Refinery supply chain

Figure 3.1 Refinery supply chain with process network integration.

Keywords Disruption Management, Uncertainty, Refinery, Supply Chain Modeling. 

M. Mishra, R. Srinivasan, and I. A. Karimi, 2003, Managing disruptions in refinery supply chain using an agent-based decision support system. Presented at the AIChE annual meeting, San... 

Pure simulation approaches are proposed by Pitty et al. (2008) and Adhitya and Srini-vasan (2010). Pitty et al. (2008) propose a discrete-event simulation model for a refinery supply chain. Operational decisions such as unloading schedules and production planning are made based on simple priority rules. Various configurations of the modelled SC are studied and compared to reveal optimization potentials. This approach explicitly considers some details of ship and pipeline transports. Adhitya and Srinivasan (2010) describe a discrete-event simulation model for an SC producing and distributing lubricant additives. Here, batch production is modelled. Again, operational production decisions are made by priority rules and a scenario analysis is conducted to evaluate the effects of other priority... 

Pitty, S., Li, W., Adhitya, A., Srinivasan, R., and Karimi, I. Decision support for integrated refinery supply chains Part 1. dynamic simulation. Computers Chemical Engineering, 32(ll) 2767-2786, 2008. 

In addition to their use as stand-alone systems, LPs are often included within larger systems intended for decision support. In this role, the LP solver is usually hidden from the user, who sees only a set of critical problem input parameters and a set of suitably formatted solution reports. Many such systems are available for supply chain management—for example, planning raw material acquisitions and deliveries, production and inventories, and product distribution. In fact, the process industries—oil, chemicals, pharmaceuticals—have been among the earliest users. Almost every refinery in the developed world plans production using linear programming. 

Figure 5.1 Refinery and petrochemical industry supply chain.

The core component of the oil supply chain is the refinery, where the received oil batches are managed to feed the crude distillation units in proportions that give origin to the desired cuts and products. However, the oil supply and the oil products distribution have to answer in agreement to their predicted demands. For this reason, fliere is the need to build decision support tools to manage inventory distribution. This work focuses on the development of a MILP model that describes the oil products distribution through a pipeline that connects one refinery to one tank farm. In order to supply die local market, the model represents the interaction between the pipeline schedule and the internal restrictions at the tank farm. Real world data from CLC (a Portuguese company) validate the model formulation. 

JuUca N., Karimi I. and Srinivasan R. 2002h. Agent-hased supply chain management - 2 a refinery application, Comput. Chem. Eng., 26, 1771-1781. 

Neiro S.M.S. and Pinto J.M. 2003. Supply Chain Optimization of Petroleum Refinery Complexes. FOCAPO 2003. (Foundations of Computer Aided Process Operations). Coral Springs, FL, USA, January. 

Refining companies are successfully implementing supply chain integrated solutions to solve these problems and improve refinery operation and profitability. However, these applications depend on the availability of accurate and live data. Some points of the supply chain— in particular planning and operation areas—are greatly influenced by the availability of reliable and updated crude oil libraries reflecting the information of the crude oil and the products that will be obtained in the different processes. 

LP crude oil valuation is specific to a refinery and its facilities, markets and constraints. The combination of LP methodologies and refinery simulation models provides the required process and economic data to adequately evaluate crude oil feedstocks. Consistency between the quality of received crude oils and the assay data used with planning LP models is critical to guarantee the success in the optimization process. If crude oil quality suffers significant variations, a continuous assay update is required to take advantage of the benefits offered by supply-chain technologies. 

The technology continuously updates crude oil libraries with limited cost, allowing supply chain models to optimize refinery planning and operation with reduced uncertainties. Trading areas could also benefit from better crude oil valuations with the updated characterization. 

What resources are moved in a supply chain Obviously, when we initially think of a supply chain, we think of materials or parts moving from one location to another and eventually ending up in the hands of a customer. For example, when we think of the supply chain for a television, we go all the way back to the mine that dug up the raw materials, then to the refinery where we process the steel or the chemicals, and next to the factory where we form the parts and assemble them into products such as circuit boards or screens. From the assembly plant that put the television together we go to the shipping company that packaged the product and delivered it to a warehouse, and finally to a retailer. The retail store puts the television on the shelf where the customer selects the product, purchases it, and takes it home. This process involves literally thousands of steps, and each step becomes critical to the success of the overall process. The customer interprets a failure in any of these steps as a failure of the entire supply chain. 

Julka, N., Srinivasan, R. and Karimi, I., 2002b, Agent-based supply chain management. 2 A refinery application. Computers and Chemical Engineering, 26 1771-1781. 

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