In this Article, the recently developed multi-model and NLP-based operability approaches are reviewed and further developed in terms of theory, application, and software infrastructure. Classical process operability concepts are also revisited and contrasted with new extensions present in both approaches. A focus is given on the comparison between distinct measures of the operability index and the handling of infeasible portions of the desired operating region. For the software infrastructure outcome, a framework for the development of process operability algorithms is provided. In particular, generated codes from the studied approaches are included in an open-source platform that will grant access of the algorithms to researchers from academia and industry. This platform has the purpose of dissemination and future improvement of process operability algorithms and methods. For the development of a versatile process operability tool, the considered approaches are adapted to support process models of generic dimensionalities. New contributions are also incorporated such as the conventional operability index calculation and other methods to find optimal design regions. Nonlinear energy systems of different input X output dimensionalities (6 x 3, 7 x 3, and 3 x 3) are addressed to demonstrate the applicability of the features available in the developed software tool to process achievability analysis, intensification, and modularization.