PMG Newsletter (Volume 03. Issue 25) (2).pdf

DESIGN+BUILD FOOD FACTORIES. ONE STOP ENGINEERING SOLUTION
TECH-KNOWLEDGE
Vol .03-Issue .25-June 2024
www.pmg.engineering
PMG
FOOD & BEVERAGE
INDUSTRY
ENGINEERING
& DESIGN
SCIENCE &
TECHNOLOGY
A
The Official PMG Engineering Newsletter

1. WHITE PAPER
2. INDUSTRY BUZZ
4. DID YOU KNOW?
3. WEEKS HIGHLIGHT
Fascinating Food Facts To Expand
Knowledge
Latest Food Industry News Updates
A Look Into The Main Events Of The Week
A. Electrical panel
B. Frozen Dessert
CONTENTS
8
9-13
2-5
6-7
PMG
2. INDUSTRY BUZZ
Latest Food Industry News Updates
3. WEEKS HIGHLIGHT
A Look Into The Main Events Of The Week
4. DID YOU KNOW?
Fascinating Food Facts To Expand
Knowledge
1. WHITE PAPER
A. Effective Workplace cleaning
B. Deep Learning in Agri-Food Systems

Effective Workplace cleaning
Introduction
READ MORE....
PMG
Cleaning at workplace is an important part. It helps
control or eliminate workplace Danger. In clean or
organise workplace employee feel happy, healthy
or does work with dedication. It has a direct effect
on employee’s work. Its leave a good impression
on Client also, visiting for meetings.
Cleaning just not only about cleanliness, but it also
includes keeping work area neat and clean, floor
free of slip and maintaining hall and removing all
the waste material. This requires paying attention
on important detail such as the layout of the
workplace, the adequacy of storage facilities and
good housekeeping which is also a basic part of
danger, incident, and fair prevention.
Purpose of workplace cleaning
Housekeeping improve productivity because all
employee or workers work in fresh mood or
stay safe or healthy and help prevent injuries
and moral or decrease the illness of workers.
It can help make a good impression on visitors,
Safety consultant for the workers’
compensation.
Every worker should play a role in clean, even if
that means keeping his or her own workplace
clean.
If the Goods place on the right place, then it will
not take too much tome to finding them. If any
item or goods is out of stock, then we can order
on time.
How we can do workplace cleaning
1. Avoid slips, trips, and falls
Report to all and clean-up spills and leaks
Keep exits clean of objects.
For help with blind sport installing mirrors or
warning.
Replace as quick as much worn, ripped and
damage flooring.
Install anti-slip floor and use mats, platform
mats
2. Dust Control and Pest Control
Vacuuming method or Use Sweeping and water
wash for cleaning
Blow-Down using compressed air for
unreachable or unsafe area.
Clean wall, ceiling machinery and other place
regularly.
Use pest control spray fog every week or month.
Don’t throw waste who produce mosquito or
other type of pest.

PMG
7. Eliminate Fire Hazards
Keep materials in the workplace which is needed
for job. Unneeded material moved in relative
storage.
Quick burning or flammable material put on
designated area away from ignition source.
Don’t go close in contaminating cloths with
flammable liquids.
Keep free passageways and fire door for
emergency.
Don’t store any item on stairwells.
If any issue is coming in electrical area, put
warning or fix them on priority.
3. Tracking materials Avoid
Work area mats should be clean which help
prevent the spread of hazardous.
Use different mop for different type of dirt, like
for cleaning oil, dust, water.
4. Material Store Properly.
Storage should not have an accumulation of
material that present hazards, fire, or pests.
Maintain manufacturing floor, maintenance area,
storage, or warehouse, or that area which create
problem with storage.
Unused equipment or material stored out of the
workers reach or avoid workplace as a storage.
5. Safety falling objects
Place all object in proper manner for avowing to
falling on employee or workers
Keep all big box or object on lower shelves and
keel all equipment away from desk or table.
Keep clean or empty the area where workers
walking regularly.
6. Use and inspect personal protective tool
Wear safety summons like safety gloves which is
protected by broken glass or other harmful
waist, safety clothe and shoes when work with
electric equipment or Glass when doing dust’s
work.
Regular inspect for clean and fix tool, remove as
soon as possible if find any damage on work area
7. Determine Frequency
All workers should take participate, at least
keeping own workplace clean.
If anyone seen anything which create any
problem, then informed
In the end of shift everyone needs to check or
remove unnecessary material from workplace.
How we can plane on Workplace
Use dustbin near Desk and throw Different waste
in different Dustbin.
Clean desk daily, check all electric equipment on
daily basis.
If working in Factory, then clean all took or
equipment after use.
Check all machine before and after use. It
reduces the incident.
Remove unused material or item instantly, it
creates more space.
Inform Immediately If notice anything wrong with
electrical equipment.

Deep Learning in Agri-Food Systems
Introduction
READ MORE....
PMG
Deep Learning (DL) is a subset of Machine
Learning, which itself is a subset of Artificial
Intelligence. Deep Learning employs a variety of
neural network (NN) architectures and algorithms
for pattern recognition and data analysis. This soft
computing technique is bringing revolutions in the
field of data science, as it can be used to analyze
huge volumes of data in all possible forms viz.
text, audio, 2D/3D image, and videos into
meaningful insights. In recent times, the agri-food
industry has also largely benefited from the
development in this field. In food processing units,
deep Learning is being implemented in machine
vision systems for inspecting inline processes,
quality of raw materials, and finished goods.
At the farm level, deep learning technology has
been successfully applied in autonomous robotic
systems tasked with picking agro-commodities
with desired characteristics. Deep learning is also
being used to monitor vegetation using low-
altitude aerial systems coupled with a wide variety
of sensors for data collection. This technique is
favorable over other AI tools as it is versatile with
the type of input data and its performance is
directly proportional to the amount of data fed.
The nature of data sourced from agro, and
biological systems is complex as it can vary from
continuous spectral information to spatial RGB
images or a combination of both.
The artificial neural network (ANN) architecture is the
simplest model for DL. It is a computational system
composed of the systematic interconnection of many
simple processing neurons operating in parallel whose
function is determined by network structure, connection
strengths, and the processing performed at the neurons
[1]. They are designed to mimic the human brain’s
nervous system, to compute sophisticated computations
for a specific task. The ANN architecture comprises
several layers – an input layer where the data are
provided, hidden layers where classification tasks are
done, and the output layer predict the output. For an ANN
to predict future data, it must be trained first, further
which it becomes able to predict similar patterns. The
basic information processing unit of an ANN is the
neuron.
PROTEIN FUNCTIONALIZATION
PROTEIN FUNCTIONALIZATION
Artificial Neural Network
Convolutional Neural Network
CNN is a specialized type of NN designed to be applied in
computer vision tasks like image classification and object
detection. Convolutional layers are the fundamental
building blocks of CNNs. This layer performs an operation
called a ‘convolution’. A convolution is a linear operation
that involves the multiplication of a set of weights with
the input.

PMG
Several researchers have implemented these
algorithms to solve crucial problems in the food
industry such as defects classification, shelf-life
prediction, dietary assessment, food
grading/sorting, inspection, etc. The process of
development and the forms of models that would
yield from DL implementation in the agri-food
system is not significantly different from those for
other systems. However, the information and
knowledge fed to the system as input data will help
to characterize the individual systems and their
features. Raw materials like fruits and vegetables
often have a non-visible defect in their surface, but
due to improper storage conditions, may get
affected by internal pest infestation and
pathological disorders. For instance, plantains with
preexisting internal damage conditions when stored
at optimum conditions (2% O2 and 5 – 10% CO2 at
10°C, 90% RH) will bypass a trained and experienced
eye. This, however, won’t be an issue if there were a
machine vision system in place.
Cleaning processing equipment requires a lot of
time and resources, including water. To address this
problem, research engineers at the University of
Nottingham have developed a system that uses DL
to reduce cleaning time and resources by 20 – 40%.
The system, which they call Self-Optimizing CIP,
uses ultrasonic sensing and optical fluorescence
imaging to measure food residue and microbial
debris in a piece of equipment and then optimize
the cleaning process [9].
Deep Learning in Cleaning
processing equipment
Application in the Agri-Food
Systems
Deep Learning in Quality Control
Quality control is a costly process, but a critical step
in the food industry. Traditional techniques are
time-consuming and hence machine vision systems
are being installed for better performance. In recent
times, several industries, as well as academic units,
have investigated the performance of models
suitable for specialized tasks. Similarly, Vasumathi
et al. [6] employed a 98.17% accurate DL technique
to sort pomegranate fruits into normal and
abnormal based on the color, number of fruit spots,
and shape of it.
Challenges in implementation
As opposed to the popular belief from science
fiction literature, achieving general artificial
intelligence is still a long journey. Till then, it is
important to develop specialized models for
completing specialized tasks. Even though a fully
functional model does not require any special
assistance while in operation, the initial setup cost
is significantly high. In terms of the complexity of
the overall deep learning-enabled system in the
industry, model selection is the most important step
in this process.

By developing its sugar-reduction technology, Better
Juice, Ltd. hopes to provide guilt-free enjoyment in ice
creams and sorbets to health-conscious consumers. With
this invention, fruit sorbets' sugar level can be reduced
by up to 70%, resulting in healthier goods. These sorbets
will be on display by Better Juice from July 15–17 at the
IFT Expo in Chicago.
Sorbets usually have a high sugar level because they
include about 50% pureed fruit and additional sugar. Even
sugar-free products include 6% to 10% sugar from fruit
concentrates. With the help of non-GMO microbes, Better
Juice's technology preserves vitamins and nutrients by
converting fruit concentrate sugars into prebiotic
oligosaccharides and non-digestible fibres.
The brand now offers sorbets with up to 70% less sugar
and 40% less calories. Flavours include apple, orange, and
strawberry.
FOOD INDUSTRY
INDUSTRY BUZZ
Better Juice Decreases Sugar
Levels in Sorbets
Frozen Foods Transform Mealtime
for Parents
Working parents find it difficult to juggle their demanding
occupations and their families' requirements in today's
hurried world. Making wholesome meals in the midst of
deadlines and meetings can be stressful. Foods that are
frozen give quick and simple dinner options, which is a
practical answer. Fathers frequently utilise frozen snacks
more than women do, according to Godrej Yummiez's
"STTEM - Safety, Technology, Taste, Ease & Mood Uplifter"
survey, which found that 83% of moms thought that their
kids would find them convenient.
By reducing the amount of time spent peeling, slicing, and
cooking, frozen meals free up parents' time to spend more
time with their families.
Compared to fresh vegetables, they maintain their
nutritional worth better, keeping vitamins and minerals
intact. Picky eaters and those with different dietary
requirements are catered to by the assortment of frozen
options, which range from veggies to whole meals.
PMG

The Organic World Launches 'Back
to School' Campaign with Natural,
Preservative-Free Foods
Global Supply Disruption Drives
Edible Oil Price Surge
World Food Safety Day Promotes Safe
Global Health Practices
With items designed to meet children's everyday
requirements, The Organic World launched the "Back to
School" programme, which aims to encourage parents to
make sustainable decisions and improve the educational
experience. A healthful peanut butter, naturally flavoured
tofu, muesli, chemical-free eggs, and pancake mixes
without preservatives are all part of the program's
nutrient-dense Breakfast Range. It also includes
traditional Indian snacks from WellBe, such as murukku,
khara sev, and kodbale. These are prepared with healthy
components like flaxseeds and red rice flour instead of
chemicals like maida and refined oil. Every product
complies with the stringent "Not In Our Aisle List" of The
Organic World, which omits more than 25 dangerous
chemicals and preservatives.
Over 40% of all purchases in the school supplies market,
which is estimated to be worth over Rs 60,000 crore, are
related to education.
Due to worldwide factors that cause price swings among different
oils, the edible oil market has recently seen major price hikes. Over
the last three months, the price of 10-kg quantities of cottonseed oil
has increased from Rs 930 to Rs 975, soybean oil from Rs 910 to Rs
970, rice bran oil from Rs 890 to Rs 950, sunflower oil from Rs 900 to
Rs 980, and mustard oil from Rs 1060 to Rs 1190.
The limited supply of sunflower oil from Russia and Ukraine as a
result of off-season conditions and weather effects is a significant
reason for these rises. Because Ukraine is a major producer, the
conflict between Russia and Ukraine has also affected the world's
supply of sunflower oil. Furthermore, disruptions in the supply of
soybean oil due to floods in Brazil and worker strikes in Argentina
have decreased exports and crushing. Geopolitical conflicts, such as
the conflict between Israel and Palestine, have further disrupted
supply chains, leading to problems with availability and price
increases.
PMG
From farm to fork, food safety is a crucial public health issue that involves
handling, preparing, and storing food correctly to avoid foodborne
infections. Particularly vulnerable populations include young people, the
elderly, and people with compromised immune systems. Strict food safety
procedures must be put in place at every stage of the supply chain, from
manufacture to consumption.
With India's fast urbanisation and rising packaged food consumption, it is
critical to guarantee the safety of food packaging. The Food Safety and
Regulations Authority of India (FSSAI) has established food-grade
regulations for packaging materials, particularly for components like
packaging inks. These inks, which are made up of pigments, solvents, and
additives, are necessary, but they may cause food contamination by
transferring dangerous substances, including toluene, mineral oil, and
benzophenone. Regulations highlighting the gravity of these health dangers
include the Bureau of Indian Standards (BIS) 2021 prohibition on toluene in
food packaging inks.
T
HE UNION MINISTER FOR FARMERS' WELFARE AND AGRICULTURE ASSESSES KHARIF SEASON READINESS.

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21 JUNE
Sipping fruity joy, celebrating health in a glass.
Happy Smoothie Day!
SMOOTHIE DAY
24 JUNE
World Pralines Day with a delightful blend of
chocolate, nuts, and pure happiness!
FPRALINES DAY

DID YOU KNOW?
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Extraction tanks are pivotal in plant protein processing, facilitating the extraction of proteins
from raw materials. These tanks employ various methods such as solvent extraction or aqueous
extraction to separate proteins from plant matrices.

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Vol .01 Newsletter
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In plant protein processing, drying equipment is indispensable for enhancing stability and
shelf life. Employing techniques such as spray drying, freeze drying, or fluidized bed drying,
these machines efficiently remove moisture from protein solutions or suspensions.

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Vol .01 Newsletter
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Washing equipment for plant proteins is essential in protein processing, ensuring purity and
quality. These machines utilize water or solvent-based solutions to remove impurities and
undesirable components from protein-rich materials. Advanced designs optimize washing
efficiency while minimizing protein loss. Precise controls maintain ideal washing parameters,
resulting in high-quality protein extracts suitable for various food applications.

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Vol .01 Newsletter
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Complete plants for the production of special baked goods encompass a comprehensive array
of machinery and systems tailored for every stage of the production process. From ingredient
handling to mixing, shaping, baking, and packaging, these plants integrate advanced
technologies and precise controls to ensure consistent quality and efficiency.

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Individual machines for the production and processing of baked goods are tailored for
specific tasks in the production line. These machines include dough mixers, dividers,
rounders, proofers, ovens, and packaging machines. Advanced designs and precise controls
optimize each machine's performance to ensure consistency and quality throughout the
baking process.

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PMG Newsletter (Volume 03. Issue 25) (2).pdf

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PMG Newsletter (Volume 03. Issue 25) (2).pdf