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.
The concept of the supply chain (SC), which first appeared in the early 1990s, has recently been the focus of much interest, as the possibility of providing an integrated management of an SC can reduce the propagation of unexpected/undesirable events throughout the network and can markedly improve the profitability of all the parties involved.
Supply Chain Management (SCM) aims to integrate plants with their suppliers and customers so that they can be managed as a single entity and to coordinate all input/output flows (of materials, information and funds) so that products are produced and distributed in the right quantities, to the right locations, and at the right time (Simchi-Levi, Kamisky, & Simchi-Levi, 2000). Therefore, SCM implies the handling of flows throughout the entire SC, from suppliers to customers while encompassing warehouses and distribution centres (DCs), and usually including after-sales services, returns, and recycling (Silver, Pyke, & Peterson, 1998). The main objective is to achieve acceptable financial returns together with the desired consumer satisfaction levels.
The SCM problem may be considered at different levels depending on the strategic, tactical and operational variables involved in decision-making (Fox, Barbuceanu, & Teigen, 2000). Therefore, a large spectrum of a firm’s strategic, tactical and operational activities are encompassed by SCM:
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The strategic level concerns those decisions that will have a long-lasting effect on the firm. It is focused on SC design, and entails determining the optimal configuration for an entire SC network, including the design of the embedded plants.
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The tactical level encompasses long/medium term management decisions, which are typically updated at a rate ranging between once every quarter and once every year. These include overall purchasing and production decisions, inventory policies, and transport strategies.
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The operational level refers to day-to-day decisions such as scheduling, lead-time quotations, routing, and lorry loading.
Therefore, in the SC models time is multifaceted in the hierarchical planning: the long strategic, the medium tactical and the short operative terms. The activities within each hierarchical layer also overlap timing. At strategic and tactical levels time is not as precise as in the operative level. The timing co-ordination along the planning hierarchy faces the challenge of coherently integrating operational and relatively aggregated multi-period tactical models.
Although a lot of attempts have been made to model and optimize the SC behavior, several deterministic and stochastic derived approaches currently exists Bok et al., 2000, Cheng et al., 2003, Guillén et al., 2005a, Guillén et al., 2005b, Guillén et al., 2005d and Tsiakis et al., 2001 , almost all of them address the SCM problem from a strategic or tactical point of view. However, from an operational perspective, and due to the complexity associated to the interdependencies between the production/distribution tasks of the network, the detailed scheduling of the various processes of the SC has been left to be decided locally. Therefore, while the single-site production scheduling problem has been an active area of research in the chemical engineering community over the last decade (Floudas & Lin, 2004) , the multi-site case has so far received little attention. Grossmann (2004) highlights that major challenges in enterprise and SC optimization include the development of models for strategic and tactical planning for process networks which must be eventually integrated with scheduling models. In his opinion, although very significant progress has been made in the area, these models still lack sufficient genera- lity.
This paper has addressed the importance of integrating planning and budgeting models. This work presents a more desired measure of the effectiveness of a production plan and schedule, based on an economic performance indicator (increment in equity) as an alternative to the commonly used makespan, profit, or cost.
With joint financial and operations, the impact of improvement goes beyond those achieved by operative schedules/plans, specifically adding the benefits of an optimized financial capacity to the benefits of an optimized use of production capacity, the latter already undertaken in routine practice by today’s scheduling and planning tools. By means of a comparison using a case study, it has been shown that significant improvements are possible when the the use of scheduling models followed by budgeting models are substituted by the integrated approach.
Besides the decrease of costs or increment of revenues and the benefits of cash flow synchronization by load rearrangement to flatten peaks balancing firm’s financial liquidity, there is an internal benefit in companies that rarely is possible to be measured with something else than intuitive reasoning. It is the opportunity cost ignored by not optimizing the quality of management decisions, and very especially in the resource assignment to functional areas that create value.
