This paper focuses on the methodologies currently available for waste minimization. The purpose is to analyze the features that render them applicable in specific cases and the gaps that have to be overcome when trying to use them for other situations. The methodologies under study will be evaluated in the light of knowledge management to understand the different information requirements that each of them entail. These considerations are summarized in a novel and more practical methodological framework to evaluate and select the proper models to organize and optimize the available data against the required information. Successful and widespread implementation of existing methodologies for waste minimization has failed to provide significant benefits in industrial applications because there is not a comprehensive approach that integrates and guides the application of the proper tool depending on the case. Each of these methodologies has been developed for particular stages in the process life cycle and they require different information which may not be available and could result too costly to obtain. The presented approach aims to integrate these methodologies and provides criteria to select the appropriate framework for the case at hand. The methodology also provides tools to identify and manage key required information to analyze the process and derive waste minimization strategies based on the application of the appropriate method. In the first steps of the proposed approach, it is taken into account that effective gathering, representation and modeling of information from all the staff levels within the organization is essential to ensure integration and success of the different waste minimization actions. Waste generation within a process has to be analyzed from the different aspects that cause it. This involves not only the manufacturing process but also other stages of the product lifecycle such as raw material storage and preparation, product distribution and in general, the logistics of the overall supply chain. The modeling of the entire life cycle of the process represents an effective way for grouping the necessary information to describe the crucial parts of a process. This will provide an accurate way to identify the areas which need attention for the purpose of pollution prevention and the activities that have to be modified to implement it. The methodology developed divides knowledge about a process into five main classes which contribute in different levels to the successful application of waster minimization tools. Mapping and organizing this knowledge provides an effective means of reducing losses due to gaps in the understanding of the process and of the signs that point towards waste generation. This contribution explores the use of an ontology-based approach for the structured organization of information aiming to identify significant waste minimization opportunities. Once the available process knowledge has been organized within the ontology-based framework, the information categories are compared with the information needed for the adequate analysis that generates options for the optimal performance of the actual process being studied. The methodology will provide a more adequate evaluation of the completeness and accuracy of existing information and generate unambiguous waste minimization options which adapt to specific situations for a given process.