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Ontology of Engineering.pdf philosophy of engineering
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- 2. Ontology - ReferenceOntology and Application Ontology - Practice 4: Reference Ontology using Concept/Mind Mapping - Suites of Ontology Modules - Functions and Capabilities - Practice 5: Engineering Application Ontology using Concept/Mind Mapping - Product Life Cycle - Commodities, Services and Infrastructure - Practice 6: Product Life Cycle Ontology using Concept/Mind Mapping
- 3. • Ontology ofengineering refers to the structured representation of knowledge in the engineering domain—formalizing concepts, entities, relationships, and properties to support consistent understanding, reasoning, and interoperability across software and teams
- 4. • Definition: Anontology in engineering is a formal, explicit specification of the key concepts and relations in an engineering domain (such as mechanical, civil, or computer science engineering). • Purpose: It enables systems to interpret, exchange, and reuse data and knowledge accurately, overcoming differences in terminology and meaning between teams, software, and data sources. • Components: • Concepts/Classes: Types of objects (e.g., Machine, Component, Load). • Individuals/Instances: Specific examples (e.g., Bridge, Pump). • Properties/Attributes: Qualitative or quantitative features (e.g., mass, material type). • Relationships: How entities interact (e.g., isPartOf, supports, operatesWith).
- 5. • In computerscience engineering, an ontology might represent concepts such as “Algorithm,” “Data Structure,” “Software Module,” and relationships like “uses,” “implements,” and “dependsOn.” • For instance, a software development tool could use this ontology to model dependencies and execution flows in complex systems. • For example, an ontology for a university might include concepts like "Student", "Professor", "Course", and "Department". The relationships could be "is_enrolled_in" (linking a Student to a Course), "teaches" (linking a Professor to a Course), and "is_part_of" (linking a Course to a Department).
- 6. Reference Ontologies A referenceontology in engineering is a comprehensive model that describes all fundamental concepts and relations within the engineering domain, intended for universal use across different projects and systems. In computer science engineering, A reference ontology provides a comprehensive model of fundamental computer science concepts, structures, and relationships designed for broad reuse across applications and tools.
- 7. Example in Engineering •In the broader engineering field, a good example of a reference ontology is one for manufacturing processes. This ontology wouldn't be for a single factory or product line. Instead, it would define core, universally applicable concepts like: • "Material": With subclasses like "Metal," "Plastic," "Composite." • "Tool": With subclasses like "CuttingTool," "MoldingTool." • "ProcessStep": With subclasses like "Machining," "Assembly," "QualityControl." • "Resource": Such as "Human," "Machine," "Energy."
- 8. • Example: SoftwareEngineering Ontology (SWEO) • SWEO models concepts like “Requirement,” “Design Pattern,” “Test Case,” “Bug,” and their interrelations, covering the entire software development lifecycle from planning to deployment and maintenance.
- 9. Key characteristics ofa reference ontology include: ▪ Standardization: Reference ontologies are developed by following established standards and guidelines, ensuring consistency and compatibility with other systems and datasets. ▪ Formalization: They are typically represented using formal languages or frameworks such as OWL (Web Ontology Language) or RDF (Resource Description Framework), enabling automated processing and reasoning. ▪ Domain Specificity: Reference ontologies focus on a particular domain of knowledge, such as biology, medicine, finance, or manufacturing. They capture the essential concepts, entities, and relationships relevant to that domain.
- 10. • Expressiveness: Referenceontologies aim to capture the richness and complexity of the domain they represent, providing detailed descriptions of concepts and their interrelationships. • Community Consensus: The development of reference ontologies often involves collaboration among domain experts, researchers, and stakeholders to ensure that the ontology reflects the consensus understanding of the domain. • Evolution: Reference ontologies are subject to ongoing refinement and updates as knowledge advances and new insights emerge in the domain. They may be versioned to track changes over time.
- 11. Application ontologies • Applicationontologies is also known as domain-specific ontologies, are specialized ontologies designed to represent knowledge within a specific application domain or context. • Unlike reference ontologies, which aim to capture general knowledge across a broad domain, application ontologies focus on modeling concepts, entities, and relationships relevant to a particular problem or application area. • These ontologies are tailored to meet the specific needs and requirements of the application they support
- 12. Agile Project ManagementOntology • This ontology might include “User Story,” “Sprint,” “Developer,” and relations like “assignedTo” or “completedIn,” extracted from the broader software engineering ontology. • Used by agile management tools to organize workflows, track progress, and automate reporting
- 13. key aspects ofapplication ontologies: Domain Focus: Application ontologies are centered around a particular domain of interest, such as healthcare, finance, engineering, or education. Scope: The scope of an application ontology can vary depending on the requirements of the application. Some application ontologies may cover a broad range of topics within a domain, while others may focus on specific subdomains or use cases. Expressiveness: Application ontologies aim to capture the richness and complexity of the domain they represent, providing detailed descriptions of concepts and their interrelationships. They may include classes, properties, axioms, rules, and constraints to support effective knowledge representation and reasoning.
- 14. Integration: Application ontologiescan be integrated with other ontologies, databases, or information sources to enhance interoperability and data exchange. Customization: Application ontologies can be customized and extended to meet the specific needs of different applications or user communities. Interoperability: Application ontologies facilitate interoperability among different systems, tools, and applications within the same domain.
- 15. Reference Ontology ApplicationOntology Semantic accuracy, interoperability Task-specific reasoning, computational use Maximal coverage Provides a minimal terminological Structure Fits the needs of a large community Fits the needs of a specific community Can’t be derived from application ontology Can be derived from reference ontology Broad, deep, covers domain exhaustively Narrow, focuses on a specific use case Designed according to strict ontological Principles Designed according to the viewpoint of an end- user in a particular domain
- 16. Phases of theontology design 1. Domain Definition •Clearly specify the area of interest (e.g., civil engineering, computer science). •Create a comprehensive domain description by collecting relevant documents, standards, and expert input. 2. Concept Identification •Identify key entities, concepts, and terms within the domain (e.g., bridge, load, sensor). •Organize these findings into a taxonomy of concepts, establishing a hierarchy and clustering related ideas. 3. Model Development •Build a conceptual model that visually or textually maps the relationships between identified concepts. •Structure the entities so interconnections (such as “supports,” “includes,” or “measures”) are explicit. 4. Ontology Implementation •Transform the conceptual model into a formal, machine-readable ontology using suitable tools (e.g., Protégé). •The finished ontology enables software and systems to reason, integrate, and automate processes using the domain’s shared vocabulary.
- 18. The Role ofOntology To provide a language which allows a group of people to share information reliably in a chosen area of work Applications • Indexing • Knowledge sharing and reuse • Artificial Intelligence • Enterprise Modelling • Software Design • Molecular Biology • Ecommerce
- 19. Categories of ontology •Domain Ontologies- it represents the particular meaning of terms as they apply to that domain • Upper Ontologies- also called as foundation ontology, it is the model of common objects that are generally applicable to wide range of domain ontology • Knowledge Representation- used to capture representation primitives • General Ontology- used to represent the common sense knowledge reusable across the domain
- 20. Main Components ofan ontology • Classes- represents concepts, which are taken in a broad sense • Attributes- describes the classes in the ontology • Relationships- Makes explicit link between the classes in the same domain • Functions- is a special case of relations
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- 22. Stage 1: ProductDevelopment or introduction: The new product is introduced; this is when all of the research and development happens. Stage 2: Product Growth: The product is more than an idea or a prototype. At this stage, the product is manufactured, marketed, and released. Distribution increases, demand increases, and competition also increases. Stage 3: Product Maturity: During this stage, the product is widely available, and there are many competitors in the marketplace. You market the product to different Segments Stage 4: Product Decline: The product is losing market share or becoming obsolete. It is well past its point of highest demand, and the demand decreases.
- 23. Product Introduction GrowthMaturity Decline Typewriter 1800s Early 1900s Mid 20th Century Late 20th century (replaced by computers) Videocassette Recorder 1950s 1980s 1990s 2000s (superseded by DVD/streaming) Electric Vehicles (EVs) 1800s 2010s-2020s (still in growth) - Virtual Reality Headsets 2010s 2020s (early growth) -
- 24. Closed-Loop Manufacturing Cycle •Waste outputs that can negatively affect the environment • Researchers assert that the introduction stage where design takes place determines between 70 percent and 90 percent of the life cycle costs • In this stage, manufacturers can also remove excess waste and continue to develop sustainable manufacturing practices • These practices should include products being reused, recycled, and remanufactured.
- 25. linear PLC Circular PLC Example: Dell’s take-back program, which takes the computers that it manufacturers and turns a majority of them into new computers. Other companies separate out product components and sell them to their partners on the commodities market, as raw materials, who then make them into new products.
- 26. The benefits ofa closed-loop system include: • Better for the environment • Does not affect performance or price • Fewer carbon emissions in manufacturing • As programs scale, they become cheaper and more effective
- 27. Commodities • Commodities areraw materials used to manufacture consumer products. • They are inputs in the production of other goods and services, rather than finished goods sold to consumers. • In commerce, commodities are basic resources that are interchangeable with other goods of the same type. • The quality of a given commodity may differ slightly, but it is essentially uniform across producers.
- 28. • Traditional examplesof commodities include grains, gold, beef, oil, and natural gas. • Hard commodities refer to energy and metals products, while soft commodities are often agricultural goods.
- 29. • Commodities thatare traded are typically sorted into four categories broad categories: metal, energy, livestock and meat, and agricultural. • Commodities are known to be risky investment propositions because their market (supply and demand) is impacted by uncertainties that are difficult or impossible to predict, such as unusual weather patterns, epidemics, and disasters both natural and human-made. • There are a number of ways to invest in commodities, such as futures contracts, options, and exchange traded funds (ETFs).