jeyaram1.final report projectdocx

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A STUDY ON THE OPERATION OPTIMIZATION OF PRODUCTION AT LOTTE INDIA
CORPORATION LIMITED
By
JEYARAM R
310614631032
A PROJECT REPORT
Submitted to the
FACULTY OF MANAGEMENT SCIENCE
In partial fulfillment of the requirements
for the award of the degree of
MASTER
OF
BUSINESS ADMINISTRATION
IN
OPERATION
ANNA UNIVERSITY
CHENNAI 600 025
JUNE, 2016

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EASWARI ENGINEERING COLLEGE
Ramapuram, Chennai
Department of Management Studies
BONAFIDE CERTIFICATE
This is to certify that the Project report titled “A STUDY OF OPERATION OPTIMIZATION
OF PRODUCTION” is the bonafide work of Mr.JEYARAM R, 310614631032 who carried
out the work under my supervision. Certified further that to the best of my knowledge
the work reported herein does not form part of any other project report or dissertation
on the basis of which a degree or award was conferred on an earlier occasion on this or
any other candidate.
Supervisor Head of the Department
Submitted to Project Viva Voce held on ________________
Internal Examiner External Examiner

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June 03, 2016
To whom it may concern
This is to certify that Mr. Jeyaram R (310614631032) who is a student of
master of business administration at Easwari Engineering College, has done
his internship at our organization from march 2016 to may 2016. As an
intern, he did work on “A study on operation optimization of production
“. The work submitted by Jeyaram was commendable his attitude and
conduct during his internship was good
For lotte india corporation limited

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DECLARATION
I hereby declare that the project entitled “A STUDY ON OPERATION
OPTIMIZATION OF PRODUCTION” submitted for the M.B.A. Degree is my
original work and the project has not formed the basis for the award of any degree,
associate ship, fellowship or any other similar titles.
Place: Chennai
Date:
JEYARAM R

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ABSTRACT
This project helps to analyze the problems that are occurred in operation optimisation of
production at the Lotte India Corporation limited. The title is “A study on problem in
operation optimisation of production in Lotte India corporation limited” and the
analysis is done on the basis of data received through Questionnaires.
This research was conducted with an aim to reduce the risk barriers and to consume the
time for increasing the production. The information gathered through this research can
be used by the company to place the right person for the right job as well as to satisfy
the employee beneficial. This can increase the goodwill of the employees.
A questionnaire is used as the instrument to collect the primary data. The tools that are
used in this project are Percentage analysis, Chi-Square test, One way Anova, mann
whitney test and Kruskal wallis test. The sample size decided from the study of 50
respondents by simple random sampling. Based on the findings from the study, suitable
suggestions have been given to the company to provide an excellent services and this will
improve the production level.

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ACKNOWLEDGEMENT
In the first instance, I oblige to the CHAIRMAN, DR.R.SHIVAKUMAR for providing
an excellent environment and infrastructure at Easwari Engineering College,
Ramapuram, for successfully completing the Project.
I thank our PRINCIPAL Incharge and Dean Dr.K.KATHIRAVAN for providing all
the required facilities, support and encouragement for the completion of project.
I take the privilege to extend my hearty thanks to our beloved HEAD OF
DEPARTMENT, Dr.R.Vasudevan, for permitting me to do this project work & support
given in carrying out this project successfully during the course of the project.
I would like to thank Mr. MILAN WAHI, MANAGING DIRECTOR, LOTTE INDIA
CORPORATION LIMITED for helping me to carry out the project in this Organization,
and whose active interest in the project and insight helped me to formulate my approach
towards the project.
I thank my Internal Guide, , DR.J.RAMYA, Assistant Professor, MBA Department for
his contributions to this project and in providing me with valuable points in completing
this project. I am deeply indebted to him for his encouragement, motivation, valuable
suggestions, unstinted support, co-operation and sustained guidance.
I also thank the other faculty members for providing me their kind co-operation and
valuable help in completing the project work.
R.JEYARAM

VII
CHAPTER CONTENTS
Chapter
No
Title Page No
LIST OF TABLE Viii
LIST OF CHARTS Ix
1 INTRODUCTION AND DESIGN OF THE STUDY 1
1.1 Introduction of the study 1
1.2 Problem statement 2
1.3 Need and Scope of the study 3
1.4 Objective of the study 3
1.5 Research Methodology 3
1.6 Chapterisation 6
1.7 Limitation of the Study 6
2 REVIEW OF THE LITERATURE 8
2.1 Conceptual Review 8
2.2 Research Review 9
3 PROFILE 14
3.1 Industry Profile 14
3.2 Company Profile 18
4 DATA ANALYSIS AND INTERPRETATION 23
4.1 Percentage Analysis 23
4.2 Statistical Analysis 43
5 RESULT AND DISCUSSION 48
5.1 Summary of the findings 48
5.2 Suggestion 48
5.3 Conclusion 49
APPENDIX 50
Questionnaire 50
Reference 52

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LIST OF TABLE
Table No Title Page
No
1.5.1 Research Background 4
3.2.1 Board of Directors 19
4.1.1 Based on age 23
4.1.2 Based on education 24
4.1.3 Based on departmets 25
4.1.4 Based on tenure 26
4.1.5 Relevant training 27
4.1.6 Based on safety 28
4.1.7 Shift timing 29
4.1.8 Based on work condition 30
4.1.9 Based on equipment provided 31
4.1.10 Process information 32
4.1.11 Relationship 33
4.1.12 Proper document 34
4.1.13 Over processing 35
4.1.14 High level of satisfication 36
4.1.15 Full automation 37
4.1.16 Weight 38
4.1.17 Over production 39
4.1.18 Quality 40
4.1.19 Level of opportunities 41
4.1.20 Overall statistics 42

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LIST OF CHARTS
4.1.1 Based on age 23
4.1.2 Based on education 24
4.1.3 Based on departmets 25
4.1.4 Based on tenure 26
4.1.5 Relevant training 27
4.1.6 Based on safety 28
4.1.7 Shift timing 29
4.1.8 Based on work condition 30
4.1.9 Based on equipment provided 31
4.1.10 Process information 32
4.1.11 Relationship 33
4.1.12 Proper document 34
4.1.13 Over processing 35
4.1.14 High level of satisfication 36
4.1.15 Full automation 37
4.1.16 Weight 38
4.1.17 Over production 39
4.1.18 Quality 40
4.1.19 Level of opportunities 41
4.1.20 Overall statistics 42

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CHAPTER 1
INTRODUCTION AND DESIGN OF THE STUDY
1.1 INTRODUCTION:
LOTTE contributes to enriching life by providing products and services that are loved and
trusted. Since LOTTE officially entered the food industry by founding LOTTE Confectionery
in 1967, it has become a leader in the Korean tourism and retail industries by establishing some
of Korea’s top hotels and department stores. LOTTE has since extended its reach into such key
industries as petrochemicals and construction. LOTTE is positioning itself as one of Korea’s
key conglomerates based on a wealth of diverse experiences and know-how. Furthermore, it is
now growing as a global conglomerate trusted by customers all over the world, making constant
efforts focused on the vision of becoming one of Asia’s TOP 10 Global Groups by 2018.
LOTTE will continue to make customers’ lives richer with its strict quality control and
differentiated services.
A brand that provides happiness to customers all over the world and builds trust with
excellent products and services – this is what LOTTE aims to be. For over 40 years since its
founding, LOTTE has successfully led a variety of business sectors and persistently developed
differentiated capabilities. As part of its plans for the future, in 2009 LOTTE proclaimed
“Vision 2018,” through which LOTTE aims to solidify its status as a global presence by
establishing more developmental strategies. Even at this moment, LOTTE is making efforts to
develop yet more excellent products and services reflecting the economic conditions and
lifestyles of countries into which it has expanded, enhancing competitiveness in the global
market. LOTTE will continue to expand in Asia, offering its superior benefits to customers
there and worldwide.
LOTTE is a valued name, beloved by customers worldwide. We improve the quality of
life of our customers with premium products and differentiated services, enhancing corporate
brand value through our many social contributions. We would like to thank all of you who have
continued to care about us and express interest in LOTTE’s efforts.

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Process optimization is the discipline of adjusting a process so as to optimize some
specified set of parameters without violating some constraint. The most common goals are
minimizing cost and maximizing throughput and/or efficiency. This is one of the
major quantitative tools in industrial decision making.
When optimizing a process, the goal is to maximize one or more of the process
specifications, while keeping all others within their constraints. This can be done by using a
process tool, discovering the critical activities and bottlenecks, and acting only on them.
The best possible performance is “Optimal Operations”. In the process industry it is called
“Process Optimization. All the part of the classical field of Industrial Engineering in production
/ manufacturing, now with refined awareness, approaches and tools. The IE discipline
maintains its focus on overall corporate goals; more “systems approach” than focusing on
indicators of success such as: zero downtime, zero defects, lowest unit cost, zero inventory,
minimize Non Value Added time, etc.
In particular, this essay focuses on the management of industrial, repetitive or continuous,
bulk or discrete, high volume production operations. In most production operations it is
possible to define objectives quantitatively very well, which leads to the possibility of (true,
quantitative) optimization solutions. Fortunately, the problem is so generic that there are
various commercial software of wide applicability to aid or automate operating decisions to
optimize performance: the ultimate Lean Operations. The practice is more frequent in large
continuous processes such as paper mills, power generation, chemical processes; but it has been
applied very profitably to discrete manufacturing in the last decade as well, mostly for
optimization studies rather than on-line.
.
1.2 PROBLEM STATEMENT
 The problem statement here is how the overproduction affects the organization and how
waste could be reduced.
1.3 NEED AND SCOPE OF THE STUDY
1.3.1 NEED OF THE STUDY
 To increase the production and reduced the lead time.
 To reduce the waste incurred in the production process

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 To improve the quality standards in the organization
1.3.2 SCOPE OF THE STUDY
 Optimization of the production process
 Waste management
 Time management
1.4 OBJECTIVES OF THE STUDY
PRIMARY
To study the problems occurred in operation optimization of production at Lotte India
Corporation Limited.
SECONDARY
 To maintain the standard sequential order in production process
 To meet customer demand on time
 time reduction by replenishment of raw material
 Implementation of fully automated machine resulting in reduction of waste
1.5 RESEARCH METHODOLOGY:
1.5.1 RESEARCH DESIGN
Research is the careful study of investigation in order to discover new fact of information
Research methodology is a way to systematically solve the research problem. It may be
understood as a science of studying how research is done scientifically. A way to systematically
solve the research problem along with the logic behind, defines research methodology. It
explains why a research study has been undertaken, how the problem has been defined, in what
way and why the hypothesis has been formulated, what data have been collected and what
particular method has been adopted, why particular technique of analysing data has been used
and a host of similar other questions are usually answered concerning a research problem or
study. The preparation of the report included extensive study of the organization and market
research, which was the primary source of the report. I have collected information from bar
owners by preparing questionnaire.

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REASEARCH BACKGROUND
Research Design Descriptive
Research Approach Survey Method
Sampling Design Non Probability Sampling
Sampling Technique Convenience Sampling
Sampling Area Chennai
Sampling Unit Nemam
Sampling Size 50
Research Instrument Questionnaire
TABLE 1.5.1: REASEARCH BACKGROUND
1.5.2 SAMPLING DESIGN
The sampling method followed by the investigator is the simple random sampling. Each unit
of the population has equal chances of entering the event.
The sampling design is used to provide information regarding the research study like
 Population
 Target Respondents
 Sample Size
 Sampling Technique
1.5.2.1 POPULATION
The population under the study is the respondents i.e. the employees of LOTTE INDIA
CORPORATION LIMITED.
1.5.2.2 TARGET RESPONDENTS
The target respondents of the study are selected based on the sampling method.
1.5.2.3 SAMPLING METHOD AND TYPE
Sampling is a process of selecting some of the elements in a population to draw conclusions
about the entire population. The technique that we use for our research study is Convenience
sampling.

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1.5.2.4 SAMPLE SIZE
The sample size selected for the study is 50.
1.5.3 DATA DESIGN
The nature of data used may be primary or secondary. Primary data is the first hand collection
of information. Secondary data is making use of published or from published sources.
1.5.3.1 DATA SOURCE:
Primary Data:
Primary data are general information gathered by the researcher for the purpose of the project
immediately at hand. When the data are collected for the first time, ordinarily experiment and
surveys constitute the principal sources of primary data for the purpose of the study.
Secondary Data:
The secondary data are those which have already been collected by someone else and
which have already collected through the journals, magazines and websites.
1.5.4 QUESTIONNAIRE DESIGN
1.5.4.1 TYPES OF QUESTIONNAIRE
 Closed end questionnaire
1.5.4.2 SCALES USED FOR QUESTIONNAIRE DEVELOPMENT
 Nominal scale
 Interval scale
1.5.4.3 VARIABLES USED TO CONSTRUCT THE QUESTIONNAIRE
 Independent variables
 Dependent variables

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1.5.5 TOOLS USED FOR ANALYSIS
 One way anova analysis
 Kruskal wallis
 Mann whitney
 Chi-square
1.6 CHAPTERISATION
Chapter 1
This chapter deals with the introduction to the study, problem statement, need and scope of the
study, objectives of the study, research methodology and limitations of the study.
Chapter 2
This chapter deals with the literature review for the research study and development.
Chapter 3
This chapter provides an outline about the industry profile and the company profile involved
in the research study
Chapter 4
This chapter deals in data analysis of the obtained responses and secondary data with various
available tools namely descriptive and inferential tools.
Chapter 5
This chapter lists out the findings of the research study, suggestions and conclusions for the
study.
1.7 LIMITATIONS OF THE STUDY
 Study is based on the primary data
 Due to the lack of time, it was not possible for the researcher to
Approach all the people.
 The respondents were asked to indicate their true responses to the

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questions being asked, but rather than giving the response, they might have been
in a form of expert comments which might have based the result of the study.
 Many respondents were reluctant to respond to the questionnaire

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CHAPTER 2
REVIEW OF LITERATURE
2.1 CONCEPTUAL REVIEW
'Operations management' is an area of management concerned with designing and controlling
the process of production and redesigning business operations in the production
of goods or services. It involves the responsibility of ensuring that business operations
are efficient in terms of using as few resources as needed and effective in terms of meeting
customer requirements. It is concerned with managing the process that converts inputs (in the
forms of raw materials, labour, and energy) into outputs (in the form of goods and/or
services).[1]
The relationship of operations management to senior management in commercial
contexts can be compared to the relationship of line officers to highest-level senior officers
in military science. The highest-level officers shape the strategy and revise it over time, while
the line officers make tactical decisions in support of carrying out the strategy. In business as
in military affairs, the boundaries between levels are not always distinct; tactical information
dynamically informs strategy, and individual people often move between roles over time.
According to the United States Department of Education, operations management is the field
concerned with managing and directing the physical and/or technical functions of
a firm or organization, particularly those relating to development, production, and
manufacturing. Operations management programs typically include instruction in principles of
general management, manufacturing and production systems, factory management,
equipment maintenance management, production control, industrial labor relations and skilled
trades supervision, strategic manufacturing policy, systems analysis, productivity analysis
and cost control, and materials planning.[2][3]
Management, including operations management,
is like engineering in that it blends art with applied science. People skills, creativity, rational
analysis, and knowledge of technology are all required for success.
Production optimization is the practice of making changes or adjustments to a product to
make it is more desirable. Multivariate optimization is one of the most common methods for
product optimization. In this method, multiple product attributes are specified and then tested
with consumers.
Due to complex interaction effects between different attributes (for example, consumers
frequently associate certain flavors with packaging colors), it is problematic to use

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mathematical methods, such as Conjoint Analysis, typically used in industrial process
optimization.
More recently companies started to adopt Evolutionary Optimization techniques for Product
optimization. Evolutionary algorithms (such as IDDEA) are used to optimize products,
concepts and messaging.
The establishment of a new type of ingredient production operation (IPO) model with fuzzy
parameters by chance-constrained method in this article. Due to the problem of the designed
ingredient production operation, which contains some fuzzy variable parameters defined by
possibility distributions with infinite supports, generally, it is often infinite dimensional
optimal problem that can not be processed directly through traditional programming
algorithms. In order to solve above problem, the approximation of the credibility functions is
studied in the ingredient production planning fuzzy chance-constrained model. And for solving
this fuzzy IPO problem efficiently, the approximation approach (AA), neural network (NN)
and genetic algorithm (GA) are contained to design an optimization method. In the end, the
paper give a practical example to show the practicability of the proposed modelling ideals and
solution method.
2.2 RESEARCH REVIEW:
TITLE: High fructose corn syrup manufacturing process
AUTHOR: john’s .white
Key point: This chapter will make the case that HFCS are so similar in manufacturing,
composition, caloric value, sweetness, and functionality as to make them interchangeable in
many food formulations; and their consumption patterns and composition in the blood
following digestion are also strikingly similar.
ABSTRACT: HFCS are an important component of the modern diet, contributed not only by
amounts naturally occurring in many fruits, vegetables, and nuts but also by sweeteners added
to processed foods and beverages. Because these sweeteners contribute metabolizable energy

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to the diet, they are called “caloric” or “nutritive” sweeteners. The most important of these are
sucrose and high fructose corn syrup (HFCS). Honey, fruit juice concentrates, and agave nectar
are popular sweeteners fitting this description, but comprise only a small fraction of the total.
Pure crystalline fructose will be included as a comparator; however, it should be understood
that as a stand-alone ingredient, fructose is a specialty sweetener with unique functionality, but
is also used in comparatively minor amounts.
TITLE: statistical process control in uk production
AUTHOR: Nigel P. Grigg (Glasgow Caledonian University, Glasgow, UK)
acknowledgement: This paper was subsequently published in British Food Journal
keywords: Food, Manufacturing, Statistical process control, United Kingdom
ABSTRACT : Statistical process control (SPC) is a common feature of quality control in most
high volume manufacturing processes. In the food industry, while there is no explicit
compulsion for organisations to make use of SPC techniques, their usage can accrue the same
benefits as in other industry sectors. Discusses the potential for application of SPC within the
industry, and presents the results of a nationwide survey of 200 food processing companies,
indicating relatively low levels of SPC usage.
TITLE: Soy solids in dairy product
Vaidehi and Shivaleela (1989) reported that addition of soy flour up to 15 per cent
level in gulabjamun mix did not had any negative effect on the its sensory characteristics.
Further, soyflour incorporation resulted in increase in the volume of the product and
yield. Deka and Rajor (1988) developed acceptable dahi like product using soy and
buttermilk solids in the ratio of 1:1.5Babje et al., (1992) examined the possibility of blending
soymilk with buffalo
milk and reported that incorporation of soymilk at 20 per cent level in buffalo milk had
no adverse effect on the taste, colour and springiness of paneer.
TITLE: Preparation of low fat butter spread
Reddy et al., (2000) standardized the process for the manufacture of protein
enriched low fat butter spread containing chhana. The standardized method consisted of
kneading of chhana to a fine paste followed by addition of butter and incorporation of 2

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per cent salt, blending for 30 min. Chhana was added at 30, 40 or 50 per cent levels to
butter in the preparation of spreads. Incorporation of chhana in butter had increased the
moisture, protein and improved the spreadability, whereas, the fat content, hardness and
flavour scores decreased. Based on the various physico-chemical and sensory attributes,
use of 40 per cent chhana was found to be best suited for the preparation of butter spread.
TITLE: Effect of concentration of coagulant on the quality of paneer
The optimum strength of coagulant required for the production of best quality of
paneer is 1% citric acid solution (Bhattacharya et al., 1971; Singh and Kanawjia, 1988).
Two per cent citric acid solution also yielded a product of good quality when prepared
from cow milk (Vishweshwaraiah and Ananthakrishnan, 1985). Shelke et al., (2002) used
citric acid solution of 1.5% during the production of chhana for rasogolla preparation.
TITLE: Effect of heat treatment of milk
Heat treatment is one of the technological requirements of the process, which
affects the sensory and microbiological quality of paneer (Ghodekar, 1989). Bhattacharya
et al., (1971) recommended heating of milk to 82°C for 5 min and cooling to 70°C before
coagulation, whereas, Rao et al., (1984) suggested a temperature of 85°C. In order to
maximize the total solids recovery, it is desirable to heat the buffalo milk to 90°C without
holding (Sachdeva and Singh, 1988a). Menu Gupta (1985) claimed extension of shelf-life
of paneer when milk was heated to 80°C and held for 10 min followed by coagulation at
70°C. Lo and Bastian (1998) reported that more whey proteins (denatured) were
recovered in cheese manufactured from milk heated to 85°C than in cheeses
manufactured from milk heated to 72°C. They found that maximum denaturation and
hydration of whey proteins occurred in milk heated above 80°C
TITLE: Utilization of whey protein/WPC in dairy products.
The dairy industry has potential in the utilization of WPC in development of
various dairy products. WPC has been successfully used in dairy spreads. An acceptable
quality of processed cheese food was prepared by replacing 20 per cent of cheese solids
with WPC (Thapa and Gupta, 1992; Irvine et al, 1984). Improvement in the sensory score
has been observed for cheese added with WPC at the rate of 10g/l to milk (Santoro, 1994)
Yoghurt has been prepared by replacing 50 per cent of skim milk solids with
WPC (35 per cent protein) and the resultant product had better flavour, body and texture

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with minimum whey separation compared to control(Jayaprakasha, 2000). Kulfi prepared
by replacing skim milk solids to an extent of 80% with WPC resulted in the product with
higher overrun, better mouth feel and improved acceptability than control kulfi
(Jayaprakasha and Brueckner, 1999)
TITLE: Filled paneer
Chawla (1981) reported that the blends of skim milk and vegetable oils were
Homogenized during the production of filled paneer. The resultant product was hard and
brittle compared to paneer prepared from unhomogenised blends. Hence, they concluded
that homogenization of filled milk for paneer preparation was not suitable.
Roy and Singh, (1999) observed beany flavour in paneer made from filled milk
using soy oil even after frying and cooking, hence the product was unacceptable. They
reported that this might be attributed to the flavour reversion phenomenon of soy oil. It
Has a strong tendency to revert when exposed to air or high temperature. Soy oil develops
Objectionable flavour through oxidation. Mild flavour reversion produces a slight beany
Flavour, which in more advanced stage, may become ‘painty’ or ‘fishy’.
The use of buffalo milk with high fat levels obviously escalates the price of
Paneer. Several attempts have been made to minimize the cost of production of paneer
Such as reduction in fat content of milk, use of milk by-products and inexpensive
Vegetable solids (Chawala et al., 1987; Dharam pal and Garg, 1989 and Kanawajia et al.
TITLE:Effect of thermization on the microbial quality of cheese
Hirvi and G riffiths (1998) stated that catalase activity was present in cheese made
from raw milk but was only present at low concentrations in cheese manufactured from
thermized milk. However, high catalase activity was observed in commercial samples of
sharp and extra sharp cheddar cheese that was apparently due to the growth of catalase
producing yeasts in cheese during maturation. Treatments at temperatures from 60° to
63°C gave at least a 4-log reduction of Salmonella sp. and a 2-log reduction of L.
monocytogenes in milk (D’Aoust, 1989 and Farber et al, 1988). In addition, pathogens
such as Salmonella spp and L.monocytogenes did not grow in hard cheeses (Johnson et
al., 1990).
TITLE: Thawing/ tempering

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Tempering of butter, frozen foods have been the most successful application of
Microwave in the dairy industry (George, 1997). Thawing of frozen products has limited
Applicability in the dairy industry. However, melting of various products like fats from
Bulk containers, offers advantages of more efficient transport (Young and Jolly, 1990).
CHAPTER 3

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3.1 INDUSTRY PROFILE:
Overview of global confectionary industry
Confectionary, sweetmeats that have sugar as a principal ingredient, combined with colorin
g matterand flavoring and often with fruit or nuts. In the United States it is usually called can
dy, in Great Britain, sweets or boiledsweets. Nonchocolate candy is roughly divided into two
classes, hard and soft; the distinction is based on the fact thatsugar when boiled passes throug
h definite stages during the process of crystallization. Fondant, or sugar cooked to the softstag
e, is the basis of most fancy candies, such as chocolate creams.
Sweetmeats, long known in the Middle East and Asia and to the ancient Egyptians, were at fir
st preserved or candied fruits,probably made with honey. One of the earliest functions of cand
y was to disguise unpleasant medicine, and prior to the 14thcent. Confections were sold chiefl
y by physicians. Medieval physicians often used for this purpose sugarplate, a sweetmeatmad
e of gum dragon, white sugar, and rosewater, beaten into a paste. One of the earliest confectio
ns still surviving ismarzipan, known throughout Europe; it is made of almonds or other nuts,
pounded to a paste and blended with sugar andwhite of egg. In the middle Ages it was someti
mes molded into fancy shapes and stamped with epigrams.
Sugarplums, made of boiled sugar, were known in England in the 17th cent., but it was not un
til the 19th cent. Thatcandymaking became extensive. The display of British boiled sweets at
the national exhibition of 1851 stimulatedmanufacture in other countries, especially in France
. In the United States in the middle of the 19th cent. About 380 smallfactories were making lo
zenges, jujube paste, and stick candy, but most fine candy was imported. With the developme
nt ofmodern machinery and increasing abundance of sugar, confectionery making became an
industrya food product generally containing a large amount of sugar, having a high caloric co
ntent and pleasant taste and smell, andeasily assimilated by the body. Ingredients include sug
ar, syrup, honey, fruits and berries, wheat flour (sometimes oat, soy,corn, or rye flour), milk a
nd butter, fats, starch, cocoa, nuts, eggs, acids, and gelatinizing agents and flavorings which a
reprocessed by heat and various mechanical means. The high nutritive value of confectionerie
s is due to the considerablecarbohydrate, fat, and protein content (see Table 1). Many confecti
ons are enriched with vitamins.
On the basis of ingredients, methods of production, and final product, confectioneries fall into
two main groups: (1) sugarconfectionery, including caramels, candies, chocolates, and cocoa
, fruitmarmalade sweets, halvah and other Orientalsweets, toffee, and dragée and (2) flour co

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nfectionery, including cookies, crackers, galettes, shortbread, wafers, cakes,pastries, and keks
(a kind of cake without icing).
Confectioneries preserve their quality for a long period, and for this reason are used as food o
n trips and hikes and byathletes. There are also dietetic and therapeutic confectioneries, whic
h differ chemically from ordinary confections. Indiabetic sweets, the sugar substances are rep
laced by sorbitol or xylitol. Sweets for anemic patients are enriched withhematogen, a source
of iron and whole protein. For those suffering from goiter and as a food supplement for th
e elderly, confections.
Growth of the chocolate industry over the last decade has been driven in large part by an
increasing awareness of the health benefits of certain types of chocolate and growing popularity
in Asian Pacific countries.
This powerful growth in demand - both locally and globally - is poorly matched against an
unpredictable supply. However, chocolate consumers are considerably price insensitive.
Except in rare circumstances consumers are willing to purchase what they consider an
“affordable luxury.”
Chocolate is one of the most popular and widely consumed products in the world, with North
American countries devouring the lion's share, followed by Europe. The variety of chocolate
products available is seemingly without limit, with the candy bars and cakes that we are all
familiar with barely being the tip of the iceberg.
Chocolate is broadly classified by the amount of cocoa it contains. Milk chocolate accounts for
more than 50% of all chocolate consumption but may contain as little as 10% cocoa. Hershey's
milk chocolate has approximately 11% cocoa, with a whole lot of milk and sugar added in.
Chocolate is considered “dark” if it has more than 60% cocoa.
Dark chocolate is rich in antioxidants, which are believed to prevent or delay certain types of
diseases, including cardiac disease. These perceived health benefits have been driving strong
growth for products with the heavier cocoa weighting.
Instead of being something to avoid or consider a special treat, consumers are finding out that
many diets and even doctors are recommending regular consumption of dark chocolate.

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According to Dr. Oz, dark chocolate “keeps you looking and feeling younger because it helps
you control your blood pressure, avoid wrinkles, keep your skin younger and stay slimmer.” A
sweet treat that you can feel good about!
Chocolate is the largest part of the $34.5 billion US confectionary industry. Confectionary
products can be roughly described as “candy” or “sweets” - so inclusive of gummies, sugar
cookies and even gum. According to the National Confectioners Association, chocolate sales
account for a whopping $21.1 billion of that candy industry – over 60%!!
That revenue of $21.1 billion in 2014 was a 2.9% increase over 2013. The greatest growth was
in premium products, which expanded 11%, and in dark chocolate products, which grew 8%.
Sales are expected to grow another 6% by 2017 to $22.4 billion.
Seasonal candy is a major driver of the confectionary industry, and in 2014 accounted for over
21% of sales – over $7 billion. This includes holiday specific packaging, shapes, colors and
even flavors tailored to occasion – religious, cultural and perhaps especially the Hallmark
holidays. Year over year growth in this seasonal category was a healthy 8.5%!
It seems like...everywhere. Grocery stores are the largest seller, followed by mass merchandise
outlets and convenience stores. While confectionary stores make up only 5% of sales, they are
typically the purveyors of higher quality, niche products – which have been increasing in
popularity as well.
THE EVOLUTION OF CONFECTIONARY INDUSTRY IN INDIA
The Indian confectionery market which is ranked 25th globally in value terms in 2009 is
expected to grow at a rapid pace and jump up to 14th position by 2014, said a report from
Datamonitor.
The report further added that over 30% of the Indian population is in the 0–14 age group, which
is the primary target segment for confectionery manufacturers. These will be the prime movers
for growth in the confectionery market in India. Add to this the rapidly growing domestic
market.
“Higher disposable income and the resultant higher purchasing power will be instrumental in
the rising value and volume growth of the confectionery market in India. With the
premiumisation trend on the rise, categories like chocolate and cereal bars are expected to gain
sales, while the market is set to grow at an even faster rate, of over 12% during 2009-14,” said
Gaurav Marchanda, a Datamonitor consumer markets analyst.

17
India grew at a compound annual growth rate (CAGR) of 10.5% during 2004–09, placing it
among the fastest growing confectionery markets globally.
The Indian confectionery market is highly consolidated, stated the report, with the top five
manufacturers accounting for a major share. International manufacturers are particularly
dominant in the market, and also lead the way in terms of new product launches. “An analysis
of the leading manufacturers in terms of growth suggests that companies like Cadbury (Kraft)
and Nestlé, with a higher focus on chocolate products, are performing relatively better than
other confectioner manufacturers,” said Marchanda.
As the Indian confectionery market continues to evolve, strong trends have come to the fore
which will shape the future of the market and categories within it. Health consciousness is one
trend that has certainly caught the attention of the manufacturers. As a result, cereal bars are
currently the fastest growing category in the Indian confectionery market. Gifting chocolates
during traditional Indian festivals like Diwali and occasions like Raksha Bandhan also continue
to gain popularity. According to Marchanda, “such products have a longer shelf-life than
traditionally available sweets, and are also accompanied by well-targeted marketing campaigns
and product positioning.
However, there are several obstacles that will inhibit growth in the market. “Added strains on
household budgets due to high food inflation in India will indirectly place pressure on the
confectionery market, as discretionary spending on comfort food items diminishes,” said
Marchanda.
Furthermore, the price of both sugar and cocoa beans (the main ingredients in chocolate) is on
the rise, which is likely to exert pressure on the profit margins of manufacturers. “Higher sugar
prices directly impact the input costs of low-value sugar confectionery products, which in India
tend to have lower price elasticity,” said Marchanda.
3.2 COMPANY PROFILE:
ORIGIN

18
The Lotte India Corporation Limited, erstwhile Parys Confectionery Limited, is a fine quality
sweets and confectionery manufacturing company in India. It is one of the oldest
confectioneries of India catering popular brands of candies and sweets to its customers in India.
Lotte India Corporation Limited is an Indian sweets and confectionery giant based in South
India. This company started its operations as a confectioner during 1914 and was the first
confectioner in India. During that period the company operated under then name of "Parys
Sweets".
Lotte Company started its branch in Chennai mainly for the production of sweet called “lotte
Chocó pie”
Lotte Co., Ltd. is a multinational food and shopping corporation with headquarters in South
Korea and Japan. Lotte was first established in June 1948 in Tokyo,. From Tokyo, Lotte
expanded into South Korea with the establishment of Lotte Confectionary Co., Ltd on April 3,
1967
Lotte India Corporation Limited caters fine quality sweets and confectionery to its customers
spread across India. Its candies are one of the most sought after candies for children.
Today, Lotte is the largest confectionery manufacturer in South Korea, and is the third largest
in terms of sales revenue when only the sales of Lotte's confectioneries are counted.
Aim / Vision / Mission
Objectives:
 To identify, promote and sustain a set of business practices for orderly and fair conduct of
company business.
 To ensure compliance with requirements of Corporate Governance under the revised clause
49 of the Listing Agreement.
 To comply with all applicable laws, rules and regulations, policies and procedures
adopted by the Company from time to time.
LOTTE COFECTIONARY UP TO THE PRESENT:
From the smallest spark comes a roaring fire.The delicious world of LOTTE Confectionery
started out with a tiny pack of chewing gum. However, with the trust and affection shown by

19
consumers, LOTTE Confectionery has continuously worked for the good health and happiness
of the nation over the past 30 years. Striving for globalization, LOTTE Confectionery is doing
its best to develop new technologies and establish new overseas markets.
FINANCIAL DETAILS
Lotte India Corporation is a Private Sector Organisation that offers services in Food
Processing/ Beverages with Annual Total Turnover of 100-250 Crs and with Employee
Strength of 251-500.The Competitors of Lotte India are ITC, and nestle.
FACTORIES:
Factory 1 - Nellikuppam, Cuddalore district, Tamil nadu - candies & toffees line.
Factory 2 - Neman village, thiruvallur district, Tamilnadu - fully automated Chocó pie & gum
production line.
COMPANY PROFILE
Name of the company : Lotte India Corporation limited
Controlling authority : Corporation Office in Chennai.
Registered office : 4/111, Mount Road,Poonamallee High road,Manapakkam,Chennai-600
089.
Number of Plants : 3Year started in Cuddalore : 1914
Shift Timings : I shift - 6.00 am to 2.00 p.m.
II shift - 2.00 p.m. to 10.00 p.m.
III shift -10.00 p.m. to 6.00 am
General Shift - 8.30 am to 12.30p.m / 1.30p.m to5.30 pm
Bankers: ICICI/ State Bank of India / Indian Bank
Insurance Company National Insurance Company

20
Nature of industr : Confectionary
Capital : 217 million
LIST OF DIRECTORS:
NAME DESIGINATION
MR.MANG KO NOH CHAIRMAN
MR.MILAN WAHI MANAGING DIRECTOR
MR.MOO SUN SONG WHOLE TIME DIRECTOR
MR. MYUNG KI MIN DIRECTOR
MR.D G RAJAN INDEPENDENT DIRECTOR
MS.YOUNGMI LEE INDEPENDENT DIRECTOR
LOCATION
Lotte Companies now days are shifting base to lower cost of production which make sense
.Production base in cities or metros have become non-viable as cost of living , cost of raw
material ,overhead cost and transportation cost have gone above the roof . Companies are
moving to low cost areas like CHINA, INDIA, UKRAINE, IRELAND, VIETNAM ETC.
Locally companies have operation in DELHI, MUMBAI, CHENNAI, moved to areas like
UTTARAKAND , JHARKHAND , JAIPUR , BADI.
Overview of Lotte India Corporation limited
Confectionery Industry, a manufacturing sector made up of companies primarily involved in
processing candies, chocolate and cocoa products and chewing gum.

21
Confectionery manufacturing started to emerge as an important industry in the late 1800s. One
of the earliest commercial operations, McCormick's Ltd, was established in London, in 1857.
Confectionery production greatly increased in Canada in the early 1900s with the establishment
of several major producers,. In these formative years the industry was concentrated in Eastern
Canada, a situation that prevails today, although in Western Canada number of smaller
manufacturers emerged during this period and new companies are still appearing. During the
past 2 decades, a considerable amount of plant consolidation has taken place. In 1961the
industry had 194 plants in production. The LOTTE confectionery industry is unique among
segments of the Canadian FOOD AND BEVERAGE manufacturing system in that it is
dependent on foreign supply for 2 of its primary ingredients: sugar and cocoa. Unfortunately,
these commodities are subject to rapidly changing prices in spite of accords such as the
International Sugar Agreement. This factor, in turn, can seriously affect the industry's sales
volumes and profit margins
Industry Details:
Lotte India Corporation limited, a subsidiary of lotte confectionery co. limited South Korean
company. Lotte India corporation limited has its roots in the Indian confectionery market since
1914, a name that still finds a prominent place in the heart of consumers. Lotte confectionery
is a $1. 5 billion global foods company and have a products range, which candy, biscuits,
chocolates and snacks with business interests across the world. Our new plant for Choco pie in
Chennai, which are largest cakes producing plant in the world will start producing export range
from the month of July 2010.
Lotte Group consists of over 60 business units employing 60,000 people engaged in such
diverse industries as candy manufacturing, beverages, hotels, fast food, retail, financial
services, heavy chemicals, electronics, IT, construction, major operations are overseen by
Shin's family in Japan and South Korea, with additional businesses in China, Thailand,
Indonesia, Vietnam, India, USA, Russia, Philippines, Pakistan and Poland.
PRODUCTS:
Caramilk, Butter Scotch, Coconut Punch, Shakti, Orange Candy, Spout, Lacto King, Pineapple
Totty, Coconut Creme, Éclairs, Lemon Barley Coconut, Frutiz Mango.

22
Lotte India’s key brand in confectionery includes coffee bite, lacto king, lotte eclairs, caramilk
and coconut punch, in gums boo pro and spout and in snacks Choco pie.
VISION 21
LOTTE Confectionery will take a giant leap to become the world's leading confectionery
company. LOTTE will travel throughout the world by opening and investing in new overseas
markets. With quality as its top priority, LOTTE Confectionery will create products that are
traditionally flavored, but have a global touch. LOTTE Confectionery will spare no efforts in
making the finest products in the world.
CHAPTER 4
DATA ANALYSIS AND INTERPRETATION
4.1 PERCENTAGE ANALYSIS

23
4.1.1 Classification of respondents based on age
Table 4.1.1
Age
No. Of
respondents Percentage
20-30 yrs 19 38%
30-45 yrs 18 36%
45 yrs & above 13 26%
Chart 4.1.1
Classification of respondents based on age
Inference
From the above table it is inferred that, 38% of respondents are 20-30 years, 36% of
respondents are 30-45 years and 26% of respondents are 45 years and above to age factor.
4.1.2 Classification of respondents based on education
Table 4.1.2
Education No. of Respondents Percentage
no.of respondents
20-30 yrs
30-45 yrs
45 yrs & above

24
Diploma Holder 17 34%
Bachelor Degree 14 28%
Master Degree 19 38%
Chart 4.1.2
Classification of respondents based on education
Inference
From the above table it is inferred that, 34% of respondents are diploma holder, 28% of
respondents are bachelor degree and 38% of respondents are master degree based on their
education factor.
4.1.3 Classification of respondents based on departments
Table 4.1.3
Department No. of Respondents Percentage
17
14
19
34%
28%
38%
Diploma Holder
Bachelor Degree
Master Degree
Chart Title
Percentage No.of Respondents

25
Production 18 36%
quality 10 20%
Operation 11 22%
Inventory 11 22%
Chart 4.1.3
Classification of respondents based on departments
Inference:
From the above table it is inferred that, 36% of respondents are belong to production, 20% of
respondents belong to quality, 22% of respondents are belong to operation and 22% of
respondents are belong to inventory.
4.1.4 Classification of respondents based on tenure
Table 4.1.4
18
10
11 11
36% 20% 22% 22%
Production quality Operation Inventory
Chart Title
No.of Respondents Percentage

26
Tenure No. of Respondents Percentage
0-5 yrs 24 48%
5-10 yrs 17 34%
10 yrs & above 9 18%
Chart 4.1.4
Classification of respondents based on tenure
Inference
From the above table it is inferred that, 48% of respondents are 0-5 years, 34% of respondents
are 5-10 years and 18% of respondents are 10 years and above to tenure
4.1.5 Classification of respondents based on relevant training
Table 4.1.5
No.of Respondents
0-5 yrs
5-10 yrs
10 yrs & above

27
Relevant training No. of Respondents Percentage
Excellent 23 46%
Good 22 44%
Fair 3 6%
Poor 2 4%
.
Chart 4.1.5
Classification of respondents based on relevant training
Inference:
From the above table it is inferred that, 46% of respondents are excellent, 44% of respondents
are good, 6% of respondents are fair and 4% of respondents are poor to relevant training.
4.1.6 Classification of respondents based on safety
23
22
3
2
46% 44% 6% 4%
Excellent Good Fair Poor
Chart Title

28
Table 4.1.6
Safety No. of Respondents Percentage
Excellent 21 42%
Good 24 48%
Fair 5 10%
Poor 0 0%
Chart 4.1.6
Classification of respondents based on safety
Inference:
are good, 10% of respondents are fair and 0% of respondents are poor to safety.
4.1.7 Classification of respondents based on shift timing
21
24
5
0
42%
48%
10%
0%
Excellent
Good
Fair
Poor
Chart Title

29
Table 4.1.7
Shift Timing No. of Respondents Percentage
Excellent 17 34%
Good 15 30%
Fair 15 30%
Poor 3 6%
Chart 4.1.7
4.1.7 Classification of respondents based on shift timing
Inference:
4.1.8 Classification of respondents based on work condition
17
15 15
3
34% 30% 30% 6%
Chart Title

30
Table 4.1.8
Work coordination No. of Respondents Percentage
Excellent 16 32%
Good 14 28%
Fair 19 38%
Poor 1 2%
4.1.8 Classification of respondents based on work condition
Table 4.1.8
Inference:
4.1.9 Classification of respondents based on equipment provided
No.of Respondents
Excellent
Good
Fair
Poor

31
Table 4.1.9
Equipment Provided No. of Respondents Percentage
Excellent 22 44%
Good 21 42%
Fair 5 10%
Poor 2 4%
Chart 4.1.9
4.1.9 Classification of respondents based on equipment provided
Inference:
4.1.10 Classification of respondents based on process information
22 21
5
2
44% 42% 10% 4%
Chart Title

32
Table 4.1.10
Process Info No. of Respondents Percentage
Excellent 20 40%
Good 22 44%
Fair 7 14%
Poor 1 2%
Chart 4.1.10
Classification of respondents based on process information
Inference:
are good, 14% of respondents are fair and 2% of respondents are poor to process information.
4.1.11 Classification of respondents based on relationship
No.of Respondents
Excellent
Good
Fair
Poor

33
Table 4.1.11
Relationship No. of Respondents Percentage
Excellent 16 32%
Good 12 24%
Fair 20 40%
Poor 2 4%
Chart 4.1.11
Classification of respondents based on relationship
Inference:
are good, 40% of respondents are fair and 4% of respondents are poor to relationship.
4.1.12 Classification of respondents based on proper document
Excellent
Good
Fair
Poor
16
12
20
2
32%
24%
40%
4%
Chart Title

34
Table 4.1.12
Proper Document No. of Respondents Percentage
Excellent 21 42%
Good 23 46%
Fair 6 12%
Poor 0 0%
Chart 4.1.12
Classification of respondents based on proper document
Inference:
are good, 12% of respondents are fair and 0% of respondents are poor to proper document.
4.1.13 Classification of respondents based on over processing
No.of Respondents
Excellent
Good
Fair
Poor

35
Table 4.1.13
Over processing No. of Respondents Percentage
yes 30 60%
no 20 40%
Chart 4.1.13
Classification of respondents based on over processing
Inference:
From the above table it is inferred that, 60% of respondents are chosen yes and 40% of
respondents are chosen no to over processing.
4.1.14 Classification of respondents based on high level of satisfaction
0
5
10
15
20
25
30
Chart Title
yes
no

36
Table 4.1.14
high level No. of Respondents Percentage
Excellent 13 26%
Good 21 42%
Fair 16 32%
Poor 0 0%
Chart 4.1.14
Classification of respondents based on high level of satisfaction
Inference:
are good, 32% of respondents are fair and 0% of respondents are poor to high level of
satisfaction.
13
21
16
0
26%
42%
32%
0%
Excellent
Good
Fair
Poor
Chart Title

37
4.1.15 Classification of respondents based on full automation
Table 4.1.15
full automation No. of Respondents Percentage
Excellent 28 36%
Good 15 30%
Fair 7 14%
Poor 0 0%
Chart 4.1.15
Classification of respondents based on full automation
Inference:
are good, 14% of respondents are fair and 0% of respondents are poor to full automation.
No.of Respondents
Excellent
Good
Fair
Poor

38
4.1.16 Classification of respondents based on weight
Table 4.1.16
Weight No. of Respondents Percentage
Excellent 17 34%
Good 20 40%
Fair 12 24%
Poor 1 2%
Chart 4.1.16
Classification of respondents based on weight
Inference:
are good, 24% of respondents are fair and 2% of respondents are poor to weight.
Excellent
Good
Fair
Poor
17
20
12
1
34%
40%
24%
2%
Chart Title

39
4.1.17 Classification of respondents based on over production
Table 4.1.17
Overproduction No. of Respondents Percentage
yes 26 52%
no 24 48%
Chart 4.1.17
Classification of respondents based on over production
Inference:
From the above table it is inferred that, 52% of respondents are chosen yes and 48% of
respondents are chosen no to over production.
26
52%
24
48%
Chart Title
yes no

40
4.1.18 Classification of respondents based on quality
Table 4.1.18
Quality No.of Respondents Percentage
Excellent 14 28%
Good 25 50%
Fair 9 18%
Poor 2 4%
Chart 4.1.18
Classification of respondents based on quality
Inference:
are good, 18% of respondents are fair and 4% of respondents are poor to quality
No.of Respondents
Excellent
Good
Fair
Poor

41
4.1.19 Classification of respondents based on level of opportunities
Table 4.1.19
Level of opportunities No. of Respondents Percentage
Excellent 11 22%
Good 14 28%
Fair 17 34%
Poor 8 16%
Chart 4.1.19
Classification of respondents based on level of opportunities
Inference:
are good, 34% of respondents are fair and 16% of respondents are poor to level of opportunities.
Excellent
Good
Fair
Poor
11
14
17
8
22%
28%
34%
16%
Chart Title

42
4.1.20 Classification of respondents based on overall statistics
Table 4.1.20
Overall statistics No. of Respondents Percentage
Excellent 14 28%
Good 18 36%
Fair 14 28%
Poor 4 8%
Chart 4.1.20
Classification of respondents based on overall statistics
Inference:
are good, 28% of respondents are fair and 8% of respondents are poor to level of opportunities.
4.2 Statistical Analysis:
14
18
14
4
28% 36% 28% 8%
Chart Title

43
ANALYSIS BETWEEN DEPARTMENT AND RELEVANT TRAINING, USING SPSS-
ONE WAY ANOVA
NULL HYPOTHESIS (H0): There is no significant difference between department and
relevant training
ALTERNATIVE HYPOTHESIS (H1): There is significant difference between department
and relevant training.
ANOVA
Sum of
Squares
df Mean Square F Sig.
Between Groups 4.066 3 1.355 2.512 .070
Within Groups 24.814 46 .539
Total 28.880 49
Inference
ANALYSIS BETWEEN QUANTITY AND OVER PRODUCTION USING SPSS- CHI
SQUARE TEST
It is inferred that there is no significant relationship between department and relevant training
of the employees. (0.070>0.05)

44
NULL HYPOTHESIS (H0): There is no significant difference between quantity and over
production
ALTERNATIVE HYPOTHESIS (H1): There is significant difference between quantity and
over production
Frequencies
quality
Observed N Expected N Residual
excellent 14 12.5 1.5
good 25 12.5 12.5
Fair 9 12.5 -3.5
poor 2 12.5 -10.5
Total 50
Overproduction
Observed N Expected N Residual
Yes 26 25.0 1.0
No 24 25.0 -1.0
Total 50
Test Statistics
quality overproducti
on
Chi-
Square
22.480a
.080b
Df 3 1
Asymp.
Sig.
.000 .777
a. 0 cells (0.0%) have expected
frequencies less than 5. The
minimum expected cell frequency is
12.5.

45
b. 0 cells (0.0%) have expected
frequencies less than 5. The
minimum expected cell frequency is
25.0.
Inference:
It is inferred that there is a no significant relationship between quantity and over production
value obtained is found to be(0.777>0.005) Ho accepted

46
ANALYSIS BETWEEN EDUCATION AND EQUIPMENT PROVIDED USING SPSS-
KRUSKAL WALLIS TEST
NULL HYPOTHESIS (H0): There is no significant difference between education and
equipment provided
ALTERNATIVE HYPOTHESIS (H1): There is significant difference between education
and equipment provided
Kruskal-Wallis Test
education n mean rank
Equipment provided
Diploma
Bachelor degree
Master degree
total
17
14
19
50
25.88
29.29
22.37
equipment_p
rovided
Chi-
Square
2.182
Df 2
Asymp.
Sig.
.336
INFERENCE:
A statistically significant difference between the different level of education (H(2) =
2.182, p = 0.336), with a mean rank of 25.88 for Diploma, 29.29 for bachelor degree and 22.37master
degree.

47
ANALYSIS BETWEEN TENURE AND FULLY AUTOMATED MACHINE USING
SPSS-MANN WHITNEY U TEST
NULL HYPOTHESIS (H0): There is no significant difference between tenure and fully
automated machine.
ALTERNATIVE HYPOTHESIS (H1): There is significant difference between tenure and
fully automated machine.
Mann-Whitney Test
Ranks
tenure N Mean
Rank
Sum of
Ranks
fullyautomated_machine
0-5 24 20.13 483.00
5-10 17 22.24 378.00
Total 41
Test Statisticsa
fullyautomat
ed_machine
Mann-Whitney U 183.000
Wilcoxon W 483.000
Z -.630
Asymp. Sig. (2-
tailed)
.529
a. Grouping Variable: tenure
INFERENCE:
It is inferred that ,there is no significant relationship between tenure and fully automated
machine (U = 183, p = .529).

48
CHAPTER 5
RESULTS AND DISCUSSIONS
5.1 SUMMARY OF FINDINGS:
 It is inferred from that 46% of respondents are excellent based on relevant training.
 It is inferred from that 48% of respondents are good in safety.
 Almost 34% of the respondents based on the shift timing.
 Most of the people are satisfied the equipment providing in a company
 The production process is made with the proper documentation is good based on the
survey
 It is inferred from that 44% of the respondents are good in the process information
 Relationship with the co-employees are not good in the company
 Almost 60% of the employees are accepted over production plays a vital role in a
company
 It is inferred from that 40% of the respondents are strongly accepted the fully
automated machine deliver the product at time
 Almost 40% of the respondents are accepted the weight act as a major constraint for
wastages
 It is inferred from that 34% of the respondents are fair based on the level of opportunity
5.2 SUGGESTION:
 To avoid sudden or frequent breakdowns, thereby increasing the productivity.
 Proper training for employees may reduce wastage and production time.
 Continuous process of production will reduce the production time.
 To recruit skillful and experienced labors and workers.
 To implement various concepts like 5s, six sigma, etc. for better product quality.
 To implement TPM for better productivity.
 Proper communication from top level management to low level management for the
smooth execution of production plan

49
5.3 CONCLUSION:
Confectionary industry is facing intense competition from asia and Europe countries. In
order to sustain the market, the productivity and the quality of the confectionaries should be
improved. Productivity improvement is to do the right things better and make it a part of
continuous process. Therefore it is important to adopt efficient productivity improvement
technique so as to ensure individuals and organization's growth in productivity.
From the study, it is obvious that ‘time’ plays an effective role than other variable like
machine, employee and wastes, in the field of confectionery production process. Hence, I
conclude that by implementing time optimization in LOTTE India Corporation Ltd, the
company can lead into the roadway of successful mass production of confectionery items
within a short span of time.

50
APPENDIX
QUESTIONNAIRE
I am a student of M.B.A from SRM Easwari Engineering College, Ramapuram, Chennai.
You are required to fill this questionnaire to enable me to undertake the study on the said
project.
4-Excellent
3-Good
2-Fair
1-Bad
1. Age
i) 20 – 30 yrs.
ii) 31 – 45 yrs.
iii) 46 yrs. & above
2. Education
i) Diploma holder
ii) Bachelor Degree
iii) Master Degree
3. Department
i) HR & Admin
ii) Sales and Marketing
iii) Finance
iv) Documentation
v) Customer service
vi) Operation

51
4. Tenure in production Field
i) 0 – 5 yrs.
ii) 6 – 10 yrs.
iii) 11 yrs. & above.
S.NO Questions Excellent Good Fair Bad
1. Does Company provides relevant training
regarding this field?
2. Does company provides required safety and
security for employees?
3. Shifting time is feasible for employee
4 All production process are made with the proper
documentation
5 Weight act as a major constrain for wastage
6 Our company works as a team with our staff
7 How satisfied are you with the equipment we
provide
8 I am kept fully informed of the up to date status of
all process
9 Overproduction plays the vital role in our
company
10 Production process line is maintained at high level
11 Over processing plays the vital role in our
company
12 Does the fully automated machine delivers the
product at time
13 Any issues having to do with quality are promptly
corrected.
14 Relationship with your co-employees.
15 I have opportunities to learn and grow
16 Degree to which your skills are used.
17 Someone at work encourages my development.
18 Availability of follow-up training.
19 My co-workers are committed to doing quality
work.

52
20 Overall, how satisfied are you working in this
department
BIBLIOGRAPHY
BOOK REFERRED:
 Ashwathappa, Operation Management, Pearson Education, 14th
edition, 2012.

WEBSITES REFERRED:
www.google.co.in
www.googlescholar.co.in
www.springer.com
www.sciencedirect.com
www.ieeexplore.com
www.ebsco.com
www.En.wikipedia.org
www.En.wikipedia.org/wiki/quality_of_service
www.service-quality.com

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