Scheduling flexible manufacturing systems for apparel production

In mid to high volume apparel production, garments are typically grouped into production lots, and each lot is processed in its own manufacturing cell, A flexible manufacturing system used in this environment enables quick cell configuration, and the efficient operation of cells. The scheduling problem is to decide when to set up a cell and consequently begin garment production in the cell, and to decide the quantity of machines to allocate to each cell, under the constraints of limited machines, The time to process a production lot depends on the quantity of machines allocated to the cell in which the lot will be processed, and thus scheduling and resource allocation are highly coupled, Past approaches separate the resource allocation and scheduling decisions because the combined problem is too complex to be solved in a practical amount of time, In this paper, an accurate and low-order integer programming model is developed which integrates scheduling and resource allocation, Insight is provided into how the model relates to the operation of a real factory, The model is solved using the Lagrangian relaxation methodology, and a new bundle method is used for optimizing the Lagrangian dual function, The combination of an accurate low-order model, Lagrangian relaxation, and the bundle method is shown to be very practical, Testing is performed using data from a real factory producing 10 to 40 lots per week (between 4500 and 8900 garments total) on 105 machines of nine different types, Numerical results show that one-week schedules are generated in less than 3.5 CPU min on a 60 MHz personal computer, and the schedules are within 16-29% of optimal.