No abstract

Mathematical modeling and simulation of cotton fabric drying in a stenter machine was performed using a finite element method. A standard κ-ɛ turbulence model was coupled with heat/mass transfer in porous media models. A novel approach to simulate all injectors enabled a new perspective of the process and the calculation of local convective coefficients. Three simulations were run: Simulation I reproduced real operational conditions; Simulations II and III estimated the effects of increasing drying air inlet velocity and decreasing translational velocity of the fabric, respectively. The highest drying air velocities occurred at the nozzles on the edges of the injectors, leading to high convective heat and mass transfer coefficients. Results indicated the drying process was not uniform along the fabric’s width. The models were acceptable in realistically predicting the drying of a cotton fabric in a stenter machine and could be useful in optimizing the stenter design considering the final product’s quality and energy consumption.

The purpose of the research was to determine the sequencing of the production of n jobs in m operations in a small footwear company in an environment of flow shop machine characteristics, which optimizes the total time of completion of the job in the production system (Makespan). We used heuristic algorithms that were applied through Lekin and WinQSB softwares, and for the optimization algorithm we designed a mathematical model that was solved by Juliabox software. Results show that the integer linear programming and local search minimize the makespan with 3807 minutes, and different production sequences for each algorithm, which consider permutation, which improves the traditional way of programming the production in 97 minutes, however, the optimization presents better results in the performance measures of average waiting time, average time of flow, and average job in process. Application of heuristic algorithms proves to be simple and fast, but the mathematical model of optimization designed and encoded in the software is a flexible and valuable tool for decision making in production programming, which could be applied in other footwear companies, and in other productive sectors whose companies have the same characteristics of the case study, reducing costs and improving delivery times.