Daniel Rossit

Industry 4.0: Smart Scheduling

Smart Manufacturing and Industry 4.0 production environments integrate the physical and decisional aspects of manufacturing processes into autonomous and decentralised systems. One of the main aspects in these systems is production planning, in particular scheduling operations on machines. We introduce here a new decision-making schema, Smart Scheduling, intended to yield flexible and efficient production schedules on the fly, taking advantage of the features of these new environments. The ability to face unforeseen and disruptive events is one of the main improvements in our proposed schema, which uses an efficient screening procedure (Tolerance Scheduling) to lessen the need of rescheduling in the face of those events.

The Dominance Flow Shop Scheduling Problem

Abstract We introduce a new line of analysis of Flow Shop scheduling problems, for the case of two jobs and assuming that processing times are unknown. The goal is to determine the domination relations between permutation and non-permutation schedules. We analyze the structural and dominance properties that ensue in this setting, based on the critical paths of schedules.

Forest management decision making based on a real options approach: An application to a case in northeastern Argentina

Abstract The Net Present Value (NPV) approach is widely applied to assess forest investments, but this method has serious shortcomings, which we propose to overcome by switching to the assessment through the Real Options Approach (ROA). The model in this paper starts with the simulation of the forest’s growth, combined with the projection of the products’ prices and valuing the assets using a binomial model. We include an option of postponement, determining the optimal period of felling. We find that ROA is more robust than the NPV approach because it relaxes the assumption of constancy of both the prices and the discount rate, allowing the determination of the optimal time of felling based on the growth rate of either the forest or the prices of its products. Contrary to the traditional NPV approach, the results obtained with ROA exhibit longer harvest turns and consequently higher profits. The key variable in the ROA, the Real Option Value (ROV) can be shown to be less (albeit moderately) sensitive to decreases of the discount rate than NPV. Moreover, ROV is moderately sensitive to decreases in the price of logs and is negligibly affected by rises in the costs of harvesting, loading and transporting rolls.