Search

The resistive heating and thermoelectric characteristics of discontinuous carbon fiber-epoxy composites are explored experimentally and numerically. Composite samples with different carbon fiber concentrations (1, 3, and 5 wt.%) were manufactured using sonication and cast molding. DC current was applied, and the temperature distributions on the surfaces of the samples were assessed visually and quantitatively using an infrared camera. The resistive heating mechanism was investigated in conjunction with applied voltage and carbon fiber loading. Experimental results show that resistive heating efficiency increased proportionately with applied voltage and carbon fiber content, and this was confirmed by numerical simulations of fiber contacts at various fiber volume fractions using representative volume elements. In parallel, the thermoelectric behavior of composites was characterized using a specially designed and fabricated test setup. The discontinuous carbon fiber-epoxy composites showed p-type thermoelectric behavior, and the generated voltage and Seebeck coefficient increased with increasing applied temperature and temperature difference.

This paper investigates inbound logistics for an OEM (Original Equipment Manufacturing) manufacturer, who aims at short production time and JIT policy. In such a case, it can be argued that the inbound vehicle routing schedule should be combined with incoming parts inventory control. In this paper, we propose a simultaneous control method of combining vehicle scheduling and inventory control for such dynamic inbound logistics. For the transportation control, a vehicle routing system, in which delivery jobs are made with shipments of one supplier, is proposed to generate a vehicle routes plan by considering production start time, travel time, waiting time, and loading/unloading time. To evaluate the performance of the generated vehicle routing plan, a goal model is also developed by considering vehicle operating cost, stock level exceeding penalty, and transportation efficiency. A generated vehicle routing plan can be rejected when the stock level is over the capacity and an appropriate number of vehicles for its manufacturing environment can be determined. Using real data from an LCD firm, a simulation study is conducted. The simulation results indicate that the simultaneous control approach requires fewer vehicles than the existing system and shows better efficiency of transportation. This method can also be used to determine the appropriate incoming part inventory level or the number of vehicles required in dynamic inbound logistics.

A major issue in supply chain inventory management is the coordination of inventory policies adopted by different members in a supply chain including suppliers, manufacturers, distributors, etc. This paper presents a fractal-based approach for inventory management in order to minimize inventory costs and smooth material flows between supply chain members while responsively meeting customer demand. Within this framework, each member in the supply chain is defined as a self-similar structure, referred to as a fractal. A fractal-based echelon does not indicate a functional level or composition of supply chain members but indicates a group of multi- or hetero-functional fractals. The basic fractal unit (BFU) consists of five functional modules including an observer, an analyzer, a resolver, an organizer, and a reporter. The application of the fractal concept into inventory management makes it easy to intuitively understand and manage supply chain inventories because similar functional modules can be iteratively applied to an inventory management system. More specifically, we apply the fractal concept to a vendor managed inventory (VMI) model, referred to as fractal-based VMI (fVMI), where a vendor assumes responsibility for maintaining inventory levels and determining order quantities for his buyers. In this paper, we develop mathematical models for the analyzer and resolver to effectively manage supply chain inventories. For validating the proposed approach, a comprehensive simulation model, representing two VMI initiatives including traditional VMI and fVMI, is constructed and used for comparative analyses of case studies.

Because the supply network of an enterprise should be flexible enough to capture and overcome market dynamics, one of the major concerns of global enterprises is to make their supply network reconfigurable. Although many strategies for flexible management of a supply network have been proposed, especially for mitigating supply network risks, it still remains unclear how to apply the strategies to a supply network and how to reconfigure the supply network. This paper examines the influence of flexibility strategies in a dynamic global market environment on the structure of supply network, and proposes a method of reconfiguring the supply network of an enterprise to cope with its flexibility strategies. A reconfigurable supply network model is proposed, and flexibility strategies are classified, and critical indices of strategies are defined. In the proposed model, each business actor is defined as a network node and each node has its own goal. A node optimizes its goal to reduce and overcome the risk of market environments. The result of optimization indicates that the supply network structure is reconfigured dynamically.

This study explores the resistive heating characteristics of discontinuous carbon fiber (CF)-epoxy composites. Test samples including 1, 3, and 5 wt.% CF were fabricated using sonication and cast molding processes. For heating performance characterization, DC currents were applied to the composite samples, and surface temperatures were evaluated visually and quantitatively using an infrared camera. To estimate the thermal performance of composites and verify the experimental results, finite element analyses were performed. The resistive heating mechanism was investigated in connection with CF loading and applied voltages. Resistive heating efficiency increased proportionately with CF concentration and applied voltage. To obtain homogeneous temperature distribution of the samples, high degree of CF dispersion is required.

Highlights? We propose a goal-regulation mechanism that applies a reinforcement learning approach to autonomous goal-formation. ? Individual goals are regulated by a neural network-based fuzzy inference system called goal-regulation network (GRN). ? The GRN is updated by a reinforcement signal from another neural network called goal-evaluation network (GEN). ? The GEN approximates the compatibility of goals with current environmental situation. ? The proposed mechanism is validated by a simulation study on a production planning problem. Up-to-date market dynamics has been forcing manufacturing systems to adapt quickly and continuously to the ever-changing environment. Self-evolution of manufacturing systems means a continuous process of adapting to the environment on the basis of autonomous goal-formation and goal-oriented dynamic organization. This paper proposes a goal-regulation mechanism that applies a reinforcement learning approach, which is a principal working mechanism for autonomous goal-formation. Individual goals are regulated by a neural network-based fuzzy inference system, namely, a goal-regulation network (GRN) updated by a reinforcement signal from another neural network called goal-evaluation network (GEN). The GEN approximates the compatibility of goals with current environmental situation. In this paper, a production planning problem is also examined by a simulation study in order to validate the proposed goal regulation mechanism.

Globalization of market and diversification of customers` needs make enterprises to collaboration of participants in supply chain. To establish collaboration, supply chain must have the flexibility and reconfigurability, which are supported by fractal based supply chain management (FrSCM). In this paper, base on the FrSCM, formulation of trust model among the enterprises in the supply chain, and development of profit sharing strategies in the supply chain based on the trust model are investigated. To evaluate trust model, generation of enterprise`s goal and its description, extraction and systematic composition of trust factors and trust evaluation are investigated. Based on the developed model, we developed the fuzzy inference engine to evaluate the trust value in terms of numerical value. And then revenue sharing strategies are developed based on the fractal concept and trust model for the collaborative SCM. The fractal concept is used to obtain the optimal production and transportation plans. In addition, the trust model will be integrated into the RS model. In such an RS model, the supply chain will obtain the maximum total profit and profit of each participant depends on its trust value.

Companies and research institutes are always threatened by rapid technological developments and corporate M&A. They are trying to secure a sustainable competitive advantage using outside knowledge and expertise under open innovation to overcome these shortcomings. As a quantitative and systematical method of selecting virtual team members for open innovation, we present a virtual team formation model and a prototype to verify its efficiency. The test scenario shows how to form a virtual team through internal and external human resources when developing a new product.

Project performance is significantly affected by the collaboration of project team members and by the levels of their knowledge. While many qualitative and quantitative studies on project performance have been conducted, only few studies have analyzed the effects of knowledge and collaboration. This paper proposes an extended project-oriented virtual organization (EProVO) model that consists of a total of 10 factors: 2 time availability factors, 3 cost factors, and 5 capability factors that are useful in evaluating the knowledge competence and collaboration competence of project members. Defining the project performance index that generally assesses project goals - quality, time and budget, and using the data from an actual R&D institute, the effects of 10 factors on project performance were analyzed, and the performance of the project team members was predicted. The predicted project performance of team members helped the decision-making process of the project team manager by providing information required for organizing the team. Furthermore, the coefficient of each factor was useful in figuring out the problems to be encountered in the behavioral styles in terms of knowledge, collaboration, time availability, and cost of running the current organization. Consequently, directions for organizational improvement of a research institute could be offered.

Virtual organization (VO) is a main organizational paradigm for enterprises to collaborate in the rapidly changing environment. Advances in information and communication technologies are accelerating collaboration among enterprises in different domains as well as unknown enterprises. In this environment, an enterprise faces more chances to cooperate with other enterprises through the internet. Trust is a key concept in many kinds of interactions, allowing an enterprise to act under uncertainty and with the risk of negative consequences. To minimize the operating risk and guarantee the success of a VO, trust evaluation of potential partners should be considered during the partner selection process. However, trust evaluation methods in the literature have limitations in applying them to small and medium enterprises because they are based on evaluation of human experts. In this paper, a goal-oriented trust model is proposed to evaluate the trust values of enterprises. In the context, trust is the probability that a trustee satisfies the goals when it completes assigned tasks. This paper introduces the concept of a goal-oriented trust model with the core constructs of a goal, a project, a task, and a capability. It further addresses an example of applying the proposed model to the partner selection process of a project-based VO creation.

Appointing a good leader to the position of team manager and having competent workers collaborate as team members is a key to success in business activities of an enterprising institution. The traditional methodologies of human resource management have defined the required abilities for team managers and team members, and evaluated those abilities of employees. However, it is difficult to consider those abilities systematically in practice. In addition, the current management paradigm undergoes rapid transitions into knowledge management. In step with these trends, this study presents a framework for analyzing the knowledge of the candidates for managers and team members for the new team, and proposes a genetic algorithm and social network measures for choosing a team manager and team members. A prototype was built for testing the feasibility of the model. The testing data are from an R&D institute's human resource management department. The results show that our proposed approach is a quantitative and systematic method for selecting proper personnel for appropriate teams.

In this era of rapid changes in the project-oriented R&D organization's environment, some are actively pursuing joint research to gain a leading edge over other R&D organizations. The condition for joint research is the knowledge that an organization needs from other organizations and the capability of collaboration. This study presents a ProVO model using the concept of virtual organization and project team formation based on knowledge and collaboration. In this model, VO is represented by the capability of carrying out a project and the cost of employment. Capability consists of knowledge competence (KC) and collaboration competence (CC). KC, in turn, consists of individual knowledge and collective knowledge from social network, while CC consists of density, degree centrality, and closeness centrality. To verify the presented model, we conducted a case study on a research institute. The analysis results show that all five project team formation factors of KC and CC are statistically significant. A prototype was also developed for selecting project team members using the binary logistics regression model. The proposed ProVO model can assist quantitative decision making on the selection of project team members by a project-oriented R&D organization from the aspects of knowledge and collaboration.

To cope with the rapidly changing manufacturing environment, enterprise collaboration is getting increasingly more attention than ever before. The virtual enterprise (VE) is a concept that supports temporary alliances of manufacturing enterprises that have various collaboration models, such as extended enterprise, networked enterprise, concurrent enterprise, etc. Selection of trustworthy partners and trust building are important in virtual domains because they have largely been affecting the success of a VE. However, because of its complexity of trust, trust models in the literature are limited in their ability to cope with dynamic and virtual environment. In this paper, we propose a trust evaluation method of supporting enterprise collaboration and maximizing the satisfaction of cooperation. In this context, trust means the goal achievement probability. Trust value of an enterprise can be obtained by a fuzzy inference system whose rule-base is based on the top-level goal of a VE. According to the selector's preference, various rules can be applied to trust evaluation. For further study, the planning and scheduling problems should be considered along with the trust-based partner selection for collaboration among manufacturing enterprises.

The turbulent environment of modern times breeds a need to ensure flexibility and responsiveness for manufacturing systems. The conventional manufacturing systems, however, are not suitable for the dynamic environment because of their rigid structure. Thus, it is necessary to establish a novel manufacturing system which is capable of proactively perceiving the environment and of autonomously adapting to the changing environments. The purpose of this paper is to propose a self-evolution framework of manufacturing systems that facilitates continuous and quick adaptation. In a self-evolutionary manufacturing system, each production resource regulates its own goal, responding to the changes in its environment. Moreover, the organizational structure of the production resources is also dynamically transformed into a form suitable to the changed goal and the emerging environment. Especially, the proposed framework adopts fractal organization for its principal control architecture.

Up-to-date market dynamics and decentralisation have brought about the need of flexible and robust organisational structures for manufacturing resources. To meet the need of such an environment, the manufacturing system should be equipped with an open, reconfigurable and scalable organisational structure. This paper proposes a novel organisational model, referred to as a relation-driven fractal organisation, to meet the requirements. The proposed model applies the concept of a fractal to its organisational structure and adopts a relational pattern between composing entities as a basic building block for organising. In this paper, the existing fractal-like systems involved in manufacturing systems are investigated, and the fractal organisation is derived as their super-ordinate concept. Then, r-FrMS, a relation-driven fractal organisation applied into distributed manufacturing systems, is proposed along with its organising mechanism which adopts employment relations between manufacturing resources as its o...

The coordination architecture and mechanisms are proposed for the goal-balancing process (GBP), which is one of the components of goal-formation process (GFP) in the fractal manufacturing system (FrMS). Since each agent in the FrMS generates, achieves and modifies its own goal autonomously during the coordination process with other agents, it is necessary to develop a systematic methodology for the goal-formations in a manufacturing system: GFP takes charge of this methodology, which enables the formation of and the changes in goal through coordination between agents in real-time in the distributed and dynamic systems. The GFP is composed of three sub-processes: the goal-generating process (GGP), the goal-harmonizing process (GHP), and the GBP. The GGP makes and propagates goals for all fractals. The GHP then eliminates or reduces possible conflicts and interferences between goals generated in GGP. The GBP is the post-process of GHP; it refines the fractal's goal, which has been ridded of conflict during ...

This paper proposes an efficient vehicle reassignment dispatching rule and demonstrates the effectiveness of the rule using an overhead hoist transport (OHT) system for a semiconductor fabrication line. The OHT system has more than 150 OHT vehicles and its target vehicle utilization level is 70%. It allows direct delivery such that an inter-bay wafer movement can be accomplished by a single vehicle. Simulation analysis is used to compare the proposed rule with the shortest travel distance first (STDF) rule and existing reassignment-based rules. While STDF rule requires 170 vehicles for the target utilization level, the proposed vehicle reassignment rule requires only 161 vehicles. At the same time, the lead time and the variance of the lead time have been significantly reduced. The proposed rule also improves system performance compared to existing reassignment-based rules.

To respond quickly to the rapidly changing manufacturing environment, it is imperative for the system to have such capabilities as flexibility, adaptability, and reusability. The fractal manufacturing system (FrMS) is a new manufacturing paradigm designed to meet these requirements. To facilitate a dynamic reconfiguration of system elements (i.e., fractals), agents as well as software modules should be self-reconfigurable. Embodiment of a self-reconfigurable manufacturing system can be achieved by using self-reconfigurable software architecture. In this paper, therefore, self-reconfigurable software architecture is designed by conducting the following studies: (1) analysis of functional requirements of a fractal and environmental constraints, (2) design of reconfigurable software architecture especially for a reconfigurable agent, (3) selection of proper techniques to implement software modules, and realization of software architecture equipped with self-reconfigurability. To validate this approach, the designed architecture is applied to the FrMS.

To meet the rapidly changing customer needs in the manufacturing environment, future manufacturing systems must be dynamically and flexibly reconfigured. The fractal manufacturing system (FrMS) is one of the new manufacturing paradigms that can meet such requirements. The basic component of the FrMS is referred to as a fractal. Consisting of self-similar agents, each fractal autonomously cooperates and negotiates with others to coordinate its tasks. Dynamic restructuring process (DRP) supports reorganization of the system configurations so that the FrMS can be adapted to dynamically changing environments. Although traditional approaches have endeavoured to demonstrate reconfigurability of a manufacturing system, they are not accurate enough to meet the requirements of circumstances such as high-level autonomy in reconfiguring the system architecture. In this paper, therefore, the DRP, which embodies self-reconfigurability of a system, is proposed focusing on the FrMS. To check the effectiveness of the DRP...

The fractal manufacturing system (FrMS) is based on the concept of autonomously cooperating agents referred to as fractals. A fractal is a set of self-similar agents whose goal can be achieved through cooperation, coordination, and negotiation among the agents for themselves. A fractal has fractal-specific characteristics (e.g. self-similarity, self-organization, self-optimization, goal-orientation, and dynamics), and it also has the characteristics of an agent (e.g. autonomy, mobility, intelligence, cooperation, and adaptability) at the same time. In the FrMS, a goal can be regarded as the status which the system aspires to be in. The goal-formation process (GFP) in the FrMS is a process of generating goals and modifying them by coordination between agents. In the GFP, conflicts may occur between goals, which can drive a system to become inefficient. In this paper, a conflict resolution mechanism via agent-based negotiation is proposed for facilitating the GFP. The scheme deals with non-fixed goals. The ...

*† Summary We have generated 47 932 T-DNA tag lines in japonica rice using activation-tagging vectors that contain tetramerized 35S enhancer sequences. To facilitate use of those lines, we isolated the genomic sequences flanking the inserted T-DNA via inverse polymerase chain reaction. For most of the lines, we performed four sets of amplifications using two different restriction enzymes toward both directions. In analyzing 41 234 lines, we obtained 27 621flanking sequence tags (FSTs), among which 12 505 were integrated into genic regions and 15 116 into intergenic regions. Mapping of the FSTs on chromosomes revealed that T-DNA integration frequency was generally proportional to chromosome size. However, T-DNA insertions were non-uniformly distributed on each chromosome: higher at the distal ends and lower in regions close to the centromeres. In addition, several regions showed extreme peaks and valleys of insertion frequency, suggesting hot and cold spots for T-DNA integration. The density of insertion events was somewhat correlated with expressed, rather than predicted, gene density along each chromosome. Analyses of expression patterns near the inserted enhancer showed that at least half the test lines displayed greater expression of the tagged genes. Whereas in most of the increased lines expression patterns after activation were similar to those in the wild type, thereby maintaining the endogenous patterns, the remaining lines showed changes in expression in the activation tagged lines. In this case, ectopic expression was most frequently observed in mature leaves. Currently, the database can be searched with the gene locus number or location on the chromosome at http:// www.postech.ac.kr/life/pfg/risd. On request, seeds of the T 1 or T2 plants will be provided to the scientific community.

This paper proposes a bid generation and evaluation scheme and an information model for real-time scheduling. It is well known that an agent-based control approach performs according to both the negotiation mechanism itself and the single agent internal strategic policies. Mobile agent-based negotiation process (MANPro), which has been proposed in our previous work, concerns the first issue of the negotiation mechanism. This paper concerns the second issue of the single agent internal strategic policies. It explains how bids are generated and evaluated and how agents obtain mutual agreement in MANPro. First, the generic bid generation and evaluation framework for MANPro-based negotiation is proposed. Then, the generic framework is applied to a real-time scheduling system for a distributed shop floor control system (SFCS).

A modern competitive environment requires rapid and effective responses to varying production demands with shorter life cycles. A feasible solution to cope with such unpredictable situations is to introduce an automated manufacturing system characterized by high flexibility, autonomy and cooperation. Much research has been done on negotiation-based scheduling and control under the distributed control architecture due to its operational flexibility and scalability. Despite many advantages, the probability of the system stalling at a deadlock state is high. Specifically, it is difficult to detect impending part flow deadlocks within the system. A system request network model is defined here to analyse various deadlock situations. Request cycles are then identified by a virtual part flow control mechanism. No request cycle in the system request network represents ‘no system deadlock’. For any request cycle, a deadlock analysis is performed. If any request cycle exists that represents either a part flow deadl...

Decomposition of tasks in ordinary manufacturing systems is usually based on the predefined goal of the system. To achieve the high-level goals (e.g. factory goal or company goal), several subgoals should be achieved in advance. However, goals can dynamically change along with the current status of the system and the external environmental situations. Thus, a manufacturing system should support the goal formations, which can bear these changes for efficient and effective operations. Therefore, it is necessary to develop a systematic methodology for goal formations in a manufacturing system. In particular, the formation and/or change of goals in real-time should be possible for distributed and dynamic systems including a fractal manufacturing system (FrMS). However, most researchers have started their study from an assumption that every goal in the system is naturally well defined. This paper proposes a methodology for the goal-formation process (GFP), which embodies one of the characteristics of a fractal...

This paper examines negotiation procedures in an agent-based distributed shop floor control system (SFCS). A distributed SFCS is under a heterogeneous environment, which is controlled through negotiations between autonomous agents. The negotiation-based control can be considered as the core of a distributed control paradigm. An efficient information exchanging mechanism and an information model with reasonable structure are indispensable for effective negotiations. This paper proposes a novel negotiation mechanism, called a mobile agent-based negotiation process (MANPro), which applies a mobile agent system to the process of information exchange. Since using mobile agents allows each component to execute asynchronously and autonomously and to adapt dynamically to the execution environment, MANPro may guarantee autonomy of agents. Moreover, it is possible to build a fully distributed and autonomous SFCS by using MANPro. MANPro is based on the agent-based control architecture, which includes a communication...

The high degree of uncertainty of customer demand makes it difficult for e-Biz companies to facilitate their profit maximization. The type of e-Biz company focused in this paper is a B2C (business-to-customer) which connects customers with product manufacturers through the Web interface. In this paper, the B2C company interacts with customers, multiple external manufacturers and a single transportation system. To deal with complicated interactions and relationships among customers, manufacturers and a transportation system, a comprehensive management system to support the B2C company is inevitable. This paper proposes a fractal-based framework for the management of e-Biz companies, where each member in the supply chain is modelled with a self-similar structure referred to as a ‘fractal’. The basic fractal unit (BFU) consists of five functional modules, including an observer, an analyser, a resolver, an organizer and a reporter. In this paper, functions of each module will be defined with UML (Unified Mode...

In order to respond to a rapidly changing manufacturing environment and market, manufacturing systems must be flexible, adaptable, and reusable. The fractal manufacturing system (FrMS) is one of the new manufacturing paradigms that address the need for these characteristics. The FrMS is comprised of a number of "basic components", each of which consists of five functional modules: (1) an observer, (2) an analyzer, (3) an organizer, (4) a resolver, and (5) a reporter. Each of these modules, using agent technology, autonomously cooperates and negotiates with others while processing its own jobs. The resulting architecture has a high degree of self-similarity, one of the main characteristics of a fractal. Despite the many conceptual advantages of the FrMS, it has not been successfully elaborated and implemented to date because of the difficulties involved in doing so. In this paper, the static functions and dynamic activities of each agent are modeled using the unified modeling language (UML). Then, relationships among agents, working mechanisms of each agent, and several fractal-specific characteristics (self-similarity, self-organization, and goal-orientation) are modeled using the UML. Then, a method for dealing with several types of information such as products, orders, and resources in the FrMS is presented. Finally, a preliminary prototype for the FrMS using AgletsTM is presented.

This paper addresses timing constraints' optimization for tasks in a single resource reserved by negotiation in agent-based distributed shop-floor scheduling. The proposed algorithm finds an optimal schedule that meets all the timing and other constraints, where timing constraints such as release times and deadlines are determined in advance through bidding-based production reservation. Even if the algorithm is terminated prematurely, it would still provide a complete schedule that is at least as good as any schedule currently obtained. Furthermore, it assists in managing unpredicted events by increasing marginal time space between the expected completion time of a task and its deadline.

For their timely response to the rapidly changing manufacturing environment and markets, future manufacturing systems must be flexible, adaptable, and reusable. Recently, bionic (or biological), holonic, and fractal manufacturing systems (FrMS) have been discussed as potential candidates for the next generation of manufacturing systems. This study focuses on the FrMS, which is based on the concept of autonomous cooperating agents referred to as fractals. The major component of the FrMS is a basic fractal unit (BFU). It consists of five functional modules: observing module (observer), analysing module (analyser), resolving and executing module (resolver), organizing module (organizer), and reporting module (reporter). Although the FrMS has many conceptual advantages, the implementation of the system has been known to be difficult. This paper is a preliminary study of the basic components and the architecture with an eye toward the future implementation of FrMS. In order to describe the characteristics of a...

In the rapidly changing manufacturing environment and marketplace of today, the selection and evaluation of an appropriate manufacturing policy is a vital issue. However, this is a difficult task for decision-makers because manufacturing objectives are multiple, complex, conflict and often vague. This paper presents a methodology for a satisfaction assessment of multi-objective schedules with results from a scheduling simulator. In addition, a general objective structure appropriate for multi-objective manufacturing scheduling is also proposed for use in satisfaction assessment methodologies. The general objective structure is a hierarchical structure of the scheduling objective that consists of a goal, subgoal and criteria. The assessment methodology was based on a neural network and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS), which is a common technique for multi-attribute decision-making problems. This paper extends TOPSIS by using fuzzy logic to deal with inaccurate and l...

Knowledge-based organizations (KBOs) such as universities, research institutes, and research centers at businesses and industries manage their projects in pursuit of the goals of their organizations. It is well understood that collaboration becomes one of the most important factors for successful completion of these projects. In performing a project jointly, it is important for project team members to know who has the required knowledge. Thus it is imperative to assess what and how much the employees know. Using a knowledge-based social network and its basic approach, a new method is proposed to analyze the knowledge and collaboration collectively possessed by the employees of a KBO. This study first deal with the methodologies of evaluating knowledge and collaboration possessed both by individuals and the organization. Since the quantitative evaluation is essential in developing a series of evaluating methods, the measures of knowledge and collaboration are derived. Then, the knowledge network types of KBO and the network roles of KBO members are discussed. Four types of knowledge-based social network and four roles of network members are also discussed respectively. An evaluation fuzzy model is proposed to test the feasibility of the knowledge-based social network and its measures. A case study is used to demonstrate effectiveness of the proposed model.

The 3D shape reconstruction of an object from its 2D cross-sections is important for reproducing it by NC machining or rapid prototyping, Although several different reconstruction methods have been proposed most of them have allowed only simple branching, or have had difficulty in handling complex branching structures. In this paper, a new method is presented for solving branching problems in surface reconstruction from a set of free-form contours in planar cross-sections. In this method, we decompose each multiple branching region into a set of single branching regions by providing a set of intermediary contours using modified distance maps. Then, each pair of contours in the single branching regions is linked with triangular facets to construct a piecewise triangular G 1 Bezier surface, An experimental result is given to show that our method gives reasonably good solutions for the representation of complex-shaped objects from planar contours.

The shape reconstruction of a 3D object from its 2D crosssections is important for reproducing it by NC machining or rapid prototyping. In this paper, we present a method of surface approximation to cross-sections with multiple branching problems. In this method, we first decompose each multiple branching problem into a set of single branching problems by providing a set of intermediate contours using distance maps. For each single branching region, a procedure then performs the skinning of contour curves represented by cubic B-spline curves on a common knot vector, each of which is fitted to its contour points within a given accuracy. In order to acquire a more compact representation for the surface, the method includes an algorithm for reducing the number of knots in the common knot vector. The approximation surface to the crosssections is represented by a set of bicubic B-spline surfaces. This method provides a smooth surface model, yet realises efficient data reduction.

As product life cycle becomes shortened, high product quality becomes necessary for survival, markets become highly diversified and global, and continuous and unexpected change becomes the key factor for success. The need for a method of rapidly and cost-effectively developing products, production facilities and supporting software including design, process planning, shop floor control systems is becoming urgent. The essence of this concept of manufacturing would be characterized by introducing a new term agility or rapidity. When compared with computer integrated manufacturing, agile manufacturing can be defined as the capability of surviving and prospering in a competitive environment of continuous and unpredictable change by reacting quickly and effectively to changing markets, driven by customer-designed products and services. Critical to successfully accomplishing agile manufacturing are a few enabling technologies such as the standard for the exchange of products (STEP), concurrent engineering, virtual manufacturing, component-based heterarchical shop floor control system information and communication infrastructure, etc. This article details key concepts of those enabling technologies and presents various activities related to agile manufacturing under development in Korea, especially an agile manufacturing test-bed at Pohang University of Science and Technology and a prototype of the life cycle engineering study of a product model made in a consumer electronic industry.

Vibration isolation of mechanical systems is achieved through either passive or active vibration control systems. Although a passive vibration isolation system offers simple and reliable means to protect mechanical systems from a vibration environment, it has inherent performance limitations, that is, its controllable frequency range is limited and the shape of its transmissibility does not change. Recently, in some applications, such as active suspensions or precise vibration systems, active vibration isolation systems have been employed to overcome the limitations of the passive systems. In this paper, a hybrid-type active vibration isolation system that uses electromagnetic and pneumatic force is developed, and a new control algorithm adopting neural networks is proposed. The characteristics of the hybrid system proposed in the paper were investigated via computer simulation and experiments. It was shown that the transmissibility of the vibration isolation system could be kept below 0.63 over the entire frequency range, including the resonance frequency.

A new methodology for interfacing Computer-Aided Design (CAD) and Computer-Aided Process Planning (CAPP) based on automatic feature recognition is proposed in the domain of complex rotationally symmetric parts. The interface system consists of three stages: (1) Initial Graphics Exchange Specification (1GES) data translation, (2) polygonal decomposition or splitting, (3) automatic recognition of precedences and features. In the data translation stage, 1GES data are transformed to multi-sectional chains of the upperhalf profile of a part and a raw stock. For the raw stock, not only a box shape but the non-rectangular one is also considered. In the polygonal decomposition stage, the removal volume is decomposed into a data structure of a Pseudo-polygon (Pgon). The Pgon data structure based on the surface classification (real, virtual, partial, and embedded) is suggested as a new feature representation scheme. In the automatic recognition stage, the geometric precedence relationship between Pgons, is...

An integrated precision inspection system has been developed for manufacturing moulds having CAD defined features. The techniques of precision measurement are implemented for CAD/CAI integration for moulds having sculptured surfaces with some basic features, such as, holes, slots and bosses. Features to be inspected are chosen in the CAD environment, and inspection planning is performed for each feature. The sampling-point strategies are: uniform distribution, curvature dependent distribution, or hybrid distribution of the two depending on the complexity of the sculptured surface. Line and plane features are divided into subintervals, and the measurement points are distributed at random positions in the subinterval. Prime number subintervals are considered for a circle feature, in order to avoid possible periodic distortion of the measurement features. The measurement path planning is performed considering collision avoidance and coordinate matching between the coordinates. The output of the planning is the machine code for a specific CMM having CNC capability. The machine code is downloaded to a specific CMM, and the measurement results are fed back to the computer. A new algorithm, called MINIMAXSURF, is developed to evaluate the form error precisely for sculptured surfaces. The algorithm considers the radius of the touch probe and evaluates the profile tolerance successfully by removing the unavoidable setup errors. The developed measurement system has been applied to real moulds, demonstrating high performance and accuracy.

This paper presents a new methodology for flexible process sequencing using a Petri net based approach. In the proposed approach Petri nets are used as a unified framework for representing both operation planning knowledge and process sequence. In specific, the approach taken comprises: (1) modeling operation selection and sequencing knowledge using a Petri net based approach, (2) representing the flexible sequence of operations using Petri net formalism, and (3) linearizing a flexible process sequence using T-INVARIANT analysis. An illustrative example of HoleMakingProcess has been used to demonstrate the Petri net modeling, the operation selection and sequencing procedure (called state propagation procedure), and the linearization procedure.