The Importance of Establishing Ontologies & Knowledge Graphs in the Aluminium Industry

Introduction

In today’s data-driven world, industries are increasingly leveraging advanced technologies to optimise processes, enhance collaboration, and drive innovation. The aluminium industry, a cornerstone of modern manufacturing and infrastructure, is no exception. One of the most promising avenues for advancement in this sector is the development and implementation of ontologies, mappings, and knowledge graphs that adhere to established standards.

This blog explores the necessity of establishing such frameworks in the aluminium industry, highlighting the benefits of standardisation, data interoperability, and the potential for transformative impacts across the sector.

What Are Ontologies and Knowledge Graphs?

Ontologies are structured frameworks that define the relationships between concepts within a particular domain. They provide a shared vocabulary and a clear set of rules for how those concepts interrelate, enabling consistent communication and understanding across different systems and stakeholders. There are multiple standards as shared in the further reading session that will help standardise the vocabulary.

Knowledge graphs are graphical representations of knowledge domains, where entities (nodes) are connected by relationships (edges). They utilise ontologies to structure data in a way that is both human-readable and machine-interpretable, facilitating advanced data analysis, querying, and visualisation.

The Need for Ontologies in the Aluminium Industry

1. Complexity of Material Data : The aluminium industry deals with a vast array of materials, alloys, processing methods, and applications. Each aluminium alloy has unique properties influenced by its composition and processing history. Managing this complexity requires a structured approach to data representation. The major challenges include inconsistent terminology, data silos and difficulty in data integration
2. Enhancing Data Interoperability: With globalisation, the aluminium industry involves collaboration across borders and organisations. Interoperability—the ability of systems and organisations to work together—is crucial. Ontologies benefits in standardised vocabulary, data sharing and integration with other domains.
3. Driving Innovation: Innovation in alloy development, processing techniques, and applications is vital for the industry’s growth.

How Ontologies Help:

1. Standardised Vocabulary: Facilitates clear communication among stakeholders.
2. Data Sharing: Enables seamless exchange of information between systems.
3. Integration with Other Domains: Allows for linking aluminum data with related fields such as materials science, engineering, and environmental science.
4. Advanced Analytics: Structured data enables sophisticated data mining and machine learning applications.
5. Knowledge Discovery: Identifying new correlations between composition, processing, and properties.
6. Decision Support: Providing engineers and researchers with tools to make informed decisions.

Mapping to Existing Standards

Adhering to established ontologies ensures compatibility and fosters collaboration. Key standards relevant to the aluminium industry include:

1. European Materials Modelling Ontology (EMMO): Purpose: Provides a unified framework for materials modelling. Relevance: Aligning aluminium ontology with EMMO ensures compatibility with broader materials science data.
2. Materials Science Ontology (MSO): Purpose: Focuses on materials properties, processing, and performance.Relevance: Mapping to MSO facilitates detailed representation of aluminium alloys and their characteristics.
3. Chemical Methods Ontology (CHMO): Purpose: Describes chemical processes and methodologies. Relevance: Captures processing methods like casting, forging, and heat treatment within the aluminium industry.

Advantages of Mapping:

1. Interoperability: Ensures that data can be integrated with other systems using the same standards.
2. Reusability: Facilitates the reuse of data and models across projects and organisations.
3. Community Collaboration: Aligns with the work of others in the field, promoting collective advancement.

Building Knowledge Graphs for Aluminium Alloys

1. Structuring Data: A knowledge graph for aluminium alloys encompasses essential components to provide a comprehensive overview. It includes materials, specifically aluminium alloys categorised by series such as 2xxx to 7xxx. Each alloy’s composition is detailed, listing the elements and their ratios. The graph also captures properties like mechanical, thermal, and electrical characteristics. It maps processing methods used, such as casting, forging, and heat treatment, and connects alloys to their applications in various industries and products. This structured data facilitates an understanding of how alloys’ compositions and processes influence their properties and uses.
2. Benefits of Knowledge Graphs: Knowledge graphs offer significant advantages. They enable enhanced querying, allowing users to find alloys with specific properties or compositions efficiently. The visualisation aspect helps users intuitively grasp the relationships and dependencies between different entities, such as how processing methods affect properties. Additionally, they support data integration by combining information from multiple sources into a unified framework, providing a holistic view that aids in comprehensive analysis and decision-making.
3. Practical Applications: In practical terms, knowledge graphs assist in material selection by helping engineers identify alloys that meet specific requirements for certain applications. They facilitate research and development by allowing the analysis of patterns across alloys, aiding in the discovery of new materials and predicting properties of novel compositions. For supply chain optimisation, knowledge graphs enable tracking of materials and processes throughout their lifecycle, improving transparency, efficiency, and the ability to respond swiftly to market demands.

The Impact on the Aluminium Industry

1. Improved Efficiency: Standardised data allows for automation of processes and reduces the time spent on data management.
2. Enhanced Collaboration :Stakeholders across the supply chain can communicate more effectively, leading to better coordination and innovation.
3. Competitive Advantage: Organisations that leverage ontologies and knowledge graphs can make more informed decisions, leading to superior products and services.
4. Regulatory Compliance: Adherence to standards ensures compliance with regulations and facilitates reporting and auditing processes.

Call to Action

For the aluminium industry to fully realise the benefits of digital transformation, establishing ontologies, mappings, and knowledge graphs is essential. Stakeholders are encouraged to:

1. Engage with Standards Bodies: Participate in the development and adoption of relevant ontologies.
2. Collaborate Across the Industry: Share best practices and resources to build comprehensive knowledge frameworks.
3. Invest in Technology and Training: Equip teams with the tools and knowledge needed to implement and utilise these systems.

Conclusion

The establishment of ontologies, mappings, and knowledge graphs adhering to standards is not just a technical exercise but a strategic imperative for the aluminium industry. It unlocks the potential for enhanced collaboration, innovation, and efficiency, positioning the industry to meet the challenges of the modern world.

By embracing these frameworks, the aluminium industry can harness the power of data to drive growth, sustainability, and competitive advantage.

Further Reading

1. European Materials Modelling Ontology (EMMO): emmc.info/emmo
2. Materials Science Ontology (MSO): purl.org/mso
3. Chemical Methods Ontology (CHMO): obofoundry.org/ontology/chmo
4. Materials Project: https://next-gen.materialsproject.org/