Alberto Bandoni

Interaction between process plant operation and cracking furnaces maintenance policy in an ethylene plant

Abstract This work addresses the problem of the determination of a maintenance policy for cracking furnaces in an ethylene plant, taking into account the interactions between the entire process plant operation and furnace performance. An important recycle stream (ethane from units downstream the furnaces) constitutes part of the feed, so nonlinear models of units from the entire ethylene process have been included in the optimization problem. The resulting model is a mixed integer nonlinear programming problem where integer variables are associated to the number of time cycles that each feed is processed in a furnace.

Optimal Planning of the Sustainable Supply Chain for Sugar and Bioethanol Production

Abstract The interest in renewable fuels such as bioethanol has significantly increased in the last years all over the world. In this work, a decision-support tool based on a mixed integer linear model for the design of sugarcane supply chains (SC) is developed. The approach considers the minimization of the total SC costs and environmental impact, which is determined according to the Life-Cycle Assessment principles. The solution is a set of Pareto optimal alternatives, i.e. SC configurations with associated strategic planning decisions. The capabilities of the proposed framework are illustrated through a case-study designed on the basis of the current situation in Argentina.

Model Predictive Control based planning in the fruit industry

Typical Fruit Industry Supply Chains are highly interconnected networks conformed by farms, packaging plants, cold storage facilities and concentrated juice plants along with clients and third party raw material and services suppliers. The operational planning of such a chain should seek to respond to the before-the-season established product delivery commitments rather than to react in the face of “on-line” customer demand as in classic chains. In this contribution the operational planning of a typical fruit industry supply chain is addressed by means of a Model Predictive Control based scheme which is a model based control strategy that shows attractive features for multivariable, highly interacting, uncertain systems. This methodology naturally allows addressing the meaningful uncertainty in the system parameters and the possibility of supply chain disruption episodes.

Back-off application for dynamic optimisation and control of nonlinear processes

Abstract The operating point of a process plant is obtained through optimisation of an objective function subject to certain constraints. Typically, the resultant point lies in the boundary of the operative region. Therefore, in the presence of disturbances, the constraints may be violated and the process may be obliged to operate in an infeasible region. The goal of this paper is to present an efficient back-off algorithm to determine the operating point which guarantees feasibility even under disturbances effects. The proposed method is especially oriented to diminish the computational time associated with nonlinear processes. For this purpose, the nonlinear process is approximated by means of a piecewise linear (PWL) model which allows a substantial computational time reduction. Finally, an example is dealt with to show the application of the proposed approach. For this purpose, a nonlinear steam generating process is modelled, optimised and controlled.