USING OPERATION ANALYSIS to IMPROVE ROW-CROP MACHINERY EFFICIENCY - r -- 1.i 'A .g,., ~ ~ ~tV .. A4 b CIRCULAR 180 JUNE 1970 AGRICULTURAL EXPERIMENT STATION Auburn, Alabama AUBURN E. V. Smith, Director UNIVERSITY CONTENTS Page R ESEARCH STUDIES..................................... 4 4 OPERATION ANALYSIS OPERATION ANALYSIS USE EXAMPLES6 SU M M AR Y- - - - - - - - - - - - - - - - - - -- - - .. . . . . . . . . . . . . . . . . 8 9 ACKNOWLEDGMENT.. REFERENCES - 10 FIRST PRINTING 3M, JUNE 1970 Using Operation Analysis to Improve Row-Crop Machinery Efficiency E. S. RENOLL, Associate Professor of Agricultural Engineering HE ROLE of farm machinery is becoming more important in production of agricultural crops. This role becomes of special importance as machines become larger. Economic pressure demands that the farm operator use his machinery as efficiently and effectively as possible. Engineers have long been interested in machinery-use problems and have used numerous approaches to solve them. Linear programming has been used by several researchers (2). Link (4,5) and Sowell (9) have used the network analysis concept and mathematical approaches as aids in selecting machinery and for determining machinery needs. The importance of machinery use and field efficiency as related to economic agricultural production was recognized by Jones (3). Machinery capacity and field machine efficiency as related to field size, row length, and terrace systems have been studied at Auburn University (6,7). This work shows that field capacity of machines varies greatly from field to field. Several agricultural engineers interested in machinery-budgeting or machinery-use programming have suggested a systems approach. Von Bargen (11) discussed this technique in his work relating to harvesting alfalfa hay. Stapleton and Barnes (10) have also done some work with the systems-analysis concept. Nearly all researchers dealing with machinery programming have been confronted with a common problem. This problem is the lack of reliable input data. Stapleton (10) cites it as a prob- lem in his work. Abelson (1) in his editorial in Science also suggests this as one of the major problem areas. The results from machinery programming are only as good as the input data. A machine operation can be no more efficient than the efficiency of the individual segments making up the total operation. Industry has recognized this fact and has used it as the basis for time and motion and operation analysis studies in factories. Research was undertaken at Auburn to examine the possibility of using the operation analysis concept to analyze field operations of row-crop machines. This also involved obtaining reliable input data which could be used as guides for comparisons in the analysis studies. The results of this study are presented in this publication. RESEARCH STUDIES The operation analysis research work was part of a machineryneeds-and-use study of row-crop machines. The field research work was conducted at the Agricultural Engineering Research Unit near Marvyn during a 4-year period. Fields used in the study ranged from 8 to 25 acres with rows 200 to 1,500 feet in length. Time measurements for field operations were recorded. Longtime intervals were recorded by a time clock on a circular time chart and short time periods were measured with a stop watch and recorded by a research assistant in the field where the machine was used. The research assistant was stationed so he could observe the field operations but was far enough removed so as not to interfere with any part of the machine operation. Field equipment used in the field studies was conventional rowcrop machinery. The machine operators were of average ability and all had several years experience. OPERATION ANALYSIS If the operation-analysis concept is used to study machine operation in the field, some type of record of machine operation must be obtained. This is essentially a study of the total production system - machines, fields, and management. An operation analysis involves three basic parts. The first is to obtain accurate time records of all activities relating to a specific machine operation in a field. An example of this would be a complete field-time record of a cotton planter in operation and would [4] TABLE 1. PLANTING OPERATION TIME RECORD 4-Row PLANTER Operation Total field operation time Actually placing seed in ground Adjustment and down time Adding seed Adding fertilizer-- - - -- - - - -- - - -- - - - -- - Adding chemicals and water_ Turning time Hr. 8 3 0 0 1 1 0 Total time Min. 0 12 24 31 36 55 19 include the increments of time related to each major segment of the total planting operation. Table 1 is an example of such a time record. The second part of the operation analysis involves dividing the time record into the primary function and supporting functions as in Table 2. In a planting operation, placing seed in the ground is the primary function. The supporting functions include such items as adding seed and chemicals and row-end turning. In Table 2, the time for each component operation has been expressed as a percentage of the total field time. Expressing these values in per cent puts them in a more useful form for later use in the third part of the operation-analysis concept. The third part of the operation analysis involves a detailed study of the information obtained in parts one and two. This would include looking at each segment of the operation to determine if the time for any individual segments appear to be excessive with respect to the total operation time. For instance, in the planting operation example shown in Table 2, each item in the primary function and the secondary functions would be examined. After the questionable segments are identified, it is necessary to examine and analyze each of these segments in detail to determine why so much time is used. This analysis would take into TABLE 2. PLANTER OPERATION ANALYSIS DATA 4-Row PLANTER Operation Primary function Total field time Pct. 40.6 4.9 6.4 20.3 23.5 4.3 Actually placing seed in ground Support function -59.4 Adjustments and down time ........................... Adding seed Adding fertilizer Adding chemicals and water Turning time [5] acceount tihe fild pii\ sicull coiiditiouiX. tile maines( iised, andi~ ali ;After a de~tailedl anlsis 1,comp1 et(Jld, Xis ehanys iii fIitiie optera tion al procedu res XXioultl 1e recoind edit for thos s egmients XXhichl sho)X the (greatest possibility for imp! OX ink the cffjiiec of tihl total operation. OPERATION ANALYSIS USE EXAMPLES 'I'ie X Jlo andt uist of oper~atlin anil is c1 n bei ilitistr atedi \v itli i tie fl]oXXii~y (\xamples. Foir the planltino perationi iniTable 2, the suipport fiii ctioi s use 59.4 per ceii t I I the total fieltd operaitinig; timie, iiitliii 4:3 per c(lit to ad(1( fertilizer, wXater, and chiemicals. Fiei oil (,S) lists some efficicice \allies obtainied from (fiien t op('rationis. Fori examipl, ini efficient p~lanitiigt operaitionis oli 40) to ctionis. Bast(d oni thiis earlier .50 per cenit XXas uised for su pport tfii wXork it seems the soupport funcitioi s tinie ili 1'al ? ar e exeessiX e andt should he exainiedl ioi the cauise. Aiter the causes hiaX c betn (eterin d, remiedies (ai he aipp~liutd. Ini d this exampifle it XX(0111(1 setlim that till majdor prbe is the floe- of' maiuteial toi the plani ter. FIG. 1. In the use of the sprayer, correct planning for the handling of materials will increase machinery operation efficiency. [6] I1 WdLL 3. P~LANTER OPEBAexI o'. A\. ix i D_ ~ 2-Hoxx COFO io'. VA'. II O)peration PrimaUry function Actulally I)IahItilI! co~tton Supp)1ort function --.---.--- Total field time~ Pct. 4.5 5 Add il seedl and f ertilizer orenids -- 8 21 "hniga -knother examp le of the use of operation analxysis is found iii the 1 dlata from Table 3. These dlata su ggest twxo possible prob~lem areas, field p~rolems and(1 anagean nt or sup isioii problemis. Turn ing time accotints for 21 per cent of the total field time wxhile planter adljustmnent amunmts to an add~itional ?6 per cent . Since these \alues seem to he exeessixve, tihe causes should be dletermnedl and remnedied. lTningll time is in fluncied lbx row5 len gth. An acre of ong rows has fexwer tarnt s than an acre of short row s. \\ 11(1] ti i ring time is exeessixve, the farn manager should exanmine field sire, rowx arrangeents, terrace laxvout, andl roxx length to dletermne if changes cani be nmade to reducee tminiii time and( thus improx e effiiecx FIG. 2. When planting, long-row fields are more efficient far machinery use than short-row fields. TABLE 4. OPERATION ANALYSIS DATA 1-Row AND 2-Row COTTONPICKER 1-row 2-row Total time Pct. Primary function Total time Pct. 74.9 25.1 6.3 14.3 4.5 Actually picking cotton Secondary function ------- -----Turning time Dumping time--- - - - - - - Cleaning time- - - - - - - - - - - 77.0 -23.0 -6.6 10.2 6.2 Turning time is also influenced by the physical condition of the turning area. Rough and uneven turn spaces require more machine turning time than smooth areas. Narrow or short turn spaces increase turn time. The excessive planter adjusting time of 26 per cent suggests several management problems. These might include poor seedbed preparation, improper planter maintenance which could cause excessive parts breakage, improper planter set-up before starting to plant, or improper operator training which could result in a trial-and-error approach to planter adjustment. Planter maintenance, repair, calibration, and adjustment should be performed prior to the start of planting. In analyzing some machine operations it is not always easy to determine which segments to study in detail. The operation analysis in Table 4 is such an example. Since no specific item in the secondary function appears to be excessively high it is not likely that any great reduction in total time for these functions can be obtained. Dumping time might be a little high and should perhaps be studied in some detail. SUMMARY Operation analysis has been used to successfully analyze some row-crop operations and the machines involved. The procedure can be used to study the total machine operating system, including the specific machines, the fields, the interaction between the machines and fields, and the management of the machines. The procedure can also be used to examine suspected problem areas in material flow, field size and row arrangement, turn areas, faulty or improper service or maintenance of the machine, and misuse of the machine. Data from efficient field operations can be used as guides for evaluating information from field operations being studied. [8] The operation-analysis concept appears to have considerable merit when planning for maximum machinery utilization. Farm managers can use this concept to help predict more accurately machine capacity for specific fields and thus better plan for efficient machine use. This concept is also helpful in projecting machine needs and sizes for handling a specific enterprise. ACKNOWLEDGMENT The author acknowledges the assistance and contribution of the part-time agricultural engineering students that helped collect data and record field observations. Grateful thanks are expressed to W. T. Dumas, Department of Agricultural Engineering, and the staff of the Agricultural Engineering Research Unit near Marvyn. [9] REFERENCES (1) ABELSON, P. R. 1965. Continuing Education. Science 150:831. (2) GAss, SAUL I. 1958. Linear Programming. McGraw-Hill Book Co., Inc., N.Y. (3) JONES, PHIL B. May, 1967. Better Field Efficiency. Successful Farm- ing. (4) LINK, D. A. 1967. Activity Network Techniques Applied to a Farm Machinery Selection Problem. Tran. of the ASAE 10(3):310-817. (5) ----------- AND C. W. BOCKHOP. 1964. Mathematical Approach to Farm Machine Scheduling. Tran. of the ASAE 7(1):8-13, 16. (6) RENOLL, E. S. 1960. Field Size and Machinery Efficiency. Highlights of Agri. Res., Auburn Univ. (Ala.) Agr. Exp. Sta. Vol. 7, No. 3. Fall issue. (7) . 1965. Row-crop Machine Capacity in Terraced Fields. Highlights of Agr. Res., Auburn Univ. (Ala.) Agr. Exp. Sta. Vol. 12, No. 2. Summer issue. ..... 1969. Row-crop Machinery Capacity as Influenced by (8) Field Conditions. Auburn Univ. (Ala.) Agr. Exp. Sta. Bull. 395. (9) SOWELL, R. S. AND D. N. A. LINK. 1967. Network Analysis and Math1967. Data Needs for Agricul- ematical Programming. Tran. of the ASAE 10(6) :820-828. (10) STAPLETON, H. AND K. K. BARNES. tural Systems Analysis. Tran. of the ASAE 10(3):303-309. A Systems Approach to Harvesting (11) VON BARGEN, KENNETH. Alfalfa Hay. Tran. of the ASAE 10(3):318-319. [ 10 ] AGRICULTURAL EXPERIMENT STATION SYSTEM OF ALABAMA'S LAND-GRANT UNIVERSITY \Vith an agriclttiral researchi unit in every llajor soil area, Aubnu if U~niversitv serv\ es t lic needs of field crop, livestock, forestr v, and lolticultural producers in each region in Alab~ama. Everv citizen of the State has a stake in ihis research program, since any advantage Ifrom new andt more economical wax's of producing and handling farm produ cts directly nisuin benefits tli e public. 3 I Il ( Q { (7 u Research Unit Identification 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. i1 12. 13. 14. 15. 16 17 18. 19. 20 21 Tenne see Volley Substation, Belle Mina. Sand Mountain Substation, Crossville. North Alabama Horticulture Substation, Cullman. Upper Coastal Plain Substation, Winfield. Forestry Unit, Fayette County. Thorsby Foundation Seed Stocks Farm, Thorsby. Chilton Area Horticulture Substation, Clanton. Forestry Unit, Coosa County. Piedmont Substation, Camp Hill. Plont Breeding Unit, Tallassee. Forestry Unit, Autouga County. Prattville Experiment Field, Prattville. Black Belt Substation, Marion Junction. Tuskegee Experiment Field, Tuskegee. Lower Coastal Plain Substation, Camden, Forestry Unit, Barbour County. Monroeville Experiment Field, Monroeville Wiregrass Substation, Headland. Brewton Experiment Field, Brewton Ornamentol Horticulture Field Station, Spring Hill, Gulf Coast Substation, Fairhope