Resumen: [EN] The global transition from traditional manufacturing systems to Industry 4.0 compatible systems has already begun. Therefore, the digitization of the manufacturing systems across the globe is increasing with exponential growth which implies a significant increase in the volume and variety of the generated data. Industry 4.0 technologies are mostly data driven and therefore, manufacturers need to be equipped with the appropriate tools and skill sets to extract useful knowledge and insights from the plethora of data continually collected form shop floors. Furthermore, quality assurance is a key domain in manufacturing that uses almost all the industry 4.0 technologies and has great impact on the sustainability of a manufacturing systems. The latest approach to higher quality and manufacturing sustainability is named Zero Defect Manufacturing (ZDM). ZDM interest has spiked the last three years illustrating the need for an alternative quality assurance approach from the traditional such as Six Sigma and Lean manufacturing. Therefore, the goal of this paper is to create a ZDM ontology that can semantically align multiple software systems that interact in a ZDM ecosystem. The development of the proposed ZDM ontology was performed using the principles introduced by Industrial Ontology Foundry (IOF) and with the use of Basic formal ontology (BFO) as an upper level ontology. The proposed ontology was utilized in the Pre-diction Optimization Designer tool developed, to assist developers to create new projects reusing existing re-sources, or to respond to a specific challenge. The use case validation results show that the combination of Natural Language Processing (NLP) using Sentence-BERT and ontology-based search methods rooted in the ZDM ontology is a promising strategy to implement effective search engines for applications in the ZDM domain.