THE COPPERBELT UNIVERSITY

SCHOOL OF MINES AND MINERAL SCIENCES

CHEMICAL ENGINEERING DEPARTMENT

TITLE: SCREEN ANALYSIS

NAME: ISAAC MUKAZA LUKUMBA
SIN: 21940397
YEAR OF STUDY: 3rd YEAR

TASK: LAB REPORT (EXPERIMENT 11)

LECTURER: MR. KATUNDU

INSTRUCTORS: MR. CHIPILI AND MR. MUSONDA
COURSE: CE 330
DUE DATE: 19th JUNE, 2024.
Group 6 members:
Isaac Mukaza Lukumba 21940397
Christopher Mwamba 21161986
Moses Mutambo 21162850
Chileshe Besa 21162115
TITLE: SCREEN ANALYSIS

ABSTRACT
This report investigates the effectiveness of size reduction operations through screen
analysis. Size reduction is a crucial process in engineering, involving the breakdown
of larger particles into smaller ones. Screen analysis is a vital tool in assessing
particle size distribution, where a weighed sample is distributed across a series of
screens with varying mesh sizes. The resulting masses retained on each screen are
recorded and analysed to determine the effectiveness of the size reduction process.

In this experiment, a 200g sample was processed, resulting in a 0.2g loss. The masses
retained on each screen were recorded, ranging from 112g to 5g on the pan. Despite
the screens being organized in descending order by size (from 425 microns to 106
microns), the masses did not follow a specific order. The results are presented in log
probability and cumulative weight percent passing and retained plots against screen
size. The standard deviation and variance of the data indicate a significant spread in
the particle size distribution.

This report highlights the importance of screen analysis in size reduction operations
and provides insights into the effectiveness of the process. The results can be used to
optimize size reduction processes in various engineering applications.

INTRODUCTION
Screen analysis is a crucial quality control procedure in mineral processing that
involves examining a sample by passing it through a series of screens with
progressively smaller openings. This process efficiently separates particles by size,
allowing for the determination of particle size distribution (PSD) and the percentage
of certain particles present in the sample. The efficiency of the screens can also be
evaluated based on the oversize and undersize fractions.

In this context, screening is a vital step in mineral processing that enables the
selection of appropriate subsequent processes for the material. For instance, finer
particles may be sent for fines dense medium separation (DMS) or leaching, while
larger particles may be sent for coarse DMS or re-crushing.
Fig 1.1: Screen sieves of different sizes. Fig 1.2: Screen sieves and sieve shaker.

The efficiency of the screening process depends on various factors, including the
type of screen (static or vibrating), panel material (steel or rubber), panel size and
geometry, feed rate, and the phenomena of probability and stratification.
Additionally, the screening process can be either dry or wet, with the latter being
preferred as it does not generate dust.

In this experiment, the focus was on determining if there is a significant difference

(0.95 probability level) between the analysis obtained by two groups. A 200g sample
of sand was used, and dry sieving was performed using Tyler mesh sieves in the lab.
The results of this analysis will provide valuable insights into the particle size
distribution and screening efficiency.

OBJECTIVE
To separate the given sample into fractions after thoroughly mixing, by using a set of
standard Tyler screens and weighing the retained fractions.
THEORY
Sieve analysis, commonly known as screen analysis, is a widely utilized method in
chemical engineering to assess and categorize particles based on their size. The
technique involves passing a sample through a series of screens with sequentially
smaller openings, measuring the quantity retained on each screen. This process is
essential for determining the particle size distribution (PSD), which significantly
influences the physical properties of materials, such as the strength of concrete,
solubility, surface area, and taste preferences.

The PSD is critical for selecting suitable processes for the material post-screening,
such as dense medium separation or leaching. The efficiency of the screening process
hinges on various factors, including the type of screen (static or vibrating), the
material and size of the panels, the feed rate, and the principles of probability and
stratification. The choice between dry and wet screening is also pivotal, with wet
screening being preferred to mitigate dust production.

MATERIALS AND METHOD

Materials

 Tyler screens of mesh sizes 106,212,250,300,355 and 425.

 Pan.
 Cover.
 Fine brush.
 Weighing balance.
 Sieve shaker(vibrator).
 Sample(sand).
Method

1. 200g of the provided sample’s mass was measured and documented.

2. The Tyler screens were cleaned using the fine brush.

3. The mass of each Tyler screen was determined and noted.

4. The Tyler screens were organized sequentially by mesh size(microns): 106,

212, 250, 300,355 and 425, with the largest mesh size (425) at the top and the
collection pan at the bottom.

5. The sample was distributed onto the topmost screen, which had a mesh size
of 425.

6. The screens were secured onto the sieve shaker apparatus.

7. The assembly was subjected to shaking for a duration of 15 minutes.

8. Following this interval, the screens were carefully detached from one another.

9. The Tyler screens containing the sample were weighted, thus the masses of
the sample retained on each screen were determined.

10. The material retained on each screen was weighed and the mass was recorded.

RESULTS AND DISCUSSION.

Table 1.1: Data collection.

Size Weight of Weigh of sieves Mass of

microns(µm) sieves(g) With sample(g) sample(g)
425 315.4 427.4 112
355 305.3 372.8 67.5
300 273.5 273.8 0.3
250 283.0 283.3 0.3
212 284.7 296.3 12.8
106 407.8 409.7 1.9
Pan 236.0 241.0 5.0
Total mass of sample retained on the screens = 112+67.5+0.3+0.3+12.8+1.9+5=
199.8g.
 Table 1.2: Data results.

Size Tyler Wt. Retained %Wt. Cuml. Wt.% Cuml. Wt.%

screen (g) Retained Retained passing
(microns)
425 112 56.056 56.056 43.942
355 67.5 33.783 89.839 10.159
300 0.3 0.15 90.139 10.009
250 0.3 0.15 90.139 9.859
212 12.8 6.406 96.545 3.453
106 1.9 0.951 97.496 2.502
Pan(receiver) 5.0 2.502 99.998 0
Where; Wt. retained: weight retained, %Wt. retained: weight percent retained, Cuml.
Wt.% Retained: cumulative weight percent retained and Cuml. Wt.% passing:
cumulative weight percent passing.

Graph 1.1: Cuml. wt% passing & Retained Vs log of Screen Size.
Graph 1.2: Log probability graph.

Statistical analysis.

��
�= �
(Eq:1) Where; � : mean.

�� : sum of values.

n: number of values in the sample.

(�−�)2
�� =
�−1
(Eq:2) Where; �� : Standard deviation.

(�−�)2
S2= �−1
(Eq:3) Where; S2 : Variance.

�.��
�= �±
�
(Eq: 4) Where; �: confidence interval.

t0.95 value was found to be 2.447

112 + 67.5 + 0.3 + 0.3 + 12.8 + 1.9 + 5.0

μ= = 28.54285
7
��
(112 − 28.54285)2 + (67.5 − 28.54285)2 + 2 × (0.3 − 28.54285)2 + (12.8 − 28.54285)2 + (1.9 − 28.54285)2 + (5 − 28.54285)2
=
7−1
�� =43.95055

S2= (�� )2=1931.67787

2.447×43.95085
� = 28.54285 ±
7
= 28.54285±40.649

Graph 1.3: Distribution curve.

DISCUSSION

At the experiment's start, a 200g sample was provided, and after completion, the
cumulative weight retained totalled 199.8g, indicating a 0.2g loss. The loss was
suspected to have occurred during sieve shaking and separation, as the screens were
stuck. After removing the Tyler screens from the vibrator and weighing them, the
following masses were recorded: 112g, 67.5g, 0.3g, 0.3g, 12.8g, 1.9g, and 5g on the
pan. Analysis revealed that the masses did not follow a specific order (ascending or
descending), despite the screens being organized in descending order by size (from
425 microns to 106 microns). For Graph 1.1: Cuml. wt.% passing & Retained Vs log
of Screen Size, we were asked to identify the screen size corresponding to 80%
cumulative weight percent passing, but the highest value was only 43.942%, so we
couldn't determine the screen size for 80%. A standard deviation of 43.95055 and
variance of 1931.67787 indicate a significant spread of data points around the mean,
suggesting varied values in the dataset.
The standard deviation shows that individual data points differ from the mean by
approximately 43.95 units on average, while the variance reflects the average
squared differences from the mean, highlighting the degree of data spread.

Table 1.3: Data collection from group 5 members.

Size microns(µm) Wt. Retained (g)

425 140.5
355 53.7
300 0.1
250 0
212 0.2
106 0.1
Pan 0.3
Total mass retained 194.9

The data presented were collected by group 5. Upon comparison with group 6’s
results, we observed differences in the masses retained on all screens, despite using
identical sample masses (200g) and screen sizes.

Several factors could account for the differences in retained masses between the two
groups:

1. Screen Handling: Differences in how the screens were handled, including

shaking intensity and duration, could affect the separation process.

2. Human Error: Misreading of scales, incorrect recording of data, or

inconsistent sample handling can introduce variability.

Table 1.4: Statistical analysis of weight retained obtained by the two groups.
Statistical analysis Group 5 Group 6
Mean 27.84286 28.54285
Standard deviation 53.5374 43.99085
Sample variance 2866.253 1931.6778
Confidence level (95%) 49.51383 40.649
 �������� �� ����� 5 2866.253
F-test= =1931.6778= 1.483815
�������� �� ����� 6

The F-test value of 1.483815 suggests that the variances of the two groups are similar,
with no significant difference between them. The variance of the first group is only
about 1.483815 times larger than the variance of the second group, indicating a
relatively low ratio of variance between the two groups.

CONCLUSION
The experiment aimed to separate a mixed sample into fractions using Tyler screens
and measure the retained weights. The results showed:

 The largest mass was retained on the first screen (425 microns)
and the smallest on the third and fourth screens.
 The total retained mass was 199.8g, with 0.2g lost during the
experiment.
 Statistical analysis revealed a high standard deviation (43.95055)
and variance (1931.67787), indicating significant variability in the
data, with individual points differing from the mean by
approximately 43.95 units on average.

 This particular F-test result implies that one set of data is

somewhat more spread out than the other, with a variance ratio
close to 1.48. However, this doesn’t automatically mean the
difference in spread is statistically important.

In summary, the experiment successfully separated the sample into fractions, with
the largest mass retained on the largest screen size, and significant variability in the
data, suggesting a spread of values around the mean.
RECOMMENDATION
 Temperature control: Maintain a consistent temperature between 20-25℃ to
prevent thermal expansion or contraction of the balance and samples.
 Humidity control: keep the relative humidity (RH) between 40-60% to
minimize moisture effects on the balance and samples.
 Use appropriate safety measures: wear protective gear (gloves, safety and
glasses.) when handling samples and screens.

REFERENCES
1. A.N. Mugala, P. Chipili & J. Musonda, 2020, Engineering Lab
Manual, The Copperbelt University School of mines and Mineral
Sciences.
2. Studocu (2020/2021) Screening analysis. [online] Available at:
https://www.studocu.com/row/document/university-of-
ilorin/chemical-engineering-laboratory-i/screening-analysis/45879543
(Accessed14/06/2024).
3. Peters, M.S. and Timmerhaus, K.D., 1991. Plant Design and
Economics for Chemical Engineers, 4th ed. New York: McGraw-Hill.

APPENDIX
Calculation for % weight retained

112
For 425 microns. Wt. %=199.8 × 100 = 56.056%

67.5
355 microns. Wt. %=199.8 × 100 = 33.783%

0.3
300 microns. Wt. %=199.8 × 100 = 0.15%

0.3
250 microns. Wt. %=199.8 × 100 = 0.15%

12.8
212 microns. Wt. %=199.8 × 100 = 6.406%

1.9
106 microns. Wt. %=199.8 × 100 = 0.951%

5
Pan. Wt. %=199.8 × 100 = 2.502%
Cumulative weight percent retained.

For 425 microns. Cuml. Wt% retained= 56.056%

355 microns. Cuml.wt% retained= 56.056%+33.783%=89.839%

300 microns. Cuml. Wt% retained= 89.839%+0.15%= 89.989%

250 microns. Cuml.wt% retained= 89.989%+0.15%=90.139%

212 microns. Cuml.wt% retained= 90.139%+6.406%=96.545%

106 microns. Cuml. Wt% retained= 96.545%+0.951%= 97.496%

Pan. Cuml.wt% retained= 97.496%+2.502%=99.998%

Cumulative weight percent passing(undersize).

For 425 microns. Cuml.wt% =99.998%- 56.056%=43.942%

355 microns. Cuml.wt% = 43.942%-33.783%=10.159%

300 microns. Cuml.wt% = 10.159%-0.15%= 10.009%

250 microns. Cuml.wt% = 10.009%-0.15%=9.859%

212 microns. Cuml.wt% = 9.859%-6.406%=3.453%

106 microns. Cuml.wt% = 3.453%-0.951%= 2.502%

Pan. Cuml.wt% = 2.502%-2.502%=0%