Kyoung Yun Kim

Ontology-based assembly design and information sharing for collaborative product development

To realize a truly collaborative product design and development process, effective communication among design collaborators is a must. In other words, the design intent that is imposed in a product design should be seized and interpreted properly; heterogeneous modeling terms should be semantically processed both by design collaborators and intelligent systems. Ontologies in the Semantic Web can explicitly represent semantics and promote integrated and consistent access to data and services. Thus, if an ontology is used in a heterogeneous and distributed design collaboration, it will explicitly and persistently represent engineering relations that are imposed in an assembly design. Design intent can be captured by reasoning, and, in turn, as reasoned facts, it can be propagated and shared with design collaborators. This paper presents a new paradigm of ontology-based assembly design. In the framework, an assembly design (AsD) ontology serves as a formal, explicit specification of assembly design so that it makes assembly knowledge both machine-interpretable and to be shared. An Assembly Relation Model (ARM) is enhanced using ontologies that represent engineering, spatial, assembly, and joining relations of assembly in a way that promotes collaborative assembly information-sharing environments. In the developed AsD ontology, implicit AsD constraints are explicitly represented using OWL (Web Ontology Language) and SWRL (Semantic Web Rule Language). This paper shows that the ability of the AsD ontology to be reasoned can capture both assembly and joining intents by a demonstration with a realistic mechanical assembly. Finally, this paper presents a new assembly design information-sharing framework and an assembly design browser for a collaborative product development.

Design formalism for collaborative assembly design

Abstract Joints in product design are common because of the limitations of component geometric configurations and material properties, and the requirements of inspection, accessibility, repair, and portability. Collaborative product design is emerging as a viable alternative to the traditional design process. The collaborative assembly design (AsD) methodologies are needed for distributed product development. Existing AsD methodologies have limitations in capturing the non-geometric aspects of designers intent on joining and are not efficient for a collaborative design environment. This paper introduces an AsD formalism and associated AsD tools to capture joining relations and spatial relationship implications. This AsD formalism allows the joining relations to be modeled symbolically for computer interpretation, and the model can be used for inferring mathematical and physical implications. An AsD model generated from the AsD formalism is used to exchange AsD information transparently in a collaborative AsD environment. An assembly relation model and a generic assembly relationship diagram are to capture assembly and joining information concisely and persistently. As a demonstration, the developed AsD formalism and AsD tools are applied on a connector assembly with arc weld and rivet joints.

Knowledge flow‐based business process redesign: applying a knowledge map to redesign a business process

Purpose – The aim of this paper is to suggest a method to redesign business processes from the viewpoint of knowledge flows using a knowledge map.Design/methodology/approach – Knowledge flows and business processes cannot be separated because knowledge is inputted and outputted through business processes. Knowledge flows inherit the feature and appearance of corresponding business processes; therefore, one can identify problems within business processes by analyzing corresponding knowledge flows. The methodology is composed of the following sections: knowledge mapping, knowledge profiling, knowledge flow identification, knowledge flow optimization and TO‐BE process visualization.Findings – This paper provides a methodology for knowledge flow‐based business process redesign and ten guidelines for knowledge flow optimization. The case study demonstrates that the proposed ideas constitute knowledge‐intensified business processes.Research limitations/implications – A more formal validation method that is base...

Systematic causal knowledge acquisition using FCM Constructor for product design decision support

Despite its usefulness, design knowledge is not often captured or documented, and is therefore lost or damaged after a product design is completed. As a way to address this issue, two major formalisms can be used for modeling, representing, and reasoning about causal design knowledge: fuzzy cognitive map (FCM) and Bayesian belief network (BBN). Although FCM has been used extensively in knowledge engineering, few methodologies exist for systematically constructing it. In this paper, we present a methodology and application-FCM Constructor-to systematically acquire design knowledge from domain experts, and to construct a corresponding BBN. To show the systems usability, we use three realistic product design cases to compare BBNs that are directly generated by domain experts, with BBNs that are generated using the FCM Constructor. We find that the BBN constructed through the FCM Constructor is similar, based on reasoning results, to the BBN constructed directly by specifying conditional probability tables of BBNs.

Robot arc welding task sequencing using genetic algorithms

This paper addresses welding task sequencing for robot arc welding process planning. Although welding task sequencing is an essential step in welding process planning, it has been considered through empirical knowledge, rather than a systematic approach. Thus, an effective task sequencing method for robot arc welding is required. Welding operations can be classified by the number of weldlines and layers. Genetic algorithms are applied to tackle those welding task sequencing problems in productivity and welding quality aspects. A genetic algorithm for the Traveling Salesman Problem (TSP) is utilized to determine welding task sequencing for a multiweldline-singlepass problem. Further, welding task sequencing for multiweldline-multipass welding is investigated and appropriate genetic algorithms are introduced. A random key genetic algorithm is presented to solve multi-robot welding task sequencing: mutliweldline with multiple robots. Finally, the genetic algorithms are implemented for the welding task sequencing of three-dimensional weld plate assemblies. Various simulation tests for a welded structure are performed to find the combination of genetic algorithm parameters suitable to weld sequencing problems and to verify the quality of genetic algorithm solutions. Robot operations for weld sequences are simulated graphically using the robot simulation software IGRIP.

Emotional Intensity-based Facial Expression Cloning for Low Polygonal Applications

People instinctively recognize facial expression as a key to nonverbal communication, which has been confirmed by many different research projects. A change in intensity or magnitude of even one specific facial expression can cause different interpretations. A systematic method for generating facial expression syntheses, while mimicking realistic facial expressions and intensities, is a strong need in various applications. Although manually produced animation is typically of high quality, the process is slow and costly-therefore, often unrealistic for low polygonal applications. In this paper, we present a simple and efficient emotional-intensity-based expression cloning process for low-polygonal-based applications, by generating a customized face, as well as by cloning facial expressions. We define intensity mappings to measure expression intensity. Once a source expression is determined by a set of suitable parameter values in a customized 3D face and its embedded muscles, expressions for any target face(s) can be easily cloned by using the same set of parameters. Through experimental study, including facial expression simulation and cloning with intensity mapping, our research reconfirms traditional psychological findings. Additionally, we discuss the methods overall usability and how it allows us to automatically adjust a customized face with embedded facial muscles while mimicking the users facial configuration, expression, and intensity.

Ontology-based modeling and integration of morphological characteristics of assembly joints for network-based collaborative assembly design

Abstract This paper presents our research on developing an ontology-based framework that can represent morphological characteristics related to assembly joints. Joints within the physical structure of an assembly are inevitable because of the limitations of component geometries and the associated, required engineering properties. Consequently, a framework is needed that can capture and propagate assembly design and joint information in a robust assembly model throughout the entire product development processes. The framework and model are based on an understanding of the morphological characteristics of an assembly and its different physical effects. The morphological characteristics are consequences of the principal physical processes and of the design intentions. Therefore, the morphological characteristics should be carefully represented while considering the geometry and topology of assembly joints. In this research, assembly joint topology is defined by a mereotopology, which is a region-based theory for the parts and associated concepts. This formal ontology can differentiate often ambiguous assembly and joining relations. Furthermore, the mereotopological definitions for assembly joints are implemented in Semantic Web Rule Language (SWRL) rules and Web Ontology Language triples. This process provides universality to the mereotopological definitions. Two geometrically and topologically similar joint pairs are presented to describe how the assembly joints can be defined in mereotopology and be transformed into SWRL rules. Web3D is also employed to support network-enabled sharing of assembly geometry. Finally, the proposed modeling framework is demonstrated using a real fixture assembly. This case study demonstrates the usability of the proposed framework for network-based design collaboration.

MM-DSS: Integrating multimedia and decision-making knowledge in decision support systems

Abstract Multimedia (MM) information systems have been utilized for decision-making tasks since they were developed in the early 1990s. Few research studies to date have paid attention to the integrated mode of MM information with a decision support system (DSS) or have investigated the role of MM information and DSS from the perspective of model-based knowledge management. This paper proposes a multimedia decision support system (MM-DSS) to address the above unexplored issues. The proposed MM-DSS manages MM information with the use of a newly developed extended attributed relational graph (ARG) and the structured modeling (SM) technique in order to support complicated decision-making processes intelligently and systematically. This paper illustrates the development of the new extended ARG and the SM method, and their integration into mathematical decision-making knowledge. The proposed MM-DSS responds to the needs of representation, storage, and retrieval of MM information in decision-making processes. Results of simulation show that the proposed MM-DSS is successful in tackling an optimization problem of factory scheduling.

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.

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 designers 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.