Analysis of the policy of operation activity of an enterprise with product reservation

Abstract

This paper examines the process of operative planning of the production of an industrial company under conditions of random fluctuations in current demand. It is shown that under these conditions there are losses, the size of which depends on the adopted policy of operation activity. The policy of operation activity is understood as the rule of making decisions on current production volumes based on information about incoming orders, probable volumes of future demand, and possible losses due to the deviation of capacity load from the normative one. In the paper, it is proposed to assess the effectiveness of each policy of operation activity using the indicator of the limit average economic effect per unit of time for an infinite number of periods. An original approach to assessing the effectiveness of the policy of operation activity with product reservation was developed. It was shown that when using this policy, there is an effect of product "overstock" on the chains of successive periods. It was proposed to select the initial reserve so that the probability of completion of the reservation chain for a given number of periods should be close to unity. Such an approach creates an opportunity to determine the expected economic effect on the chains of reservation of various product types and, as a result, to assess the policy effectiveness in general. An assessment of the effectiveness of the policy with reservation in the form of the dependence of the policy effectiveness indicator on the values of cost indicators was obtained. Comparison of this assessment with a similar assessment of the effectiveness of the policy of fulfilling incoming orders allowed finding a condition under which the policy with reservation is more profitable. It involves ensuring that the magnitude of losses per unit of production associated with the product stock storage does not exceed half the sum of the magnitude of losses per unit of production due to downtime and excess capacity load.