Abstract: To adapt to the digital transformation of enterprises, a step-by-step optimization algorithm （SOA） is proposed to solve the one-dimensional cutting stock problem using the linear programming method, which is difficult to generate all feasible cutting patterns and solve with inequality constraints, resulting in inconsistent results with the number of parts in the demand order. Firstly, Preliminary results were obtained by applying inequality constraints on the number of parts using a finite cutting pattern model that limits the number and utilization of cutting patterns; Then, by filtering the results twice, an optimal set of cutting patterns consisting of cutting patterns containing excess parts is obtained; Finally, the optimal cutting pattern set is split into subproblems, which are solved by generating all feasible cutting patterns and applying equality constraints to the number of parts to obtain the exact solution of the one-dimensional cutting stock problem. The calculation results show that the application of the step-by-step optimization algorithm accurately corresponds to the type and quantity requirements of the parts, with faster calculation speed and wider adaptability.