Yanina Fumero

Simultaneous design and scheduling of a semicontinuous/batch plant for ethanol and derivatives production

Abstract The interest on renewable fuels has greatly increased in the last years. Particularly, ethanol production arises as a good solution to many current economic-environmental problems. Yeast production from the ethanol residuals constitutes a sustainable alternative. Usually, this kind of plants is designed using single product campaigns. However, since yeast degradation is fast and a continuous supply must be assured, the mixed product campaign policy is the most appropriate. Besides, a stable context can be assumed to justify this approach that takes advantage of the special structure of the plant. Therefore, in this paper, a mixed integer linear programming model is formulated for simultaneous design and scheduling of a semicontinuous/batch plant for ethanol and derivatives production. The optimal plant configuration, unit sizes, number of batches of each product in the campaign and its sequencing is obtained in order to fulfill the ethanol and yeast demands minimizing the investment cost.

Simultaneous design and scheduling of a plant for producing ethanol and derivatives

Abstract In this paper, a mixed integer linear programming model is formulated for the simultaneous design and scheduling of a semicontinuous/batch plant for producing ethanol and two types of yeast. Yeast productions emerge as a sustainable alternative for ethanol residues. The optimal plant configuration, unit sizes, number and size of batches in the campaign and its sequencing is obtained in order to fulfill the ethanol and yeast demands minimizing the investment cost. A novel set of scheduling constraints is proposed for this kind of plants.

A decomposition algorithm for the simultaneous batching and scheduling of multistage batch facilities

Abstract In this work, the simultaneous batching and scheduling problem of multistage batch plants is addressed using mathematical programming. The proposed model can handle multiple orders per product with different due dates, variable processing times, zero-wait transfer policy, and sequence-dependent changeover times. Given the plant configuration, the equipment utilization maximum and minimum capacities and the total required amount of each order, the proposed approach determines the number and size of batches for each customer order, the assignment of batches and their sequence on each unit, and the timing of selected batches, in order to minimize the production and changeover costs. In order to enhance the computational performance of the simultaneous optimization, a solution method based in a decomposition scheme is developed that enables to generate near optimal solutions or the optimal solution of the integrated problem, with reasonable computational effort.

An MILP model for planning of batch plants operating in a campaign-mode

A mixed integer linear programming (MILP) for the detailed production planning of multiproduct batch plants is presented in this work. New timing decisions are incorporated to the model taking into account that an operation mode based in campaigns is adopted. This operation mode assures a more efficient production management adjusted to the specific context conditions of the considered time horizon. In addition, special considerations as sequence-dependent changeover times and different unit sizes for parallel units in each stage are taken into account. The problem consists of determining the amount of each product to be produced, stored and sold over the given time horizon, the composition of the production campaign (number of batches and their sizes), the assignment, sequencing and timing of batches, and the number of repetitions of the campaign, for a given plant with known product recipes. The objective is to maximize the net profit fulfilling the minimum and maximum product demands. The proposed model provides a useful tool for solving the optimal campaign planning of installed facilities in reasonable computation time, taking different decisions about the operations management.

Detailed Supply Chain Design Considering Production Campaigns

Abstract Until now, supply chain (SC) design models have been mainly focused on SC integration, where nodes allocation and links among them are selected in order to allow an efficient operation of the whole system. Usually, the detailed configuration and operation of the plants have not been taken into account. In this work, a heuristic strategy is presented in order to design the SC, including the structure and the operation of plants with mixed product campaigns. The incorporation of plant design and mixed product campaign in the SC design model leads to a non linear formulation. Hence, a two stages approach is addressed in order to solve this problem through linear models. In the first stage, a SC design standard model is solved in order to obtain the network design with minimum logistic cost and the production of each selected plant. These results are used to estimate the possible campaigns composition for each plant. In the second stage, specific scheduling constraints are incorporated in the plant design model to determine the optimal mixed product campaign configuration and the structure of each plant, minimizing the investment cost. This methodology allows obtaining the SC logistic configuration and, for each selected plant, the optimal mixed production campaign simultaneously with the plant design, in order to meet a specified economic criterion fulfilling demand requirements.