Knowledge Change Management and Analysis during the Engineering of

Cyber Physical Production Systems Fajar J. Ekaputra1, Marta Sabou1, Estefanía Serral2, Stefan Biffl1

1) Vienna University of Technology, Christian Doppler Laboratory for „Software Engineering Integration for

Flexible Automation Systems“ (CDL-Flex) 2) ) KU Leuven, Department of Decision Sciences and Information

Management

The Fourth Industrial Revolution

Source: Forschungsunion Wirtschaft und Wissenschaft, Acatech,”Securing the future of German manufacturing industry. Recommendations for implementing the strategic initiative INDUSTRIE 4.0 .Final report of the Industrie 4.0. Working Group.”, 2013

Cyber-Physical Systems (CPS)

Flexible, adaptive manufacturing (CPPS) (e.g., modern Hydro Power Plants)

Smart, distributed transportation systems

Multi Disciplinary Engineering Environment

The typical environment for designing Cyber Physical Production Systems such as modern Hydro Power Plants

Domain Expert

KnowledgeEngineer

ElectricalEngineer

Mechanical Engineer

Project Management

Electrical Engineering

Mechanical Engineering

“Knowledge Change”

Related Tasks

Knowledge Engineering

Project Supervisor

?

Project Manager

The engineering process is iteratively conducted.

Software Engineering SoftwareEngineer

A Hydro Power Plants Use Case: Use Case Settings

PMOProject

Manager

OPMMechanical

Engineer

?

EPLElectricalEngineer

Three local data sources for managing signal changes: •  PMO for project management data •  OPM for mechanical engineering data •  EPL for electrical engineering data

Implicitly connected - if one data source changed, it might affect the data on other sources Therefore, Knowledge Change Management is an important part of it

A Hydro Power Plants Use Case: Example Signal Data

OPM Signals

EPL Signals

Implicit Links

Key Challenges

§  How to manage changes in complex multi-disciplinary engineering settings? –  How to integrate the heterogeneous data? –  How to detect and propagate changes in the integrated datasets? –  How to use change data to support advanced queries?(e.g., what

are the signals that have been changed in the last month?; how many racks were added during the last changes?)

Solution Approach (1)

§  Based on Ontology-Based Information Integration [1,2]

§  Consists of three main components –  Local ontologies –  A common ontology –  Mapping / transformation

between local and common ontologies

Mechanical EngineeringTools

Electrical EngineeringTools

Local Ontology(PMO)

Local Ontology (EPL)

Local Ontology (OPM)

Common Ontology(CCO)

Lifting schema and data into local ontologies

Project ManagementTools

[1] H. Wache et al., “Ontology-based integration of information-a survey of existing approaches,” in IJCAI-01 Workshop on Ontologies and Information Sharing, 2001, pp. 108–117. [2] D. Calvanese, G. De Giacomo, and M. Lenzerini, “Ontology of Integration and Integration of Ontologies.,” in International Description Logics Workshop, 2001, p. 2.

Solution Approach (2)

Extending OBII with knowledge change management capabilities [3]

[3] F. J. Ekaputra, “Knowledge Change Management in Engineering,” in Semantic Web for Intelligent Engineering Applications, Springer, 2016.

Solution: implementation with SW Technologies

Hydro Power Plants’ Common Concept Ontology

Adapted from Sabou et al., “Semantic Modelling and Acquisition of Engineering Knowledge,” in Semantic Web for Intelligent Engineering Applications, Springer, 2016.

Change Representation

Feasibility Evaluation

§  Three users from three domains –  Project manager –  Mechanical Engineer –  Electrical Engineer

§  Eight signals commits from three data sources –  Six valid commits and two invalid commits –  Each commit contains small number of signals

§  Evaluation result: –  Successful validation and propagation of changes –  Successful analysis on the changes

Key Findings and Future Work

•  Knowledge Change Management and Analysis is a key task in supporting the engineering of CPPS

•  We proposed a technology-agnostic solution based on the extension of Ontology Based Information Integration approach

•  We implemented the solution with SW technologies in the use case of Hydro power plant engineering

•  Our solution prototype is feasible in test settings •  Future extensions require improved scalability and better

ease of use