Article
Design and Performance Test of the Coffee Bean Classifier
Ansar
1,
*, Sukmawaty
1
, Murad
1
, Surya Abdul Muttalib
1
, Riyan Hadi Putra
2
and Abdurrahim
2
Citation: Ansar; Sukmawaty; Murad;
Muttalib, S.A.; Putra, R.H.;
Abdurrahim. Design and
Performance Test of the Coffee Bean
Classifier. Processes 2021, 9, 1462.
https://doi.org/10.3390/pr9081462
Academic Editor: Arkadiusz Gola
Received: 22 June 2021
Accepted: 19 August 2021
Published: 21 August 2021
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1
Department of Agricultural Engineering, Faculty of Food Technology and Agroindustry,
University of Mataram, Mataram 82115, Indonesia; sukmawaty14@unram.ac.id (S.);
muradfatepa@unram.ac.id (M.); ancadewi@yahoo.com (S.A.M.)
2
Fresh Graduate of Department of Agricultural Engineering, Faculty of Food Technology and Agroindustry,
University of Mataram, Mataram 82115, Indonesia; riyanhadiputra@yahoo.com (R.H.P.);
abdurrahimdul96@gmail.com (A.)
* Correspondence: ansar72@unram.ac.id
Abstract:
Currently, some coffee production centers still perform classification manually, which
requires a very long time, a lot of labor, and expensive operational costs. Therefore, the purpose of
this research was to design and test the performance of a coffee bean classifier that can accelerate the
process of classifying beans. The classifier used consisted of three main parts, namely the frame, the
driving force, and sieves. The research parameters included classifier work capacity, power, specific
energy, classification distribution and effectiveness, and efficiency. The results showed that the best
operating conditions of the coffee bean classifier was a rotational speed of 91.07 rpm and a 16
◦
sieve
angle with a classifier working capacity of 38.27 kg/h: the distribution of the seeds retained in the
first sieve was 56.77%, the second sieve was 28.12%, and the third sieve was 15.11%. The efficiency of
using a classifier was found at a rotating speed of 91.07 rpm and a sieve angle of 16
◦
. This classifier
was simple in design, easy to operate, and can sort coffee beans into three classifications, namely
small, medium, and large.
Keywords: classifier; coffee beans; efficiency; specific energy; sieves
1. Introduction
Coffee is a beverage that has a distinctive taste and aroma, so it is in demand by
many people throughout the world [
1
,
2
]. Coffee contains many bioactive compounds
such as caffeine, chromogenic acid, and diterpenoid alcohol, which are beneficial to
health
[3–5].
Additionally, coffee contains macronutrients such as carbohydrates, pro-
teins, fats, and micronutrients, such as trigonelline and chromogenic acid, as a source of
natural antioxidants [6–8].
Many factors determine the quality and price of coffee [
9
,
10
], one of which is the
uniform size of the diameter of the beans [
11
,
12
]. Uniformity of size not only makes the
product more attractive to consumers but can also improve the quality of subsequent
processing [
13
,
14
]. The smallest seed size tends to burn excessively when roasting, while
the largest tends to be undercooked which can affect the taste and aroma [
15
]. Therefore,
before marketing, the coffee beans must be graded to determine the classification based on
the size of the diameter of the seeds, and the broken, moldy, or germinated seeds must be
separated [16,17].
In general, farmers, collectors, and retailers market coffee beans without classification
because their time is limited for classification [
18
,
19
]. According to Vogt [
20
], the process of
classification of coffee beans is still conducted manually in several coffee production centers,
so it requires a very long time, a lot of labor, and expensive operational costs. The use of
human labor for classification also has drawbacks, such as judgments that are subjective
and inconsistent with the object being assessed [
21
,
22
]. Coffee beans with a high degree of
diameter difference require a long classification process [
23
,
24
]. Adhikari et al. [
25
] also
explained that coffee bean classifiers on the market were generally only used for the initial
Processes 2021, 9, 1462. https://doi.org/10.3390/pr9081462 https://www.mdpi.com/journal/processes
