Antonio Espuña

Incorporating environmental impacts and regulations in a holistic supply chains modeling: An LCA approach

Abstract Corporate approaches to improve environmental performance cannot be undertaken in isolation, so a concerted effort along the supply chain (SC) entities is needed which poses another important challenge to managers. This work addresses the optimization of SC planning and design considering economical and environmental issues. The strategic decisions considered in the model are facility location, processing technology selection and production–distribution planning. A life cycle assessment (LCA) approach is envisaged to incorporate the environmental aspects of the model. IMPACT 2002+ methodology is selected to perform the impact assessment within the SC thus providing a feasible implementation of a combined midpoint–endpoint evaluation. The proposed approach reduces the value-subjectivity inherent to the assignment of weights in the calculation of an overall environmental impact by considering endpoint damage categories as objective function. Additionally, the model performs an impact mapping along the comprising SC nodes and activities. Such mapping allows to focus financial efforts to reduce environmental burdens to the most promising subjects. Furthermore, consideration of CO 2 trading scheme and temporal distribution of environmental interventions are also included with the intention of providing a tool that may be utilized to evaluate current regulatory policies or pursue more effective ones. The mathematical formulation of this problem becomes a multi-objective MILP (moMILP). Criteria selected for the objective function are damage categories impacts, overall impact factor and net present value (NPV). Main advantages of this model are highlighted through a realistic case study of maleic anhydride SC production and distribution network.

Simultaneous optimization of process operations and financial decisions to enhance the integrated planning/scheduling of chemical supply chains

Abstract This paper addresses the integrated planning/scheduling of chemical supply chains (SC) with multi-product, multi-echelon distribution networks taking into account financial management issues and suggests a novel approach for enterprise wide management. In order to tackle this problem, it is derived a mathematical formulation combining a scheduling/planning model with a cash flow and budgeting formulation. To motivate the use of such integrated model, a sequential scheme representing traditional enterprise practices is firstly applied. Within this strategy, scheduling and planning decisions are taken firstly, and finances are fitted afterwards considering the cash flows associated to the scheduling/planning decisions previously computed as input parameters. The comparison between the results of the sequential approach and those of the integrated model highlight the advantages of the latter option, in which scheduling/planning and cash management decisions are optimized in unison with a common objective of maximizing the change in equity achieved by the company. The modeling approach developed in this paper and the obtained results suggest that a new conceptual strategy in enterprise management systems consisting of the integration of the financial models of the enterprise with those dealing with the operative area is a must to improve the firm’s performance and its overall earnings and ensuring also healthy cash flow management.

Control and optimization of the divided wall column

The divided wall column (DWC) is, in terms of capital costs and energy savings, a promising alternative for separating ternary mixtures. Since its design was proposed, almost 50 years ago, many authors have addressed design considerations. Operation and control of the DWC have received much less attention. However, some works have been published recently. Preliminary results reported indicate that feedback diagonal control structures may be used to control the DWC. In this work, the study of feedback diagonal control strategies has been further extended to consider the DWC control design in detail. Different control structures have been systematically analyzed and compared under performance and robustness considerations. In order to study the effect of the energy optimization on the controllability of the DWC, a column at optimal nominal operating conditions is compared to a column under non-optimal operation. Finally, a complete control strategy is proposed. Linear analysis tools are used for the multiple input multiple output (MIMO) feedback control analysis, and simulations using a non-linear model are performed to study the non-linear behavior of the control systems.

Optimisation of water use in batch process industries

Abstract The water management in the batch process industries has been optimised considering the reuse of water effluents in the same plant through storage tanks. For a given production plan, the characterisation of the water streams associated to the different production tasks is established. The connections between the available tanks and the water streams have been determined targeting different aspects: freshwater demand, water cost, utility demand of water streams and water reuse network costs. The water reuse system has been modelled, simulated and optimised. A software tool has been developed that permits an easy application of the methodology.

On-line fault diagnosis system support for reactive scheduling in multipurpose batch chemical plants

Abstract In this work, a simple strategy for the development and implementation of a fault diagnosis system (FDS) that interacts with a schedule optimiser in batch chemical plants is presented. The proposed FDS consists of an artificial neural network (ANN) structure supplemented with a knowledge-based expert system (KBES) in a block-oriented configuration. The system combines the adaptive learning diagnostic procedure of the ANN and the transparent deep knowledge representation of the KBES. The information needed to implement the FDS includes a historical database of past batches, a Hazard and Operability (HAZOP) analysis and a model of the plant. Two motivating case studies are presented to show the results of the proposed methodology. The first corresponds to a fed-batch reactor. In this example, the FDS performance is demonstrated through the simulation of different process faults. The second case study corresponds to a multipurpose batch plant. In this case, the results of reactive scheduling are shown by simulating different abnormal situations. A performance comparison is made against the traditional scheduling approach without the support of the proposed FDS.

Batch production and preventive maintenance scheduling under equipment failure uncertainty

This paper deals with production scheduling of multipurpose batch plants in the presence of equipment failure uncertainty. Uncertainty analysis is incorporated at the production scheduling stage to improve the probability of performing the resulting schedule. So, the need of complete rescheduling of the production plan is reduced and more effective reactive scheduling strategies can be applied each time a deviation from the expected plant status occurs. The probability of performing the predicted schedule will depend on equipment failure forecasts. The effects of equipment failure on the production schedule are minimized by computing the reliability indexes for each plant unit and for each scheduled task. Avoiding the use of equipment with low reliability indexes is balanced against production requirements (demand). Preventive maintenance tasks may be also introduced to compensate for possible delays produced by the use of equipment units with low reliability indexes. The incorporation of these methodologies into the overall planning framework is also shown and illustrated with case studies.

Study of the divided wall column controllability: influence of design and operation

Abstract The main objective of this work is to studh the influence of design and operating conditions on the divided wall column (DWC) controllability. Firstly, two designs for which the total distillation cost is minimised are compared. For each design, different optimal reflux to minimum reflux ratio is assumed. Secondly, three non-optimal designs are compared with an optimal one. Adding trays to different column sections, the distribution of the distillation effort is changed. The effect of this change on the controllability is studied. The DWC has extra operation degrees of freedom and the operation that minimises the boilup is searched. The influence of the operating conditions over the controllability is studied comparing optimal and non-optimal nominal operations.

Scheduling and control decision-making under an integrated information environment

The complexity of decision-making in process industries and the need of highly competitive organizations require new supporting tools to coordinate and optimize the information flow among decision levels. This work presents a framework for integrating the scheduling and control decision levels by means of an ontology, which allows and coordinates the information exchange among the different modeling paradigms/conventions currently used for the enterprise-wide optimization (EWO). The scheduling of two multiproduct batch plants with increasing complexity is presented for illustrating the proposed working procedure.

An agent-based approach for supply chain retrofitting under uncertainty

In this work, decisions that have a long lasting effect on the supply chain (SC) such as the design and retrofit of a production/distribution network are considered. The retrofitting tasks are accomplished by using a SC agent-oriented simulation system, which model each entity belonging to the SC as an independent agent. The starting point is a set of possible design options for the existing SC. For each design alternative a performance index is obtained through the agent-based framework by looking for the best value of the operational variables associated to the resulting network. The proposed methodology allows to address the design of complex SCs which are hard to be modelled otherwise, for example by means of standard mathematical programming tools. Specifically, the multi-agent system is suitable for SCs that are either driven by pull strategies or operate under uncertain environments, in which the mathematical programming approaches are likely to be inferior due to the high computational effort required. The advantages of our approach are highlighted through a case study comprising several plants, warehouses and retailers.

Neural network based framework for fault diagnosis in batch chemical plants

Abstract In this work, an artificial neural network (ANN) based framework for fault diagnosis in batch chemical plants is presented. The proposed FDS consists of an ANN structure supplemented with a knowledge based expert system (KBES) in a block-oriented configuration. The system combines the adaptive learning diagnostic procedure of the ANN and the transparent deep knowledge representation of the KBES. The information needed to implement the FDS includes a historical database of past batches, a hazard and operability (HAZOP) analysis and a model of the batch plant. The historical database that includes information related to normal and abnormal operating conditions is used to train the ANN structure. The deviations of the on-line measurements from a reference profile are processed by a multi-scale wavelet in order to determine the singularities of the transients and to reduce the dimensionality of the data. The processed signals are the inputs of an ANN. The ANNs outputs are the signals of the different suspected faults. The HAZOP analysis is useful to build the process deep knowledge base (KB) of the plant. This base relies on the knowledge of the operators and engineers about the process and allows the formulation of artificial intelligence algorithms. The case study corresponds to a batch reactor. The FDS performance is demonstrated through the simulation of different process faults. The FDS proposed is also compared with other approaches based on multi-way principal component analysis.