Knowledge-Based Design Guidance System for Cloud-Based Decision Support in the Design of Complex Engineered Systems

The automation and intelligence highlighted in Industry 4.0 put forward higher requirements for reasonable trade-offs between humans and machines for decision-making governance. However, in the context of Industry 4.0, the vision of decision support for design engineering is still unclear. Additionally, the corresponding methods and system architectures are lacking to support the realization of value-chain-centric complex engineered systems design lifecycles. Hence, we identify decision support demands for complex engineered systems designs in the Industry 4.0 era, representing the integrated design problems at various stages of the product value chain. As a response, in this paper, the architecture of a Knowledge-Based Design Guidance System (KBDGS) for cloud-based decision support (CBDS) is presented that highlights the integrated management of complexity, uncertainty, and knowledge in designing decision workflows, as well as systematic design guidance to find satisfying solutions with the iterative process “formulation-refinement-exploration-improvement” (FREI). The KBDGS facilitates diverse multi-stakeholder collaborative decisions in end-to-end cloud services. Finally, two design case studies are conducted to illustrate the proposed work and the efficacy of the developed KBDGS. The contribution of this paper is to provide design guidance to facilitate knowledge discovery, capturing, and reuse in the context of decision-centric digital design, thus improving the efficiency and effectiveness of decision-making, as well as the evolution of decision support in the field of design engineering for the age of Industry 4.0 innovation paradigm.

Impact of deep eutectic solvents (DESs) and individual DES components on alcohol dehydrogenase catalysis: Connecting experimental data and molecular dynamics simulations

For a knowledge-based design of enzyme catalysis in deep eutectic solvents (DESs), the influence of the DESs properties (e.g., water activity, viscosity), and the impact of DESs and their individual...

Relationships between the material properties of silicone hydrogels: Desiccation, wettability and lubricity

Silicone hydrogels (SiHy), represent composite matrices composed of hydrophobic gas permeable silicone (Si) rich core and a surface enriched with hydrophilic polymer moieties. Their utilization in contact lens design requires number of SiHy properties (hydration, wettability, lubricity) to be optimized for the challenging conditions at the ocular surface. Typical limitations in literature are that (i) these properties are studied in isolation, monitoring only one parameter but not the rest of them, and (ii) measurements are performed with hydrated samples immediately after removal from storage solutions. Here we study the simultaneous evolution of critical material properties (evaporative loss of water, water contact angle, coefficient of friction) of different SiHy subjected to continuous blink-like desiccation/rehydration cycling. SiHy with wetting agents incorporated in their core (narafilcon A, senofilcon A) were particularly susceptible to extended desiccation. Stenfilcon A, a material with only 3% bulk Si content maintained its performance for 4 h of cycling, and delefilcon A (80% surface water content) resisted extended 8 h of desiccation/rehydration runs. Strong correlation exists between the evolution of SiHy wettability and lubricity at ≥4 h of blink-like cycling. Understanding the interplay between SiHy properties bears insights for knowledge based design of novel ophthalmic materials.