DCR-based causal design knowledge evaluation method and system for future CAD applications

This paper presents a new causal design knowledge evaluation method and system for future CAD applications. Current product development processes still include unintended feedback due to insufficient product design knowledge. Previous research on design knowledge support system focuses on search by matching keywords and file names, or search by specific indices, which has various drawbacks. Furthermore, current CAD systems need manual input to incorporate the designer’s knowledge. To systematize the knowledge management process for the next-generation CAD systems, a prerequisite is to capture ever-evolving causal design knowledge. In this paper, we present a new causal knowledge network evaluation method, which has not been well addressed in design knowledge support system research. For the network evaluation, we present a degree of causal representation (DCR)-based knowledge network evaluation method. In this method, causality and network connectivity are used for the causal knowledge network with weighted vertices and weighted network connectivity for a network with weighted edges. To validate the proposed method, this evaluation method has been compared with structural measures. Finally, the causal design knowledge evaluation system, KNOES, is implemented and tested with a new valve design scenario.     

Causal design knowledge: Alternative representation method for product development knowledge management

This paper presents a mathematical comparison of procedural knowledge and causal knowledge, and discusses the potential roles and feasibility of causal knowledge across product development knowledge management. Since reuse of knowledge is so important in product development, various knowledge management approaches have been introduced. Most of the product design knowledge is represented by procedural knowledge, which unfortunately requires cumbersome processes to define, and is typically inadequate for representing the kind of knowledge generated during the product development process. A causal knowledge representation, however, can help us to overcome this limitation and is an alternative formalism for representing product design knowledge. In this paper we compare the procedural and causal knowledge representations. We present the mathematical definitions of two knowledge paradigms, then mathematically describe the relationship between the two. Both knowledge paradigms are then compared based on the perspective of knowledge expression, decision alternative representation, reasoning capability, and knowledge cultivation. This paper concludes that causal knowledge representation is superior to procedural knowledge representation based on the four perspectives. Finally, the knowledge systems are modeled using Systems Modeling Language (SysML), and we present a case study that demonstrates the causal knowledge features using a realistic example from industry.     

Facial configuration and BMI based personalized face and upper body modeling for customer-oriented wearable product design

To realize truly customer-oriented wearable products, individual users’ unique characteristics and features should be properly captured and represented. This research focuses on an efficient methodology to generate low polygonal virtual human face models, which overcome the limitation of existing high polygonal models. To determine individuals’ characteristics in the conceptual design stage of wearable products, a computerized and personalized 3D face model should be efficiently generated and be able to interact with wearable products. This research formulates a computerized 3D face via a 3D feature-based transformation. The developed algorithm is able to concisely and efficiently create a 3D face by using frontal and lateral pictures of users. The performance of this algorithm is well adapted both to typical PCs and to mobile devices. The generated virtual face models can serve as communication media in a multi-device based collaborative design environment. Through experiments, the validity of the proposed modeling method is considerably acceptable with respect to the quality of the similarity between 3D faces and individual pictures. Finally, this paper discusses how the developed personalized face modeling can be successfully utilized for customer-oriented wearable product design by showing compatible matching of a hairstyle product as a user study.     

Fabrication of an a-IGZO thin film transistor using selective deposition of cobalt by the self-assembly monolayer (SAM) process

Interest in transparent oxide thin film transistors utilizing ZnO material has been on the rise for many years. Recently, however, IGZO has begun to draw more attention due to its higher stability and superior electric field mobility when compared to ZnO. In this work, we address an improved method for patterning an a-IGZO film using the SAM process, which employs a cost-efficient micro-contact printing method instead of the conventional lithography process. After a-IGZO film deposition on the surface of a SiO2-layered Si wafer, the wafer was illuminated with UV light; sources and drains were then patterned using n-octadecyltrichlorosilane (OTS) molecules by a printing method. Due to the low surface energy of OTS, cobalt was selectively deposited on the OTS-free a-IGZO surface. The selective deposition of cobalt electrodes was successful, as confirmed by an optical microscope. The a-IZGO TFT fabricated using the SAM process exhibited good transistor performance: electric field mobility (micro(FE)), threshold voltage (V(th)), subthreshold slope (SS) and on/off ratio were 2.1 cm2/Vs, 2.4 V, 0.35 V/dec and 2.9 x 10(6), respectively.