An Ontology to Support Semantic Management of FMEA Knowledge

Abstract

Risk mitigation has always been a special concern for organization's strategic management. Various tools and techniques have been developed to manage risk in an effective way. Failure Mode and Effects Analysis (FMEA) is one of the tools used for effective assessment of risk. It analyzes all potential failure modes, their causes, and effects on a product or process. Moreover it recommends actions to mitigate failures in order to enhance product reliability. Organizations spend their resources and domain experts make their efforts to complete this analysis. It further helps organizations identify the expected risks and plan strategies in advance to tackle them. But unfortunately the analysis produced after spending a lot of organizational assets and experts' struggles, is not reusable due to its natural language text based description. Information and communication technology experts proposed some solutions but they are associated with some deficiencies. Authors in [13] proposed an ontology based solution to extract and reuse FMEA knowledge from the textual documents, and this article is the first step towards its implementation. In this article we proposed our ontology for Process Failure Mode and Effects Analysis (PFMEA) for automotive domain, along with its implementation, reasoning, and data retrieval through it.

Automatic Acquisition of Failure Mode and Effect Analysis Ontology for Sustainable Risk Management

“…This algorithm mapped 1357 instances to FMEA ontology with 100% accuracy. For this experiment, we selected an existing ontology presented by authors in [1] and evaluated it for ontoQA features. This ontology was the part of a complete knowledge management system.…”

“…Later on, in [1], they provided implementation details of FMEA ontology and its query analyzer. They divided FMEA domain in six core concepts, e.g., FMEA, Process, Failure mode, Later on, in [1], they provided implementation details of FMEA ontology and its query analyzer. They divided FMEA domain in six core concepts, e.g., FMEA, Process, Failure mode, RPN, Control method, and Mitigation action.…”

“…This is why enterprises are seeking to establish robust risk management systems. Risk management is referred to the process of identification of potential risk in advance, its analysis and deciding certain precautions to mitigate it [1] Effective risk management helps organizations achieve their objectives and sustain in the market by developing a certain level of trust between organization, its stakeholders and customers.…”

“…Motivation behind this piece of research is to develop a solution for populating FMEA ontology from existing worksheets in order to reutilize the existing knowledge for decision-making in future. For this, we evaluated an existing FMEA ontology [1] using OntoQA features. We found it rich with respect to schema, classes, and relationships among the classes.…”

High-speed Train Control System Big Data Analysis Based on the Fuzzy RDF model and Uncertain Reasoning

“…There are various context representation models were presented [19], including key-value model, object oriented model and ontology-based model. The ontology is the best model of event context representation, but the traditional ontology cannot handle uncertain knowledge which limits its application in uncertain event processing, so in recent years there have been some fuzzy ontology model and reasoning research: The logic based fuzzy model [6] attempts to integrate fuzzy logic into ontology design structure [16]; The distributed fuzzy reasoning Petri net and fuzzy ontology [22] were used for distributed fuzzy reasoning extensively [14].…”