A multi-attribute quality control cost model is presented in this thesis. The mathematical model expresses the expected total cost of the quality system per lot as a function of the decision variables, nᵢ and cᵢ, i = 1, 2, . . . , m, where nᵢ is the sample size for the ith attribute. cᵢ is the acceptance number for the ith attribute. m is the number of attributes. The expected total cost is denoted by C_T and can be expressed as C_T = E (cost of sampling inspection). E (cost of accepting the lot). E (cost of rejecting and scrapping the lot). E (cost of rejecting and screening the lot). An optimal sampling plan can be obtained by determining the nᵢ and cᵢ, i = 1, 2, …, m, that minimizes C_T. The nᵢ and cᵢ are found by means of a search technique that has proved useful in attribute quality control systems. In addition to the model development and optimization, a sensitivity analysis is performed on the use of the gallllla distribution as an estimate of the true process distribution for single and triple attribute systems. Also, a model sensitivity analysis is performed on errors in the estimation of the Cₐᵢ, the cost of accepting a defective unit. / Master of Science