Hyunbo Cho

Graph-theoretic deadlock detection and resolution for flexible manufacturing systems

Flexible manufacturing systems are capable of producing a broad variety of products and changing their characteristics quickly and frequently. This flexibility provides for more efficient use of resources, but makes control of these systems more difficult. Control problems previously unstudied now require practical resolution, like system deadlock. A system deadlock is a situation that arises due to resource sharing in manufacturing systems, when the flow of parts is permanently inhibited and/or operations on parts cannot be performed. This problem has been ignored by most scheduling and control studies, which usually assume infinite machine queue capacity and unlimited tooling resources. FMSs, however, have little or no queue capacity and limited tooling resources. In this paper, graph-theoretic deadlock detection and resolution procedures are presented which are suitable for real-time control of manufacturing systems. These procedures determine whether part movement in the system causes system deadlock or not. To this end, a system status graph representing part routings is virtually updated for every part movement before parts move physically to the next destination. Two types of system deadlocks, part flow deadlock and impending part flow deadlock, are detected using the updated system status graph. If a deadlock detection and recovery method is used to recover from a deadlock using a storage buffer, only part flow deadlocks need to be detected. On the other hand, if no buffer is available, both types of existing as well as impending system deadlocks need to be detected to avoid a deadlock situation. >

Enabling technologies of agile manufacturing and its related activities in Korea

Abstract 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.

A novel method for measuring semantic similarity for XML schema matching

Enterprises integration has recently gained great attentions, as never before. The paper deals with an essential activity enabling seamless enterprises integration, that is, a similarity-based schema matching. To this end, we present a supervised approach to measure semantic similarity between XML schema documents, and, more importantly, address a novel approach to augment reliably labeled training data from a given few labeled samples in a semi-supervised manner. Experimental results reveal the proposed method is very cost-efficient and reliably predicts semantic similarity.

Intelligent workstation controller for computer-integrated manufacturing: Problems and models

Abstract A shop floor control system (SFCS), an integrated part of computer-integrated manufacturing, oversees the production required to fill orders. To effectively control these activities, it is necessary to define a control architecture and functional perspective of how a SFCS operates. In this paper, a hierarchical SFCS (shop, workstation, equipment) is adopted. The paper presents the problems and models necessary to develop an intelligent workstation controller (IWC) at the middle level of a SFCS. The IWC is responsible for selecting a specific process routing, allocating resources, scheduling and coordinating activities across the equipment, monitoring the progress of activities, detecting and recovering from errors, and preparing reports. The IWC fulfills this responsibility using three functions—planning, scheduling, and execution. Requirements for the development of the IWC are to create a process plan representation model, specify the evolution of a process plan from the shop down to the equipment, and define all of the functions to be integrated into an intelligent controller. A deadlock detection and resolution model is also presented to maintain the system in a deadlock-free state. Finally, the IWC software is created to demonstrate the architectural linkages with other controllers. As a result, the development of the IWC will save cost and time in developing control software for automated manufacturing systems.

Improving memory-based collaborative filtering via similarity updating and prediction modulation

Memory-based collaborative filtering (CF) makes recommendations based on a collection of user preferences for items. The idea underlying this approach is that the interests of an active user will more likely coincide with those of users who share similar preferences to the active user. Hence, the choice and computation of a similarity measure between users is critical to rating items. This work proposes a similarity update method that uses an iterative message passing procedure. Additionally, this work deals with a drawback of using the popular mean absolute error (MAE) for performance evaluation, namely that ignores ratings distribution. A novel modulation method and an accuracy metric are presented in order to minimize the predictive accuracy error and to evenly distribute predicted ratings over true rating scales. Preliminary results show that the proposed similarity update and prediction modulation techniques significantly improve the predicted rankings.

On the functional quality of service (FQoS) to discover and compose interoperable web services

Despite its prevalence, the service-oriented architecture (SOA) still has an imperative challenge to achieve interoperability within and across enterprise applications. Minimal conditions for interoperability are: (1) to discover and plug in proper services for integration and (2) to support for seamless data exchanges between component services. A similarity-based approximate matching is a practical approach for both, in that the service discovery relies on functional matches between a query and service descriptions, and the seamless data exchange is granted by mapping information from a service to others. To these ends, this paper comprehensively investigates functional attributes of web services and their manipulation, and particularly highlights an information compatibility and mapping analysis. The functional quality of service (FQoS) allows service discovery and selection to step forward. Simulation results show that the present FQoS metrics are effective in service discovery.

An iterative semi-explicit rating method for building collaborative recommender systems

Collaborative filtering plays the key role in recent recommender systems. It uses a user-item preference matrix rated either explicitly (i.e., explicit rating) or implicitly (i.e., implicit feedback). Despite the explicit rating captures the preferences better, it often results in a severely sparse matrix. The paper presents a novel iterative semi-explicit rating method that extrapolates unrated elements in a semi-supervised manner. Extrapolation is simply an aggregation of neighbor ratings, and iterative extrapolations result in a dense preference matrix. Preliminary simulation results show that the recommendation using the semi-explicit rating data outperforms that of using the pure explicit data only.

Hybrid algorithm for discrete event simulation based supply chain optimization

Supply chain optimization, as a key determinant of strategic resources mobility along the value-added chain, allows each participant in the global network to capitalize on its particular strategic competency. Simulation is widely used to test the impact on supply chain performance for the strategic level decisions, such as the number of plants, the modes of transport, or the relocation of warehouses. However, the complexity of supply chain optimization problem and the stochastic nature of simulation cause the unaffordable computational load; the evaluation of a large number of alternatives for supply chain optimization is in a class of NP-hard problem and the number of simulation replications is required for accurately evaluating the performance of each alternative. The objective of the present work is to propose hybrid algorithm with the application of the nested partitioning (NP) method and the optimal computing budget allocation (OCBA) method to reduce the computational load, hence, to improve the efficiency of supply chain optimization via discrete event simulation. The NP method is a global sampling strategy that is continuously adapted via a partitioning of the feasible solution region. The number of candidate alternatives to be evaluated can be reduced by the application of NP. The OCBA method minimizes the number of samples (simulation replications) required to evaluate a particular alternative by allocating computing resources to potentially critical alternative. Carefully designed experiments show extensive numerical result to illustrate the benefits of the proposed approach.

Discovering and integrating distributed manufacturing services with semantic manufacturing capability profiles

Integrating distributed manufacturing systems is a longstanding dream of industrial engineers. The advent of internet technologies has provided opportunities to fulfill this dream, and has presented new challenges to overcome. Since most current internet technologies (e.g. SOA, web service) originated in business applications, it is difficult to apply them directly to manufacturing systems. The difficulties stem particularly from differences in meaning and usage of manufacturing terms and an inability to express semantic information about manufacturing services. The present paper aims to extend the universal description, discovery, and integration (UDDI) registry specification to include semantic descriptions about manufacturing services and to support reasoning of those descriptions for service discovery. Specifically, we provide OWL-based definitions for manufacturing service capability profiles and a description logic (DL)-based reasoning procedure for matching queries to service descriptions. An illustrative process is presented with a prototype implementation for a discrete part manufacturing case.

Development of a saw gas sensor for monitoring so2 gas

Abstract We have developed a new type of SO 2 gas sensor by applying a particular inorganic thin film on SAW (surface acoustic wave) devices. The sensor consists of twin SAW oscillators with a centre frequency of 54 MHz fabricated on LiTaO 3 piezoelectric single crystals. One delay line of the sensor is coated with a CdS thin film that selectively adsorbs and desorbs SO 2 , while the other is uncoated for use as a stable reference. Deposition of CdS thin film has been carried out by the spray pyrolysis method using an ultrasonic nozzle. Mass loading and electric-field changes induced by the SO 2 gas adsorbed onto the CdS film result in corresponding frequency shifts directly proportional to the gas concentration. The relative change in the frequency of the two oscillators is monitored with a digital signal-processing circuit. SO 2 sensor properties investigated include sensitivity, response time and repeatability. The sensor shows promising performance as a microsensing tool and is capable of measuring concentrations in air less than 200 parts per billion of SO 2 .