A. Espuña

Global strategy for energy and waste analysis in scheduling and planning of multiproduct batch chemical processes

Abstract Energy integration and waste minimization have received increasing attention in the chemical industry. Recent studies have addressed the specific problems that arise in batch chemical processes. However, a production plan built up using schedules developed beforehand may become inefficient or even fail to attain its production targets. Furthermore, production plans satisfying demand objectives may reduce or even eliminate energy integration or waste minimization opportunities. In this work, waste and energy minimization are treated as an integral part of the constrained production scheduling problem with limited resources. The methodology developed is based on a comprehensive and rigorous modelling framework used to describe the detailed batch process operations as a preliminary step towards their optimization. The methodology will be presented and results from case studies will be provided to illustrate the complex interaction between energy integration, waste minimization and production planning in multiproduct batch processes.

ANALYSIS OF DIFFERENT CONTROL POSSIBILITIES FOR THE DIVIDED WALL COLUMN: FEEDBACK DIAGONAL AND DYNAMIC MATRIX CONTROL

Abstract This work addresses the control of the divided wall column (DWC) as a basic issue to be considered when this kind of distillation arrangement is used to take profit of its potential to reduce energy consumption. Different control structures of diagonal feedback control are compared using multiple input multiple output (MIMO) linear analysis tools in the frequency domain. A controllability analysis of the process is done for the separation of different mixtures and for different operating conditions, including optimal operation. As a result, it is seen that a trade off appears between energy minimisation and controllability. As an alternative, application of dynamic matrix control (DMC) to the DWC is also evaluated. Through simulation, the ability of DMC for disturbance rejection and setpoint tracking is studied and compared with that of the feedback diagonal control. Important limitations of using DMC for the composition control of the DWC are finally highlighted.

Towards an ontological infrastructure for chemical batch process management

A crucial step for batch process improvement and optimization is to develop information structures that streamline data gathering and, above all, are capable of integrating transactional data into a system using the analytical tools that are developed. Current trends in electronics, computer science, artificial intelligence and control system technology are providing technical capability that greatly facilitates the development of multilevel decision-making support. In this paper, we present the batch process ontology (BaPrOn), wherein different concepts regarding batch processes are categorized and the relationships between them are examined and structured in accordance with ANSI/ISA-88 standards, which provide a solid and transparent framework for integrating batch-related information. This paper also focuses on systematic integration of different actors within the control process. The proposed approach bases the conceptualization through the ANSI/ISA-88 representation, providing the advantage of establishing a more general conceptualization of the batch process domain. The capabilities of the envisaged ontological framework were assessed in a test bed PROCEL pilot plant: scheduling-monitoring and control-rescheduling was closed, information quality was accessed by knowledge description, and an optimum decision-making task was performed. The ontological structure can be extended in the future to incorporate other hierarchical levels and their respective modeling knowledge.

Method to incorporate energy integration considerations in multiproduct batch processes

Abstract Systematization of an energy saving grass-root design and retrofitting technology based on process integration is a subject of increasing interest in plants running under the batch mode of operation. In this work, the solution to the product changeover problem is studied in order to achieve a feasible and optimized heat exchance network design for multiproduct batch plants. A new methodology is presented which is based on: (a) the campaign-mode of plant operation; and (b) the study of energy integration for each campaign. The concept of Macronetwork is also introduced. This includes the heat exchanger network of all campaigns in an overall design, and contemplates the common matches between networks of campaigns of different products. Algorithms to obtain the best feasible matches and energy targets are presented and results of test-case studies are discussed to illustrate this methodology.

Decision support framework for coordinated production and transport scheduling in SCM

The efficient coordination of production and distribution systems becomes a challenging problem as companies move towards higher collaborative and competitive environments. Focusing on the operational level of supply chain management (SCM), a framework is proposed to address the interrelated production and transport scheduling problems from the perspective of a production plant of a multi-site system that owns, or leases on a long-term basis, a fleet of vehicles to distribute the products. This framework aims to support the coordination of production and transport activities to properly manage the inventory profiles and material flows between sites. Both production and transport problems are defined as detailed scheduling problems, and different algorithms, either mathematical or heuristic-based, can then be used for their resolution. The flexibility and applicability of the proposed modeling framework is illustrated through two different case studies, which highlight the benefits of coordinating both activities in such a complex supply chain (SC) environment.

Incorporating on-line scheduling strategies in integrated batch production control

Abstract Given a set of product recipes, the main goal of production scheduling is to attain an optimal solution which satisfies the market demand taking into account a variety of constraints and specific policies. Thus, a schedule is generated capable of accepting certain degree of variability during batch production. But, in most cases an on-line adjustment to the real conditions is required. In this paper, it is presented a reactive scheduling algorithm, which adapts the current schedule to real time disturbances, integrated to a supervisory system capable of handling the new schedule generated thus, filling the existing gap between high production scheduling and low sequential control levels in the Chemical Process Industries. Changes of tasks start times and units reassignment are considered in a decision tree level based on heuristic rules.

A new look at energy integration in multiproduct batch processes

Abstract Systematization of an energy saving grass-root design and retrofitting technology based on process integration is a subject of increasing interest in plants running under the batch mode of operation. In this work, the solution to the changeover product problem is studied in order to achieve a feasible and optimized heat exchange network design for multiproduct batch plants. A new methodology is presented which is based on: a) the campaign-mode of plant operation, b) the study of energy integration for each campaign. The concept of Macronetwork is also introduced. This includes the heat exchanger network of all campaigns in an overall design, and contemplates the common matches between networks of campaigns of different products. Algorithms to obtain the best feasible matches and energy targets are presented and results of test-case studies are discussed to illustrate this methodology.

A combined scheduling reactive scheduling strategy to minimize the effect of process operations uncertainty in batch plants

Abstract This paper deals with production scheduling of multipurpose batch chemical plants under uncertainty. The uncertainty associated with process operations causes that production can not be carried out exactly as scheduled. Variations in task processing times and equipment availability can make the initial schedule inefficient. A combined strategy has been proposed to minimize effects due to these variations. It involves the generation of robust schedules and then the application of a reactive scheduling procedure to adapt the original schedule to the new scenario. An industrial based case study is used to show the advantages of this combined strategy.

Proactive approach to address the uncertainty in short-term scheduling

The identification of reliable schedules serves a valuable function as a basis for coordinating outside activities within the highly dynamic and uncertain supply chain (SC) environment. A contribution is made in the area of proactive scheduling with the development of a stochastic modeling framework to support the short-term scheduling problem with uncertain operation times and equipment breakdowns. A set of scenarios for the uncertain parameters is anticipated in the decision stage, along with information concerning the reactive scheduling approach to be taken during schedule execution. A robust predictive schedule is pursued, with the flexibility to absorb disruptive events without major changes when rescheduling is required. Either rigorous or heuristic techniques can be used to optimize a robustness measure that explicitly accounts for the eventual wait times and idle times that may arise during execution. The application of the framework to different case studies shows the flexibility of the predictive schedule, the different decisions that can be drawn based on the rescheduling strategy considered, and the importance of exploiting the information of the uncertainty as well as the incorporation of the rescheduling policy proactively.

Toward integrated production and distribution management in multi-echelon supply chains

Abstract The effective management of multi-site systems involves the proper coordination of activities performed in multiple factories, distribution centers (DCs), retailers and end-users located in many different cities, countries and/or continents. To optimally manage numerous production and transportation decisions, a novel monolithic continuous-time MILP-based framework is developed to determine the best short-term operational planning to meet all customer requests at minimum total cost. The formulation lies on the unit-specific general precedence concept for the production scheduling problem whereas the immediate precedence notion is used for transportation decisions. To illustrate the applicability and potential benefits of the model, a challenging example corresponding to a supply chain comprising several locations geographically spread in six European countries has been solved to optimality with modest CPU times. Several scenarios with different logistics features were addressed in order to remark the significant advantages of using the integrated approach.