Operations Research - Optimum Production Planning

This paper is concerned with the details of the derivation of an operations research model, specifically linear programming, to solve production scheduling problems. While some results are presented for an actual study, the calculation of cases of a more general nature have not yet been completed. Production managers from those segments of the mining industry that experience a seasonal or highly variable sales demand find it rather difficult to develop overall producing plans for their organizations. In an attempt to solve this technical problem, demands are usually met by keeping production corresponding exactly to sales. This results in a fluctuating production schedule which is costly to maintain because of overtime premiums in periods of high requirements and because of costs associated with an idle mine plant during slack periods. An alternate solution may be to produce part of the desired amount and make up any deficiencies by using overproduction in previous time periods. This tends to smooth the production pattern through the use of a stockpile. However, because of associated storage costs, the solution may again be undesirable if it yields comparatively large surpluses. In general, this type of scheduling problem has an infinite number of solutions which satisfy the requirements. These are largely dependent on the extent to which an operation is geared to changes in production and on the size of its stockpiling facility. The determination of an efficient schedule is implied, therefore, as one lying between two extreme solutions, i.e., one that minimizes surpluses and one that minimizes output fluctuations. These conflicting objectives result in an economic balance problem between the costs of carrying surpluses forward from slack periods versus the cost of high production levels during peak demands. Various methods of operations research have been developed to handle problems whose genesis is explained above. It is very seldom, however, that these quantitative means are used in practice by the mining industry. Those who are familiar with mining operations know that most managers have not progressed satisfactorily in this area. Production planning systems which most mines employ today are often no more than rough records of management's mental planning. For small mines these means are normally sufficient; but as operations grow larger and become more complex, this type of planning ability is no longer adequate. Managers may find themselves losing control of cost relationships, taking longer to outline production sequences, and becoming forgetful of certain resource availabilities. ORIGIN AND SCOPE OF A SCHEDULING PROBLEM The more fundamental aspects of the production scheduling problem can be brought into focus by demonstrating how it exists in a bituminous coal mine* located in southwestern Pennsylvania. This mine, operating in the Pittsburgh seam, uses a definite room-and-pillar block system of mining, which is planned and carried out with only slight variations to meet local conditions. The coal seam, which is firm and varying in thickness from 8 to 9 ft with the bottom 6% ft being extracted, is under 500 ft of cover and opened by a shaft. The bulk of the coal (60%) is obtained from the pillaring activity with the mains and sections, which are considered primarily as development activities, contributing the balance of 12% and 28%, respectively. All coal is won by a ripper-type continuous miner in conjunction with shuttle-cars directly behind a loading machine. Track haulage is employed to move coal from these machine centers to the shaft bottom. The coal, thus mined, is shipped to one destination as part of a mixture of coals to be used in the making of steel. A material flow diagram of this distribution scheme is illustrated in Fig. 1. PROBLEM STATEMENT From the above types of shipments and mining limitations, the basic problem is to determine an economic means of producing and stockpiling a single coal product produced in three different machine centers (main, section, and pillar). Fig. 2 shows total demand for coal as a function of time. Because of the extremely high peak demands, slack period production must be stored and then distributed