What do information reuse and automated processing require in engineering design? Semantic process
Abstract: Purpose: The purpose
of this study is to characterize, analyze, and demonstrate
machine-understandable semantic process for validating, integrating, and
processing technical design information. This establishes both a vision and
tools for information reuse and semi-automatic processing in engineering design
projects, including virtual machine laboratory applications with generated
components.
Design/methodology/approach: The process model has been developed
iteratively in terms of action research, constrained by the existing technical
design practices and assumptions (design documents, expert feedback), available
technologies (pre-studies and experiments with scripting and pipeline tools),
benchmarking with other process models and methods (notably the RUP and DITA),
and formal requirements (computability and the critical information paths for
the generated applications). In practice, the work includes both quantitative
and qualitative components.
Findings: Technical design processes may be greatly enhanced in terms of
semantic process thinking, by enriching design information, and automating
information validation and transformation tasks. Contemporary design
information, however, is mainly intended for human consumption, and needs to be
explicitly enriched with the currently missing data and interfaces. In
practice, this may require acknowledging the role of technical information or
knowledge engineer, to lead the development of the semantic design information
process in a design organization. There is also a trade-off between
machine-readability and system complexity that needs to be studied further,
both empirically and in theory.
Research limitations/implications: The conceptualization of the semantic
process is essentially an abstraction based on the idea of progressive design.
While this effectively allows implementing semantic processes with, e.g.,
pipeline technologies, the abstraction is valid only when technical design is
organized into reasonably distinct tasks.
Practical implications: Our work points out a best practice for technical
information management in progressive design that can be applied on different
levels.
Social implications: Current design processes may be somewhat impaired by
legacy practices that do not promote information reuse and collaboration beyond
conventional task domains. Our work provides a reference model to analyze and
develop design activities as formalized work-flows. This work should lead into
improved industry design process models and novel CAD/CAM/PDM applications, thereby
strengthening industry design processes.
Originality/value: While extensively studied, semantic modeling in
technical design has been largely dominated by the idea of capturing design
artifacts without a clear rationale why this is done and what level of detail
should be favored in models. In the semantic process presented in this article,
the utility and the chief quality criteria of semantic models (of technical
information and artifacts) are explicitly established by the semantic
processing pipeline(s). This constructively explains the significance of
semantic models as communication and information requirement interfaces, with
concrete use cases.
Keywords: semantic process,
design process, engineering design, engineering information management, pipeline
data processing
Author: Ossi Nykänen, Jaakko
Salonen, Mikko Markkula, Pekka Ranta, Markus Rokala, Matti Helminen, Vänni
Alarotu, Juha Nurmi, Tuija Palonen, Kari T Koskinen, Seppo Pohjolainen
Journal Code: jptindustrigg110029
