Industry 4.0

Industry 4.0 Adoption Patterns Research

The research on the ‘Fourth Industrial Revolution’ is a research, analysis and exploration into industry 4.0 adoption patterns, identifying leading practices, best practices as well as develop missing practices out of the conclusions. It will highlight the quantitative and qualitative analysis of organizations from 26 countries across 56 industries on the subject of ‘evolution and adoption of the Fourth Industrial Revolution”. The conclusions will be drawn based on analyzing industry 4.0 investments, performance, current behaviors, patterns and future intent.

Research Focus

Information and research is sought on topics related to the understanding and comparison of Industry 4.0 concepts, including, but not limited to:

  • What is Industry 4.0 – what does include and what not
  • Most common Industry 4.0 concepts
  • Ontology foundations of Industry 4.0 concepts
    • What common Industry 4.0 class type objects exist?
    • Which common Industry 4.0 stereotype and subtype objects exist?
    • What are the most common object descriptions?
    • How do these class, stereo, type and sub-type objects semantically relate
    • Is there a pattern in the objects and relationships, where a generic conceptual structure could be derived? (Polovina, von Rosing, Laurier, 2014)
    • Can an Industry 4.0 meta model be created (Polovina, Scheruhn, von Rosing, 2017)
    • Are there any gaps in the existing concepts (Polovina, Scheruhn, Weidner, von Rosing, 2016)
  • Patterns (von Rosing, & von Scheel, 2016)
    • What works well (repeatable patters)
    • What doesn’t work well (anti-patterns)
  • Specify the difference and the common between Industry 4.0 modelling, Industry 4.0 engineering and Industry 4.0 architecture concepts (von Rosing, Urquhart, Zachman, 2015).
  • Model and viewpoint considerations:
    • Typical Industry 4.0 artefacts used?
    • Which challenges are being addressed by current Industry 4.0 artefacts
    • What challenges are not being addressed by current models?
    • Are there any underlying relationships between the Industry 4.0 artefacts
  • Industry 4.0 Enterprise Architecture considerations:
    • Typical Industry 4.0 Business and Technology Architecture views? (compare TOGAF, Archimate, BA Guild and Layered Architecture concepts)
    • Typical Industry 4.0 Layered Architecture views? (compare TOGAF, Archimate, BA Guild and Layered Architecture concepts)
  • Industry 4.0 Enterprise Engineering considerations:
    • Industry 4.0 LifeCycle considerations:
      • Could Industry 4.0 be considered with a LifeCycle perspective?
      • What would typical Industry 4.0 LifeCycle phases be?
      • What would the Industry 4.0 LifeCycle tasks/steps be within the phases?
      • Which Roles would typically be involved in the Industry 4.0 lifecycle?
      • Could there be a Continuous feedback loop build into the Industry 4.0 LifeCycle?
    • Industry 4.0 Maturity considerations:
      • Does a maturity concept fit to Industry 4.0?
      • Does Industry 4.0 have a maturity consideration?
      • What are the most common maturity areas that could fit to Industry 4.0?
    • Categorization considerations:
      • What are the most common categorization and classification used in Industry 4.0 concepts?
      • Are there specific Categorization schemes?
      • Are there specific Industry 4.0 concept tagging types?
  • Industry 4.0 Advantages/Benefits of Early Adaptors (von Rosing, Hove, Subbarao, Preston, 2012; von Rosing, Fullington, Walker, 2017).

Research Approach

When involving in such a complex industry research and analysis as defined in the research focus, this is where the Global University Alliance (GUA) has developed a unique collaborative process between academia and industry. (von Rosing, Laurier, 2015) As illustrated in figure 1, they do this through defining clear research themes, with detailed research questions, where they analyse and study patterns, describe concepts with their findings. This again can lead to additional research questions/themes as well as development of artefacts which can be used as reference content by practitioners and industry as a whole.

Overview of the Academia vs. Industry Concept
Figure 1: Overview of the Academia vs. Industry Concept.

The Academia vs. Industry process has two types of different cycles. The one where Academia is leading the research and innovation, this is called the Academia Industry Research (AIR) process. (Laurier, von Rosing, 2017). See figure 2.

Global University Alliance - Theory [AIR]
Figure 2: The AIR theory.
The other is where practitioners from Industry describe concepts and develop artefacts and thereby they bring about innovation. This process is called the Academia Industry Design (AID). (Laurier, von Rosing, 2017). See figure 3.

Global University Alliance - Theory [AID]
Figure 3: The AID theory.
In order to establish both rigor as well as relevance, both of these loops are important for the Industry 4.0 research focus.

Global University Alliance - Theory [AIR & AID]
Figure 4: The AIR and AID theory model concepts combined.

Research Team

The Industry 4.0 research & analysis contacts are:

Research Leader:
Georg Etzel
Head of Industry 4.0 Research, Global University Alliance
CEO, LEADing Practice

As far as partners are involved, the following people act as collaboration partner contacts:

Enterprise Standard Body:
Mikael Munck, LEADing Practice
Head of Smart Automation and Artificial Intelligence

Enterprise Architecture Framework:
John A. Zachman, Zachman International
Inventor and Father of Enterprise Architecture

International Organization for Standardization:
Johan H Bendz, ISO
SC 7, WG 42 Convener

IEEE Coordinator:
Rich Hilliard, Institute of Electrical and Electronics Engineers
Editor of IEEE Std 1471:2000, Project editor, ISO/IEC/IEEE 42010

Software Standards Body:
Henk DeMan
OMG VDML Chairman

NATO Coordinators:
Johan Goossens
NATO Allied Command Transformation
Branch Head, Technology & Human Factors

UNESCO Coordinator:
Dr. Selin N. Şenocak
UNESCO Chair Holder
Cultural Diplomacy, Governance and Education
Director, Occidental Studies Applied Research Center
Political Sciences and International Relations Faculty Member

CSIR Coordinator:
Rentia Barnard
Research Institute CSIR, Enterprise Architect Research Group Leader

Information Security Standard Body
Steve Durbin, CEO of Information Security Forum

The team involved in this work are among others the following academics, researchers and analysts:

  • Industry 4.0 Ontology (meta objects), Prof. Wim Laurier
  • Industry 4.0 Semantics (relations and rules), Prof. Simon Polovina
  • Comparing Industry 4.0 concepts, methods and approaches, Prof. Mark von Rosing
  • Typical enterprise models applied, Prof. Hans Scheruhn
  • Industry 4.0 strategies applied, Jamie Caine
  • Industry 4.0 KPIs, Ulrik Foldager
  • Industry 4.0 Roles, Maxim Arzumanyan
  • Industry 4.0 Engineering concepts, Prof. Ardavan Amini
  • Industry 4.0 SMART concepts, Prof. Elizabeth Uruchurtu
  • Most common Industry 4.0 Stakeholder & Concerns, Maria Hove

References

  • Laurier, W., von Rosing, M., (2017) Academia Industry Research (AIR) & Design (AID) – a collaborative process between academia and industry, Global University Alliance.
  • Polovina S., von Rosing M., Laurier W. (2014) Conceptual Structures in LEADing and Best Enterprise Practices. In: Hernandez N., Jäschke R., Croitoru M. (eds) Graph-Based Representation and Reasoning. ICCS 2014. Lecture Notes in Computer Science, vol 8577. Springer, Cham, DOI https://doi.org/10.1007/978-3-319-08389-6_25.
  • Polovina, S., Scheruhn, H. J., von Rosing, M., (2017). Modularising the complex meta-models in enterprise systems using conceptual structures. In: SUGUMARAN, Vijayan, (ed.) Developments and trends in intelligent technologies and smart systems. Advances in Computational Intelligence and Robotics (ACIR) . Hershey, PA, IGI Global, 261-283.
  • Polovina, S., Scheruhn, H. J., Weidner, S., von Rosing, M., (2016) Discovering the Gaps in Enterprise Systems via Conceptual Graphs & Formal Concept Analysis, In: HAEMMERLÉ, Ollivier, STAPLETON, Gem and ZUCKER, Catherine Faron, (eds.) Poster proceedings The 22nd International Conference on Conceptual Structures (ICCS 2016). ICCS.
  • Polovina, S., Scheruhn, H. J., Weidner, S., von Rosing, M., (2016) Highlighting the Gaps in Enterprise Systems Models by Interoperating CGs and FCA, CEUR Workshop Proceedings, 1637, 46-54.
  • von Rosing, M., & Laurier, W. (2015). An Introduction to the Business Ontology. International Journal of Conceptual Structures and Smart Applications, 3(1), 20–41. doi:10.4018/IJCSSA.2015010102.
  • von Rosing, M., & von Scheel, H. (2016). Using the Business Ontology to develop Enterprise Standards. International Journal of Conceptual Structures and Smart Applications, 4(1), 48–70. doi:10.4018/IJCSSA.2016010103.
  • von Rosing, M., Bach, B., & von Scheel, H. (2017). Using the Role Oriented Modelling concepts to develop smart applications. International Journal of Conceptual Structures and Smart Applications. Volume 5, Issue 1.
  • von Rosing, M., Fullington, N., Walker, J., Using the Business Ontology and Enterprise Standards to Transform Three Leading Organizations (2016), International Journal of Conceptual Structures and Smart Applications, 4(1), (pages 71-99).
  • von Rosing, M., Hove, M., Subbarao, R., Preston, T., (2012) Getting Business Transformation Right – Combining BPM and EA, Commerce and Enterprise Computing (CEC), IEEE 13th Conference.
  • von Rosing, M., Urquhart, B., & Zachman, J. A. (2015). Using a Business Ontology for Structuring Artefacts: Example – Northern Health. International Journal of Conceptual Structures and Smart Applications, 3(1), 42–85. doi:10.4018/IJCSSA.2015010103.
  • von Rosing, Zachman, J. (2017). The Need for a Role Ontology. International Journal of Conceptual Structures and Smart Applications. Volume 5, Issue 1.