Intelligent available-to-promise system under manufacturing uncertainty

Available-to-Promise (ATP) caters to customer order inquiries pertaining to order fulfillment based on resource availability, via considering time phasing and future scheduled receipts. Through this, business decision makers are armed with the requisite information to make informed ordering and manufacturing decisions. Often, deterministic information is assumed to be readily available, i.e., uncertainties are not factored in most manufacturing settings; in reality, the opposite endures. This paper aims to address this through proposing a fuzzy mathematical programming model to solve the problem of order-promising under supply uncertainties. The model minimizes the cost associated with order rejections, promised order lapses, and inventory holding of the finished products and supply materials. In addition, the model caters to order fulfillment, provides a master production schedule for each product and material requirement planning of its respective raw material. Possibility theory is employed to solve the fuzzy mathematical model. After which, the model is evaluated against a deterministic ATP model under different scenarios. Furthermore, sensitivity analysis of the fuzzy model is performed with respect to different user-specific input parameters.