Utilize este identificador para referenciar este registo: http://hdl.handle.net/10362/6620
Título: An information model for lean, agile, resilient and green supply chain management
Autor: Cabral, Izunildo Fernandes
Orientador: Grilo, António
Palavras-chave: Lean
Supply chain management
Information model
Data de Defesa: 2011
Editora: Faculdade de Ciências e Tecnologia
Resumo: In modern business environments, an effective Supply Chain Management (SCM) is crucial to business continuity. In this context, Lean, Agile, Resilient and Green (LARG), are advocated as the fundamental paradigm for a competitive Supply Chain (SC) as a whole. In fact, competition between supply chains (SC) has replaced the traditional competition between companies. To make a supply chain more competitive, capable of responding to the demands of customers with agility, and capable of responding effectively to unexpected disturbance, in conjugation with environmental responsibilities, and the necessity to eliminate processes that add no value, companies must implement a set of LARG SCM practices and Key Performance Indicators (KPI) to measure their influence on the SC performance. However, the selection of the best LARG SCM practices and KPIs is a complex decision-making problem, involving dependencies and feedbacks. Still, any decision-making must be supported by real and transparent data. This dissertation intends to provide two integrated models to assist the information management and decision-making. The first is an information model to support a LARG SCM, allowing the exchange and storage of data/information through a single information platform. In this model three types of diagrams are developed, Business Process Diagram (BPD), Use Cases Diagram and Class Diagram to assist the information platform design. The second is a decision-making model, designated LARG Analytical Network Process (ANP) to select the best LARG SCM practices/KPI to be implemented in SCs. Both models are developed and validated within the automotive SC, namely in Volkswagen Autoeuropa.
Descrição: Dissertação para a obtenção de Grau de Mestre em Engenharia e Gestão Industrial
URI: http://hdl.handle.net/10362/6620
Aparece nas colecções:FCT: DEMI - Dissertações de Mestrado

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