Journal of Experimental Research. March 2013, Vol 1 No 1 www.er-journal.com E-mail: editor-in-chief@er-journal.com Received: Nov. 10, 2012 Accepted for publication: Jan. 30, 2013 Models for Repair and Maintenance Costs of Rice Mills in Soueastern States of Nigeria Oluka S.I. & Nwani S. I Department of Agricultural & Bioresource Engineering Enugu State University of Science & Technology Enugu, Nigeria E-mail: ikeoluka@yahoo.com Abstract This paper reports on various factors at contribute to e ownership costs of rice mills in Soueastern Nigeria. The machinery costs were monitored for ten years under two management systems of Private sector and Farmers Cooperative ownerships systems. The management systems used in e study are Farmers Co-operative System (FCMS) and e Private Ownership Management Systems (POMS). In each of e management systems, e costs of two commonly available rice mills were investigated and compared. The results indicate at e average unit cost per hour for operating e rice mills were N37.20 and N33.75 for POMS and FCMS respectively. The FCMS recorded more hours of usage of 576 hours while POMS recorded 521 hours per annum. Analysis of e data obtained indicates at e average correlation coefficient of determination of e Rice Mills were 0.99 (99%) wi e regression coefficient of 16 and 0.228 for parameters A and B respectively. A maematical model for e total accumulated use in hours (TAUH) and total accumulated repair and maintenance costs (TARMC) were 0.228 developed and expressed as TARM = 16TAUH. The model will serve as a guide to rice mill owners for anticipated repairs and maintenance costs versus total hours of usage as well as for replacement decisions and general farm budgeting. Keywords: Modeling, rice-mills, repair, maintenance, ownership costs, management, INTRODUCTION It has been e policy of e Federal Government of Nigeria: to import some agricultural machinery in order to boost agricultural mechanization' aimed at increasing food production in e country. The machines, implements and equipment which were imported to facilitate mechanization of Nigeria's agriculture need to be maintained. Oluka (2000) stated at between 1975 and 1985, e Federal Government of Nigeria imported and distributed 19,906 tractors and only 59% were functional at e time of e survey while 26.66% were not in operational conditions. 13.5% or 2154 tractors were not serviceable. The reasons for e high rate of machinery breakdown may be attributed to poor maintenance culture in e country. Machines can only work productively, if ey are kept in good order and is means a regular servicing and maintenance of e working parts. To prevent shortening e life span of any machine, engine or equipment, maintenance of e system is very essential. Efforts to maintain machines, implements and equipments lead to repair and maintenance costs often expressed as at expenditure necessary to restore or maintain e technical soundness and reliability of e machine. They are attributed to wear and tear, random failure and accidents. Repair and maintenance costs also comprise replacement of parts including tyres, fueling, lubrication, operators labour, etc. resulting to variable and fixed costs. (Kepner et al, 1987). However, repair costs constitute a major share in e operating cost of a machine. It has been estimated at e cost generally tends to range from 10-15% of e total cost of e machine operation and also tends to increase wi e machine age (Rotz 1985). 10
During e first year of use, e costs are almost zero as most of e repairs would be covered by a grant agreement. The cost of repairs should increase as e machine becomes older. The cost of repairs would continue to increase but at a stage, e cost will attain a constant value near to e end of e machine life. This costs analysis is very important as it constituted a main factor which influences e ownership costs of a machine as well as optimal time for machinery replacement. Fundamental to e knowledge of farm machinery ownership cost is an understanding of how a machine is operated, managed and valued overtime. There is erefore e need to study, assess and appraise e various management and cost factors associated wi owing, leasing or renting machinery (Oluka, 2009). This is necessary to assist farm managers and farm machinery owners as well as machinery operators in taking informed decisions regarding eir machines and also to assist em develop practical framework for calculating and analyzing e various components of machinery costs over a period of time. Also, e study will enable farmers to determine wheer ey have profited or not in eir respective farm business of using farm machinery as well as help in making management plans, decisions and in comparing different machines and models for appropriate farm power and machinery selection. This study is specifically focused on two different rice milling machines under two different management systems. The main objective of e study is to carry out an investigative research survey on e various management and ownership costs, and specifical1y: To determine e ownership costs of Rice Mills in Soueast Nigeria. To develop a maematical model for repair and maintenance cost of e Rice Mills in e region based on (1) above. B TARM = A (TAUH)... 2.1 TARM = Total Accumulated Repair and Maintenance, % of e purchase price. TAUH = Total Accumulated Used in Hours of % of wear out life. A & B = Model parameters. Parameter A was used to express e magnitude of e repair and maintenance costs while parameter B describes e distribution of repair and maintenance cost roughout e machine life. The first order exponential model in equation 2.1 predicts very low repair costs in e initial stage of machine life wi a moderate increase in later life. Therefore is model represents more real life situation and can provide reliable estimate of e repair costs. The same model was adopted by (Ward 1985). The model accommodates wear rate which varies from one machine to oer by including e variable parameter B. As e value of B approaches one (I), e annual repair rate approaches a constant value its value is increased e repair costs were-pushed more towards e later life of e machine (Rotz 1985). Following wide acceptance and application of Rotz (1985) equation, is work is based on e principles of equation 2.1 to develop maematical models for rice mills in Soueast Nigeria. Meodology The study used e investigative survey research approach using sets of well structured questionnaires and oral interview. The study was limited to two management systems namely: Private Ownership Management System (POMS) represented and Farmer's Co-operative Management System (FCMS). During e study, bo qualitative and quantitative data were obtained based on observations, existing records, and relevant publications. Information obtained include: age of machines, purchase price, hour of use, total fixed and variable costs such as repair and maintenance costs, fuel, lubrication, operator's salaries, etc. Model Development Rotz (1985) developed a maematical model which states us: The total number of hours used were directly obtained from each establishment, eier from questionnaire or from oer-written document, 11
Depreciation: The depreciation costs were determined by using e straight line meod (Oluka, 1998): D=PL/N Where D = depreciation P = purchase price of machinery N= useful or economic life of machinery (years) L= salvage value of e machinery (N). A useful life of 10 years and salvage of 5% were assumed. Interest Rate: The interest rate depends on e prevailing situations in e banking sector of e economy. Mirani et al (1989) used e interest rate of 12 % as e average investment to determine e unit cost of operation of farm tractors in Pakistan. Oluka (1998) used interest rate of 14% based on e prevailing interest rate in Nigeria.. In is study, e interest rate of 20% of e investment is used based on e current interest rate in e country. I = r(p + s) 100 I = annual interest. r = interest rate % p = initial cost s = salvage value Shelter is a vital cost factor in determining e cost of farm machinery. Shelter is provided to increase e expected life of any farm machinery. Also e average annual repair cost estimates will be reduced and smaller for sheltered machines. Oluka (2000) stated at costs due to shelter vary according to types and complexities of e structures. In most cases, cheap structures are used as shelter and e cost of such cheap structure may be assumed to be 0.5% of e purchase price. However, in some cases 0.5% of e purchase price may appear to be inadequate. In is study, 0.5% of e purchase price of e machinery was used to calculate e cost of housing of e machines under consideration. Operator's salary depends on e existing circumstance and it differs from place to place. In is study, actual salaries of e operators in e establishments studied were used. Fuel and lubricants: Though, data pertaining to fuel, oil and lubrication consumption were collected from records available in e establishment covered by e study, e data is purely dependent on type and e age of e machine as well as e level of e operator of e machine. Some machines naturally consume fuel and oil more an oers and sometimes e operators contribute to his style or meod of operating e machine. Repair and maintenance costs: The repair and maintenance costs of e farm machinery studied were determined by adapting repair and maintenance percentage approximation as applied by Oluka, (2000). The cost percentage approximation schedule suggests at e repair and maintenance costs for any farm machinery could be averaged to 6% of e purchase price a year for 10 years of 6000 hours life. A schedule of repair and maintenance cost as a percentage of purchase price were developed assuming at overhauls were done when needed. The repair and maintenance schedule is as follows: st 1 'year = 00% nd 2 = 1% rd 3 = 3.7% 4 = 8.5% 5 = 2.5% 6 = 10% 7 = 4.5% 8 = 5.75% 9 = 11.25% 10 = 6.5% Analysis of Results Table 4.1: Total hours of usage and accumulated repairs and maintenance costs under e Private Ownership Management System. Operator's salary: The cost associated wi operator's salary is purely negotiable. There may be no formula for assessing e operator's salary especially in private and co-operative enterprises. 12
Table 4.2: Regression analysis of total hours used versus total cost of Repairs and Maintenance for e Rice Mills under e same Management Systems. Table 4.4: Regression analysis of total hours versus total costs of repair and maintenance of Rice Mill (Black Stone) under (FCMS) Repair & Maintenance Model: black stone under 0.058 POMS = TARM = 13 TAUH Repair & Maintenance Model: Lister under POMS 0.101 = TARM = 15TAUH Table 4.3: Total hours of usage and accumulated repairs and maintenance costs under Farmers Cooperative Management System (FCMS). Model for Black Stone under FCMS = TARM = 18TAUH Model for HR Lister under FCMS =TARM = 16TAUH 0.077 0.072 Table 4.5: Statistical Analysis of e total accumulated repair and maintenance costs of e rice mills under difference management systems. 13
Average for e rice mills Model = TARM = 16TAUH 0.228 Oluka S.I. & Nwani S. I - Models for Repair and Maintenance Costs of Rice Mills distributed along e life of e machines indicating at e rice mans have high frequency of break down wiout a. corresponding high frequency of repair and maintenance in e Soueast Nigeria. Summary table 4.6: Summary of e regression correlation analysis under different management systems and Machine types Rice milling machine (Black Stone) 0.058 POMS TARM 13TAUH 0.017 FCMS TARM =18TAUH Rice Milling Machine (LISTER) 0.101 POMS Tarm = 15TAUH 0.072 FCMS Tarm=16TAUH However e average correlation and regression coefficient used as model for rice mills is TARM = 0.228 16TAUH RESULTS AND DISCUSSIONS The results of e ten years study are presented in tables 4.1, 4.1A, 4.2, 4.2B, 4.3, 4.3B, 4.4A, 4.4B and 4.5 and 4.5. The table 4.5 was developed from tables 4.1A to 4.4A. By regression analysis of data in table 4.1A to 4.4A e regression coefficients of A and B were determined and fitted into e Rotz (1985) equation of 2.1 us obtaining e maematical relationships between e accumulated use and repair costs on e two rice mills under different management systems as stated in summary table 4.5. Table 4..5 shows e model parameters A and B, parameter B represents e degree of distribution of repair and maintenance cost rough e life time of e rice mills- Parameter A quantifies e magnitude of e rice mill costs in e study areas, The results of table 45 as explained by e low values of B shows at repair and maintenance costs are not properly Also e table contains e correlation coefficient of determination for e various two mills under different management systems. The correlation coefficient was higher for Black stone under POMS and lower for HR Lister under FCMS. The correlation coefficient of determination explains e total variation in e accumulated rice mill use, wi repair and maintenance costs. The variation could be attributed to e influence of ownership cost factors. CONCLUSION A research for e determination of a maematical model for rice mills (Black stone and HR Lister) was carried out under two management systems, Private Ownership Management System (POMS) and Farmer's Co-operative Management Stem (FCMS) in e study area. The research covered a period of ten years. The analysis of e result reveals at: 1. Total accumulated repair and maintenance costs of rice mills have strong positive correlation wi average correlation coefficient of 0.990 i.e. 99%. 2. The maematical model or e average total accumulated repair and maintenance costs (farm) and average total accumulated use in hours (TAUH) can be expressed as TARM = 0.228 16TAUH is is e model when used will lead to increased rice production in Soueast Nigeria. 3. There is high value magnitude of repair and maintenance cost in study area as indicated by e high value of parameter A. Probably is may be reasons for high rate of rice mills breakdowns and repairs in e region. 4. The management of rice mills should be left under farmers co-operative management system as it proves better an e private management system. This may be e reasons why governments allocate farm inputs rough co-operative systems. 5. The model equally predicts a time of disposal of a farm machine as a scrap instead of continuous consumption of money in repairing. 14
REFERENCES Agricultural society of Agriculture Engineers (1985). Repair costs of 2 and 4 Wheel Drive Tractors Vol. 28 0.4 page 1074. Agricultural society of Agricultural Engineers (1980). Management Data, Agricultural Engineers Year Board, ASAE, St. Joseph, MI 49085. Kepner, R. A., Bainer, R, and Berger, E. L (1978). Principles of Farm Machinery, Third Edition, The A VI Publishing Company, Inc. Westport, CT. Oluka, S. I. (2000). Costs of Tractor Ownership under different management systems in Nigeria. Nigerian Journal of Technology Vol. 19, No. 1,200. Oluka, S. I. (1998). Costs Study of Tractors, Equipment Hiring and Management System. Technology and Research Journal 01.2(1) pages 58-69. Rotz, C. A. (1985). A Standard Model for Repair Costs of Agricultural Machinery A.5.AE., Paper No. 85-1527. Ward, S. M., Nulty, P.B., Cunney, M.B. (1985). Repair Costs of 2 and 4 WD factors. Transition of American Society Agricultural Engineering 1985 (1074-1076). 15