ppt on opc

1. PRESENTATION ON BASIC QUALITY TOOLS USED IN
AGRICULTURE
Name- Rupesh Kumar Das
UID- k10741
Course- B.Tech
Branch- Mechanical
Sem- 6th
Sub- Operation planning and control

2. QUALITY management can be used as a competitive
advantage for an organization. According to ISO
9001:2008, organizations should ensure that customer
requirements are determined, to ensure their
satisfaction . Thus, organizations need to improve their
processes and for that use a set of practices, which
include various techniques and tools, including most
importantly quality tools.
Ishikawa [2] discusses the importance of implementing
quality tools, stating that 95% of quality problems can
be solved by simple tools such as the basic quality
tools.

3. Cause and effect diagram in food safety standard
To better understand the food safety standard, and
plan for food safety implementation, this utilizes a
cause and effect diagram to capture key factors
influencing food safety implementation in Thailand. The
cause and effect diagram, also known as the fishbone or
Ishikawa diagram, is an effective tool to be used as a
guideline to improve food safety standard.
Man
 Proper safety training
 Safety communication among employees
 Proper dress
 Employee health

6. Material
Based on a number of food safety-related literature, the Material
factor consists of four items, as followings
Freshness
Age of raw material
Certified document of raw material
Contract farming
Method
Based on a number of food safety-related literature, the Method
factor consists of seven items, as followings.
Utilization of first in first out approach
Document control
Package selection
Clear separation of related of non-relate zones
Clear separation of entrance and exit
No production line criss-cross

7. Management
Based on a number of food safety-related literature, the Management
factor consists of five items, as followings.
Food safety policy
Commitment to food safety development
Food safety team
Supplying in necessary resources
Consultation
Environment
Based on a number of food safety-related literature, the
Environment factor consists of five items, as followings.
Pest control Light control
Temperature control
Ventilation control
Dust control

8. Weed classification using histogram
Since in practice there are only two types of herbicides used: for broad leave weed
and narrow leave weed (grass), the objective is to develop an algorithm that can
• Recognize the presence of weeds
• Differentiate the presence of broad leaves weeds and narrow leaves weeds.
Method and Identification
show the classification images of broad and narrow weeds, which are taken in the
field. These images are processed by Histogram Maxima with threshold. The
algorithms gave 100% accuracy to detect the presence or absence of weed cover.
For areas where weeds are detected, results show over 95 percent classification
accuracy over 140 sample images with 70 samples from each class as shown in
Table I.

11. Result
A real-time weed control system is developed and tested in
the lab for selective spraying of weeds using vision
recognition system. In this paper, feature extraction based
system for weed classification and recognition is developed.
The system shows an effective and reliable classification of
images captured by a video camera. The system composes of
four main stages: image capturing, image pre-processing,
feature extractions and classification. Histogram Maxima with
Threshold is used in this paper to classify the weeds.

12. Pareto chart
Pareto chart was created by plotting the cumulative
frequency of the relative frequency of the causes in
descending order, after that the most essential
factors for the analysis are graphically apparent
and orderly format.

13.  For all nine contributing causes 80:20 rule was applied,
80% of the causes were considered and found that old
plant and machinery, improper production planning and
handling losses were vital.
Result
At the milk plant, Mohali the average milk loss from
January 2014 to March 2014 was 42679 liter per month
after implementation of quality control tools from
month April 2014 to June 2014 the average loss was
29220 liter. The average saving is 13459 liter per
month. Hence productivity increased by 31%.

14. Flow chart
Once the flow diagram has been drawn up and the nature of the flows
between the different agents clarified, the next step is to quantify these
flows, both in physical and in monetary terms. This allows the analyst to
assess the relative importance of the different segments or sub-chains
of the chain, which in turn will allow an appropriate use of time and
resources.
 Supply = Inputs from backwards agents +/- stocks
= Corresponding output of backward agents - transport
losses +/- stocks
 Utilization = Output supplied to forward agents + own consumption +
wastage and losses +/- stocks

16. Result
The commodity chain is the name given to the succession of operations and of
agents which, starting upstream with a raw material, eventually emerge
downstream, after several stages of transformation and increases in value,
with one or more final products at consumer level. A chain is thus a series of
operations (transformations) of agents and of markets, which lead to
physical flows and their counterparts in monetary value.
Conclusion
This case study started with a diagnostic of the quality management function
of the agriculture involved in the study. This diagnostic allowed identifying a
priority area to increase its quality level. It was concluded that the most
important problem the agriculture is facing is related to the production
process which must be improved to reduce the high number of
nonconforming component.

17. References
[1] ISO 9001:2008, Quality management systems.
Requirements, ISO, 2008.
[2] K. Ishikawa, Guide to Quality Control. NY: Quality
Resources, 1968.
[3] J. Tarí, and V. Sabater, “Quality tools and techniques: Are
they necessary for quality management?”. Int. J. Production
Economics, Volume 92, 2004, pp. 267 280.
[4] G. Paliska, D. Pavletic and M. Sokovic, “Quality Tools -
Systematic use in process industry”, Journal of Achievements
in Materials and Manufacturing Engineering, November 25(1),
2007, pp. 79–82.