Jeongsam Yang

Managing uncertainty to improve decision-making in NPD portfolio management with a fuzzy expert system

Highlights? We model a decision-making framework for portfolio management under uncertainty. ? We adopt the strategic bucket, scoring models and portfolio matrixes. ? We develop a fuzzy-based portfolio expert system. ? The system was applied to the portfolio analysis in an electronics firm. The importance of new product development (NPD) for a companys growth and prosperity is emphasized and a number of methods have been suggested to help decision-making for NPD project portfolio management. In spite of their utilities, however, little attention was paid to develop a supporting system for portfolio management that can help quick but careful decision-makings under uncertainties. Therefore, this research proposes a decision-making framework that uses a fuzzy expert system in portfolio management for dealing with the uncertainty of the fuzzy front-end of product development. For the purpose of developing the framework, we adopted the three tools - strategic bucket for strategic resource allocation, scoring models for evaluating projects and portfolio matrixes for balancing projects - to find an optimal set of projects in the portfolio. In particular, this research established fuzzy inference-based models for evaluation criteria which are too ambiguous to be numerically described. Also, based on the evaluation results, the final selection of projects is made by an expert system, which can encompass the operational knowledge and company strategy in the rule-based system. The suggested framework was applied to the portfolio analysis in an electronics firm in Korea and verified its feasibility.

Repairing CAD model errors based on the design history

For users of CAD data, few things are as frustrating as receiving unusable, poor quality data. Users often waste time fixing or rebuilding such data from scratch on the basis of paper drawings. While previous studies use the boundary representation (B-Rep) of CAD models, we propose an approach to repairing CAD model errors that is based on the design history. CAD model errors can be corrected by an interdependency analysis of the feature commands or of the parametric data of each feature command, as well as by a reconstruction of the feature commands through rule-based reasoning of an expert system. Unlike other correction methods based on B-Rep models, our method repairs parametric feature models without translating them to a B-Rep shape, and it also preserves parametric information.

An XML-Based Macro Data Representation for a Parametric CAD Model Exchange

AbstractA macro-parametric approach, which is a history-based method of parametric CAD model exchange, has recently been proposed. CAD models can be exchanged in the form of a macro file that comprises a sequence of modeling commands. As a set of event-driven commands, a standard macro file can transfer the designer intent such as parameters, features and constraints. Moreover, it is suitable for a network environment because standard macro commands are open and explicit, and the data size is small. This paper introduces XML technology to represent the macro-parametric exchange. Using XML to represent macro-parametric commands enables the management of a large amount of dynamic content, Web-enabled distributed applications, and the inherent characteristics of structure and validation.

Development of a BIM-based structural framework optimization and simulation system for building construction

Building construction has become increasingly complicated and extensive. Building information modeling (BIM), which is a technology that allows for the consistent management of information, is regarded as a necessary tool for managing the process of building construction from beginning to end. However, the information provided by BIM is rarely applied to on-site construction planning and scheduling. In this paper, we describe a BIM-based structural framework optimization and simulation system for managing construction planning and scheduling. Moreover we conduct a dynamic visualization of the construction process according to the optimized schedules by applying a predefined calculation formula and logic along with 3D geometry data and process data to determine the amount of work required for major construction processes. In addition, if more than two different construction schedules are fed into the system, it is able to compare construction schedules using its comparison simulation function.

Construction of a computer-simulated mixed reality environment for virtual factory layout planning

To survive the cut-throat competition in the manufacturing industry, many companies have introduced digital manufacturing technology. Digital manufacturing technology not only shortens the product development cycle times but also improves the precision of engineering simulation. However, building the virtual objects needed for a digital manufacturing environment requires skilled human resources; it is also costly and time-consuming. A high precision environment with the similar resources is also needed for a high precision simulation. In this paper, we propose a method of constructing a mixed reality-based digital manufacturing environment. The method integrates real objects, such as real images, with the virtual objects of a virtual manufacturing system. This type of integration minimizes the cost of implementing virtual objects and enhances the users sense of reality. We studied several methods and derived a general framework for the system. Finally, we developed our idea into a virtual factory layout planning system. To assign the pose and position of real objects in virtual space, we applied a circle-based tracking method which uses a safety sign instead of the planar-square-shaped marker generally used for registration. Furthermore, we developed the framework to encapsulate simulation data from legacy data and process data for visualization based on mixed reality.

A multichannel visualization module for virtual manufacturing

The immersive virtual reality (VR) for manufacturing planning helps to cut down the product development period and to improve the quality of the production. However, the immersive VR equipments are generally expensive, both in terms of development and buying. Users spend time to manually repair complex 3D shapes because of imperfect translations between 3D engineering CAD models and the proprietary format of the VR system. In this paper, the proposed VR module uses a commercial virtual manufacturing system (VMS) as the viewer of the immersive VR system on a cluster of PCs and adopts the modified simulation algorithm. The module can make the data translation process unnecessary and ensure good coherence under simulation. At experiment, the proposed immersive VR module was interfaced with the Delmia VMS. Its clustering modules can reduce the cost of VR experiment while offering high performance.

Development of a decision making system for selection of dental implant abutments based on the fuzzy cognitive map

Dental implant is a medical operation used to restore the functions of damaged or missing teeth. Correct implantation requires the proper selection of size and shape among the implant structures. In this paper, we propose a method of constructing a Web-based decision making system that enables the selection of a suitable type of abutment by taking into account the patients anatomical data and preferences that are based on an experts knowledge and experience for those patients. After the classification of the types of abutment that can be connected to fixtures of implants, we built a knowledge base and case base library according to the characteristics of osseous tissue and teeth shape to select optimal abutment. Moreover, we introduce a fuzzy cognitive map that takes into consideration experts knowledge for factors that affect implantation. After the determination of the cause-and-effect relationship among the concepts of the fuzzy cognitive map, an osseointegration factor with the highest conceptual concentration weight is inferred from the decision making system. In addition, the selection process for abutment is expressed as a decision making tree and then, it is applied for the rule-based reasoning and case-based reasoning. The optimized selection result is finally extracted based on the fuzzy membership function using fuzzy inference.

Development of a lightweight CAE middleware for CAE data exchange

Computer-aided engineering (CAE) analysis is considered essential for product development because it decreases the simulation time, reduces the prototyping costs, and enhances the reusability of product parts. The reuse of quality-assured CAE data has been continually increasing in order to shorten the product development cycle and to improve the product quality. However, less attention has been paid to systematic research on the interoperability of CAE data because of the diversity of CAE data and because the structure of CAE data is more complex than that of CAD data. In this paper, we suggest a CAE data exchange method for the effective sharing of geometric and analysis data. The method relies on heterogeneous CAE systems, a virtual reality system, and our developed lightweight CAE middleware for CAE data exchange. We also designed a generic CAE kernel, which is a critical part of the CAE middleware. The kernel offers a way of storing analysis data from various CAE systems, and, with the aid of a script command, enabling the data to be translated for a different system. The reuse of CAE data is enhanced by the fact that the CAE middleware can be linked with a virtual reality system or a product data management system.

An interactive data-driven driving simulator using motion blending

Compared to the motion equations the data-driven method can simulate reality from sampling of real motions but real-time interaction between a user and the simulator is problematic. Existing data-driven motion generation methods simply record and replay the motion of the vehicle. Character animation technology enables a user to control motions that are generated by a motion capture database and an appropriate motion control algorithm. We propose a data-driven motion generation method and implement a driving simulator by adapting the method of motion capture. The motion data sampled from a real vehicle are transformed into appropriate data structures called motion blocks, and then a series of motion blocks are saved into the motion database. During simulation, the driving simulator searches for and synthesizes optimal motion blocks from the motion database and generates motion streams that reflect the current simulation conditions and parameterized user demands. We demonstrate the proposed method through experiments with the driving simulator.

A collaboration model for new product development through the integration of PLM and SCM in the electronics industry

An NPD project has the distinctive feature that the schedule must change frequently owing to internal or external factors.We suggest a collaboration model integrating PLM and SCM as an approach to support complicated NPD procedures.This model is capable of shortening the lead time of an NPD process through vertical or horizontal work reference.We introduce a practical case study to evaluate this model. As customer requirements for high-tech products vary and become complicated, the lifecycle of these products becomes much shorter. In response to this market environment, many manufacturing companies have established a global simultaneous launch strategy for new products to occupy markets before competitors. In this process, careful scheduling of the global simultaneous launch strategy is critical. In particular, to meet the launch schedule for each country in which a new product will be released, a collaboration process among relevant departments must be prepared, and correct product information should be maintained among major cooperative work support systems according to new product development business processes. This paper suggests a collaboration model integrating product lifecycle management and supply chain management as an approach to supporting complicated new product development procedures. We use a practical case study to evaluate this model.