A STUDY ON EMPLOYEE’S PERFORMANCE APPRAISAL TOWARDS SRI RAMCO SPINNERS AT RAJAPALAYAM

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CHAPTER I

INTRODUCTION TO PERFORMANCE APPRAISAL

1.1 INTRODUCTION

Performance appraisal has been considered as the most significant an indispensable

tool for an organisation, for an organisation for the information it provides is highly useful in

making decisions regarding various personnel aspects such as promotion and merit increases.

Performance measures also link informance gathering and decisions making processes which

provide a basis for judging the effectiveness of personnel such as recruiting, selection,

training and compensation. This research will concentrate on examine the effect of the

performance appraisal on an individual as wel as on the organisation. The sample size 100

has been chosen from the north Indian states. The data used for the is primary data collected

through the help of questionnaire filled by the samples. The data was evaluated with the help

of statistical tools i.e., descriptive statistics, regression, correlation, residual analysis and chi-

square test. The findings of the research show that there is a noticeable effect of the

performance appraisal on the organisation as well as on the individual.

Performance appraisal is a formal, structured system of measuring and evaluating an

employees job, related behaviours and out comes to discovers how and why the employee is

pertly performing on the job and how the employee can perform more effectively in the

future so the employee, organisation, and society all benefit.

Performance appraisal is a process of summarizing, assessing and developing the

work performance of an employee. In order to be effective and constructive, the performance

manager should make every effort to obtain as much objective information about the

employee's performance as possible.

Performance Appraisal is a review and discussion of an employee's performance of

assigned duties and responsibilities based on results obtained by the employee in their job,

not on the employee's personality characteristics. Personality should be considered only when

it relates to performance of assigned duties and responsibilities.

It is a structured formal interaction between a subordinate and supervisor, that usually

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takes the form of a periodic interview (annual or semi-annual), in which the work

performance of the subordinate is examined and discussed, with a view to identifying

weaknesses and strengths as well as opportunities for improvement and skills development.

In many organizations - but not all - appraisal results are used, either directly or

indirectly, to help determine reward outcomes. That is, the appraisal results are used to

identify the better performing employees who should get the majority of available merit pay

increases, bonuses, and promotions.

By the same token, appraisal results are used to identify poorer performers, who may

require some form of counselling, or in extreme cases, demotion, dismissal or decreases in

pay.

1.2 PROFILE OF SRI RAMCO SPINNERS

Textile Industry is the one that has occupies the predominant position in the

traditional industries and it is basic for cloth which is one of the basic necessaries of man. It

is one that provide employment to several crores of families directly and indirectly.

At first, man uses leaves as cloth. After that, he started to use the skin of hunted

animals as cloth. Thereafter, he had started to prepare cloth with the hair of goat. As

twisting of hair has taken much time, he had started to twist the cotton with the help of

spindle and then with the help of reeling wheel, cotton was made soft and twisted thread.

Thereafter, during 1490, Mr.Leando Dawinsy has introduced flyer and bobbin structure in

place of spindle. During 1722, Hargreaves has replaced the reeling wheel with Spinning

machine and with that, quality yarn could be produced.

Thereafter, during 1738, the machine which has been manufactured with Drawing

Roller (invented by Mr.Paul) and Saxony Wheel (invented by Mr.Wyat) was very useful in

producing yarn. Later on, Mr.Paul and Mr.Wyat have formed 5 machines that has 50

spindles in Birmingham and this is the first invented Spinning Machine in this world.

Textile Industry that has grown in Britain and England was started at first, in India at

Mumbai and thereafter at Coimbatore.

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Indian Textile Industry has its own speciality. In puranic period itself, our ancestors

had known the technique of preparing a saree that can be put into a match box itself.

Indian Climatic condition is favourable to cultivate the all types of cotton and from

that, variety of yarn could be produced. Nowhere in the world, such type of climatic

condition is prevailing. This is the boon for India to lead in Textile Industry.

When India has got freedom, it has 370 spinning mills only and now it has multiplied

into 2000 mills. We import 10% cotton from foreign countries. Produced yarn is being sold

to northern states and also to foreign countries.

INDIAN TEXTILE INDUSTRY - BIRD EYE VIEW

In India, Textile Industry constitute 20% of Industrial production.

23% of export products are of textile products.

At world level, India occupies 3rd place in the production of cotton.

India occupies 2nd place in the production of yarn.

India exports large quantity of cotton yarn.

92% of cotton mills, are under organized sector.

Textile Industry provides employment to 200 lakhs of people.

In aggregate, India has 392.8 lakshs of spinning spindles and this is 22% of world

spindleage. At world level, India fulfills the demand of 25% of cotton yarn.

As per the recently published Circular of SIMA, 40% of cotton yarn is being

produced by Southern States. Out of 40% of cotton yarn being produced by Southern States,

38% of cotton yarn is being produced by Tamilnadu and it is matter of proud for Tamilnadu

people.

In Tamilnadu, best and skilled administration of Spinning Mills and the best co-

operation being extended by the workers are responsible for occupying leading place in

Textile Industry.

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In Textile Industry, we should work with enthusiastic and with awareness and it is the

best way to improve our mill.

In Rajapalayam, for Mr.Chinniyaraja and Mrs.Chittamal couple,

Mr.P.A.C.Ramasamy Raja was born on 28.04.1894. After the demise of his father,

Mr.P.A.C.Ramasamy Raja has taken the position of Grama Munsiff. Though he hailed from

a farmer family, Mr.P.A.C.Ramasamy Raja was interested in business. With his utmost

effort, he has brought the Railway transport and electricity supply during 1927 and 1937

respectively, for Rajapalayam.

There after, on 05.09.2012, he has started a cotton mill named RAJAPALAYAM

MILLS LTD with his own fund and the fund collected from the shares of Public. At first,

he has started the mill with 6000 spindles and then increased the spindles to 40,000 and also

624 O.E.Rotors. At present, that firm is functioning as Ramco Group which consists of 3

international trade mills, 6 internal trade mills and also the sectors such as cement,

computer software, Bio-technology, Asbestos roof.

Sri Ramco Spinners., (A Division of Ramco Industries Ltd.,) was started during 1991.

This firm was started with 12096 spindles from the machineries imported from Japan. In

this mill, counts ranging from 10 to 100 - single and double yarn counts are being produced

and they are being exported foreign countries such as Japan, Indonesia, Hongkong, Korea and

Bokraine. From our knitting yarn, Foreigners are preparing inner dress such as Banian and

shirting, suiting and bed sheet from the weaving yarn. Now, in our mills, 650 employees

are working. Our mill which was started with 12096 spindles has grown gradually and

during 2005, B unit was started with 26496 spindles. During 2007, it has grown further and

C Unit was started with 43296 spindles.

In India, owing to the introduction of New Economic Policy of Indian Government,

we have to manage the severe competition in Spinning industry and we have to sustain the

same. If we produce the yarn with good quality, least manufacturing cost and in time, we

can won market. Further we should minimize the wastages in production. We should work

with our utmost ability and grow along with our mill.

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We are availing the cotton bales (basic input) from Northern States such as Maharashtra

and Gujarat and also from the foreign countries. Then, those bales are being inspected and

stacked at the Cotton godown.

For getting yarn from the cotton, we use the following process/machineries.

Mixing

Blowroom

Carding

Sliver Lab, Ribbon Lab (SLM / RLM)

Comber

Drawing

Simplex

Spinning

Cone Winding

Propeller Winding

TFO

Re-winding

Gassing

Soft Winding

Packing

At first. for producing yarn, we take the necessary bales from godown by removing

the cloth and iron belt. We should take equal quantity of cotton from each bale and put the

same for mixing. On mixing the cotton of various bales, care should be taken to remove the

tangible contamination such as jute, cloth and Polythene thread.

Cotton has to be taken by cutting the mixing in rectangular position and feed the same

in the conveyer in equal quantity. Lap that is produced, has to be kept in its place by packing

the same with proper cloth.

In Carding, cotton leaves are being separated, considerable amount of dust is being

removed and then the cotton is being transformed into sliver.

In Carding Sliver, 18 or 20 cans of SLM are being put and make it as sliver lap.

Ribbon Lap are being prepared by joining 6 sliver laps through RLM. This method has to

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followed for preparing combed yarn only. For the production of Karded yarn, drawing

machine has to be run by putting cans directly from the Carding.

Comber machine, wastes the short length cotton leaves got from RLM lap and then

produces the combed sliver with sliver shape. Thin and thick placed yarn got from Drawing

Combed sliver are being corrected with drafting and doubling process. Simple machine

produces roving in bobbin pump, by pulling the Drawing sliver with required length and

twist. Spinning machine produces cops in spinning pumps by pulling the roving with required

length and twist.

Benefits being offered to the workers

1. Leave and Festival holidays are being given to workers as per Tamilnadu Government

Industrial Rules and Act 1948.

2. Ramco Co-operative Mini Super Market was established with the aim of providing

grocery, cloth and other things to the workers at a reasonable price.

3. Co-operative Credit Society was established for providing loan upto Rs.15,000/- with

minimum interest and easy installment (36 monthly installment) to the workers to

meet their family expenses.

4. Ramco Holiday Home was formed for providing recreation to the workers with their

wives in Courtalam for every year.

5. Education subsidy up to Rs.5000/- is being granted annually for education (school,

medical, engineering, higher education) of eligible children of workers.

6. On every Sports Day (which is being celebrated on Pongal day), our respected

Chairman award prizes and things to the workers who have worked for maximum

number of days and also for best workers.

7. Uniform cloths are being provided to all the workers.

8. Our Management offers other more benefits also, to the workers.

Safety

1. 4th March of every year is being observed as Protection Day by all the employees of

our Group.

2. During 1997, 1999 and 2002, District Safety Award was awarded to our mill for

running the mill without Accident.

3. Weighty goods should not be carried at the head.

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4. We should not touch the machine the running machine with our hands. We should

touch the machine, after ensuring the stoppage of machine

5. Electric pluck should be closed with its cover, after the usage.

6. Metal bangle and threads should not be wore at the hands.

Loose dress should not be put.

7. During working hours, Shoe or Chappal should be were compulsorily.

8. During working at height places, helmet should be wore compulsorily.

9. Temporary and non protective power connection should not be used.

10. Taking of Toxicant goods and smoking inside the mill premises, should be

prohibited.

11. Movements of protective instruments at the machine, should be monitored then and

there. If any one of the instrument found defective, they should repaired

immediately.

Production aim

To formulate procedures for the activities of process control department of

production, maintenance and quality assurance.

Production plan

Production plans in drawn every month depending on the confirmed order pattern in

different counts and the production capacity. In case of any new count or count with any new

mixing, the processing parameter and machine parameter and machine parameters are fixed

after conducting trials and /or as per the recommendation from the buyer. Ring frame is

allocated is based on the production plan. The plan is transmitted to FM, AFM, MA, cotton

cleft and sales clerk, packing clerk, packing clerk, SM (M), SM (QA), machinery auditor

assistant spinning master for their references through LAN. Also the cone pattern is

transmitted to FM, AFM, MA, ASMS and packing clerk for their references through LAN.

The production plan are informed to regular customers such as DOKOBO through

Mitsubishi. For other customers the production is completed as per the L/C condition.

Any changes in the production pattern, either at the request of the customer or as

necessitated by contingency is effected in the plan and the customer (both regular and non

regular) is informed accordingly. ASMS and/or shift clerks monitor the process as per the

production plan.

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In processing and/or machine ASMS and/or shift clerks with the help of production,

maintenance, carry out parameters in all departments through count change memos operatives

in line with the standard processing parameters and machine parameters. After count

changing/machine parameter changing, the count change memo is handed over to shift to

clerk/ supervisor/ASMS by mentioning the time of changing the parameters. If it is count

change, the shift clerk is checking the wrapping test results are handed over to QAD along

with the count change memo for this file. Any wheel changes for wrapping correction, the

wrapping is and also checked by QA clerks. The count change memo is initiated by the

ASMS and forwarded to S.M (M) and AFM. In the absence of shift supervisor/ASM it is

initiated by the AFM.

In production plan the quantity, type of mixing; count status, processing parameters

reference and machine parameters reference are given to facilitate to carry out the production

in line with the customer requirements.

In production plan, the count status is referred in alphanumeric form, in which the

first letters represents the of the lot i.e., waxed or unwaged and the next letter represents the

type of yarn to be produced i.e., 1kg or 2kg or 2.2kg etc.,

For carded counts we use the same processing and machine parameters as per the

reference number but the silver lap. Ribber lab and comber processes are by-passed

processing and machine parameters are given up to- rewinding stage. For single yarn we use

the processing. Parameters up to machconer and for double yarn we extend the processing

parameters up to rewinding. Production plan is reviewed every month to ensure

effectiveness of the schedule will be taken up for analysis and possible causes for the delay

will identified for taking corrective action.

Productive Activities

Trained personnel as per the standard work instructions displayed in every department

and supervised by ASM\shift supervisor and\or shift clerks carry out the production. The

responsibilities for ASM and shift clerks described. To carry out the production\process

smoothly and to avoid ambiguity, standard processing parameters and machine parameters

are fixed. The standard processing parameters are reviewed and updated whenever there is a

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change due to improvement realized through any trails, up gradation in technology, any

change in the character of raw materials processed etc., the standard processing parameters

and machine parameters are given and also the standard TPI particulars recommended by the

buyer and TPI maintained for others according to the count is also given.

Some of the standard processing parameters are mentioned through periodical offline

testing at OA Department. ONLINE MONITORING is also followed wherever visual display

is installed in the machine. This is explained in the processing parameters documents.

Similarly machine parameters are mentioned/check during machinery audit, maintenance and

clearing. Any deviations in the machine parameters are corrected to the standard. The

frequencies for monitoring are so fixed that the deviation in the prameterrs will be corrected

befors the dispatch of lots. The there is material processed is verified for the conformance. If

there is any deviation in any aspect it will be handled as per. The utilize the human resources

effectively; standard work assignments have been fixed in every department. These work

assignments will be changed and updated based on the time study, research institutions are

recommendations, any possible improvement due to technological up gradation in machines,

layout changes, in work methods etc.,

1.3 INDUSTRY PROFILE

India spinning industry has gone from strength to strength since a very long time now as it was the hub of cotton manufacturing. Cotton is not only consumed to the highest extant

in india but it has also become one of the most profitable textile in the export industry. The

yarn spinning industry covers almost 25 percent of the total industrial production of one of

the worlds 10 longest economies. Trends one reviewed every yarn in accordance with the

need and fashion. The spinning industry and in india is on set to hit the global market with

other fabrics as well like the cotton textiles with other fabrics as well like the cotton textiles

with its enthusiasm and consistency in work.

It has already reached a phenomenal status in india by heating the obstacles that caused a

downfall since past few years and in how on its way to cover a wider area in the spinning

sectors.

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ABOUT RAMCO GROUP

Ramco group is one of the south India strongest and most respected industrial groups.

It has nine companies and 16 business units under its fold. The group has well diversified

business interests like cement, cotton yarn, fiber cement products, software systems, surgical

dressing etc.,

The ramco group was famed by Sri.P.A.C.Ramasamy Raja of rajapalayam

rajapalayam mills the first company of the group was started in 1988. It was he, who made

rajapalayam what it is today for Sri P.A.C Ramasamy raja, religion and charity were part and

parcel of life. He realized that it was only education which could erase poverty and the

pitiable conditions of the people. In a fiercely competitive global market space Ramco group

is created new markets maintaining the status quality. Ramco group feels proud to say where

delivering quality to our highly discerning customers worldwide. Regardless of time zones

with a total turnover of more than rs.3000 crore, assets worth rs.4 crores and personal

numbering over 9000 the group is looking towards the future from position of strength. Its

been the ramco groups belief for over 50 years now. The managements faith on productivity

and technological up graduation has ensured that its competitiveness in the market place.

Technology comes help you stay a head. It been the ramco group textile division it

is the state of the art technology established first in Asia. In which human hands free your

manufacturing system is highly appreciated by the customers of ramco group textile division

from all over the world. Totally 80000 spindles is running by the same system. Machineries

supplied by Reiter in Switzerland. The total 80000 spinners disturbed among Sri Ramco

spinners, sandhiya, sri Vishnu shanker mills, rajapalayam mills ltd, textile business is the first

business venture of ramco group with settling up of rajapalayam mills ltd in 1983.

The textile business of ramco group comprises of following business unit,

Rajapalayam mills ltd

Sudharshan mills ltd

Sri Vishnu shanker mill ltd

Rajapalayam spin text

Sri ramco spinners

Rajapalayam textiles.

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Sandhiya spinning mill ltd

Thanjavur spinning mills ltd

Today, under the stewardship of P.R.Ramasubramaniya Raja, the RS.15000 million

ramco groups is a well diversified galaxy of starts with interest spinning from cements, the

production of cotton and synthetic yarn, software systems and more. He has inspired the

group is one of the Indias most respected group has achieved international recognition for its

quality and services.

SRI RAMCO SPINNERS

Sri Ramco spinners are a 100% export oriented textile division of ramco industries

limited. It belongs to ramco a group which has been growing rapidly. Today, ramco is a rib

rant of companies aggregating a turnover of about RS.8 billion[about USD 190 million] with

manufacturing activities in textile, cement fibers and many readymade plaster of

paries,surgical dressings, computer software and Bio-technology.

Sri Ramco spinners are the division of ramco industries limited manufacturing cotton

yarn; Sri Ramco spinners commenced operations in 1991 with state of the art machinery and

controls from Japan, Switzerland, and Germany. They yarn manufactured has made inroads

in industrial market and won appreciation from the worlds decreeing customers. The current

production rate is about 9 tonners per day in the count range of number 300 combed to

number 120 combed [both single and double yarn knitting/wearing and taxed/untaxed].

Sri Ramco Spinners was established in year 1991 on august 1 with a view to

concentrate on high quality ring yarn. The products of mills are the markets leaders in quality

and price and enjoy the acceptance in domestic as well as foreign markets. The mills export

considerable volume spindles. All the machinery of the mill are modernized on a continuing

basis and latest technology in incorporated in them with the result that high quality products

manufactured.

A Sri Ramco spinner has so startedita B units in the year 2006. The whole unit has

got machiners of LMV, Coimbatore. Right from blow room to spinning. It has started its

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production of various counts ranging from no.30 to no.120 both for domestic and exports

markets. We can producing value added products in higher quality segments.

A Sri Ramco spinner has grown up rapidly and it developed its c unit in the year

2008 with Reiter project starting from Switzerland with very high speed and high

productivity machineries. The company work on the principle started as system should

work; men should follow the system. The company work on the principle started as system

should work; men should follow ensures on system it also operators on the 7s kaizen

methods as follows.

SEIRI - sort out and eliminate the unnecessary things.

SEITION - systematic arrangements of things.

SEIKETSU - clean the place and machine well.

SEITSUKE - Have positive work attitude

SHIKKARI - Not to give up systems at any situation.

SHITSUKOKU - Follows the system persistently.

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1.4 OBJECTIVES OF THE STUDY

1. To study the employees behaviour towards performance appraisal system.

2. To study the employees effectiveness towards performance appraisal system.

3. To measures and compare the actual and standard performance.

4. To identify employees expectation towards performance appraisal system.

5. To provide feedback to improve the employees performance.

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1.5 SCOPE OF THE STUDY

The study finds out the exiting performance appraisal system in Sri Ramco Spinners

products. And this study also helps to evaluate employees performance in percent status.

This study understanding the employees work culture involvement and satisfaction. The

project will also help the organisation future planning and also helps to deciding employees

promotion, transfer, pay increase and incentives

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CHAPTER -II

REVIEW OF LITERATURE

2.1 Review of Literature

Generating request streams on Big Data using clustered renewal processes.

October 2013

Cristina L. Abad | Mindi Yuan | Chris X. Cai | Yi Lu | Nathan Roberts | Roy H. Campbell

Abstract:

The performance evaluation of large file systems, such as storage and media

streaming, motivates scalable generation of representative traces. We focus on two key

characteristics of traces, popularity and temporal locality. The common practice of using a

system-wide distribution obscures per-object behavior, which is important for system

evaluation. We propose a model based on delayed renewal processes which, by sampling

interarrival times for each object, accurately reproduce popularity and temporal locality for

the trace. A lightweight version reduces the dimension of the model with statistical

clustering. It is workload-agnostic and object type-aware, suitable for testing emerging

workloads and what-if scenarios. We implemented a synthetic trace generator and validated

it using: (1) a Big Data storage (HDFS) workload from Yahoo!, (2) a trace from a feature

animation company, and (3) a streaming media workload. Two case studies in caching and

replicated distributed storage systems show that our traces produce application-level results

similar to the real workload. The trace generator is fast and readily scales to a system of 4.3

million files. It outperforms existing models in terms of accurately reproducing the

characteristics of the real trace.

Performance evaluation of component-based software systems: A survey

August 2010

Heiko Koziolek

Abstract:

Performance prediction and measurement approaches for component-based software

systems help software architects to evaluate their systems based on component performance

specifications created by component developers. Integrating classical performance models

such as queueing networks, stochastic Petri nets, or stochastic process algebras, these

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approaches additionally exploit the benefits of component-based software engineering, such

as reuse and division of work. Although researchers have proposed many approaches in this

direction during the last decade, none of them has attained widespread industrial use. On this

basis, we have conducted a comprehensive state-of-the-art survey of more than 20 of these

approaches assessing their applicability. We classified the approaches according to the

expressiveness of their component performance modelling languages. Our survey helps

practitioners to select an appropriate approach and scientists to identify interesting topics for

future research.

Database system performance evaluation models: A survey

October 2012

Rasha Osman | William J. Knottenbelt

Abstract:

Considerable research has been conducted into software system performance

modelling leading to various software performance engineering methodologies. Most of these

methodologies target the software architecture level of systems, with limited work

investigating the performance of database designs and systems. In this paper, we present a

categorization of queueing network performance models of database systems in the literature.

These models are classified based on the level of detail at which database transactions are

modelled. In addition, we present a survey and evaluation of performance evaluation

methodologies proposed to map database system specifications onto queueing network

models with appropriate workloads. The paper identifies future research directions that

should encourage a wider application of these methodologies in mainstream industrial

practice.

Security adoption and influence of cyber-insurance markets in heterogeneous networks

April 2014

Zichao Yang | John C.S. Lui

Abstract:

Hosts (or nodes) in the Internet often face epidemic risks such as virus and worm

attack. Despite the awareness of these risks and the importance of network/system security,

investment in security protection is still scare, and hence epidemic risk is still prevalent.

Deciding whether to invest in security protection is an interdependent process: security

investment decision made by one node can affect the security risk of others, and therefore

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affect their decisions also. The first contribution of this paper is to provide a fundamental

understanding on how network externality with node heterogeneity may affect security

adoption. Nodes make decisions on security investment by evaluating the epidemic risk and

the expected loss. We characterize it as a Bayesian network game in which nodes only have

the local information, e.g., the number of neighbors, and minimum common information,

e.g., degree distribution of the network. Our second goal is to study a new form of risk

management, called cyber-insurance. We investigate how the presence of a competitive

insurance market can affect the security adoption and show that if the insurance provider can

observe the protection level of nodes, the insurance market is a positive incentive for security

adoption if the protection quality is not very high. We also find that cyber-insurance is more

likely to be a good incentive for nodes with higher degree. Conversely, if the insurance

provider cannot observe the protection level of nodes, we verify that partial insurance can be

a non-negative incentive, improving nodes utility though not being an incentive.

Modeling and evaluating of typical advanced peer-to-peer botnet

February 2014S

Qinting Han | Wenqiu Yu | Yaoyao Zhang | Zhiwen Zhao

Abstract:

In this paper, we present a general model for an advanced peer-to-peer (P2P) botnet,

in which the performance of the botnet can be systematically studied. From the model, we

can derive five performance metrics to describe the robustness, security and efficiency of the

botnet. Additionally, we analyze the relationship between the performance metrics and the

model feature metrics of the botnet, and it is helpful to study the botnet under different model

feature metrics. Furthermore, the proposed model can be easily applied to other types of

botnets. Finally, taking the robustness and security into consideration, an optimization

scheme for designing an optimal P2P botnet is proposed.

Spectral expansion solution for a class of Markov models: application and comparison

with the matrix-geometric method

September 1995

Isi Mitrani | Ram Chakka

Abstract:

Many two-dimensional Markov models whose state space is a semi-infinite strip (i.e.

finite in one dimension and infinite in the other) can be solved efficiently by means of

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spectral expansion. This method and its application are described in the context of an

M/M//N queue with general breakdowns and repairs. The results of experiments aimed at

evaluating the relative merits of the spectral expansion and the matrix-geometric solutions are

also presented.

Machine learning algorithms for accurate flow-based network traffic classification:

Evaluation and comparison

June 2010

Murat Soysal | Ece Guran Schmidt

Abstract:

The task of network management and monitoring relies on an accurate

characterization of network traffic generated by different applications and network protocols.

We employ three supervised machine learning (ML) algorithms, Bayesian Networks,

Decision Trees and Multilayer Perceptrons for the flow-based classification of six different

types of Internet traffic including peer-to-peer (P2P) and content delivery (Akamai) traffic.

The dependency of the traffic classification performance on the amount and composition of

training data is investigated followed by experiments that show that ML algorithms such as

Bayesian Networks and Decision Trees are suitable for Internet traffic flow classification at a

high speed, and prove to be robust with respect to applications that dynamically change their

source ports. Finally, the importance of correctly classified training instances is highlighted

by an experiment that is conducted with wrongly labeled training data.

End-to-end protocols for Cognitive Radio Ad Hoc Networks: An evaluation study

September 2011

Marco Di Felice | Kaushik Roy Chowdhury | Wooseong Kim | Andreas Kassler | Luciano

Bononi

Abstract:

Cognitive radio ad hoc networks (CRAHNs) constitute a viable solution to solve the

current problems of inefficiency in the spectrum allocation, and to deploy highly

reconfigurable and self-organizing wireless networks. Cognitive radio (CR) devices are

envisaged to utilize the spectrum in an opportunistic way by dynamically accessing different

licensed portions of the spectrum. To this aim, most of the recent research has mainly focused

on devising spectrum sensing and sharing algorithms at the link layer, so that CR devices can

operate without interfering with the transmissions of other licensed users, also called primary

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users (PUs). However, it is also important to consider the impact of such schemes on the

higher layers of the protocol stack, in order to provide efficient end-to-end data delivery. At

present, routing and transport layer protocols constitute an important yet not deeply

investigated area of research over CRAHNs. This paper provides three main contributions on

the modeling and performance evaluation of end-to-end protocols (e.g. routing and transport

layer protocols) for CRAHNs. First, we describe NS2-CRAHN, an extension of the NS-2

simulator, which is designed to support realistic simulation of CRAHNs. NS2-CRAHN

contains an accurate yet flexible modeling of the activities of PUs and of the cognitive cycle

implemented by each CR user. Second, we analyze the impact of CRAHNs characteristics

over the route formation process, by considering different routing metrics and route discovery

algorithms. Finally, we study TCP performance over CRAHNs, by considering the impact of

three factors on different TCP variants: (i) spectrum sensing cycle, (ii) interference from PUs

and (iii) channel heterogeneity. Simulation results highlight the differences of CRAHNs with

traditional ad hoc networks and provide useful directions for the design of novel end-to-end

protocols for CRAHNs.

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CHAPTER III

RESEARCH METODOLOGY

3.1 RESEARCH

Research methodology is the way to systematically solve the research problem it may

be understood as a science of studying low-Research is done scientifically. If involves the

various data collection techniques the method of Analysis of data intergroup ting

summarization.

3.2 RESEARCH METHODOLOGY

I is finding a problem solution in particular t in a problem solution in a particular

problems for the organisations (or) company. Research methods it is way to systematically

solve the research methods it is way to systematically solve the research problem.

3.3 RESEARCH DESIGN

A research design is the arrangement of conditions for collection and analysis of data

in a manner that aims to combine relevances to the research purpose with economy in

procedure.

3.4 SAMPLING DESIGN

A research design is the arrangement of conditions for collection and analysis of data

in manner that aims to combine relevance to the procedure it is a simple random sampling in

SRI RAMCO SPINNNERS IN RAJAPALAYAM.

3.5 SAMPLING TECHNIQUE

It is market by prior formulation of specific research questions. The investigator

already knows a lot about the research problems.

3.6 DESCRIPTIVE RESEARCH

It is methods on specific information or specific information specific formulation of

research in particular problem solution.

22

3.7 SAMPLING

Sampling method is the process of learning about the population on the basis of

sample. Sample is that part of universe which we select for the purpose of investigation.

3.8 SAMPLE SIZE

No. of respondents 113

3.9 PERIOD OF STUDY

The survey was collected during the period of 45 days

3.10 DATA COLLECTION

Structural questionnaire should be used for collection of data. the data covers both,

Primary data

Secondary data

Primary data

Primary data has been collected in the form of questionnaire

Secondary data

Secondary data sources like catalogue of the company and various internet sites such

as www.ramco.group.com and www.google.com has been used.

Percentage

Chi-square

ANOVA

F-test (or)t-test

Rank correlation

After collection of data, the data, the data should be analysed with the help of (SPSS

16.0) above tools.

23

3.11 LIMITATION OF THE STUDY

The study is conducted only for the employees with special reference in Sri

Ramco spinners.

As the numbers of question is more the respondents were not ready to spend

much of their time.

Respondents may not disclose their honest and opinion about management.

Since the project period was held during the month of march, the financial

year and the employees were very busy and had delay in giving the datas

24

CHAPTER IV

ANALYSIS AND INTERPRETATION

4.1 ANANLYSIS

After the data have been collected, the research turns to the task of analysising them.

The analysis of data requires a number of closely related operations such as establishment of

raw data through coding tabulation and then drawing statistical inferences.

Analysis work after tabulation is generally based on the computation of the various

percentages, co efficient etc, by applying various defined statistical formula.

4.2 INTERPRETATION

Inter predation refers to the task of drawing inferences from the collected facts after

an analytical and /or experimental study. The task of interpretation has two major aspects.

1. The effort to establish continuity in research through linking the result of a given

study with those of another.

2. Establishment of some experience effort.

25

4.3 PERCENTAGE ANALYSIS

Table 4.1

CLASSIFICATION OF THE RESPONDENTS BASED ON THEIR GENDER

(Sources: Primary Data)

S. No Particulars No. of Respondents Percent%

1 Male 58 51.33

2 Female 55 48.67

Total 113 100%

26

Chart 4.1

CLASSIFICATION OF THE RESPONDENTS BASED ON THEIR GENDER

INTERPRETATION

Table 4.1 shows that various classification of respondent according to gender. Here

for the entire respondents 58 are male and remaining 55% are female.

51.33

48.67

Male Female

Percentage

27

TABLE 4.2

CLASSIFICATION OF THE RESPONDENTS BASED ON THEIR AGE


S.No Particulars No. of Respondents Percent%

1 20-30 13 11.5

2 31-40 45 39.8

3 41-50 43 38.1

4 Above 50 12 10.6

Total 113 100%

28

Chart 4.2

CLASSIFICATION OF THE RESPONDENTS BASED ON THEIR AGE

INTERPRETATION

Table 4.2 shows that various classification of respondents according to age. Her for

the entire respondents majority 39.8% respondents are 31-40, are 38.1 respondents are 41-

50, 11.5% respondents are 20-30 and remaining 10.6% are above 50.

11.5

39.838.1

10.6

20-30 31-40 41-50 Above 50

Percentage

29

Table 4.3

CLASSIFICATION OF THE RESPONDENTS BASED ON THEIR DEPARTMENT


S.No Particulars No. of Respondents Percent

1 Spinning 13 11.5

2 Winding 22 19.5

3 Mixing 20 17.7

4 Simplex 19 16.8

5 Cone Winding 24 21.2

6 Packing 15 13.3

Total 113 100

30

Chart 4.3

CLASSIFICATION OF THE RESPONDENTS BASED ON THEIR DEPARTMENT

INTERPRETATION

Table 4.3 shows that various classification of respondents according to department.

Her for the entire respondents cone winding21.2%, respondents are winding 19.5%, mixing

17.7%,simplex 16.8%,packing 13.3%,and remaining spinning11.5%.

11.5

19.517.5 16.8

21.2

13.3

Spinning Winding Mixing Simplex Cone Winding Packing

Percentage

31

Table 4.4

CLASSIFICATION OF THE RESPONDENTS BASED ON THEIR

MARITAL STATUS


S.No

Particulars No. of Respondents Percent

1 Married 55 48.7

2 Unmarried 58 51.3

Total 113 100%

32

Chart 4.4


MARITAL STATUS

INTERPRETATION

Table 4.4 shows that various classification of respondents according to marital status.

Her for the entire respondents majority 51.3% are unmarried, and remaining 48.7% are

married.

48.7

51.3

Married Unmarried

Percentage

33

Table 4.5


EDUCATION QUALIFICATION



1 School 59 52.2

2 Diploma 51 45.1

3 UG 3 2.7

4 PG 0 0

Total 113 100%

34

Chart 4.5


EDUCATION QUALIFICATION

INTERPRETATION

Table4.5 shows that various classification of respondents according to education

qualification. Her for the entire respondents majority 52.2% respondents are school, are

diploma 45.1% respondents are UG,2.7% ,and remaining 0% are PG

52.2

45.1

2.70

School Diplomo UG PG

Percentage

35

Table 4.6

CLASSIFICATION OF THE RESPONDENTS BASED ON THEIR EXPERIENCE



1 Below 5 40 35.4

2 5 to 10 50 44.3

3 10 to 15 11 9.7

4 Above 15 12 10.6

Total 113 100%

36

Chart 4.6

CLASSIFICATION OF THE RESPONDENTS BASED ON THEIR EXPERIENCE

INTERPRETATION

Table 4.6 shows that various classification of respondents according to experience.

Her for the entire respondents 44.3% are 5-10,35.4% respondents are below 5, are

10.6%respondents are above 15 and remaining 9.7% are above 15.

35.4

44.3

9.7 10.6

Below 5 Category 2 10 To 15 Above 15

Percentage

37

Table .4.7


MONTHLY INCOME


S.No Particulars Frequency Percent

1 Below 3000 24 21.2

2 3000 to 6000 40 35.4

3 6000 to 9000 10 8.9

4 9000 - 12000 22 19.5

5 Above 12000 17 15.0

Total 113 100%

38

Chart 4.7


MONTHLY INCOME

INTERPRETATION

Table 4.7 shows that various classification of respondents according to income. Her

for the entire respondents below 3000-6000, 35.4% respondents are below 3000,21.2% are

19.5% respondents are 9000-12000,15.0% respondents are above12000,and remaining 8.9%

are 6000-9000.

21.2

35.4

8.9

19.5

15

Below 3000 3000 to 6000 6000 to 9000 9000 - 12000 Above 12000

Percentage

39

Table 4.8

CLASSIFICATION OF THE RESPONDENTS BASED ON THEIR COMPANY


S.No Particulars No. of Respondents Percentage

1 Rating Scale 15 13.3

2 MBO 33 29.3

3 Grade system 23 20.4

4 360 and Measurement 23 20.4

5 Others 19 16.8

Total 113 100%

40

Chart 4.8

CLASSIFICATION OF THE RESPONDENTS BASED ON THEIR COMPANY

INTERPRETATION

Table 4.8 shows that various classification of respondents according to respondents

based on their company. Her for the entire respondents 29.3% respondents are MBO, 20.4%

respondents are grade system,20.4% respondents are 360 and measurement, and respondents

are 16.8% and others and remaining 13.3% are rating scale.

13.3

29.3

20.4 20.4

16.8

Rating Scale MBO Grade system 360 and Measurement

Others

Percentage

41

Table 4.9

CLASSIFICATION OF THE RESPONDENTS IN PERFORMANCE IN THE

ORGANIZATION



1 Supervisor 33 29.2

2 Department Head 32 28.3

3 Peers 15 13.3

4 Supadinate 33 29.2

Total 113 100%

42

Chart 4.9

CLASSIFICATION OF THE RESPONDENTS IN PERFORMANCE IN THE

ORGANIZATION

INTERPRETATION

Table 4.9 shows that various classification of respondents performance in the

organization. Her for the entire respondents majority 29.2% supervisior are 29.2%

respondents are supadinate, 28.3% respondents are department head and remaining 13.3% are

peers.

29.2 28.3

13.3

29.2

Supervisor Department Head Peers Supadinate

Percentage

43

Table 4.10

CLASSIFICATION OF THE RESPONDENTS EFFECTIVENESS OF THE

APPRAISAL SYSTEM IN SRI RAMCO SPINNERS



1 Effective 52 46.0

2 Ineffective 61 54.0

Total 113 100%

44

Chart 4.10

CLASSIFICATION OF THE RESPONDENTS EFFECTIVENESS OF THE

APPRAISAL SYSTEM IN SRI RAMCO SPINNERS

INTERPRETATION

Table 4.10 shows that various classification of respondents according to Effectiveness

of the appraisal system in Sri Ramco spinners. Her for the entire respondents majority 54.0%

respondents ineffective, and remaining 46.0% are effective.

46

54

Effective Ineffective

Percentage

45

Table 4.11

CLASSIFICATION OF THE RESPONDENTS SYSTEM ACTOR IN JOINING IN

THE ORGANIZATION



1 Within 1 Month 25 22.1

2 At the time joining 48 42.5

3 At The End Of Year 31 27.4

4 If Any Other 9 8.0

Total 113 100%

46

Chart 4.11

CLASSIFICATION OF THE RESPONDENTS SYSTEM ACTOR IN JOINING

IN THE ORGANIZATION

INTERPRETATION

Table 4.11 shows that various classification of respondents according to respondents

based on their company. Her for the entire respondents 42.5% respondents are at the time

joining, 27.4% respondents are at the end of the year ,22.1% respondents are within 1 month,

, and remaining 8% are if any other.

22.1

42.5

27.4

9

Within 1 Month At the time joining at the end of year if any other

Percentage

47

Table 4.12

PURPOSE USING PERFORMANCE APPRAISAL IN YOUR COMPANY


S. No. Particulars No. of Respondents Percent

1 Fixing the Salary 40 35.39823

2 Promotion 46 40.70796

3 Training 10 8.849558

4 Productivity 17 15.04425

Total 113 100.0000

48

Chart 4.12

PURPOSE USING PERFORMANCE APPRAISAL IN YOUR COMPANY

INTERPRETATION

Table 4.12 shows that various classification of respondents purpose using

performance appraisal in your company. Her for the entire respondents 40.70% respondents

are promotion, 35.39% respondents are fixing the salary,15.04% respondents are

productivity, and remaining 8.84% are training.

0

5

10

15

20

25

30

35

40

45

50

Fixing the Salary Promotion Training Productivity

Percentage

49

Table 4.13

FREQUENCY INTERVAL OF PERFORMANCE APPRAISAL IN

YOUR COMPANY



1 Quarterly 34 29.05983

2 Half 48 41.02564

3 Annualy 31 26.49573

Total 113 100.0000

50

Chart 4.13

FREQUENCY INTERVAL OF PERFORMANCE APPRAISAL

IN YOUR COMPANY

INTERPRETATION

Table 4.13 shows that various classification of respondents frequency interval of

performance appraisal in your company. Her for the entire respondents 41.02% respondents

are half, 29.05% respondents are quarterly, ,and remaining 26.49% are annually.

0

10

20

30

40

50

60

Quarterly Half Annualy

percentage

51

Table 4.14

FEEL ABOUT THE PERFORMANCE APPRAISAL SYSTEM



1 Strongly Agree 24 20.51282

2 Agree 11 9.401709

3 Neutral 13 11.11111

4 Disagree 30 25.64103

5 Strongly disagree 35 29.91453

Total 113 100.0000

52

Chart 4.14

FEEL ABOUT THE PERFORMANCE APPRAISAL SYSTEM

INTERPRETATION

Table 4.14 shows that various classification of respondents Feel about the performance

appraisal system. Her for the entire respondents 29.91% respondents are strongly disagree,

25.64% respondents are disagree,20.5% respondents are strongly agree, and respondents are

11.11% and others, and remaining 9.04% are neural.

0

5

10

15

20

25

30

35

40

Strongly Agree Agree Netural Disagree Strongly disagree

Percentage

53

Table 4.15

PERFORMANCE APPRAISAL SYSTEM IS SATISFIED


S. No. Particulars Frequency Percent


2 Agree 48 41.02564

3 Neutral 24 20.51282

4 Disagree 9 7.692308


Total 113 100.0000

54

CHART 4.15

PERFORMANCE APPRAISAL SYSTEM IS SATISFIED

INTERPRETATION

Table4.15 shows that various classification of respondents performance appraisal

system is satisfied. Her for the entire respondents 41.02% respondents are agree, 20.51%

respondents are strongly agree,20.51% respondents are neutral, and respondents are 7.69%

and disagree and remaining 6.83% are strongly disagree.

0

5

10

15

20

25

30

35

40


percentage

55

Table 4.16

ACCESSIBLE AND AVAILABLE TO DISCUSS MY SUGGESTION,

QUESTIONNAIRE




2 Agree 49 41.88034

3 Neutral 10 8.547009

4 Disagree 12 10.25641


Total 113 100.0000

56

Chart 4.16

ACCESSIBLE AND AVAILABLE TO DISCUSS MY SUGGESTION,

QUESTIONNAIRE

INTERPRETATION

Table 4.16 shows that various classification of respondents accessable and available to

discuss my suggestion, questionnaire. Her for the entire respondents 41.88% respondents are

agree, 26.49% respondents are strongly agree,10.25% respondents are disagree, and

respondents are 9.40% and strongly disagree and remaining 8.54% are neutral.

0

10

20

30

40

50

60


percentage

57

Table 4.17

PROVIDE SUPPORT AND ENCOURAGEMENT TO ME IN AREA IN I WORKING

TO IMPROVE ARE DEVELOP




2 Agree 37 31.62393

3 Neutral 22 18.80342

4 Disagree 12 10.25641


Total 113 100.0000

58

Chart 4.17

PROVIDE SUPPORT AND ENCOURMENT TO ME IN AREA IN WORKING TO

IMPROVE ARE DEVELOP

INTERPRETATION

Table 4.17 shows that various classification of respondents. Provide support and

encouragement to me in area in I working to improve are develop. Her for the entire

respondents 31.62% respondents are agree, 22.22% respondents are strongly agree,18.80%

respondents are neutral, and respondents are 13.67% and strongly disagree and remaining

10.25% are disagree.

0

10

20

30

40

50

60


percentage

59

Table 4.18

AGREED THE LOW DISAGREE OF COMMUNICATION GAP




2 Agree 21 18.58407

3 Neutral 15 13.27434

4 Disagree 34 30.0885


Total 113 100.0000

60

Chart 4.18

AGREED THE LOW DISAGREE OF COMMUNICATION GAP

INTERPRETATION

Table 4.18 shows that various classification of respondents agreed the low degree of

communication gap. Her for the entire respondents 30.08% respondents are disagree, 24.77%

respondents are strongly agree,18.58% respondents are agree, and respondents are 13.27%

and neutral and remaining 13.27% are strongly disagree.

0

5

10

15

20

25

30

35

40


percentage

61

Table 4.19

MOTIVATING THE PERFORMANCE APPRAISAL SYSTEM IN YOUR

ORGANISATION




2 Agree 20 17.69912

3 Neutral 8 7.079646

4 Disagree 31 27.43363


Total 113 100.0000

62

Chart 4.19

MOTIVATING THE PERFORMANCE APPRAISAL SYSTEM IN

YOUR ORGANISATION

INTERPRETATION

Table 4.19 shows that various classification of respondents motivating the

performance appraisal system in your organisation. Her for the entire respondents 30.08%

respondents are strongly agree, 27.43% respondents are disagree,17.69% respondents are

agree, and respondents are 17.69% and strongly disagree, and remaining 7.07% are neutral.

0

5

10

15

20

25

30

35

40


Percentage

63

Table 4.20

APPRAISAL SYSTEM ABLE TO SHOW THE PROGRESS ONE HAS MODE IN

ORDER TO HIS/HER




2 Agree 15 12.82051

3 Neutral 25 21.36752

4 Disagree 25 21.36752


Total 113 100.0000

64

Chart 4.20

APPRAISAL SYSTEM ABLE TO SHOW THE PROGRESS ONE HAS MODE IN

ORDER TO HIS/HER

INTERPRETATION

Table 4.20 shows that various classification of respondent appraisal system able to

show the progress one has mode in order to his/her. Her for the entire respondents 21.36%

respondents are strongly agree, 21.36% respondents are Neutral,21.36% respondents are

disagree, and respondents are 19.65% and strongly disagree and remaining 12.82% are

agree.

0

5

10

15

20

25

30


Percentage

65

ANALYSIS USING CHI-SQUARE

EDUCATIONAL QUALIFICATION * PERFORMANCE

Count

PERFORMANCE

Total

5

4

3 2

1

EDUCATIONAL

QUALIFICATION

School

7

6

8

12

26

59

Diplomo

18

2

3

19

9

51

UG

2

1

3

PG

0

Total

25

10

12

31

35

113

66

Chi-Square Test

Frequencies

Observed N Expected N Residual

1 40 28.3 11.8

2 50 28.3 21.8

3 11 28.3 -17.3

4 12 28.3 -16.3

Total 113

Test Statistics

Chi-Square 41.513a

df 3

Asymp. Sig. .000

a. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell

frequency is 28.3.

67

ANALYSIS USING CHI-SQUARE

YEARS OF EXPERIENCE * PERFORMANCE

Count

PERFORMANCE

Total

5

4

3 2

1

YEARS OF

EXPERIENCE

Below 5

11

4

3

12

10

40

5 10

8

3

4

15

20

50

10 15

4

1

2

4

0

11

Above 15

2

2

3

0

5

12

Total

25

10

12

31

35

113

68

Chi-Square Test

Frequencies

Observed N Expected N Residual

1 40 28.3 11.8

2 50 28.3 21.8

3 11 28.3 -17.3

4 12 28.3 -16.3

Total 113

Test Statistics

6 15

Chi-Square

41.513a

46.336b

Df 3 4

Asymp. Sig. .000 .000

a. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell

frequency is 28.3.

b. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell

frequency is 22.6.

69

ANOVA

ANOVA

Sum of Squares df Mean Square F Sig.

Age

Between Groups

4.068

1

4.068

6.092

.015

Within Groups 74.126 111 .668

Total 78.195 112

Marital

Status

Between Groups

4.907

1

4.907

23.355

.000


Total 28.230 112

Experie

nce

Between Groups

.087

1

.087

.098

.755


Total 98.779 112

70

ANOVA

Sum of Squares df Mean Square F Sig.

Perfor

mance

Between Groups

31.975

1

31.975

15.421

.000

Within Groups 230.149 111 2.073

Total 262.124 112

Satisfac

tion

Between Groups

.086

1

.086

.068

.795

Within Groups 140.303 111 1.264

Total 140.389 112

Discuss

Between Groups

19.599

1

19.599

13.863

.000

Within Groups 156.932 111 1.414

Total 176.531 112

71

Weighted average

S.No

Particular

Number of

respondents

Weight

W

WX

1

2

3

4

5

Highly satisfied

Satisfied

Moderate

Dissatisfied

Highly dissatisfied

24

12

5

47

25

5

4

3

2

1

120

48

15

94

25

Total

113

15

302

Weighted average = XW = WX / W

= 302/113

= 2.67257

72

T-Test

One-Sample Statistics

N Mean Std. Deviation Std. Error Mean

1 113 1.49 .502 .047

One-Sample Test

Test Value = 0

95% Confidence Interval of the

Difference

T df Sig. (2-tailed)

Mean

Difference Lower Upper

1

31.479

112

.000

1.487

1.39

1.58

73

Correlation

Correlations

1 2

1

Pearson Correlation

1

.228*

Sig. (2-tailed) .015

N 113 113

2

Pearson Correlation

.228*

1

Sig. (2-tailed) .015

N 113 113

*. Correlation is significant at the 0.05 level (2-tailed).

Correlations

1 2

Spearman's rho

1

Correlation Coefficient

1.000

.186*

Sig. (2-tailed) . .048

N 113 113

2


.186*

1.000

Sig. (2-tailed) .048 .

N 113 113

74

Correlations

1 2

Spearman's rho

1


1.000

.186*

Sig. (2-tailed) . .048

N 113 113

2


.186*

1.000

Sig. (2-tailed) .048 .

N 113 113

*. Correlation is significant at the 0.05 level (2-tailed).

75

CHAPTER V

FINDINGS AND SUGGESTIONS

5.1 FINDINGS

1. Most of the male workers are worked in the company.

2. Most of the respondents (31-40) are years age group of workers in this

company.

3. Most of the respondents are worked in the cone winding.

4. Most of the respondents are unmarried worker in this company.

5. Most of the respondents are qualified school.

6. Most of the respondents are experienced (5-10) years.

7. Mostly of the respondents are getting Rs.3000-6000 only our monthly salary

income.

8. Mostly of the respondents are MBO respondents based on their company.

9. Most of the respondents are supervisor respondents in performance in the

organization.

10. Mostly of the respondents are ineffective effectiveness of the appraisal system

in sri Ramco spinners.

11. Mostly of the respondents are at the time joining are respondents system actor

in joining in the organization.

12. Most of the respondents are promotion are performance appraisal in your

company.

13. Most of the respondents are half frequency interval of performance appraisal

in your company.

14. Most of the respondents are strongly disagree are feel about the performance

appraisal system.

15. Most of the respondents are agree with performance appraisal system is

satisfied.

16. Most of the respondents are agree with accessible and available to discuss my

suggestion, questionnaire.

17. Most of the respondents are agree with provide support and encourage to me

in area in I working to improve are develop.

76

18. Most of the respondents are disagree with agreed with low disagree of

communication gap.

19. Most of the respondents are strongly agree with motivating performance

appraisal system in your organization.

77

5.2. SUGGESTIONS

1. The employees have to develop them to accept the changes in their working

conditions.

2. There also exists a companies provide extra promotional activities to the

employees performance appraisal.

3. It the company has o give the work load on the basis on the abilities of the

employees. It will improve their performance.

4. The employees have to improve their trust and confidence with their

management.

5. The employees are expected more to feel freely to tell their opinion to their

boss. It the company allows this it will improve the employees performance

appraisal.

78

5.3 CONCLUTSION

The project titled a study on employee performance appraisal in made the researcher

to experience a lot. Each interview was a new challenge of researcher and with this study the

company can identify the employees job satisfactions as well as job involvement. These

employees are satisfied then the company will survey move towards its ultimate goal with in

a limited period of time.

79

BIBLIOGRAPHY

Books:

o Human resource management - C.B Gubta

o Human resource management fillippa

o Business statistics R.S.N Pillai

Websites:

www.sriramcospinners.com

www.wikipedia.com

www.sriramcoproduct.com

80

A Study on employees performance appraisal towards

Sri Ramco spinners at Rajapalayam

Questionnaire

1. Name :

2. Gender :

a) Male b) Female

3. Age

a) 20-30 b) 31-40 c) 41-50 d) Above 50

4. Department

a) spinning b) winding c) mixing

d) Simplex e) cone winding f) others

5. Marital status

a) Married b) Unmarried

6. Educational qualification

a) School b) Diplomo c) under graduation

d) post graduation

7. Experience

a) Below 5 b) 5-10years c) 10-15 years

d) Above 15 years

8. Monthly Income

a) Below 3000 b) 3000- 6000 c) 6000- 9000

d) 9000- 12000 e) Above 12000

9. What type performance appraisal system is used in your company?

a) Rating scale b) MBO (many by objective) c) grade system

d) 360and measurement system e) others

10) Who is appraising in your performance in the organization?

a) Supervisor b) Department head c) peers d) supadinate

11) Opinion about the effectiveness of the appraisal system in Sri Ramco spinners?

a) Effective b) Ineffective

81

12) When did you come to know about system actor in joining in the organization?

a) With in the 1 month b) at the time joining c) at the end of year d) if any

other please specify

13) The main purpose using performance appraisal in your company?

a) Fixing the salary b) promotion c) training & development d) productivity

14) What is the frequency interval of performance appraisal in your company?

a) Quarterly b) half yearly c) annually

Rate on your opinion of 1-5 to indicate your option.

1. Strongly agree 2. Agree 3. Natural 4. Disagree 5. Strongly disagree

Measurement Items

5

4

3

2

1

1) how do you feel about the performance appraisal system

2) are your about the performance appraisal system is

satisfied

3) Makes times to me accessible and available to discuss my

suggestion, questionnaire.

4) Provide support and encouragement to me in area in I

working to improve are develop.

5) You have agreed the low degree of communication

gap.

6) Are you motivating the performance appraisal system in

your organization.

Documents

A STUDY ON EMPLOYEE’S PERFORMANCE APPRAISAL TOWARDS SRI RAMCO SPINNERS AT RAJAPALAYAM