Bull Runner Project
-
Upload
aggarwalneeraj5 -
Category
Documents
-
view
216 -
download
0
Transcript of Bull Runner Project
-
8/8/2019 Bull Runner Project
1/16
Bull Runner Project
Neeraj Aggarwal, James Knapp, and Pratik Shah
EIN 6179 Six Sigma
Professor Beata Abbs
May 5, 2010
-
8/8/2019 Bull Runner Project
2/16
Executive Summary
The main problem occurring that we decided to analyze and try to fix
were the wait times involved in waiting and commuting through Bull Runner.
The Bull Runner Shuttle system performs with long wait times varying on
average from 13 to 19 minutes as against the expected time of 8 minutes
causing delays and frustrations among commuters. This has been a problem
for quite some time and the Bull Runner Operation team already knows this.
Their thoughts on fixing this in the recently has considered inserting a GPS
system to allow for the buses to know where the others are located. They
think this will let the buses flow more efficiently and create a more
consistent wait time for riders. This could help but we feel more needs to be
done and analyzed in order to make commuters happy.
Our goal for this project deals with using an array of different methods
through Six Sigma and analyzing this data to reduce wait times. We will only
be analyzing 2 out of the 5 routes, which our solution will be employed to all
once they are found. The desired wait time between buses will be set to 8
minutes in which the recorded average as of the beginning of the project was
16 minutes. We will use a whole semester in which to find out which data to
gather, gather it, and use it to our advantage. The use of the voice of the
customers, riders, as well our strategy in this time limit will be directly
related to the significance of our results. Once all the tools are used properly
controlling and maintaining the solution or solutions will also be looked at.
-
8/8/2019 Bull Runner Project
3/16
Background
Any student at a major university can tell you that one of the most
frustrating parts of the day deals with parking. It times of over an hour at
some campuses have been recorded in which parking spots were not
available. This turns into missed classes, quizzes, tests, and just about
anything a student needs not to miss in order to do as good as they can. To
fix this problem many universities such as USF have developed a shuttle
system in which various locations off of campus are shuttled to there and
back. USF calls their system Bull Runner and just like many of the other
systems it can be called insufficient at times. Considering the main reason
for the shuttles in the first place deals with being late for class, if the shuttles
are late what would the point be?
The Bull Runner Shuttles have been around for quite some time at USF
and take on the routes A, B, C, D, and E. Multiple buses run on each route
and vary throughout the day in the amount per route. Drivers drive at
different speeds but always follow the proper route in which they are order
to drive. The system does follow a consistent path each week in which the
same number of buses will start and stop on certain routes at certain times.
This leads way to a system that can be analyzed in which it does have
consistent variables although the wait times are very inconsistent.
Approach
-
8/8/2019 Bull Runner Project
4/16
The approach to this project could be considered the most important
aspect of the entire thing. We first started to observe the operation as a
whole from an outsiders perspective. We found that Bull Runner actually
has a website in which you can track the routes and buses by a map. This
website showed their estimated arrival times and the actual times and
places they were in current time. Another resource we found that might be
somewhat beneficial was Bull Runner management. After creating our
mission, vision, and strategy our first strategic plan developed the map in
which you see below.
Boun
dary
Boun
dary
S I P O C
Suppliers Input Process Output Customer
Parking &
Transportat
ion services
Bull
Runner
buses
Transportat
ion
Student
Bus Stops Staff
USF Card
Tracking
System
This mapped set the guidance to what we were looking at as a whole.
-
8/8/2019 Bull Runner Project
5/16
Rick Fallen the person involved in management which we were able to
contact us helped us a great deal. We were able to get information on the
pay of each driver, information on the new GPS system, and he allowed us to
pass surveys out on the bus to get the voice of the actual customer. The
next major step involved finding our variables and strategizing what variable
effected the wait time. A detailed look below:
Y-Variable
Wait Time between buses
X-Variable
Number of Buses
Drivers
Condition of Buses
Different day times
Number of Stops
Traffic Conditions
Communication System response
Driver Changeover
From this data our goal throughout the entire project will be to find which of
these X-variables will affect the Y-variable, wait time between buses.
Voice of the Customer
An important aspect of any project should involve the people that are
considered the customers of the system. In our case this would be the users
of the Bull Runner System at anytime throughout the week. Our strategy at
first was to send out an email to receive information from all of the Bull
-
8/8/2019 Bull Runner Project
6/16
Runner users that went to USF. This strategy overlooked the challenge
having access to send a mass email to all of these USF students. Our next
strategy involved Rick Fallen in which he permitted us to leave these surveys
in the shuttles in which the customers rode. The list of question below
describe the information that we wanted to achieve and they either had
rating from 1-10 in which you could answer, multiple choice, or fill in the
blank answers. Questions:
1. How many times a week you use Bull Runner service?
2. Which Bull Runner route do you travel most often?
3. What is your average wait time to board the Bull Runner?
4. Do you have information on the schedule following which Bull runner
makes stops at your stop?
5. Bull Runner always arrives at my stop on time?
6. On an average, how many co-passengers are there on Bull Runner trips
you take between 07:00 AM and 05:00 PM?
7. On an average, how many co-passengers are there on Bull Runner trips
you take between 05:00 PM to mid night?
8. I am satisfied with the pull chain stop alert system.
9. How do you rate Bull Runner Service?
10.Please include any comment (Positive or Negative) on Bull Runner
service.
-
8/8/2019 Bull Runner Project
7/16
We not only wanted to hear about the waiting times of Bull Runner, but the
system as a whole. If it lacked in other areas we might have been able to
analyze these areas as well and use them to our advantage.
Process Mapping
Once some information can be retained the fact of mapping out the
process of a whole can be crucial in finding the weak links in the chain so to
speak. The process map we have created shows the process of an everyday
user enters the shuttle to when they exit. As you look at it you will notice
that the shuttle has contact with one another and use this to gage how fast
they should drive. Process Map:
One of the most interesting notes to take from this involves the fact that
drivers actually slow down in order to keep a proper distance from the next
driver. The reason for this makes sense in the need for spacing the shuttles,
but this obviously will slow down the system as a whole.
Tools Used
Throughout this project a various amount of tools were used. The first
tool we used involved the quality function deployment in which we tried to
focus on Bull Runner as a whole. This data exhibited below:
Quality Function Deployment
How
WhatCI
Timely avialbility 5155
Availability at
desired location 13
Room to sit 333
Cleaniness 22
Safe to travel 36
Quiet atmosphere 11
Comfortable 2
20
18 5 23 45 27 48 3 3 18
Strong 9
Medium 3
Weak 1
Number
of stops
Tracking
&
Commun
ication
System
CustomerNeeds
Metrics
Numbe
r of
Buses
Number
of drivers
Conditio
n and
year of
Manufact
ure Schedule
Seating
capacity
Time
betweeb
buses
Administ
ration
quality
-
8/8/2019 Bull Runner Project
8/16
By observing the totals in the lowest and furthest to the right sections, it
helps in the overall assessment of Bull Runner.
The next step in using certain tools we choose the Ishikawa Diagram.
This diagram helped us focus on the all the factors that were involved in the
process. The Xs on the diagram show were the factors to be considered are
located and there are 6 different categories in which we focused on. These
categories are management, man, method, measurement, machine and
materials. This diagram is below:
-
8/8/2019 Bull Runner Project
9/16
Bull Runner has a website in which it was very helpful in collecting data
called the Bull Runner tracking system. We also rode the shuttles as while in
order to receive data from these trips and see firsthand the steps taken.
Through this data and Minitab our team developed many different graphs on
to determine the appropriate factors that effects the wait time. These
graphs are shown below some have brief descriptions of why they were
used:
Stability chart in order to see if there persists of any common factors dealing
with the wait times:
Normality Chart much with the same reasoning to find out if a consistent
duration of waiting time exists:
-
8/8/2019 Bull Runner Project
10/16
Normalization plot of the data to see if we can find a formula within these
wait times:
We compared the wait times vs. the time of day in order to see if a certain
time of the day held higher average wait times than other times:
-
8/8/2019 Bull Runner Project
11/16
Turned the line chart into a graph that would be easier to see the differences
in a bar chart for wait times relevant to the time of the day:
The number of buses was our next area of focus and to see if this affected
the wait times:
We took a further in depth look of actually riding the bus all of Monday and
comparing these times to wait times:
We took the wait times between five and six and compared the number of
buses to wait times:
Through Minitab we were able to test for a significant P-value < .005:
-
8/8/2019 Bull Runner Project
12/16
We tested for the same relevant to the time of day:
-
8/8/2019 Bull Runner Project
13/16
All of these tools were crucial in the outcome and solutions to our project.
Through the use of Minitab and graphs the project could be broken down and
analyzed from many different angles.
Critical X identification and Improvement Approaches
We found four critical X factors that affect the wait time in a negative
way. The first X factor deals with the number of buses per route. At times
bus utilization can be handled better and our solution to the problem is to
increase the number of buses to a maximum of 5 per route. The next X
factor deals with the routes themselves. Unnecessary steps throughout the
routes are taken in which new routes will be utilized. One of the X factor that
involves technology deals with the use of adjusting the lights so that the
buses travel through with less stops. This goal will work if the routes are
scheduled properly and the lights change at the proper times. The last X
factor that contributes is to set standards of operating the shuttles by the
drivers. Drivers as of now differ from one to the next in terms of the speed
in which they drive. The ability to influence standards among all will set a
better system and place and prove beneficial in the long run. A list of the
solutions to implement is below:
1. Increasing the number of Buses to a maximum of 5.
2. Shortening the route by removing unnecessary miles.
-
8/8/2019 Bull Runner Project
14/16
3. Adjusting schedules and providing Traffic light monitoring to avoid
traffic lights.
4. Setting standard operating procedures for drivers.
Risk Assessment and Mitigation Strategy
To implement the use of our first solution we first graphed the
difference in wait times compared to the number of buses used:
We ran the numbers to find out how much this would cost the company:
1. Additional Cost = Average cost of running a bus * # of hours
Avg. Cost = $42/hr.
# of hours = 10 hrs a weekday*days in a year
Additional Cost For Route D = $109,500 per year
2. Annual Savings to Customers = (227193)*5/7(Weekdays/(16-8)/60*Average Student
Salary
Annual Savings to Customers = $21,637
3. Savings From Additional Bus = $10,687
The next area of focus involved the path taken by the buses
throughout the trips. By taking a new strategy on how the path should be
taken miles can be cut off the trip and yet all the necessary places can still
be stopped at. A series of bullet points displays our findings:
-
8/8/2019 Bull Runner Project
15/16
Extra miles traveled each day = 1.2 miles
Average number of trips per day = 45.5 trips
Number of extra miles per day = 54.6 miles
Annual fuel saving without extra miles = $3919
Annual time cut off for customers = 2 minutes per hour
Extra time if used for work instead of waiting = $13521 per year
The other two solutions involve implementing new technology to the lights
as well as making a systematic schedule that all drivers must follow. This
also involves standardizing arriving and leaving times for all drivers in order
to implement the system correctly.
Control
Once all of the steps to our solution have been taken controlling them
will be the next phase. Any problem can receive a solution and it may work,
but it can fail if not properly controlled. The most important way of
controlling these solutions involves following the system correctly. If Bull
Runner converts back to its old ways in any area it can break the new
approach and ruin the advances taken. The number of shuttles as well as
the routes taken cannot be strayed from at any point in time and it must be
consistent. For the last two solutions a proper system should be
implemented and if done properly it should be consistent and not changed.
One variable will always be in need of analyzing and that is the drivers.
Checks on whether all drivers are properly holding true to the system will be
-
8/8/2019 Bull Runner Project
16/16
given. Examinations on knowledge of the system as well as paths and times
taken will be recorded. If drivers do not abide by the system properly
necessary steps will be taken and possible relieving them of their duties may
be the only solution at times.
Conclusion
Through our approach and results it seems as though we may have
found a proper solution. All necessary steps were taken in finding the
appropriate X factors and then analyzing them. The factors that seem to
affect the wait times are very plausible and are well backed up through the
data we found. The next step will be to implement these findings and see if
the forecasted results occur. We hope to show Rick Fallen our results and
encourage him to try the solutions and see how they work. These four
solutions are to add Bus drivers, optimize the routes, change the times in
which the lights will turn, and to set a systematic way of having more
consistent drivers and travel times. All of this will in turn make for less wait
times and overall not only save Bull Runner money, but the customers as
well. If a little more can be put into Bull Runner it can be an efficient system
in which other universities will be jealous of and want for themselves.