Analysis and Optimization of Bullrunner Service
(Route C)
ESI 4221
Patricia Anzalone
Group Members:
Ammar Hamadah
Ibrahim Al Balushi
Alessio Vicari Bedetti
Emir Erseven
Brandon Malley
Mohammed Alaqil
Mohammed Alowaini
Optimizing Time for the Bull Runner
Introduction:
● For this project, we are trying to optimize the bus service which will correct the inaccuracy of arrival time shown in the app. Innovative redesign on this service is essential because smaller buses during peak time (times close for classes to start or when the classes is over) will cause students to be late or miss their classes due to the limited amount of space on the bus.This is a serious problem for students who utilize the bull runner service on a daily basis, …show more content…
Passengers arriving to his/her destination, he/she will pull the cord in order to notify the driver to stop at the next destination.
Current Situation
● Passengers are having a difficult time getting off due to crowdedness.
● Student with disabilities take between 2-4 minutes to be seated.
● Sometime a student takes time searching for his/her ID to show it the driver.
● Drivers changing out for shifts lead to change in the arrival time.
● Having an abundance of passengers trying to get on the bus will cause a delay in the departing time of that stop since the driver can’t leave until everyone is seated or stabilized.
Analysis:
● More buses operating at peak hours.
● Making sure that the drivers have an accurate percentage of the space available.
● Driver should ask people to move back to create more space.
● App should be modified in a way where passengers can request bus service 30 mins before travel to help transportation dept. decide the bus size.
● Eliminate any unnecessary stops where the bus has to pull out of the way and add additional time to get back on route. Traffic buildup will cause a major delay in allowing the bus to return to its normal route.
Plan:
● A shuttle that has at least 20 seats behind the bus during peak …show more content…
We recorded the data into excel and created X-Bar charts,R-charts and S-Bar charts to show our data over time. You can see the Upper and Lower control limits. The charts that are on the left side represent the raw data we collected through our observations, looking at the charts we see that there are couple nonconforming data that we gathered during. The charts that are on the right side are the charts created by eliminating the data that are out of control. Meaning that the second charts give us a clue of how these data would look like without the nonconforming units. Our data has been collected throughout the day, so from the first data to the twenty sixth it represents the time during the day which would be from 10AM to 11PM. As can be seen from the charts the bus tends to be late during the rush hours, and it arrives early during early morning and late night cycles. All of the out-of-control situations happen to be at these specific time spans. We got a Cp that is 1<Cp meaning that the variability of the system is high and it is
(Route C)
ESI 4221
Patricia Anzalone
Group Members:
Ammar Hamadah
Ibrahim Al Balushi
Alessio Vicari Bedetti
Emir Erseven
Brandon Malley
Mohammed Alaqil
Mohammed Alowaini
Optimizing Time for the Bull Runner
Introduction:
● For this project, we are trying to optimize the bus service which will correct the inaccuracy of arrival time shown in the app. Innovative redesign on this service is essential because smaller buses during peak time (times close for classes to start or when the classes is over) will cause students to be late or miss their classes due to the limited amount of space on the bus.This is a serious problem for students who utilize the bull runner service on a daily basis, …show more content…
Passengers arriving to his/her destination, he/she will pull the cord in order to notify the driver to stop at the next destination.
Current Situation
● Passengers are having a difficult time getting off due to crowdedness.
● Student with disabilities take between 2-4 minutes to be seated.
● Sometime a student takes time searching for his/her ID to show it the driver.
● Drivers changing out for shifts lead to change in the arrival time.
● Having an abundance of passengers trying to get on the bus will cause a delay in the departing time of that stop since the driver can’t leave until everyone is seated or stabilized.
Analysis:
● More buses operating at peak hours.
● Making sure that the drivers have an accurate percentage of the space available.
● Driver should ask people to move back to create more space.
● App should be modified in a way where passengers can request bus service 30 mins before travel to help transportation dept. decide the bus size.
● Eliminate any unnecessary stops where the bus has to pull out of the way and add additional time to get back on route. Traffic buildup will cause a major delay in allowing the bus to return to its normal route.
Plan:
● A shuttle that has at least 20 seats behind the bus during peak …show more content…
We recorded the data into excel and created X-Bar charts,R-charts and S-Bar charts to show our data over time. You can see the Upper and Lower control limits. The charts that are on the left side represent the raw data we collected through our observations, looking at the charts we see that there are couple nonconforming data that we gathered during. The charts that are on the right side are the charts created by eliminating the data that are out of control. Meaning that the second charts give us a clue of how these data would look like without the nonconforming units. Our data has been collected throughout the day, so from the first data to the twenty sixth it represents the time during the day which would be from 10AM to 11PM. As can be seen from the charts the bus tends to be late during the rush hours, and it arrives early during early morning and late night cycles. All of the out-of-control situations happen to be at these specific time spans. We got a Cp that is 1<Cp meaning that the variability of the system is high and it is