Transformer Testing | Type Test and Routine Test of Transformer

Under Electrical Transformer


 

 







For confirming the specifications and performances of an electrical power transformer it has to go through numbers of testing procedures. Some tests are done at manufacturer premises before delivering the transformer. Mainly two types of transformer testing are done at manufacturer premises- type test of transformer and routine test of transformer. In addition to that some transformer tests are also carried out at the consumer site before commissioning and also periodically in regular & emergency basis through out its service life.

Type of Transformer Testing

Tests done at factory

1. Type tests
2. Routine tests
3. Special tests

Tests done at site

1. Pre-commissioning tests
2. Periodic/condition monitoring tests
3. Emergency tests

Type Test of Transformer

To prove that the transformer meets customer’s specifications and design expectations, the transformer has to go through different testing procedures in manufacturer premises. Some transformer tests are carried out for confirming the basic design expectation of that transformer. These tests are done mainly in a prototype unit not in all manufactured units in a lot. Type test of transformer confirms main and basic design criteria of a production lot.

Routine Tests of Transformer

Routine tests of transformer is mainly for confirming operational performance of individual unit in a production lot. Routine tests are carried out on every unit manufactured.

Special Tests of Transformer

Special tests of transformer is done as per customer requirement to obtain information useful to the user during operation or maintenance of the transformer.

Pre Commissioning Test of Transformer

In addition to these, the transformer also goes through some other tests, performed on it, before actual commissioning of the transformer at site. The transformer testing performed before commissioning the transformer at site is called pre-commissioning test of transformer. These tests are done to assess the condition of transformer after installation and compare the test results of all the low voltage tests with the factory test reports.
Type tests of transformer includes

1. Transformer winding resistance measurement
2. Transformer ratio test.
3. Transformer vector group test.
4. Measurement of impedance voltage/short circuit impedance (principal tap) and load loss (Short circuit test).
5. Measurement of no load loss and current (Open circuit test).
6. Measurement of insulation resistance.
7. Dielectric tests of transformer.
8. Temperature rise test of transformer.
9. Tests on on-load tap-changer.
10. Vacuum tests on tank and radiators.

Routine tests of transformer include

1. Transformer winding resistance measurement.
2. Transformer ratio test.
3. Transformer vector group test.
4. Measurement of impedance voltage/short circuit impedance (principal tap) and load loss (Short circuit test).
5. Measurement of no load loss and current (Open circuit test)
6. Measurement of insulation resistance.
7. Dielectric tests of transformer.
8. Tests on on-load tap-changer.
9. Oil pressure test on transformer to check against leakages past joints and gaskets.

That means Routine tests of transformer include all the type tests except temperature rise and vacuum tests. The oil pressure test on transformer to check against leakages past joints and gaskets is included.

Special Tests of transformer include

1. Dielectric tests.
2. Measurement of zero-sequence impedance of three-phase transformers
3. Short-circuit test.
4. Measurement of acoustic noise level.
5. Measurement of the harmonics of the no-load current.
6. Measurement of the power taken by the fans and oil pumps.
7. Tests on bought out components / accessories such as buchhloz relay, temperature indicators, pressure relief devices, oil preservation system etc.

Transformer Winding Resistance Measurement

Transformer winding resistance measurement is carried out to calculate the I²R losses and to calculate winding temperature at the end of a temperature rise test. It is carried out as a type test as well as routine test. It is also done at site to ensure healthiness of a transformer that is to check loose connections, broken strands of conductor, high contact resistance in tap changers, high voltage leads and bushings etc.There are different methods for measuring of transformer winding, likewise
♣ Current voltage method of measurement of winding resistance. 

♣ Bridge method of measurement of winding resistance.       

  ♠ Kelvin bridge method of Measuring Winding Resistance.       

  ♠ Measuring winding resistance by Automatic Winding Resistance Measurement Kit.
NB:- Transformer winding resistance measurement shall be carried out at each tap.

Transformer Ratio Test

The performance of a transformer largely depends upon perfection of specific turns or voltage ratio of transformer. So transformer ratio test is an essential type test of transformer. This test also performed as routine test of transformer. So for ensuring proper performance of electrical power transformer, voltage and turn ratio test of transformer one of the vital tests.The procedure of transformer ratio test is simple. We just apply three phase 415 V supply to HV winding, with keeping LV winding open. The we measure the induced voltages at HV and LV terminals of transformer to find out actual voltage ratio of transformer. We repeat the test for all tap position separately.

Magnetic Balance Test of Transformer

Magnetic balance test of transformer is conducted only on three phase transformers to check the imbalance in the magnetic circuit.

Procedure of Magnetic Balance Test of Transformer

1. First keep the tap changer of transformer in normal position.
2. Now disconnect the transformer neutral from ground.
3. Then apply single phase 230 V AC supply across one of the HV winding terminals and neutral terminal.
4. Measure the voltage in two other HV terminals in respect of neutral terminal.
5. Repeat the test for each of the three phases.

In case of auto transformer, magnetic balance test of transformer should be repeated for LV winding also.
There are three limbs side by side in a core of transformer. One phase winding is wound in one limb. The voltage induced in different phases depends upon the respective position of the limb in the core. The voltage induced in different phases of transformer in respect to neutral terminals given in the table below.

	Left side phase	Central phase	Right side phase
	AN	BN	CN
Voltage applied at left side phase	230 V	180 V	50 V
Voltage applied at central phase	115 V	230 V	115 V
Voltage applied at right side phase	50 V	180 V	230 V

Magnetizing Current Test of Transformer

Magnetizing current test of transformer is performed to locate defects in the magnetic core structure, shifting of windings, failure in turn to turn insulation or problem in tap changers. These conditions change the effective reluctance of the magnetic circuit, thus affecting the current required to establish flux in the core.

1. First of all keep the tap changer in the lowest position and open all IV & LV terminals.
2. Then apply three phase 415 V supply on the line terminals for three phase transformers and single phase 230 V supply on single phase transformers.
3. Measure the supply voltage and current in each phase.
4. Now repeat the magnetizing current test of transformertest with keeping tap changer in normal position.
5. And repeat the test with keeping the tap at highest position.

Generally there are two similar higher readings on two outer limb phases on transformer core and one lower reading on the centre limb phase, in case of three phase transformers. An agreement to within 30% of the measured exciting current with the previous test is usually considered satisfactory. If the measured exciting current value is 50 times higher than the value measured during factory test, there is likelihood of a fault in the winding which needs further analysis.
Caution: This magnetizing current test of transformer is to be carried out before DC resistance measurement.

Vector Group Test of Transformer

In three phase transformer, it is essential to carry out a vector group test of transformer. Proper vector grouping in a transformer is an essential criteria for parallel operation of transformers.There are several internal connection of three phase transformer are available in market. These several connections gives various magnitudes and phase of the secondary voltage; the magnitude can be adjusted for parallel operation by suitable choice of turn ratio, but the phase divergence can not be compensated. So we have to choose those transformer for parallel operation whose phase sequence and phase divergence are same. All the transformers with same vector ground have same phase sequence and phase divergence between primary and secondary. So before procuring one electrical power transformer, one should ensure the vector group of the transformer, whether it will be matched with his or her existing system or not. The vector group test of transformer confirms his or her requirements.

Insulation Resistance Test or Megger Test of Transformer

Insulation resistance test of transformer is essential type test. This test is carried out to ensure the healthiness of over all insulation system of an electrical power transformer.

Procedure of Insulation Resistance Test of Transformer

1. First disconnect all the line and neutral terminals of the transformer.
2. Megger leads to be connected to LV and HV bushing studs to measure insulation resistance IR value in between the LV and HV windings.
3. Megger leads to be connected to HV bushing studs and transformer tank earth point to measure insulation resistance IR value in between the HV windings and earth.
4. Megger leads to be connected to LV bushing studs and transformer tank earth point to measure insulation resistance IR value in between the LV windings and earth.

NB : It is unnecessary to perform insulation resistance test of transformer per phase wise in three phase transformer. IR values are taken between the windings collectively as because all the windings on HV side are internally connected together to form either star or delta and also all the windings on LV side are internally connected together to form either star or delta.
Measurements are to be taken as follows:
For auto transformer: HV-IV to LV, HV-IV to E, LV to E. For two winding transformer: HV to LV, HV to E, LV to E. Three winding transformer: HV to IV, HV to LV, IV to LV, HV to E, IV to E, LV to E.
Oil temperature should be noted at the time of insulation resistance test of transformer. Since the IR value of transformer insulating oil may vary with temperature. IR values to be recorded at intervals of 15 seconds, 1 minute and 10 minutes.
With the duration of application of voltage, IR value increases. The increase in IR is an indication of dryness of insulation.
Absorption coefficient = 1 minute value/ 15 secs. value.
Polarization index = 10 minutes value / 1 minute value.

Magnetizing Current Test of Transformer

Magnetizing current test of transformer is performed to locate defects in the magnetic core structure, shifting of windings, failure in turn to turn insulation or problem in tap changers. These conditions change the effective reluctance of the magnetic circuit, thus affecting the current required to establish flux in the core.

1. First of all keep the tap changer in the lowest position and open all IV & LV terminals.
2. Then apply three phase 415 V supply on the line terminals for three phase transformers and single phase 230 V supply on single phase transformers.
3. Measure the supply voltage and current in each phase.
4. Now repeat the magnetizing current test of transformertest with keeping tap changer in normal position.
5. And repeat the test with keeping the tap at highest position.

Generally there are two similar higher readings on two outer limb phases on transformer core and one lower reading on the centre limb phase, in case of three phase transformers. An agreement to within 30% of the measured exciting current with the previous test is usually considered satisfactory. If the measured exciting current value is 50 times higher than the value measured during factory test, there is likelihood of a fault in the winding which needs further analysis.
Caution: This magnetizing current test of transformer is to be carried out before DC resistance measurement.

Vector Group Test of Transformer

In three phase transformer, it is essential to carry out a vector group test of transformer. Proper vector grouping in a transformer is an essential criteria for parallel operation of transformers.There are several internal connection of three phase transformer are available in market. These several connections gives various magnitudes and phase of the secondary voltage; the magnitude can be adjusted for parallel operation by suitable choice of turn ratio, but the phase divergence can not be compensated. So we have to choose those transformer for parallel operation whose phase sequence and phase divergence are same. All the transformers with same vector ground have same phase sequence and phase divergence between primary and secondary. So before procuring one electrical power transformer, one should ensure the vector group of the transformer, whether it will be matched with his or her existing system or not. The vector group test of transformer confirms his or her requirements.

Insulation Resistance Test or Megger Test of Transformer

Insulation resistance test of transformer is essential type test. This test is carried out to ensure the healthiness of over all insulation system of an electrical power transformer.

Procedure of Insulation Resistance Test of Transformer

1. First disconnect all the line and neutral terminals of the transformer.
2. Megger leads to be connected to LV and HV bushing studs to measure insulation resistance IR value in between the LV and HV windings.
3. Megger leads to be connected to HV bushing studs and transformer tank earth point to measure insulation resistance IR value in between the HV windings and earth.
4. Megger leads to be connected to LV bushing studs and transformer tank earth point to measure insulation resistance IR value in between the LV windings and earth.

NB : It is unnecessary to perform insulation resistance test of transformer per phase wise in three phase transformer. IR values are taken between the windings collectively as because all the windings on HV side are internally connected together to form either star or delta and also all the windings on LV side are internally connected together to form either star or delta.
Measurements are to be taken as follows:
For auto transformer: HV-IV to LV, HV-IV to E, LV to E. For two winding transformer: HV to LV, HV to E, LV to E. Three winding transformer: HV to IV, HV to LV, IV to LV, HV to E, IV to E, LV to E.
Oil temperature should be noted at the time of insulation resistance test of transformer. Since the IR value of transformer insulating oil may vary with temperature. IR values to be recorded at intervals of 15 seconds, 1 minute and 10 minutes.
With the duration of application of voltage, IR value increases. The increase in IR is an indication of dryness of insulation.
Absorption coefficient = 1 minute value/ 15 secs. value.
Polarization index = 10 minutes value / 1 minute value.

Dielectric Tests of Transformer

Dielectric tests of transformer is one kind of insulation test. This test is performed to ensure the expected over all insulation strength of transformer. There are several test performed to ensure the required quality of transformer insulation, dielectric test is one of them. Dielectric tests of transformer is performed in two different steps, first one called Separate source voltage withstand test of transformer, where a single phase power frequency voltage of prescribed level, is applied on transformer winding under test for 60 seconds while the other windings and tank are connected to the earth and it is observed that whether any failure of insulation occurs or not during the test. Second one is induced voltage test of Transformer where, three phase voltage, twice of rated secondary voltage is applied to the secondary winding for 60 second by keeping the primary of the transformer open circuited. The frequency of the applied voltage should be double of power frequency too. Here also if no failure of insulation, the test is successful. In addition to dielectric tests of transformer there are other type test for checking insulation of transformer, such as lightning impulse test, switching impulse test and partial discharge test.

Induced Voltage Test of Transformer

The induced voltage test of transformer is intended to check the inter turn and line end insulation as well as main insulation to earth and between windings-

1. Keep the primary winding of transformer open circuited.
2. Apply three phase voltage to the secondary winding. The applied voltage should be twice of rated voltage of secondary winding in magnitude and frequency.
3. The duration of the test shall be 60 second.
4. The test shall start with a voltage lower than 1/3 the full test voltage, and it shall be quickly increased up to desired value.

The test is successful if no break down occurs at full test voltage during test.

Temperature Rise Test of Transformer

Temperature rise test of transformer is included in type test of transformer. In this test we check whether the temperature rising limit of the transformer winding and oil as per specification or not.In this type test of transformer, we have to check oil temperature rise as well as winding temperature rise limits of an electrical transformer.

Transformer Oil Analysis - An Essential Part of a Cost-Efficient Maintenance Program

It is well known that regular oil analysis is useful in monitoring the condition of engines, turbines and other oil lubricated equipment. The same can be said for transformer oils used to insulate many transformers and other electrical distribution equipment. The analysis of insulating oils provides information about the oil, but also enables the detection of other possible problems, including contact arcing, aging insulating paper and other latent faults and is an indispensable part of a cost-efficient electrical maintenance program.

Ensuring Transformer Reliability
Transformer maintenance has evolved over the past 20 years from a necessary item of expenditure to a strategic tool in the management of electrical transmission and distribution networks. Extreme reliability is demanded of electric power distribution, and even though the failure risk of a transformer and other oil-filled electrical equipment is small, when failures occur, they inevitably lead to high repair costs, long downtime and possible safety risks. Moreover, transformers are too expensive to replace regularly and must be properly maintained to maximize their life expectancy.
By accurately monitoring the condition of the oil, suddenly occurring faults can be discovered in time and outages can potentially be avoided. Furthermore, an efficient approach to maintenance can be adopted and the optimum intervals determined for replacement. Some of the checks are relatively simple: the operation of the gas relays, the operation of the on-load tap-changer, checks on oil leaks, etc. However, breakdown of one of the most crucial elements, the oil paper insulating system, can only reliably be detected by routine oil analysis.

The oil used in transformers has several functions.

It acts as an Insulator, suppresses corona discharge and arcing also seves as coolant.

It must have high dielectric strength, thermal conductivity, and chemical stability, and must keep these properties when held at high temperatures for extended periods.

The Information Gold Mine
By measuring the physical and chemical properties of oil, in addition to the concentrations of certain dissolved gases, a number of problem conditions associated with either the oil or the transformer can be determined. The following are some common tests performed on electrical insulating oils.
Moisture Content
One of the most important functions of a transformer oil is to provide electrical insulation. Any increase in moisture content can reduce the insulating properties of the oil, which may result in dielectric breakdown. This is of particular importance with fluctuating temperatures because, as the transformer cools down, any dissolved water will become free, resulting in poor insulating power and fluid degradation. In addition, many transformers contain cellulose-based paper used as insulation in the windings. Again, excessive moisture content can result in the breakdown of this paper insulation with a resultant loss in performance.
Acid Number
Just like industrial oils, transformer oils are oxidized under the influence of excessive temperature and oxygen, particularly in the presence of small metal particles which act as catalysts, resulting in an increase in Acid Number, due to the formation of carboxylic acids. Further reaction can result in sludge and varnish deposits. In the worst-case scenario, the oil canals become blocked and the transformer is not cooled well, which further exacerbates oil breakdown. Furthermore, an increase in the acidity has a damaging effect on the cellulose paper.
Oil degradation also produces charged by-products, such as acids and hydroperoxides, which tend to reduce the insulating properties of the oil. An increase in Acid Number often goes hand-in-hand with a decrease in dielectric strength and increased moisture content as shown in Fig1
Dielectric Strength
The dielectric strength (ASTM D300-00) of a transformer oil is defined as the maximum voltage that can be applied across the fluid without electrical breakdown. Because transformer oils are designed to provide electrical insulation under high electrical fields, any significant reduction in the dielectric strength may indicate that the oil is no longer capable of performing this vital function. Some of the things that can result in a reduction in dielectric strength include polar contaminants, such as water, oil degradation by-products and cellulose paper breakdown.
Power Factor
The power factor (ASTM D924) of an insulating oil is the ratio of true power to apparent power. In a transformer, a high power factor is an indication of significant power loss in the insulating oil, usually as a result of polar contaminants such as water, oxidized oil and cellulose paper degradation.
Dissolved Gas Analysis (DGA)
Dissolved gas analysis (often referred to as DGA), is used to determine the concentrations of certain gases in the oil such as nitrogen, oxygen, carbon monoxide, carbon dioxide, hydrogen, methane, ethane, ethylene and acetylene (ASTM D3612). The concentrations and relative ratios of these gases can be used to diagnose certain operational problems with the transformer, which may or may not be associated with a change in a physical or chemical property of the insulating oil.
For example, high levels of carbon monoxide relative to the other gases may indicate thermal breakdown of cellulose paper, while high hydrogen, in conjunction with methane may indicate a corona discharge within the transformer. Some of the more common key gas analysis fault conditions can be seen in Fig 2.
Furans
Furan derivatives are a measure of the degradation of cellulose paper. When the paper ages, its degree of polymerization reduces, so its mechanical strength decreases. The degree of polymerization can only be determined directly by taking a sample of paper, a very complex operation and almost never performed in practice. However, the degree of polymerization of the paper can be directly related to the concentration of furan derivatives in the oil. Furan derivates are formed as a direct result of the breakdown of the polymeric structure of cellulose paper. The content of furan derivatives is relatively easy to measure in the oil, using HPLC and is thus a way of measuring the aging of the paper.
Just like machinery oil analysis, electrical insulating oil analysis can play a vital role in preventing unscheduled outages in electrical transmission and distribution equipment by determining the condition of the equipment itself, and other vital components including the condition of the oil and the cellulose paper insulation. For all critical oil-filled electrical equipment, including transformers, circuit breakers and voltage regulators, regular, routine oil analysis should be the cornerstone of any PM program.
Proper Transformer Sampling (ASTM D923)
Just like machinery oil analysis, the ability of insulating oil analysis to provide an early warning sign of a problem condition is dependent on the quality of the oil sample that is sent to the lab. A sampling point on any equipment should be identified and clearly labeled for the technician. As with sampling locations in other types of equipment, the same location should be used each time a sample is collected to ensure representative conditions are tested. This point should be located in a place where a live oil sample can be collected rather then in an area where the oil is static.

Fluids with specific gravity greater then 1.0, such as askarels, should be sampled from the top because free water will float. For fluids with a specific gravity less than 1.0, such as mineral-based transformer oils, synthetic fluids and silicone oils, the sample should be taken from the bottom since water will tend to drop to the bottom in these fluids.

There are a number of environmental variables, such as temperature, precipitation, etc., to consider before collecting a sample. The ideal situation for collecting a sample from an electrical apparatus is 95°F (35°C) or higher, zero percent humidity and no wind. Cold conditions, or conditions when relative humidity is in excess of 70 percent, should be avoided, as this will increase moisture in the sample. Collecting a sample during windy conditions is also not recommended because dust and debris enter the clean sample easily and disrupt accurate particle counts. If sampling the oils is unavoidable when the outside temperatures are at or below 32°F (0°C), it should not be tested for water content or any properties that are affected by water such as dielectric breakdown voltage.
For dissolved gas analysis, an elaborate procedure must be followed, including the use of a glass syringe; with strict adherence to sampling protocol to ensure that the concentration of dissolved gases is not influenced in any way by sampling procedure. This procedure is described in detail in ASTM D3613.

OPERATIONAL ANALYSIS OF A SELECT SPINNING MILL

                                                                       -AN EMPRICAL STUDY

ABSTRACT

The Indian Textile Industry is the second largest in the world, next to Chinese and is one of the largest foreign exchange earners for the country. Textile is a key contributor to GDP to the order of 4%. The textile sector employs over 20 million people and is the second largest employment generator. Textile businesses are also affected by the global melt down. The industry in India is experiencing an increase in the collaboration between national and international companies. International apparel companies like Hugo Boss, Liz Claiborne, Diesel, Ahlstorm, Kanz, Baird McNutt, etc have already started their operations in India and these companies are trying to increase it to a considerable level.

National and the international companies that are involved in collaborations include Rajasthan Spinning & Weaving Mills, Armani, Raymond, Levi Strauss, De Witte Lietaer, Barbara, Jockey, Vardhman Group, Gokaldas, Vincenzo Zucchi, Arvind brands, Benetton, Esprit, Marzotto, Welspun, etc. Therefore, it is the right time to concentrate on operational cost to compete with the global leaders by concentrating on the world class quality products. An empirical study is made on the cost aspects of a textile mills discloses the possibility of cost reduction and improvement for profitability. This paper presents proactive aspects and relationship of the production with raw material consumption and yield .Cobb Douglas production function has been used to find the behavour of costs with the production per spindle shift. It also presents suggestions for improving productivity and profitability.

1. INTRODUCTION

The Indian textile industry, until the economic liberalization of Indian economy was predominantly an unorganized industry. The economic liberalization of Indian economy in the early 1990s led to stupendous growth of this Indian industry. Now Textile industry is the most prominent industry in India as it supplies cloth to the populations. It also assists for the survival of other small scale industries. Textile industry has shown its major growth in the post quota regime under the WTO agreement. Textile accounts for 14% of the total Industrial production and contributes nearly 30% of the total exports. Textile is a key contributor to GDP to the order of 4%. The intense global competition in textiles has stimulated cost-cutting measures and new investments that have significantly increased the efficiency of transforming cotton fiber into yarn. Continuous improvement in production, waste reduction and productivity would automatically lead of success of the enterprise.

The Spinning Industry in India is on set to hit the global market 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 beating the obstacles that caused a downfall since past few years and is now on its way to cover a wider area in the spinning sector.

2. STATEMENT OF THE PROBLEM

Indian 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 extent in India but it has also become one of the most profitable textiles in the export industry. The productivity in case of spinning mill is confined to gms per spindle shift. An elaborate and detailed assessment is made on various sectors of the yarn spinning such as, production, consumption, and materials. Everyone should try to get increased production at the least possible cost.

For this purpose it is necessary to find the behaviour of the production, raw material and yield .Tuning this well would enhance the productivity. On the other hand the costs associated with the production should also be evaluated to achieve the production with the least possible costs. It is necessary for everyone to improve productivity as well as profitability for their survival in the global economic crisis. It is right time to find solution to this type of problems.

3. OBJECTIVES OF STUDY

The following may be taken as the objectives of the study:

3.1.To find the relationship between production and raw material consumption and yield.

3.2.To find the association between Spinning production and costs.

3.3.To predict the spinning production using Cobb Douglas production function.

3.4.To offer plausible suggestions for improvement in cost and efficiency.

4. REVIEW OF LITERATURE

1. Imran Sharif Chaudhry et al (2009) have made study on “Factors Affecting Cotton Production in Pakistan: Empirical Evidence from Multan District”. They examined the factors

affecting cotton production. In that study Cobb-Douglas Production Function was used to assess the effects of various inputs like cultivation, seed and sowing, irrigation, fertilizer, plant production and labour cost on yield.

2 . Moosup Jung, et al (2008) made a study on” Total Factor Productivity of Korean Firms and Catching up with the Japanese firms “.They measured and compared the TFP of both

Korean and Japanese listed firms of 1984 to 2004.They used the Chain Linked Index Number method developed by Good et. al.(1999). They found that the average TFP of Korean firms grew about 44.1% between 1984 and 2005, with 2.1% annual growth rates. Industry was observed to be outstanding.

3.  Danish A. Hashim made research on” Cost and Productivity in Indian Textiles” for

Indian Council for Research on International Economic Relations. His observations and findings are: There is an inverse relationship between the unit cost and productivity: Industry and States, which witnessed higher productivity (growth) experienced lower unit cost (growth) and vice- versa. Better capacity utilization, reductions in Nominal Rate of Protection and increased availability of electricity are found to be favourably affecting the productivity in all the three industries.

4. Gokhale, G S (1992) an important factor that affects material productivity is the quality of cotton that is used to produce a particular kind of yarn or cloth. Using too good a cotton variety would contribute to excessive cost, but using cotton that is not good enough would mean increased breakage, a heavier work load for the worker, who consequently can only attend to a lesser number of machine units. The material productivity is influenced by a number of factors such as quality of material used, type of technology used, level of maintenance and life of machinery, count produced and the like.

5. Productivity also depends upon such factors as layout of machines, mechanical transport for material handling and machine maintenance. As a result of all these factors, productivity of the worker is largely governed by a proper machine allocation. This can easily be determined by work-study.

6. SITRA (1998) stated that the size of the mills decides the volume of business and also the economic viability of the business unit. Selection of suitable size is important for smooth conduct of business, over-capacity as well as under- capacity would bring pressure on the business.

5. SIGNIFICANCE OF THE STUDY

The new textile policy is to be seen in the backdrop of fast changing international scenario in the post-.GATT era and its implications on Indian textile sector. Textile and clothing have been brought within the framework of GATT in the Uruguay round of the multilateral trade negotiations. The first impact of this negotiation would be felt by the Indian textile industry after the expiry of Multi Fiber Agreement (MFA) on December 31, 2004. Expiry of MFA would have implications on both inter-national as well as domestic markets. The Indian textile industry has to be globally competitive to be able to sustain its presence not only in the international market but also in the domestic.

On the other side technological capability is embodied in the human and physical capital in command of the industry. In a dynamic sense it means the ability of the industry to articulate its business problems in terms of technology and also the ability to access human, physical, financial and organizational resources to find solutions to the articulated technological problems.

6. METHODOLOGY:

Comprehensive research work was done to achieve the objectives of the study. Ten year data - 1998-99 to 2007-08 of Sambandam Spinning Mills Salem has been employed for this study. In the first step the association between productions, raw material consumption and yield are arrived by employing the multiple regressions. In the next step the relationship between spinning production per spindle shift and related costs per spindle shifts are arrived by using the Cobb Douglass production function. Based on this spinning production per spindle shifts are estimated and the production achievements are compared between the two units of the same company.

Statistical tools such as Regressions, Analysis of variance technique has been employed to the test the hypotheses.

6.1. DATA ANALYSIS:

The data related to the two units of SSM Ltd has been analyzed towards its production and operational costs. The following table shows the production, raw material consumption and yield of SSM Ltd Unit-1 and Unit-2 for 10 years from 1998-99 to 2007-08.

                                             Table No: 1                                                                                                                                Production, Raw Material Consumption and Yield

	SSM LTD –UNIT-1				SSM LTD –UNIT-2
						Raw-
						material
	Production	Raw material		Production		Consumed
	(in-akh	Consumed	Yield	(in-Lakh		(in-Lakh		Yield
	Kgs)	(in-Lakh Kgs)	(Ratio)	Kgs)		Kgs)		(Ratio)
1998-99	20.33	26.38	0.77	21.58		32.18		0.67
1999-00	19.27	26.60	0.72	19.54		30.49		0.64
2000-01	19.19	26.12	0.73	18.56		29.02		0.64
2001-02	19.19	26.12	0.73	18.08		28.31		0.64
2002-03	18.00	24.38	0.74	19.41		28.08		0.69
2003-04	17.52	22.90	0.77	25.10		36.18		0.69
2004-05	20.91	26.45	0.79	23.90		36.97		0.65
2005-06	20.98	27.03	0.78	24.35		37.55		0.65
2006-07	19.25	30.63	0.63	27.65		41.78		0.66
2007-08	26.55	40.28	0.66	29.59		45.09		0.66

The following hypotheses have been framed to test the relationship between production and costs of the two units.

HYPOTHESIS.1:

THERE IS NO SIGNIFICANT RELATIONSHIP BETWEEN YARN PRODUCTION, RAW MATERIAL CONSUMPTION AND YIELD RATIO OF SSM LTD UNIT-1.

To study the significant relationship between the yarn production, raw material consumption and yield ratio multiple regression analysis is employed.. Here we take the yarn production as dependent variable and other factors as independent variables. The following table shows the results of fitting a multiple linear regression model:

Table .2

Coefficients:

		Standard	T
Parameter	Estimate	Error	Statistic	P-Value
CONSTANT	-18.4159	1.76891	-10.4109	0.0000
Raw material consumption	0.673339	0.0197851	34.0326	0.0000
Yield	27.1733	1.84076	14.762	0.0000

The fitted multiple regression models involving the explanatory variables are given

below:

PRODUCTION = -18.4159 + 0.673339*RAW MATERIAL CONSUMPTION + 27.1733*YIELD.

From the model it is observed that there is a positive relationship between yarn production and raw material consumption. It shows that yarn production would increase by 0.67 units, if the raw material consumption increases by 1 unit assuming the yield remains the same.

It also shows that there is a positive relationship between yield and yarn production. That is the yarn production would increase by 27 units if the yield increases by 1 unit assuming the consumption remains the same.

The validity of the model has been tested by ANOVA. The output of the ANOVA is presented as :

                                         Table No.3 - Analysis of Variance

Source	Sum of Squares	Df	Mean       Square	F-Ratio	P-Value
Model	56.9084	2	28.4542	646.83	0.0000
Residual	0.307931	7	0.0439901
Total (Corr.)	57.2163	9

Since the P-value in the ANOVA table is less than 0.05, there is a statistically significant relationship between the variables at the 95.0% or higher confidence level. Hence fitted model is the most suitable model to describe the relationships of the variables.

Table.4. Related Statistics

R2	Standard	Mean Absolute Error	Dubin-Watson Statistics
	Error of Estimate
99.4618 percent	0.209738	0.136684	1.30309(P=0.0942)

The R-Squared statistic indicates that the model as fitted explains 99.4618%of the variability in production. The standard error of the estimate shows the standard deviation of the residuals to be 0.209738.

The mean absolute error (MAE) of 0.136684is the average value of the residuals. The Durbin-Watson (DW) statistic tests the residuals to determine if there is any significant correlation based on the order in which they occur. Since the P-value is greater than 0.05, there is no indication of serial autocorrelation in the residuals at the 95.0% confidence level.

HYPOTHESIS.2:

THERE IS NO SIGNIFICANT REATIONSHIP BETWEEN YARN PRODUCTION, RAW MATERIAL CONSUMPTION AND YIELD RATIO OF SSM LTD UNIT-2

To study the Significant Relationship between the Yarn Productions, Raw Material Consumption and yield ratio multiple regression analysis is employed. Here we take the yarn production as dependent variable and other factors as independent variables. The following table shows the results of fitting a multiple linear regression model:

                                                         Table 5

                                                        Coefficients:

		Standard	T
Parameter	Estimate	Error	Statistic	P-Value
CONSTANT	-20.9637	0.963011	-21.7689	0.0000
s2rawmaterial consumption	0.657836	0.00502045	131.031	0.0000
s2yield	31.8798	1.45079	21.9741	0.0000

The fitted multiple regression models involving the explanatory variables are given below:

S2YARN-PRODUCTION = -20.9637 + 0.657836*S2RAWMATERIAL CONSUMPTION + 31.8798*S2YIELD.

From the model it is observed that there is a positive relationship between yarn production and raw material consumption. It shows that yarn production would increase by 0.66 units, if the raw material consumption increases by 1 unit assuming the yield remains the same.

It also shows that there is a positive relationship between yield and yarn production. That is the yarn production would increase by 31.88 units if the yield increases by 1 unit assuming the raw material consumption remains the same. The validity of the model has been tested by ANOVA.

The output of the ANOVA is presented as			:
		Table No.6
		Analysis of Variance
Source	Sum of Squares	Df	Mean Square	F-Ratio	P-Value
Model	142.31	2	71.1552	8996.15	0.0000
Residual	0.0553666	7	0.00790951
Total (Corr.)	142.366	9

Since the P-value in the ANOVA table is less than 0.05, there is a statistically significant relationship between the variables at the 95.0% or higher confidence level. Hence fitted model is the most suitable model to describe the relationships of the variables.

                                                      Table .7-Related Statistics

R2	Standard	Mean Absolute Error	Dubin-WatsonStatistics
	Error of Estimate
99.9611 percent	0.0889355	0.0593909	3.17366 (P=0.9427)

The R-Squared statistic indicates that the model as fitted explains 99.9611% of the variability in production. The standard error of the estimate shows the standard deviation of the residuals to be 0.0889355. The mean absolute error (MAE) of 0.0593909 is the average value of the residuals. The Durbin-Watson (DW) statistic tests the residuals to determine if there is any significant correlation based on the order in which they occur. Since the P-value is greater than 0.05, there is no indication of serial autocorrelation in the residuals at the 95.0% confidence level

COBB DOUGLAS PRODUCTION FUNCTION:

Generally for the same level of input factors, everyone should get almost the same level of output. In spinning mills the production and cost related to the spinning department has been considered as the important indicator of the operational performance. Therefore production and cost related to the spinning department has been taken for the analysis. To test production achievement of the companies, the Cobb-Douglas Production Function is employed. The Cobb-

Douglas Production Function assess the effects of various inputs like raw material, labour store cost, power, interest, depreciation and other costs involved in the production of yarn. The log

linear form of production function used is based on the following equation.

LnY =α+β1LnX1+ β2LnX2 + β3LnX3+ β4LnX4 + β5LnX5 + β6LnX6 + β7 LnX7 +uµ Where,

Ln Y = Dependent Variable –Spinning production per Spindle shift. X1= Xn are independent variables;

X1 = Raw Material cost /Spindle shift;                                                                                                      X2 = Salaries and Wages/spindle shift                                                                                                     X3= Stores cost / Spindle shift;                                                                                                                X4 = Power cost / Spindle shift

X5 = Other costs/ spindle shift;                                                                                                                  X6 = Interest cost/ spindle shift

X7 = Depreciation cost/ spindle shift

α = constant /Intercept.

β= co-efficient;

u =Random disturbance term; Ln = Natural Logarithms.

To predict the production, first of all the dependent and independent variables are to be fixed in the production function equation and processed to get constants and co efficient. To arrive this following steps are carried out.

In the first step data related to the production function as given in the following tables have been applied in the multiple regression models after converting the same in its log form to arrive the constants and coefficients. In the second step the resultant constants and coefficients are applied in the Cobb Douglas production function to estimate the production. In the third step the ten year averages of independent variables of all the four companies have been calculated. In the fourth step such average cost is applied in the production function along with the constants and co-efficient to predict the production of each company to evaluate the production achievement of the companies. The following table shows the unit wise constants and coefficients variables related to the production function.

                                                             Table 8.

                             Constants and Coefficients –   SSM Ltd Unit-1 and Unit-2

	COMPANY		SSM-UNIT-1		SSM-UNIT-2
	CONSTANTS		3.66		3.92
	CO-EFFICIENTS
	Mat. cost /sple sft		0.21		0.72
	S& Wages/sple sft		-0.06		0.29
	Stores/Sple Sft		-0.08		0.36
	Power/Sple Sft		0.77		-0.83
	Other costs/Sple Sft		-0.51		1.77
	Interest/Sple Sft		-0.29		-0.5
	Dep/Sple Sft		0.01		0.93
The regression equation for SSM LTD UNIT-1 is				given below:
Ssm-1.pdnpersplesft = 3.6585			+ 0.206866*ssm-1.rawpersft - 0.0619988*ssm-

1.swpersplesft - 0.0816154*ssm-1.storpersplesft + 0.773897*ssm-1.powerpersplesft - 0.510007*ssm-1.otherpersplesft - 0.287602*ssm-1.intpersplesft + 0.0112882*ssm- 1.deppersplesft.

It shows that there is a positive relationship between production per spindle shifts and raw material cost, power cost and depreciation. That is the production per spindle shift increases by the respective co-efficient level if the raw material, power and depreciation increases by one unit assuming the other variables remain constant.

Similarly the equation shows negative relationship between production per spindle shifts and salaries and wages, stores, other cost and interest cost. That is the production per spindle shift decreases by the respective co-efficient level if salaries and wages, stores, other cost and interest cost decreases by one unit assuming the other variables remain constant.

The regression equation for SSM LTD UNIT-2 is given below:
pdnpersplesft	=	3.92029		+	0.71877*rawpersft	+	0.294551*swpersplesft	+
0.361561*storpersplesft			-	0.833235*powerpersplesft		+	1.7669*otherpersplesft	-
0.497305*intpersplesft + 0.933198*deppersplesft
.

It shows that there is a positive relationship between production per spindle shifts and raw material cost, salaries and wages, stores, other costs and depreciation. That is the production per spindle shift increases by the respective co-efficient level if the raw material cost, salaries and wages, stores, other costs and depreciation by one unit assuming the other variables remain constant.

Similarly the equation shows negative relationship between production per spindle shifts and power cost and interest cost. That is the production per spindle shift decreases by the respective co-efficient level if power cost and interest cost decreases by one unit assuming the other variables remain constant.

                                                       Table 9

PREDICTED PRODUCTION--COBB-DOUGLAS PRODUCTION FUNCTION

	COMPANY	SSM-UNIT-1	SSM-UNIT-2
	PREDICTED PRODUCTION
1	Gms/Sple Sft	112.45	109.4
	COST-APPLIED	Average uniform cost applied
2	Mat.cost/Sple Sft	7.08	7.08
3	S& Wages/ Sple Sft	0.89	0.89
4	Stores/Sple sft	0.28	0.28
5	Power/Sple sft	2.21	2.21
6	Other costs/sple sft	1.43	1.43
7	Interest/sple sft	0.67	0.67
8	Dep/sple sft	0.72	0.72
9	Total Cost /Sple Shift	13.28	13.28
10	Cost per Gms	0.1181	0.1214
11	RANKS-Production	1	2
	Spindle Shifts-one day ( assuming
12	25,000 spindle and 3 shift working)	75000	75000
13	predicted production –One day	8434	8205
14	Total Costs-one Day	996000	996000
15	cost per kg	118	121

It has been observed that predicted production differs within the units of the same company. The production achievement ranks given .It also shows that increased production causes reduction in cost

7. FINDINGS

The following are finding arrived from the data analysis:

1.The yarn production depends on the raw material input and yield percentage. The data have been tested with the multiple regression analysis. It shows that there is a significant association between the Production, raw material consumption and yield ratio.

2.The Cobb Douglass production function shows the relationship between production per spindle shift and various component costs per spindle shifts. Prediction of production is made based on the co-efficient and constants arrived from the regression equation. It shows that there is a difference in production though the same uniform costs are applied. The table also shows the one day production and respective costs and also the cost per Kg. The cost per kg in SSM Ltd Unit-1 is lesser because of greater production per spindle shift.

8. SUGGESTIONS

The following strategies may help the Textile Mills to meet the global challenges to grow up as a global leader by improving the profitability:
1. Buy high yield raw cottons after testing the samples.
 Cottons without contamination would give more yields. Before going for production the cotton has to be tested for its yield and then order for raw materials. This would increase the productivity.
2. Reduction in cost per machine shift would reduce the cost of manufacturing.
 Monitor the costs by applying activity based costing and remove the unnecessary activities and save the costs.
 3. Increase the spindle utilization and make spin plan before starting the production so that count change, count run outs and other reasons for spindle stoppage may be reduced to optimize the spindle utilization.
4. Interest Charges: 
Due to the injection of more debt funds heavy interest charges occurs. Mills are unable to use debt funds to magnify the profit as they are very often subject to so many risks. Borrowing at lower rate of interest and timely use of debt capital shall reduce the interest burden. To avoid heavy interest use matching principle in the mixing of Short term and long term funds. Long-term funds in the form of issue of bonds for specific period and short term funds like commercial papers may be planned in addition to the other sources of finding funds so as to get optimal capital-mix.
5. TUF loan:
 Government has been giving Technology Up gradation Fund to modernize the plant at lower rate of interest. This is a boon to the textile sector since it would increase the productivity as well as the profitability.
 6. Business Intelligence: 
It is a process through which the performance of the organization is monitored with KPI’s (Key Performance Indicators) and reported for immediate action and follow up. It is a “Measure-Monitor-Manage- Analyze-Plan system. Alerts and work flow corrections are also indicated by the business Intelligent Software. Close watch over the financial leverage, Asset leverage, Cash flow management and working capital shall make a concern to reduce the interest burden and at the same time enjoy the benefit of zooming profit by taking timely actions with the help of the business Intelligence software.
7. Unused capacity management:
The actual situation would show the unused capacity in a particular period may be managed by doing job works so as to recover the cost and increase profitability.
8.Close Watch on Yarn Prices and try for Exploring for Value addition 
 Before making production plan Market trend has to be assessed and to source best customers ,use up-selling, cross selling and diversifying techniques and explore new markets for potential customers to improve profit margins.To review the market prices time to time.

9. Long term deals with Suppliers with  better pricing on Raw material /products/ spares.


9. CONCLUSION

The improvement in profitability depends on the improvement in productivity of an individuals and operational performance of a company. In this paper the relationship between production, raw material consumption and yield are arrived to find the behavour of the same. This can be used for improving the productivity. The Cobb Douglass production function and prediction of production also exposes the cost areas to be concentrated. Every company can enhance their productivity and profitability if they improve the operational activities at lesser cost. These are within the control of the management. Hence, one makes drill down approach to increase the profitability as well as the productivity by ascertaining the association successfully.

Courtesy : 1Dr.G.GANESAN & C.DHANAPAL