Optimal stock control and procurement by reusing of obsolescences in manufacturing

Production, procurement planning and logistic organization are complex tasks in companies with multiple production/stocking sites. For companies operating in fashion markets, these tasks are harder due to the high demand variability and frequent turnover of trends that make products outmoded rapidly. In the field of industry informatics under an Industry 4.0 scenario, this paper presents a data and processing framework that mix a Decision Support System (DSS) and a Mixed Integer Linear Programming (MILP) model to maximize the potential revenue of the outmoded products. The solution proposed considers both the investment for missing components and the transportation costs between hubs and takes into account constraints on the overall number of items produced, the budget for new component orders and the minimum lot scheduling thresholds. Moreover, to avoid the increment of obsolescences due to raw material orders, the MILP model bounds purchased components to a percentage of used ones. A real worldwide dataset provided by a fashion company, market leader in the design, manufacture and distribution of fashion, luxury, sports and performance eyewear, was used to test performances and repeatability of the mathematical model under different configurations. The results obtained show a huge positive impact on the financial results.