An adaptable automated visual inspection scheme through online learning

The problem of product rate variation (PRV) attempts to balance the production rate with the customer demand. Although this problem is reviewed numerously in literature, none of them considered PRV under an uncertain environment. In practical situations, the demand of each product is unknown in advance, and just an approximation of it is considered. In the real situation, we try to predict the demand of each product, and then the production schedule can be arranged. In this paper, an attempt has been made to optimize the flow between uncertain demand of each product and production schedule by using stochastic programming. In fact, we have applied probability density functions to show the uncertainty of demands; then, we have optimized the deviation of production schedule from the ideal rate of production. Also, we have implemented a real numerical case study to demonstrate the applicability of the proposed method and compare the finding results with deterministic solution by constructing a simulation study.