# A Semantic Model in the Context of Maintenance: A Predictive Maintenance Case Study
## 4 Two-Cycle Methodology to Build a Semantic Model
### The Vocabulary Cycle  
To achieve explicitness for a semantic model in the context of maintenance, [PERSON] and [PERSON] (1995) introduced a methodology to create an ontology as an enterprise model [42]. They listed a set of carefully characterized problems, named competency questions, and used them as a foundation to build an ontology. They intended this ontology to solve the competency questions. Today, it is one of the most widely used methods to build an ontology. Competency questions are a way to determine the scope of an ontology and to sketch a list of questions to be answered [42]. These are forms of the questions in the domain of interest used to easily define the scope and boundaries of an ontology. In the Z-BRE4K project, competency questions were created after repeated discussions with three business owners. The businesses involved a lighthouse manufacturing process producing automotive chassis, cold forming tooling, and molding machines. The list of competency questions for this study is as follows:  
* In each use case, which machines are considered? * For each use case, what stakeholders and/or actors are considered? * For each machine, what is the bill of materials (represented as a hierarchy diagram)? * In a specific use case, which component is critical for the management of assets? * For each critical component, what are the failure modes? * For each failure mode, what are the effects? * For each failure mode, what is the criticality? * Before the failure, what actions are needed? * After the failure, what actions are needed? * Which sensors are required for each critical component? * Which critical components are associated with a sensor? * For any sensor, what signals are collected? These questions can be used to check the following questions: Does the ontology include sufficient information in response to these questions? Is a specific level of detail or representation of a particular area required to answer the questions? The list of competency questions does not need to be exhaustive and can be considered a sketch [43]. Figure 1: Two-cycle methodology. From these competency questions, entities are easily captured. Since they will be the basis of the taxonomy of the ontology, competency questions are useful to recognize the relationships between entities. The easiest way to capture entities is to find nouns in the competency questions. For instance, we can easily find the nouns _failure_modes_ and _critical_components_ in the question, \"For each critical component, what are the failure modes?\" To answer this question, the relationship between _failure_modes_ and _critical_components_ is needed. Based on this competency question, we designed the logical diagram in Figure 2 with the following contexts:  
* Each _System_ as a maintainable item plays its own _Role_, and the _Role of the System_ inheres in _Maintenance_Process_Definition_
* Each _System_ consists of the _System_part_ and the _Embedded Data-Source_Component_
* The _Embedded Data-Source_Component_ generates the _Source_Data_
* Each _System_part_ has a _Quality_, a _Failure_Mode_, and an _Indicator showing performance_
* Each _Failure_Mode_ has a _Failure_Sympton_ and an _Indicator_ presenting its risk, probability, and so on
* Depending on the condition, the _System_ requires _Maintenance_
* The _Product_Provider_ provides the _System_
* The _Maintenance_Service_Provider_ provides the _Maintenance_Process_Definition_
* The _Business_Customer_ owns the _System_  
After identifying the entities and their relationships from the knowledge extraction process, they are compared to the reference ontologies. The identified entities and their relationships are elaborated to reflect the same philosophy and to enable communication with the references. Thus, to suit the requirements of end-users, the ontology in this paper can be merged with one or more reference ontologies. In this phase, the similar contexts in the references are carefully and manually checked.