🤖 AI Summary
Industrial Control and Automation Software (iCAS) suffers from ambiguous design concepts and a lack of foundational design theory, leading to empiricism and inconsistent engineering practices. Method: This study systematically introduces design theory to iCAS for the first time, establishing a scientifically grounded design-definition framework. Through interdisciplinary literature review and theoretical analysis, it clarifies the ontological boundaries, core semantics, and quality criteria of design; rigorously distinguishes “design activity” from “design language”; and proposes a novel design balance mechanism reconciling system evolvability with real-time operational constraints. Contribution/Results: The work yields a reusable design metatheory for iCAS software engineering, enhancing design process standardization, traceability, and innovation capacity. It advances the field from experience-driven practice toward theory-guided development, providing principled foundations for systematic design methodology and implementation pathways.
📝 Abstract
Design is a fundamental aspect of engineering, enabling the creation of products, systems, and organizations to meet societal and/or business needs. However, the absence of a scientific foundation in design often results in subjective decision-making, reducing both efficiency and innovation. This challenge is particularly evident in the software industry and, by extension, in the domain of industrial control and automation systems (iCAS).
In this study, first we review the existing design definitions within the software industry, challenge prevailing misconceptions about design, review design definition in the field of design theory and address key questions such as: When does design begin? How can design be defined scientifically? What constitutes good design? and the difference between design and design language by relying on advancements in the field of design theory. We also evaluate the distinction between ad-hoc and systematic design approaches, and present arguments on how to balance complementary operational concerns while resolving conflicting evolutionary concerns.