Friday, February 18, 2022

Project Development

 Welcome to my last blog for this semester👌

💟

1. Our team chemical device: Breath Analyzer

The Breath Analyzer is able to detect alcohol in the driver's breathe and to sober the driver with the loud buzzer noise and cold splashing water. We aimed to reduce the number of drink and drive incidents with our chemical device.


2. Team planning, allocation, and execution

Team planning:

We first came out with the materials we needed for our chemical device.

BOM

Then we decided on how should we spread out the tasks so that we don't need to rush everything at the last minute.

link: 

Initial Gantt chart template (click)

Finalized Gantt Chart Template (click)


We also listed the potential risk we might encounter during the building of prototype by using the risk assessment. 

Example of risk assessment

Lastly, we came out with our first draft prototype drawing:

Draft Prototype

At first, we wanted to use the spray bottle to splash the water, however, we neglected the force of the motor is not strong enough. Moreover, we wanted to have a cushion layer as the drunk person might hold the device tightly unconsciously. The final prototype solved all the problems and it will be shown below.


Role allocation:

CEO(Chief Executive Oficer)- Kalyani

CSO(Chief Safety Officer)- Madelaine

CFO(Chief Financial Officer)- Jolyn

COO(Chief Operating Officer)- Cui Han (me)


Allocated Tasks:

Things need to prepare: 

1. Body to contain all the components(Change from 3D print to laser cut to save time).

2. Spray bottle(3D Print).

3. Arduino code for MQ-3 sensor, led, buzzer, and spraying water.

4. Assemble the final chemical device.


Execution Plan:

TASK

ALLOCATION

DURATION

3D printed bottle

MADELAINE

2 hrs

Laser cutting body

JOLYN

2 hrs

Arduino program alcohol sensor,alarm and LED

CUI HAN

1 DAY

Integration of all parts and electronics

KALYANI

1 hr


3. Design and Build Process

  • Design and build of 3D printed bottle (done by Madelaine) click maddie
Water tank


  • Design and build of the body (done by Jolyn) click jol




  • Design and build of code and Arduino board (done by Cui Han)
 1. Connect the MQ-3 sensor to the arduino board and test it with an alcohol swap.

MQ-3 sensor

Arduino board

GND

GND

VCC

5V

A0

A0

MQ-3 sensor connection

(Gas sensor is used since MQ-3 cannot be found in tinkercad)
Tinkercad


Code used to warm up the sensor:

Warming up of sensor

Initially we set the delay as 3000ms, but the sensor was not able to work well. After some research, we decided to extend the delay to 20000ms so there's enough time for the sensor to warm up properly.

2. I wanted to add in the LED to show the difference when alcohol is detected and when alcohol is absent. So I used the output signal from sensor as the input signal for the LED.

MQ-3 sensor

Arduino board

LED

(+resistor)

GND

GND

Short side

VCC

5V

Long side

A0

A0

pin13

with LED

 Code added in:

int LED = 13 ; 

void setup(){

pinMode(13, output);

pinMode(AlCOHOL_sensor, input);}

void loop(){

 if (ALCOHOL_detected == 1)  

         {  

           Serial.println("ALCOHOL > 500");  

           digitalWrite(LED, HIGH);  }

 else  

         {  

           Serial.println("No ALCOHOL detected");  

           digitalWrite(LED, LOW); }

 

NO Alcohol sensed

Alcohol detected


 



Lastly, I added in the buzzer so it can produce a loud sound to sober the driver. Initially, we wanted to use a speaker, after some discussions we felt that the buzzer is good enough and it can help to reduce the cost.

MQ-3 sensor

Arduino board

LED

(+resistor)

Buzzer

GND

GND

Short side

-

VCC

5V

Long side

-

A0

A0

Pin13

pin8

 

Full code:











    Video:


    When alcohol is detected, the buzzer will ring with a jumping tone, when alcohol is absent, the tone becomes flat.


    • Integration of all parts and electronics(done by Kalyani) click kaya



    Finalized drawing of our chemical device:



    4. Problems and solutions

     

    Key problems

    Solution 

    The pump we were given did not have a connection that would allow us to connect it to the arduino, so we could not program it.

    We operate the water system using a switch.

    We wanted to use spray bottle for our water, but could not program it so that it sprays when the alcohol is detected.

    We 3D printed a hollow cylinder with a hole on the sides so the water shoots out.

    We wanted to 3D print our body, but it took a lot of time.

    We laser cut our body , it was easier and more efficient.

     

    Limitations

    Eliminate/ limit

    Arduino boards and maker uno were given by the school, this led to our product to not be as compact as we wanted it to be.

    Self-source for smaller arduino boards and maker uno.


    Pump provided by the school was not able to connect to arduino .

    We can source for pumps that have the ability to be connected to the arduino uno and it should not be too fragile.

    The beep sound will not stop unless there is certainly no alcohol in the surrounding atmosphere .

    • Eliminate the sound system.

    • Program it even further so that the sound can be eliminated after the alcohol level has lowered to a certain level.


    5. Project Design Files as downloadable files 

    Draft body DXF (click)

    Final body DXF (click)

    Assembled body: 


    Final Product: 

    Water tank :

    Fusion:

    water tank stl file (click)


    Arduino code file (click)


    Hero shot:




    Team photos:




    I LUV OUR GROUP ❤

    Thursday, February 3, 2022

    Hypothesis Testing

    Welcome to my blog🌕


    Objective: Using hypothesis testing to compare the flying distance of the 2 catapults, by using data from different samples with the same number of tests.


    DOE PRACTICAL TEAM MEMBERS (fill this according to your DOE practical):

    1. Person A (Bjorn)

    2. Person B (Darren)

    3. Person C (Gwyn)

    4. Person D (Cui Han)

    5. Person E (Hai Jie)

     

     

    Data collected for FULL factorial design using CATAPULT A (fill this according to your DOE practical result)

    :


     

    Data collected for FRACTIONAL factorial design using CATAPULT B (fill this according to your DOE practical result):



    Bjorn will use Run #1 from FRACTIONAL factorial and Run#1 from FULL factorial.

    Darren will use Run #7 from FRACTIONAL factorial and Run#7 from FULL factorial.

    Gwyn will use Run #6 from FRACTIONAL factorial and Run#6 from FULL factorial.

    Cui Han will use Run #4 from FRACTIONAL factorial and Run#4 from FULL factorial.

    Hai Jie will use Run #3 from FRACTIONAL factorial and Run#3 from FULL factorial.

     

    USE THIS TEMPLATE TABLE and fill all the blanks

    The QUESTION

    The catapult (the ones that were used in the DOE practical) manufacturer needs to determine the consistency of the products they have manufactured. Therefore they want to determine whether CATAPULT A produces the same flying distance of projectile as that of CATAPULT B.

     

    Scope of the test

    The human factor is assumed to be negligible. Therefore different user will not have any effect on the flying distance of projectile.

     

    Flying distance for catapult A and catapult B is collected using the factors below:

    Arm length = 27.5 cm

    Start angle = 25 degree

    Stop angle = 45 degree

     

    Step 1:

    State the statistical Hypotheses:

    State the null hypothesis (H0):

     

    Catapult A and B produce the same flying distance of projectile.

    μA=μB

     

     

    State the alternative hypothesis (H1):

     

    Catapult A and B produce different flying distance of projectile.

    μAμB

     

     

    Step 2:

    Formulate an analysis plan.

    Sample size is 8<30 Therefore t-test will be used.

     

     

    Since the sign of H1 is  , a left/two/right tailed test is used.

     

     

    Significance level (α) used in this test is 0.05

     

     

    Step 3:

    Calculate the test statistic

    State the mean and standard deviation of sample catapult A:

    nA=8

    x̄A=82.4

    sA=3.29

     

     

    State the mean and standard deviation of sample catapult B:

    nB=8

    x̄B=77.9

    sB=2.03

     

     

     

    Compute the value of the test statistic (t):





     









    SL:0.05, at A=0.025, t0.975, v=14, t=2.145

     

    Step 4:

    Make a decision based on result

    Type of test (check one only)

    1. Left-tailed test: [ __ ]  Critical value tα = - ______

    2. Right-tailed test: [ __ ]  Critical value tα =  ______

    3. Two-tailed test: [ __ ]  Critical value tα/2 = ± 2.145

     

    Use the t-distribution table to determine the critical value of tα or tα/2


     

     




    Compare the values of test statistics, t, and critical value(s), tα or ± tα/2

     

    Calculated t=3.08, from the chart, t=±2.145, t is not in the acceptable range

    Therefore Ho is rejected.

     

     

    Conclusion that answer the initial question

     

    Catapult A and B produce different flying distance of projectile.

     

    Compare your conclusion with the conclusion from the other team members.

     

    What inferences can you make from these comparisons?

    We all rejected the null hypothesis and this shows that the 2 catapults produce different flying distances even when the settings are the same.

     

    From the comparison, it shows that the design of the catapult is very important, the quality of the catapult is not persistent throughout even if there is a minor difference. Even we used a different set of data, and the t values obtained were very different, but it produced the same trend, which is the 2 catapults produce different flying distances. Hence I can infer that for both full and factorial analysis, the same trend will be produced if the settings for both full and fractional are kept the same.

     


    Reflection:

    I think hypothesis testing is very useful when we want to compare the test results, and it can help us to determine the properties of similar products based on the sample data. I found it difficult to produce the null hypothesis at the beginning, but after several practices, it became easier and clearer to me. Also, we have very different values since different sets of data were used, but the overall trend is the same. It is also important to determine which test and which formula to use based on the hypothesis generated. so I think this method is very helpful in future projects.