Petri net workflow modeling for digital publishing measuring quantitative dependability attributes

This work presents the concept of workflow modeling using Generalized Stochastic Petri Nets (GSPN) for the Digital Publishing business process and how the attributes of dependability are measured in a quantitative form. In this approach, these are measured from the workflow model itself instead from a combinatorial model adapting some methodologies and strategies for combinatorial model build to the creation of the workflow process definition, improving the analysis of a workflow model. This approach will lead to make the model more versatile. Contrasting the analysis provided in other research projects, our work proposes an analysis of quantitative dependability over a workflow model, and not only an analysis of its structure and performance.; Publishing market competence is highly close and prices are regulated by the market itself with a very little gap between cost and profit. How reliable or, even more, trustable a print-shop could be to its client means to increase or decrease that gap of profitableness. Applying these measure concepts to the Digital Publishing pre-press process provides a better workflow management in this area than current procedures, since this process is based on its trustworthiness.; Modeling the business process of Digital Publishing using the theory of WorkflowNets and translating them into GSPN, we obtain a Quantitative Dependability WFnet based Model (QDWM). The methodology for creating a QDWM, which allows workflow modeling measuring quantitative dependability attributes is introduced, and the results for a case study on preflight and ripping stages of the Digital Publishing workflow are presented. A contrast between results from a Fault Tree Model (Combinatorial Model) and a QDWM, shows that the later is able to measure quantitative dependability attributes maintaining its main intended function: to be a workflow model.