Integration of enterprise levels based on an ontological framework

Enterprises are highly complex systems in which one or more organizations share a definite mission, goals and objectives to offer a product or service. In this study, an ontological framework is built as a mechanism for exchanging information and knowledge models for multiple applications and effective integration between hierarchical levels. The potential of the general semantic framework that is developed is demonstrated using a case study concerning the enterprise supply chain network design-planning problem.     

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.     

A new Lagrangian decomposition approach applied to the integration of refinery planning and crude-oil scheduling

The aim of this paper is to introduce a methodology to solve a large-scale mixed-integer nonlinear program (MINLP) integrating the two main optimization problems appearing in the oil refining industry: refinery planning and crude-oil operations scheduling. The proposed approach consists of using Lagrangian decomposition to efficiently integrate both problems. The main advantage of this technique is to solve each problem separately. A new hybrid dual problem is introduced to update the Lagrange multipliers. It uses the classical concepts of cutting planes, subgradient, and boxstep. The proposed approach is compared to a basic sequential approach and to standard MINLP solvers. The results obtained on a case study and a larger refinery problem show that the new Lagrangian decomposition algorithm is more robust than the other approaches and produces better solutions in reasonable times.     

A novel two-stage Lagrangian decomposition approach for refinery production scheduling with operational transitions in mode switching☆

To address large scale industrial processes, a novel Lagrangian scheme is proposed to decompose a refinery scheduling problem with operational transitions in mode switching into a production subproblem and a blending and delivery subproblem. To accelerate the convergence of Lagrange multipliers, some auxiliary constraints are added in the blending and delivery subproblem. A speed-up scheme is presented to increase the efficiency for solving the production subproblem. An initialization scheme of Lagrange multipliers and a heuristic algorithm to find feasible solutions are designed. Computational results on three cases with different lengths of time hori-zons and different numbers of orders show that the proposed Lagrangian scheme is effective and efficient.     

A multi-level simulation approach for the crude oil loading/unloading scheduling problem

An integrated approach for refinery production scheduling and unit operation optimization problems is presented. Each problem is at a different decision making layer and has an independent objective function and model. The objective function at the operational level is an on-line maximization of the difference between the product revenue and the energy and environmental costs of the main refinery units. It is modeled as an NLP and is constrained by ranges on the unit's operating condition as well as product quality constraints. The production scheduling layer is modeled as an MILP with the objective of minimizing the logistical costs of unloading the crude oil over a day-to-week time horizon. The objective function is a linear sum of the unloading, sea waiting, inventory, and setup costs. The nonlinear simulation model for the process units is used to find optimized refining costs and revenue for a blend of two crudes. Multiple linear regression of the individual crude oil flow rates within the crude oil percentage range allowed by the facility is then used to derive linear refining cost and revenue functions. Along with logistics costs, the refining costs or revenue are considered in the MILP scheduling objective function. Results show that this integrated approach can lead to a decrease of production and logistics costs or increased profit, provide a more intelligent crude schedule, and identify production level scheduling decisions which have a tradeoff benefit with the operational mode of the refinery.     

Supply chain optimisation for the process industries: Advances and opportunities

Supply chain management and optimisation is a critical aspect of modern enterprises and a flourishing research area. This paper presents a critical review of methodologies for enhancing the decision-making for process industry supply chains towards the development of optimal infrastructures (assets and network) and planning. The presence of uncertainty within supply chains is discussed as an important issue for efficient capacity utilisation and robust infrastructure decisions. The incorporation of business/financial and sustainability aspects is also considered and future challenges are identified.     

Integration of production planning and scheduling: Overview, challenges and opportunities

We review the integration of medium-term production planning and short-term scheduling. We begin with an overview of supply chain management and the associated planning problems. Next, we formally define the production planning problem and explain why integration with scheduling leads to better solutions. We present the major modeling approaches for the integration of scheduling and planning decisions, and discuss the major solution strategies. We close with an account of the challenges and opportunities in this area.     

The effect of uncertainty on the optimal closed-loop supply chain planning under different partnerships structure

In a global economy, the key to success is providing products around the world at the right time in the right quantity and quality, at a low cost. Efficient supply chains have an important role in guaranteeing this success. Optimized planning of such structures is required and uncertainties regarding product demands and prices, amongst other supply chain conditions, should also be considered. In this paper, we look into supply chain planning decisions that account for uncertainty on product portfolios demand and prices. A multi-period planning model is developed where the supply chain operational decisions on supply, production, transportation, and distribution at the actual period consider the uncertainty on products’ demand and prices. Different decision scenarios, involving the evaluation of the supply chain economical performance, are analyzed (e.g. global operating costs/profit realized) for different criteria on the importance of the partners within the global chain (i.e. partners’ structure). A Mixed Integer Linear Programming (MILP) formulation is formulated for each planning scenario and the optimal solution is reached using a standard Branch and Bound (B&B) procedure. The final results provide details on the supply chain partners production, transportation and inventory, at each planning period, while accounting for the importance of each partner in the global chain as well as demand/price uncertainties. The applicability of the developed formulation is illustrated through the solution of a real case-study involving an industrial chain in the pharmaceutical sector.     

Mathematical programming and game theory optimization-based tool for supply chain planning in cooperative/competitive environments

This work proposes to improve the tactical decision-making of a supply chain (SC) under an uncertain competition scenario through the use of different optimization criteria, which allows to manage not only the specific objectives of the SC of interest, but also the way how its clients address their selection between different potential suppliers, identifying best market share for the SC of interest and the strategy to attain it. The resulting multi-objective optimization problem has been solved using the ?-constraint method in order to approximate the Pareto space of non-dominated solutions while a framework based on game theory is used as a reactive decision making support tool to deal with the uncertainty of the competitive scenario. The use of the proposed system is illustrated through its application to a multi-product, multi-echelon supply chain case study, which is intended to cooperate or to compete with another SC of similar characteristics.     

The multi-echelon vehicle routing problem with cross docking in supply chain management

Multi-echelon distribution networks are quite common in supply chain and logistics. Deliveries of multiple items from factories to customers are managed by routing and consolidating shipments in warehouses carrying on long-term inventories. On the other hand, cross-docking is a logistics technique that differs from warehousing because products are no longer stored at intermediate depots. Instead, cross-dock facilities consolidate incoming shipments based on customer demands and immediately deliver them to their destinations. Hybrid strategies combining direct shipping, warehousing and cross-docking are usually applied in real-world distribution systems. This work deals with the operational management of hybrid multi-echelon multi-item distribution networks. The goal of the N-echelon vehicle routing problem with cross-docking in supply chain management (the VRPCD-SCM problem) consists of satisfying customer demands at minimum total transportation cost. A monolithic optimization framework for the VRPCD-SCM based on a mixed-integer linear mathematical formulation is presented. Computational results for several problem instances are reported.     

A generalized method for the synthesis and design of reactive distillation columns

Owing to the combination between the reaction operation and the separation operation involved, it is extremely difficult to determine in advance the optimum configuration of a reactive distillation column and this makes process synthesis and design a great challenging task. Currently, no easy-to-use and yet effective methods are available to guide process synthesis and design, restricting considerably the applications and therefore the impacts of reactive distillation columns to the chemical process industry. In this paper, a generalized method is proposed for the synthesis and design of reactive distillation columns in terms of the insights from process intensification. The method is initiated from a simple process design with all feeds of reactants at the middle of the process and all stages as reactive ones. In terms of an economical objective function, it can be evolved into the optimum process design via sequential structure adjustments, including reactive section arrangement, feed stage relocation, feed splitting, and catalyst redistribution. The generalized method proposed is characterized by great simplicity in principle, the capability to tap the full potentials of process intensification, and the high robustness to the initial guess of process configuration as well as the thermodynamic properties of the reacting mixtures separated. Four example systems are employed to evaluate the generalized method proposed and the obtained outcomes demonstrate its effectiveness and applicability to the synthesis and design of various reactive distillation columns.     

Multiscale strategic planning model for the design of integrated ethanol and gasoline supply chain

The design and planning of an integrated ethanol and gasoline supply chain is addressed, and is composed of harvesting and production sites for ethanol, petroleum refineries, distribution centers where blending takes place, and the retail gas stations where blends of gasoline and ethanol are sold. We postulate a superstructure that combines all the components of the supply chain and different means of transportation, and model this multiscale design problem as a multiperiod MILP model. In order to identify regions where investments are needed and the optimal configuration of the network, a strategic planning model is considered in which gasoline stations are aggregated in different regions. A detailed formulation is considered where regions are disaggregated into gas stations to determine the retrofit projects for the selection of blending pumps over their expected life. Also, the application of these MILP models with two large‐scale problems are illustrated. © 2013 American Institute of Chemical Engineers AIChE J, 59: 4655–4672, 2013     

A fundamental principle and systematic procedures for process intensification in reactive distillation columns

A fundamental principle is developed for process intensification through internal mass and energy integration in reactive distillation columns and three systematic procedures are devised for process synthesis and design. For reactive distillation columns involving reactions with highly thermal effect, process intensification can be achieved with an exclusive consideration of internal energy integration between the reaction operation and separation operation involved. However, in the case of a highly endothermic reaction with an extremely low reaction rate and/or small chemical equilibrium constant, internal mass integration has also to be considered between the reactive section and stripping section. For reactive distillation columns involving reactions with negligibly or no thermal effect, process intensification can be performed with an exclusive consideration of internal mass integration. For reactive distillation columns involving reactions with moderately thermal effect, process intensification must be conducted with a careful trade-off between internal mass and energy integration. Five hypothetical and two real reactive distillation systems are employed to evaluate the principle and procedures proposed. It is demonstrated that intensifying internal mass and energy integration is really effective for process intensification. Not only can the thermodynamic efficiency be improved substantially, but also the capital investment can be further reduced.