4 15 9 9 9 12 10 7 10 15.

The working of Starbucks Cafe store at the University of Cincinnati was simulated using Arena simulation software as a part of the academic curriculum of MS-Business Analytics at the University of Cincinnati. The project included using Input Analyzer to fit the data to probability distributions, Arena Software to prepare and run the model and Output Analyzer and Process Analyzer to get the statistically significant results by comparing outputs of two models. Using these results, a new model was suggested to the Starbucks Cafe store to improve their efficiency economically. A Simulation Model of Starbucks Cafe using Arena Software • 1.

The second edition of Simulation Using ProModel covers the art and science of simulation in general and the use of ProModel simulation software in particular. The lead author is the Chief Technology Advisor for ProModel Corporation. Modeling and simulation for this audience. Each workshop participant will be provided with evaluation disks for two software packages that are the two most popular discrete event modeling and simulation programs used in the US: Rockwell Automation Arena and ProModel Process Modeling (ProModel).

The students use the distribution of outputs from the original model to generate appropriate output and then compare that output to output pulled from the distributions of each improvement scenario. This comparison is then used to determine a 95% confidence interval for the NPV and the probability of the NPV being zero or less. Finally, several weeks before the semester is finished, students travel to the company to present their findings and recommendations. Student learning on these projects is multifaceted. Learning how to use ProModel is the level that the students are most aware of during the semester, as it takes much of their time.

It’s a field that is rife with variation, but with simulation, I firmly believe that it can be properly managed. Patient flow and staffing are always a top concern for hospitals, but it’s important to remember that utilization levels that are too high are just as bad as levels that are too low, and one of the benefits of simulation in healthcare is the ability to staff to demand. Check out Dale’s work with Robert Wood Johnson University Hospital where they successfully used simulation to manage increased OR patient volume. About Dale Since joining ProModel in 2000, Dale has been developing simulation models used by businesses to perform operational improvement and strategic planning.

Promodel Simulation Examples Free

As most of the food items available at Starbucks are readily available and doesn’t require any preparation, e.g. Snacks, cakes, cookies etc., this is a feasible option. The model was renovated with the above suggestions and here is a glimpse of the new model – • Changes – 1. The process module (and hence the queue) for Food items was removed 2. The Resource capacity for Cash counter was increased from 1 to 2 3.

Q4 (a) (50% marks) Explain any five of the following six ProModel terms. Give examples as required. - Resources - Entities - The JOIN statement - The LOAD/UNLOAD statements - Path networks - The MOVE statement (list and explain the various forms) (b) (25% marks) List the equivalent ProModel expression for each of the following: - Exponential operand - Not equal to operand - Logical AND - Division operand - Logical OR (c) (25% marks) Explain, in simple English, what is occurring in the following blocks of ProModel code. (i) INC Var1 IF Var1. Q5 (a) (50% marks) The following data sets are outputs from a simulation model assessing the impact of different scheduling rules on overall time a product spends in production. Perform an appropriate statistical test to determine whether there is a significant difference between the two scheduling rules in terms of the overall time a product spends in the system.

Reneging happens after a person joins the queue but later leaves because he/she feels waiting no longer is tolerable or has utility. Literature indicates that both decisions can be the result of complex behavioral traits, criticality of the service and service environment (servicescape).

Do not forget that we handle topics like composite curve method, Heat and Power Integration, Thermal pinch, Azeotropic distillation and Distillation Boundaries which has given a lot of students a difficult time to do their assignments and get excellent grades. Online pro-model software experts Tutoversal.com has a team of online assignment writing experts that help you in answering all the problems that you are almost blowing your head.

• With (indicates the probability and the label to which the entity needs to be directed). • Else (indicates the label to which the entity needs to be directed if the else condition becomes true).

Duration 2 Hours No. Of Pages Cover + 5 pages Department(s) Industrial Engineering Course Co-ordinator(s) Requirements: MCQ Handout Statistical Tables Yes Graph Paper Log Graph Paper Other Material. Q1 (100% marks) A manufacturing company is considering the introduction of a machine Preventative Maintenance Program, at a cost of €20,000 per year, and its associated impact on the frequency of machine breakdowns and resultant repair costs. Currently, when a machine breaks down it has to be repaired, costing money. Machine repair costs vary according to the probability shown in Table 1 below. Every time a machine breakdowns it costs the company between €2000 and €6000. Table 1 Probability Distribution of Machine Repair Cost Machine Repair Cost (€ ) Probability of Repair Cost 2000.15 4000.55 6000.30 The elapsed time between breakdowns is given by the distribution function: f(x) = x/8, 0 ≤ x ≤ 4 weeks (x = weeks between machine breakdowns) With the introduction of the Preventive Maintenance Program the probabilities associated with repair costs are predicted to reduce as shown in Table 2 below.

In May, Charley officially retired from the company and to honor his innovative and productive career ProModel held two celebrations this summer at two of our locations in Orem Utah and Allentown Pennsylvania. The events were attended by ProModel staff and many of Charley’s long time colleagues who have been with him from the start. In recent years, Charley has written about his team’s original vision for ProModel back in 1988, “We set out to revolutionize the use of simulation in the business world by introducing the first graphically oriented simulation tool for desktop computers. Farhad Moeeni Simulation is one of the required courses for the MBA degree with MIS concentration at Arkansas State University. The course was developed a few years ago with the help of a colleague (Dr. John Seydel).

For simplicity assume instantaneous repair times in all case - i.e. Model cumulative time based on frequency between breakdowns.

It is generally preferable to enter the experiment before entering the model. By first defining the objects such as resources in the experiment, the drop down list can then be selected when entering the model graphically [8]. Elements The following section describes in brief the various elements used by the simulation team in developing the project.

Witness Simulation

For example, the time between arrivals and the service times generated must allow for something other than uniform distribution rounded to the nearest whole number [7]. Distribution Selection To test the compatibility of a set of observed frequencies with some theoretical frequency, we must first identify the theoretical distribution we wish to try. If we are dealing with a discrete variable, we record the frequency occurring within which each individual value occurs. If the variable is continuous, we break the range of values into equal interval or class. The relative frequency in each interval is then the observed frequency count in each class divided by the total number of data points [7].

Cash 2 Model with capacity 2 for Cash counter resource. Food Item resource absent. Cash and Hot 2 Model- capacity 2 for both Cash Counter and Hot Beverage Resources.

The probability for this is input in the module as 98% for availability. Here is the dialog box – Another decision module is placed for food item named ‘Decision for Food items’ which decides whether the customer wants any food item. The probability for this is 20% customers here opt to buy food items and they go through the food item server, rest go directly to the beverage counter. Here is the dialog box – 4. Customer waits in queue for food item The customers who opted for Food items wait in queue of the food items customers before they are served the food items. Customer gets the food item A process module named ‘Food items served here’ is added to the model with action as ‘Seize Delay Release’ and the expression for the service time of this process is the one we got from Input Analyzer. Here is the dialog box of the Process module for Food item.

Customer gets the food item 6. Customer waits in queue for hot/cold beverage 7. Customer gets hot/cold beverage 8. Customer leaves the system There are certain decision modules which decide the path of the customer in the Model. Also, the model consists assign and record modules to calculate the average customer time in the system and the number of customers who bought food items and hot, cold beverages. The important parameters in the Arena model are the Resources and Queues. Here is an overview of the model parameters – Arena Starbucks Type / Action 1.

During this time period students discover that they do not have all the data and information they need to replicate the actual process. In many cases they do not have the data and/or information because the company does not have that information or how the model is operated is not the same as designed. Students then have to contact the process owner and operators throughout the six weeks to determine the actual business rules used and/or make informed assumptions to complete their model. Once the model has been validated and the students have a deep understanding of the process, students start modeling process changes that will eliminate waste in the system, increase output, and decrease cost. Examples of methods used to improve the process include changing business rules, adding strategically placed buffers and resources, and reallocating resources. To determine the most effective way to improve the process, a cost benefit analysis in the form of an NPV analysis is completed.

SSLC, in the heart of MainStreet, houses offices and meeting spaces for student groups and organizations. ‘Starbucks’ is one of the favorite and busiest places at SSLC.

Queues – There are 3 queues in the model. We will analyze the waiting time in each queue after we run the model. Here is a snapshot of the queue information from Arena – • 3.2 Simulating the Model The Arena Software has on option of Run window where we have to mention the Run information like replication length, number of replications etc. The model prepared here was run for 3 hours and 30 replications were made to consider variabilities. Here is a snapshot of the Run dialog box – The entities were given an animation of persons so the entities could actually be seen when the model is in run mode. • CHAPTER 04 RESULTS AND INTERPRETATION 4.1 Results The Arena Software produces a detailed and structured result window which allows the user to view results by Entity, Queue, Resource and anything that is specifies in the model. The category overview has a pre-defined KPI as the Number out.

Each resource has its own service time which was fitted by the distributions. Here is a table of the resources – 1. Resource 1 Cash Counter Person Seize Delay Release 2.

An example is a work piece Waiting in turn to be processed on a busy machine. The operands of queue block are Queue ID indicating the name of the queue, Capacity of the queue and the Balk label which is used to direct the entity to an alternative block other than the seize block [8]. SEIZE: It is used in conjunction with the queue block and is used to model the status delays. When a resource becomes idle the entity from the previous queue block enters the seize block and seizes the resource. The state of the resource now changes from idle to busy. The operands of seize block include priority for the allocation of entities waiting for the same resource.

If you do a seach specifically of my user ID plus those tags, you will get a list of the questions I've specifically offered out here. Select * from SomeTable Additionally, there are plenty of other Q&A associated with VFP and OleDB. Microsoft odbc visual foxpro driver cannot update the cursor. Then, your queries are as simple as.

Table 2 Probability Distribution of Machine Repair Cost with Maintenance Program Machine Repair Cost (€ ) Probability of Repair Cost 2000.40 4000.50 6000.10 With the Preventive Maintenance Program in place the elapsed time between breakdowns is now defined by the following probability distribution: f(x) = x/18, 0 ≤ x ≤ 6 weeks Manually simulate the above system for one year (52 weeks) in its current state and with the Preventative Maintenance Program in place. Based on your analysis what recommendations would you give to the company. In both cases use column 1 of the random number table (at the back of the examination paper) in the equation to calculate the time between breakdowns and column 2 of the table in the assessment of the resultant repair costs.

ProModel is a flexible, multipurpose simulation program for Windows systems. The program is in use in a variety of industrial applications, with 3 core functions.