Machinery management data available.

Machinery Management Data Available

MACHINERY management--the planning, selection, scheduling, operation, maintenance and control of field machine systems--has progressed from 1950s field studies with stop watches and penciled notations to the latest in computer simulation and data analysis. The ASAE machinery management committee was organized in 1960 and remains quite active, but research by pioneers such as Ken Barnes and Dave Link at Iowa State is still studied and quoted by today's experts.

Machinery management papers given at the June 1990 ASAE meeting ranged from when farm machines should be replaced to knowledge-based systems so sophisticated they can only be interpreted by experts. Due to the limited number and availability of those experts, few farmers have direct access to that information which makes it primarily a tool (or toy) of researchers. But some programs are directly usable by farms on their own or in small groups.

The Purdue Machinery Cost Calculator figures accounting and economic costs for tractors, plows, disk, planters, combines and grain heads for each of the next 20 years in When Should You Replace Your Farm Machines (ASAE paper 905006) by D.H. Doster, Dept. of Ag. Econ. & G.W. Krutz, Dept. of Ag. Enr., Purdue U., West Lafayette, IN).

With proper input, the program calculates the costs of a presently owned machine and a similar-sized replacement machine. Comparing costs of each machine permits selection of the lower cost machinery services.

Doster and Krutz say it's generally best to retain present machines as long as expected next-year costs are less than the minimum average costs, as defined by this program, for the similar-sized replacement machine. Machinery cost coefficients can be developed to create crop budgets, but no downtime costs are included and the authors say that if they were, trading would occur more frequently.

The program is not designed to compare differences in earnings because of more timely field work by a larger machine and they suggest that farmers needing that information attend the Purdue Top Farmer Crop Workshop where they can estimate earnings differences from using various size machines on a given farm.

They add that cost factors are only one reason for trading machinery. There may be little cost difference between the best trading date and a date a year or two earlier or later. Within a time frame of four years or so, a trade might be made when a different size machine is needed and/or cash or a "good deal" is available; otherwise, don't trade.

Applying the principles of a military handbook (MIL-HDBK-472) to combine maintainability can permit combine designers to continuously improve designs that require high maintainability, says A. Hari, visiting scholar from Israel, who with P. Krishnan and N.E. Collins of the Ag. Engineer Department, U. of Delaware, Newark wrote ASAE paper 907011, Predicting Downtime Duration Associated with Repair and Maintenance of Combines.

"Maintainability can be defined as the measure of the ability of an item to be retained in or restored to specified condition when maintenance is performed by personnel having specified skill levels, using prescribed procedures and resources, at each prescribed level of maintenance and repair (MIL-STD-721C, 1981)," say the authors.

They add that Critical Time Maintenance Activities performed due to breakdown of equipment cause extra costs, including losses of income due to lost crop and costs of poor crop quality and back-up solutions. Therefore, their method concentrates on predicting downtime based on cumulative historical data, expert subjective estimations and some tests.

Existing data is used when available and a process is included for making predictions when necessary. The procedure can be applied to a single part, component or entire machine and is based on the philosophy that failure rates and downtime are related to maintenance activities for a harvesting operation. Program accuracy depends on the accuracy of data and estimates used, and the authors recommend long-term data collection from designers, warranty claims, parts sales, dealers and customers.

Investment analysis is one of a farm's most difficult management decisions, but a Texas A&M team aims to reduce that difficulty. In Machinery Management Tool for Checking the Physical Constraints of Overall Farm Plans, (ASAE paper 907022) S.A. Freeman & A.D. Whittaker, Dept. of Ag. Engineer and J.A. McGrann, Dept. of Ag. Economics, Texas A&M, College Station offer a machinery management program. It evaluates the physical feasibility of an overall future farm plan plus consequences of changes in the farm's time, labor and machinery resources caused by within-season decisions or changes. This involves,

1) A calendar of field operations to be performed and time and labor constraints involved in production,

2) A program to analyze the physical feasibility of the calendar and possible solutions when the calendar cannot be completed within the defined constraints,

3) The ability to evaluate an overall future farm plan, and

4) The ability to assess progress toward completion of the defined calendar as a result of changes in available time, labor and machinery at any point in the season and recommend possible corrective action if progress is behind schedule at any point.

The authors say, "The farm manager or producer does not need a machinery management tool capable of completely duplicating his/her decision-making process. Nor are they interested in spending a great deal of time learning to use a complex tool, especially if the tool is based on detailed data which they cannot easily supply or will have to estimate."

Therefore, the program was developed to be a decision support system, not a decision-making system, using a limited amount of input data from the farmer and considering his to be an expert on local conditions such as operations scheduling and normal weather conditions.

Another Texas A&M U.-developed machinery selection/management program aims to:

1) Predict in-soil performance of a given tractor,

2) Enable machinery selection for given farm, crop, machinery and weather conditions,

3) Determine cost to own and operate different machinery combinations and define the least cost system, and,

4) Accept readily available information; return easy-to-read and understand output.

But in Farm Machinery Selection and Management System, (ASAE paper 907018), authors, C. Kotzabassis & B.A. Stout, Ag. Engineering Department, Texas A&M, College Station, and H.T. Wiedemann, Texas A&M Research & Extension Center, Vernon, Texas, say the program was designed for "farm managers and consultants, machinery dealers, extension specialists and universities. At this point of time program complexity is still a prohibitive factor for use by farmers," and "there's little potential for program simplification without losing information power." It's an "expert systems" program which must be translated by a "human expert" for farm application.

In A Knowledge-Based Machinery Management System, (ASAE paper 907059), K.E. Oskoui & W.B. Voorhees, USDA-ARS, Morris, MN, & B.D. Witney, Scottish Center of Ag. Engineering, Scotland, models weather/soil/machine interactions in a decision support/making system.

Economics of different machinery management strategies are emphasized: balancing higher timeliness and variable costs of small machinery with higher capital and compaction costs of large machines, comparing lower costs and timeliness penalties (from greater work rate) of reduced-till and no-till with lower yields and higher chemical costs of these systems.

The first program module simulates a given farming system with given climate, soil type and crop conditions, calculates alternative and feasible machinery systems and creates rules for choosing the most suitable machinery system. The second module uses rules created by the first module plus information in the system and obtained from the user to select the most suitable machinery system(s) from a pool of candidates.