Metodika hodnocení odolnosti průmyslových dodavatelských řetězců

Abstract

This dissertation thesis deals with the management of industrial supply chains. It examines the current trends in this field, focusing on the concept of management of resilient supply chains, whose origin is a response to the unstable conditions of the global market environment. The application of this concept to real management of industrial supply chains is, however, very problematic. One of the limiting factors is the absence of systematic procedures and tools for measuring and assessing the resilience of supply chains. There are only rigid (closed) and highly subjective scoring tools. This drawback has motivated the author to define the following objectives of this dissertation thesis: - to characterize and analyse the possible approaches to the management of supply chains, focusing on the concept of resilience, - to propose a methodology for measuring and evaluating the resilience of industrial supply chains, - to verify the methodology through a case study from the environment of metallurgical supply chain. This work includes a definition of the problems of supply chain management in order to meet the first of the presented objectives. It mainly examines the contemporary management concepts, including the management of lean, agile, green and resilient supply chains. The main goal of this work is to design a methodology for measuring and evaluating the resilience of industrial supply chains, which eliminates the shortcomings of the existing tools. The creation of a flexible and objective methodology takes advantage of the methods of multi-criteria evaluation of options called AHP (analytic hierarchy process) and ANP (analytic network process). The verification of the proposed methodology (the last objective of this dissertation thesis) is performed on a case study from the environment of an illustrative metallurgical supply chain. The verification was carried out by means of SuperDecisions software, which is a leading tool in the application of AHP and ANP methods.