As the Business Process Re-engineering entails simultaneously redesigning processes, organizations and the information systems that support them in order to drastically improve the cost, time, quality and customer perception of the company's goods and services [1]. The business process modelling is the technique that is used to analyze, design, and optimize the business processes taking place in an organization. The benefit of process management is now being acknowledged as the competition shifts from cost and quality to flexibility and responsiveness as the key target for this study in Queuing Systems [1]. In this study, a process model of license office queuing system was created using BPMN (business process modelling notation). The process models the system is created through simulation. Simulation is helpful technique for determining the performance of system by making business process simulation model of license office queuing system. Consumers now-a-days are much pickier and price conscious. In order to deliver high-quality service at reasonable rates, performance measures like waiting times and activity costs are crucial which can be done by performing Simulation. Business process modelling and simulation can provide valuable insights into the performance of a system and potential improvements in the system through visual connector and graphics [2]. The simulation makes it possible to foresee the consequences of renovations as well as the length of procedures and bottlenecks and thus the avoidance of bad decisions [3].

The license office is the critical component of the government’s infrastructure, responsible for issuing and renewing various types of licenses, such as driver’s licenses and professional licenses. Most citizens have to face difficulty when they go to the license office to renew their licenses or for making new licenses. Especially, when they are in an emergency situation like those how want to go outside the country. All this happens due to overcrowding in the License office and time-consuming registration process. At this time, Business Reengineering is Important with Authentic Strategy [4]. At this, we have to detect the bottleneck situation to overcome crowding. After getting the token number citizens have to wait for a long time for their turn. The high volume of customers and complexities in processes involved in registration can lead to long wait times, frustrated customers, and inefficiencies in the system. Due to this some of the citizens also have to return home without getting their work done. This makes visitors dissatisfaction. Moreover, it is not a user-friendly way if someone needs his license urgently. Using this information, we can develop a simulation model for License office queuing system and determine performance of system explore potential improvements in current system. For making the business process simulation model Any Logic simulation software is used which elevates working process of current system. Aim of our system is to provide a good workflow for both clients who want to create or renew their license as well as workers by taking those steps to online app that are not critical or not require any physical presence. This solution will provide a good simulation of workflow.

The term "business process reengineering", or BPR, is not new in the corporate world. Since it was first offered as a vehicle for transformation in the American corporate sector, it has been more than 20 years. Early in the 1990s, the private sector (US-based businesses) used BPR as a key tool for bringing about dramatic change in the business process [5]. Business process modelling and simulation are powerful tools that can provide valuable insights into the performance of a system and potential improvements [6]. Business process modelling is a technique used to analyze, design, and optimize business processes in an organization [7]. On the other hand, simulation allows the prediction of the impacts of changes and the determining the bottlenecks, helping to avoid poor judgment about the process [8].

Queuing systems are an essential component of organizations, particularly in government offices responsible for maintaining the work of offices. License offices, such as the one in Gujrat, face the challenge of providing quality service at competitive prices while dealing with a high volume of customers and the complexities of the registration process. This can lead to long wait times, frustrated customers, and inefficiencies in the system. To improve overall satisfaction, it is crucial to optimize the license office queuing system and provide better service to citizens. In this research paper, we determine the effectiveness of business process modelling and simulation to design and optimize the license office queuing system in Gujrat. The study combines qualitative and quantitative methods to investigate the current state of the license office. Identify inefficiencies and propose solutions for improvement. The aim is to provide a good workflow for both clients and workers and take some steps online to reduce wait times and improve customer service [9-11].The proposed solution is to make certain processes automatic and implement an online registration system. This will help reduce wait times and increase the number of registrations by improving customer service. The study will use simulation software, Any Logic, to develop a simulation model for the license office queuing system and determine its performance, exploring potential improvements in the current system [12].

Simulation, queuing model analysis & Flow analysis are the major techniques for determination of the business process in quantitative manner. The queuing model helps to determine the queuing system of the process, while the flow analysis helps to describe the workflow of the process. Whereas the simulation model is constructed in order to get the statistical results of model by running it again and again in simulation software [12].

The research methodology used in this study includes a combination of qualitative and quantitative methods.

1. The qualitative methods include interviews with customers and staff, observations of the current system, and a review of the literature on business process modelling and simulation.
2. The quantitative methods include data collection and analysis of the number of customers, wait times, and service time. Data collection was done through observation and a questionnaire survey which was conducted from the citizens in license office and from senior police inspector (director) of license office. The data collected data was then analyzed to compare the results of simulation & real-world data. This study proposes a queuing model for business process model analysis that satisfies all of the requirements for the fundamental patterns of process modelling. 

To validate the results of simulation model, an experimental study was conducted at Gujrat License office. The study was conducted over a period of two days, during which statistical data was collected at the license office. Their arrival times, service time and waiting time were carefully noted and the average number of successful registrations were also noted. The stats of current process of the license office which were collected through the observation and survey are as follow:

1. Current Process

       Survey- Day: 1 (Friday)

Table 1.1: Data Collection through Survey on Day 1.

The above table includes the stats collected on Friday. As Friday is different from other days of the week. There is break of 1 hour for Jummah prayer during working hours of the office moreover, the number of citizens coming to License office on Friday is also greater than the usual days of the week that’s why there overcrowding in office whole day. As stats shows in Table 1.1, almost 10 people came to office before opening time of office in order to get early token. Out of those 10 citizens 9 got registered in first two hours of office opening and 20 more came during that time. So, the total waiting persons after first two hours were 21. Similarly, in next two hours from 11am to 1pm almost 11 persons got registered successfully and 25 more persons came during that time so that the total waiting person first four hours were almost 35. Similarly in last four hours office working almost 24 persons got registered and 15 more came during that time. Hence, at the closing time of the office there were still 31 persons left waiting. They returned from office without getting registered.

Figure 1.1: Graph of Collected Data from Survey on Day 1.

Figure 1.1 is the bar graph of the statistical data collected on Friday as shown in above table. This graph shows the number of citizens came in license office, successful registrations, and total waiting person.

Day: 2 (Saturday)

Table 1.2: Data Collection through Survey on Day 2.

The above table shows the stats collected on Saturday. As Saturday is just like usual days of the week. There is no break during working hours of the office, just there is changes in shifts office workers moreover, and the number of citizens coming to License office on Saturday is also just like the usual days of the week. As stats shows in Table 1.2, almost 12 people came to office before opening time of office in order to get early token. Out of those 12 citizens 11 got registered in first two hours of office opening and 25 more came during that time. So, the total waiting persons after first two hours were 26. Similarly, in next two hours from 11am to 1pm almost 12 persons got registered successfully and 22 more persons came during that time so that the total waiting person first four hours were almost 36. Similarly in last four hours office working almost 28 persons got registered and 15 more came during that time. Hence, at the closing time of the office there were still 27 persons left waiting. They returned from office without getting registered.

Figure 1.2: Graph of Collected Data from Survey on Day 2.

Figure 1.2 is the bar graph of the statistical data collected on Saturday as shown in above table. This graph shows the number of citizens came in license office, successful registrations, and total waiting person. 

The data collected through the experimental study showed that the average service time for a single person was 17minutes while maximum 20 minutes and minimum 15-mins. The average waiting time for a single person was 45 minutes and maximum waiting time was approximately 1hour 15-minutes and minimum 25 minutes as shown in (Table 1.1 & 1.2). While the utilization of service resources was approximately 98%. Due to which some people have to return to their homes without getting registration. So, we made simulation of our purposed solution to demonstrate the results of our solution that is presented.

BPMN

Figure 1.3: BPMN of Problem or Current Process.

In this BPMN a complete process of License office is mentioned. First of all, when a person comes to license office, he gets his token number from the receptionist and sits on the waiting area until the announcement of his token number. When his turn comes, the person goes to the registration counter and provide the necessary details required for the registration such name, id-card number, and date of birth etc. after verification of these details he provides the necessary documents to the teller. The teller verifies his documents and do biometric verification of the persons after successful verification the details of the persons saved, and he gets registered for the test-driving license. The BPMN of the Current process is shown in (figure 1.3).

Simulation

Figure 1.4: Simulation of Current Process.

The simulation logic of the current process of the license office is shown in figure 1.4. The process starts on arrival of sources (Persons) and the time measures starts as person enters in the queue after entering the office. The queue has capacity of maximum 8 persons whereas the waiting time for the person in a queue to get token number is 1-2 seconds. After getting Token from token counter each person has to do wait for his turn in by sitting in waiting area. On announcement of token number, the person goes to teller resource pool where registration and verification service is provided to the person. There are 2 tellers which work at a time and after successful registration the person leaves the office. This simulation model is properly scheduled according to working hours of office for six days of week from Monday to Saturday.

Figure 1.5: State Chart of Current Process.

Figure 1.5 shows state chart of current process in which customer enter the office and enter in queue to get token and after this waiting for turn and then goes to the counter to register his/her application after giving the data to teller, teller make him to verify for biometric verification and after passing all states successfully customer Leave the Office. There state chart was simulated with two variable one with color, which shows at which state the customer by deferring with colors and second one name is, Int, which shows how many of customers are queued to enter in respective state.

Running Model

Figure 1.6: Running Model after 1 & Half Hour.

Figure 1.7: 3D View of Process Model.

Figure 1.6 shows that after 80 minutes of office opening time almost 41 persons came to office out which 8 got registered successfully and 30 persons are in waiting area for their turn while 2 are currently on registration counter & 1 is going toward registration counter as his token number is announced.

Figure 1.8: Simulation Running Model View at Closing Time of Office.

By running this simulation model completely according to office timing from 9:00am to 6:00pm, it was clearly observed that almost 80 citizens came to the license office in a single day out of which 54 got registered successfully and 23 are still waiting in waiting area 3 others are on teller resource pool. So, 26 persons had to return homes without getting registered shown in Figure 1.8.

        2. Purposed Solution

         Day: 1 (Friday)

Table 2.1: Table about Data According to the Proposed Solution on Day 1 Test.

The above table includes the stats of Friday according to purposed solution. As Friday is different from other days of the week. There is break of 1 hour for Jummah prayer during working hours of the office from 1:00pm to 2:00pm moreover, the number of citizens coming to License office on Friday is also greater than the usual days of the week.  As stats shows in Table 2.1, almost 25 persons came to office got registered successfully and the total waiting person is 0. Similarly, in next two hours from 11am to 1pm almost more 25 persons came got registered successfully so that the total waiting person in first four hours is 0. Similarly in last four hours office working almost 40 persons came and got registered successfully. Hence, at the closing time of the office there was no person left waiting.

Figure 2.1: Graph of Data Form Proposed Solution Simulation on Day 1 Test.

Figure 2.1 is the bar graph of the statistical data collected on Friday as shown in above table. This graph shows the number of citizens came in license office, successful registrations, and total waiting person.

Table 2.2: Table about Data According To the Proposed Solution on Day 2 Test.

The above table shows the stats according to purpose solution on Saturday. As Saturday is just like usual days of the week. There is no break during working hours of the office, just there is changes in shifts office workers moreover, and the number of citizens coming to License office on Saturday is also just like the usual days of the week. As stats shows in Table 2.2, almost 25 persons came to office in first two hours of office opening and all 25 got registered during that time. So, there no waiting person after first two hours. Similarly, in next two hours from 11am to 1pm almost 25 persons came and got registered successfully whereas from 1:00pm to 2:00pm 13 persons came to office and got registered. Similarly in last four hours office working almost 37 persons got registered. Hence, at the closing time of the office there was no person left unregistered. Moreover, it is also noted that 100 persons got registered in whole day during office timing.

Figure 2.2: Graph Of Data Form Proposed Solution Simulation on Day 2 Test.

Figure 2.2 is the bar graph of the statistical data from table 2.1. This graph shows the number of citizens came in license office, successful registrations, and total waiting person. According to this graph the registration rate of citizens was 100 percent.

BPMN

Figure 2.3: BPMN of Proposed Solution or Process.

The BPMN model of purposed solution is given in figure 2.3. In this BPMN model a pool (Person) is made with three lanes named as Teller, office & Application. First of all, people opens the Application and do sign-up or login by providing required information. There is collaboration between pool (Person) and pool (System). So, the login details are authenticated by the System. After successful login the person start his registration by providing necessary detail which are required by the system. These details are saved in the system and a token is generated by the system. The person, then goes to office on at specific date and time as mentioned on token number. When person visits the office, he goes to teller give him all the required documents for verification. The teller gets documents and verifies the documents. After successful verification teller gets biometric verification of the person and all these details are saved in the system. In the end person leaves the office.

Simulation

Figure 2.4: Simulation of Proposed Solution.

In this simulation there is little change in the process of Gujrat License office. As the registration service is transferred to online E-Licensing app through which a person can register himself by providing the required details and gets his appointment token on which time and date is mentioned. On given date and time the person has to come in the License office just for his biometric verification and also for verification of his documents. This task requires only 7-10 minutes. Moreover, he does not need to wait for his turn in long queues for a while because everyone has been given a specific time of 10. The person just needs to be there in license office before his time starts. The simulation model is shown in figures 2.4 & 2.5.

Figure 2.5: 3D View of Simulation of Proposed Solution.

Running Model

Figure 2.6: Running Model of Proposed Process or Solution at Start of Office Timing.

Figure 2.6 shows that 21 people registered online out of which 15 persons came to license office on the given date and time. They simply verified their token at token counter and went to waiting area and in first hour of office time almost persons successfully got biometric verification and verification of documents.

State Chart

Figure 2.7: State Chart of Proposed Solution.

Figure 2.7 shows state chart of proposed process/system in which customer login the app and enter its data and register for License application, after this customer gets a token number with date and time mentioned on it. Customer will go to the office at mentioned time and data. Now, he has to only verify biometric and leave the office. There state chart was simulated with two variable one with color which shows at which state the customer by deferring with colors and, second one name, Int, which shows how many of customers are queued to enter in respective state.

Figure 2.8: Running Model of Proposed Solution at End of Office Timing.

Figure 2.9: Results of Proposed Solution at End of Office Timing.

By running this simulation model completely according to office timing from 9:00am to 6:00pm, it was clearly observed that almost 100 persons came to the license office in a single day on their specified times given to them and all of them got biometric verification and successfully verified their documents. Moreover, it is also noted that by reducing the service time the waiting time of citizens is also reduced and furthermore there were no large queues of citizens at reception due to online appointments and the registration system. No one has to do wait for long time as all them got registered online through E-Licensing App shown in figures 2.8 & 2.9.

Let’s compare the states of both, current and proposed, system.

         3. Is-a (Current System)

The current system is a long process that was compulsory to done in Office, which require more time to deal with single customer, which cause more person in waiting for token or turn for registration process, this results in Overcrowding in office.

Before 9:00am, 10 persons comes before time to get token early, so this 10 are on waiting. From 9:00-11:00am, there were 9 successful registrations, 20 were newcomers. However, since there were already 10 people waiting before this time period, the total number of people waiting increased to 21? From 11:00-1:00pm, there were 11 successful registrations. In addition, there were 25 new people who arrived during this time period, people waiting increased to 35. From 1:00-2:00pm, there were no successful registrations, as it’s a break time, but 5 newcomers arrived during this time period, and since there were already 35 people waiting before this period, the total number of people waiting increased to 40. From 2:00-6:00pm, there were 24 successful registrations, 15 were newcomers. However, since there were already 40 people waiting before this period, the total number of people waiting decreased to 31? After this, office time ends and all the persons in waiting list have to get back to home without getting themselves registered.

Table 3: Data Collection through Survey on Day.

We have done this on different days and results shows waiting person increases as office time gets advance.

          4. To-be (Proposed)

In our proposed system, we cut of the token getting and registration process form office and make it online. As customer get himself registered in app and come to office for only biometric verification. After implementing this in simulation, there was a surprise improvement in Waiting Time. As, all of the person have their own specific time to come to Office, Moreover, Time taken for dealing with one customer decreased. 

Before 9:00am, there were 0 successful registrations, 0 were newcomers. 0 waiting. From 9:00-11:00am, there were 25 successful registrations, 25 were newcomers. 0 waiting. From 11:00-1:00pm, there were 25 successful registrations. In addition, there were 25 new people who arrived during this time period, people waiting is 0. From 1:00-2:00pm, as this is a Break time to Offer prayer, there were 0 registrations. In addition, there were no new people arrived during this time period. So, waiting persons are 0. From 2:00-6:00pm, there were 0 successful registrations, 40 were newcomers. However, people waiting is 0. After this, office time ends and all the persons in waiting list have to go back to home without getting himself registered.

Table 4: Data Collection through Survey on Day.

Comparison

Here is the comparison that shows the current system and proposed system details.

Table 5: Comparison between Current & Purposed System.

The experimental study also identified the several areas of office for improvement in the working and queuing system. The results of the study showed that the current license office queuing system is experiencing bottlenecks and inefficiencies. The main issues identified were long wait times, underutilized staff, and slow customer service. The proposed solution for improvement in office working is automating certain processes. The simulation results showed that these solutions would significantly reduce wait times and increase staff utilization for example, the study found that there could be a significant amount of idle time between persons arrival. Moreover, it was also found by the study that service time can also be reduced by increasing the number of resources or by shifting some time-consuming tasks to E-Licensing app. By using E-Licensing app user can register himself for license by providing necessary details and get an appointment. In this way the persons only have to go to the license office for a specific time just for the verification of his provided details and documents and for biometric verification. So, by implementing this automated system in the License office, almost 100 people can get registered on daily bases. In this way the process of working in the Gujrat license office can run more smoothly without overcrowding of persons. This might be easy for citizens and also for the staff of the office. 

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