California State University
Long Beach
Civil Engineering Department
Materials for Civil Engineering
Laboratory
CE 200L
Short-Form Lab Report
Report No: 5
Report Title: Concrete Quality Control
Submitted By: Hayden Robbins, Jordan Albernathy, Daniel Gonzalez, Danny
Le, Denny Ng
Section: 02 Team No: #2
Date Due: 10/31/17 Date Submitted: 10/31/17
Grading
Distribution of the 10 Points Total Score for the Report
Item Criterion Max Points Earned Points
1 Use of Laboratory Equipment N/ A
2 Data Collection, Compilation, Reduction, and Interpretation 2
3 Technical Presentation — tables, graphs, sketches, etc. 5
4 Written communication — reducing data, calculations, results 3
Total
Please staple this cover sheet to the report in the designated place at the upper left corner only.
Please do not use a folder.
CE 200L
Report No 5
Concrete Quality Control
1. Object
a) To learn about techniques used for quality control audits of plants manufacturing portland
cement concrete (PCC)
b) To become familiar with fundamental terminology used in statistical analysis
c) To become familiar with the fundamentals of statistical method used in quality control
2. References
CE 200 Student Notes and Workbook (Pages 19 – 27) and the references cited on Page 19 of
said workbook
3. Procedure
The above-listed references were read, and the instructions given during the briefing period
were followed.
4. Data Recorded by Team
a) Team Information
Section: 02 Team: #2
Leader: Jordan Abernathy Recorder: Denny Ng
Other members: Hayden Robbins, Danny Le, Daniel Gonzalez
Member(s) absent: N/A
– 1/5 –
b) Concrete Field and Laboratory Data
f ′c Frequency
2,700 4
2,800 4
2,900 5
3,000 6
3,100 9
3,200 20
3,300 37
3,400 20
3,500 10
3,600 4
n 119
5. Concrete Quality Analysis
a) Plotted Data
Plot of Frequency Histogram (Bar Chart)
– 2/5 –
b) Mean Value
ƒ′c Range or Class Mid-Point (psi) No of Specimens No of Specimens (f) ×
(xi) (f) Range Mid-Point (xi)
2,700 4 10,800
2,800 4 11,200
2,900 5 14,500
3,000 6 18,000
3,100 9 27,900
3,200 20 64,000
3,300 37 122,100
3,400 20 68,000
3,500 10 35,000
3,600 4 14,400
n = 119 Σ = 385,900
n =119 =
3,242.86 psi
c) Median Value
Median n=119 = 3,300 psi, corresponding to the value of specimen # 60
d) Standard Deviation
Class Deviation Frqncy.
Deviation Frequency ×
Interval from the (of
Squared Deviation Squared
Mid-Point Mean Occrnce.)
(xi) (xi – ) (xi – )2 (f) (f(xi – )2)
2,700 -543 294,850 4 1,179,400
2,800 -443 196,250 4 785,00
2,900 -343 117,650 5 588,250
3,000 -243 59,050 6 354,300
3,100 -143 20,450 9 184,050
3,200 -43 1,850 20 37,000
3,250 120,250
3,300 57 37
24,650 493,000
3,400 157 20
66,050 660,500
3,500 257 127,450 10 509,800
3,600 357 4
n= 119 Σ = 4,911,550
=
Variance ⇒ 119
= 41,273.5
– 3/5 –
σ = 203.16 psi
e) Range of Strength Values Expected ⅔ of the Time
Strength to be expected at least ⅔ of the time: 3,039.70 – 3,446.02 psi
f) Coefficient of Variation
CV =
σ =
6.26 %
g) Conclusion
For conclusions, using Standard American English and complete
sentences, please characterize the quality control program imple-
mented at the plant that produced the portland cement concrete
(PCC) addressing the following:
(i) An assessment of the quality control program implemented
at the plant manufacturing the concrete, basing said as-
sessment on:
• The computed coefficient of variation, and
• The graphic representation (histogram) of the data
The coefficient of variation came out to be 6.26%
which is within a reasonable value. A good variance is
– 4/5 –
between 5-15%, anything with a variance above 15%
should not be allowed to continue production.
Based on our histogram we can determine that our data
has a clear defined mode (3,300 psi) and provides con-
sistent results.
(ii) A statement of which of the two methods in Paragraph (i)
above would give a more reliable indication of the ac-
ceptability of quality control.
The coefficient of variance provides the best indication
for acceptability because it provides a numerical value
that can be used to compare good quality concrete to in-
ferior ones.
(iii) A statement of as to which factor, above all others,
would increase the reliability of, and confidence in,
the data being analyzed.
The factor, that which above all others, would increase
the reliability of the data analyzed, is having a larger
sample size. This is because the larger the sample size
is, the higher the increase of accuracy in the data that
is being analyzed.
– 5/5 –
