MODELS FOR THE TACTICAL PLANNING OF A CENTRALIZED SUPPLY CHAIN UNDER UNCERTAINTY. APPLICATION IN A SUPPLY CHAIN FOR THE AUTOMOTIVE SECTORAuthor:
PEIDRO PAYÁ DAVID.
Year:
2006.
University:
POLITÉCNICA DE VALENCIA [
www.upv.es].
Place of defense: Universidad Politécnica de Valencia.
Place of preparation: Universidad Politécnica de Valencia.
Summary: Over the years, most companies have focused on improving the efficiency and effectiveness of their business processes internally. However, as a new way of doing business, a growing number of companies have begun to realize the strategic importance of the planning, control and design of a Supply Chain (SC) as a whole. In this regard, the profits arising from the close cooperation between the members of the chain to plan and execute operations, which are reflected in a higher level of efficiency in the use of the various resources available. In addition, the opportunity to manage in an integrated way a CS can reduce the spread of certain unwanted and unexpected events along the same and can decisively affect the achievement of the objectives and achieving profitability of all its members. Now, given this scenario, companies can not compete effectively long-term isolation from the network of suppliers and customers that make up its CS. Businesses can not find the cost reduction or increased their profits at the expense of other stakeholders (partners) within the chain, but must look to the SC as a whole is more competitive. As a result of this process, coordinating activities through its network of suppliers and customers is becoming a critical element in the success of an enterprise. Coordination and integration of all key business activities undertaken by the different actors in the chain from the supply of raw materials to the distribution of final products to customers is part of the process of planning a CS, one of the key processes within the Management of the Supply Chain. In addition, the complex and dynamic nature of the relationships between the various players in the CS, involves a significant degree of uncertainty in decisions relating to planning the same. The uncertainty, according to Galbraith, is defined as the difference between the amount of information required to execute a task and the information actually available. In the decision-making process involved in the planning of a CS is not always available all the necessary information, which is why the uncertainty is one of the main factors that influence the effectiveness of a CS in both design and in its operability and uncertainty that tends to spread up and down the chain, significantly affecting its functioning. Uncertainty traditionally has been treated using stochastic techniques based on probability distributions derived from an analysis of past cases. However, sometimes the historical data either do not exist or are not reliable because, for example, market turbulence. Furthermore, the reduction of life cycles and increasing customer expectations have made the TOS, especially innovative products, very difficult to handle. In this context, demand for the product is highly variable and the compilation of statistics (required by the stochastic modeling) is becoming less reliable. For that reason, stochastic techniques may not be well suited for the treatment of uncertainties applied to a CS, such as the case of uncertain demand. The Theory of Sets Difusos and Theory of Possibility emerge as viable alternatives for managing the uncertainty in the planning of a CS, as they have been used widely and successfully applied in many different areas. These theories have been used to build systems that s 8 on difíc 373 iles to define precisely, trying to handle the vague, imprecise and non-specificity inherent in the development of human preferences, restrictions and objectives,
