A manufacturing systems modelling using system dynamics:forming a dedicated modelling tool

Discrete event simulation is a popular aid for manufacturing system design; however in application this technique can sometimes be unnecessarily complex. This paper is concerned with applying an alternative technique to manufacturing system design which may well provide an efficient form of rough-cut analysis. This technique is System Dynamics, and the work described in this paper has set about incorporating the principles of this technique into a computer based modelling tool that is tailored to manufacturing system design. This paper is structured to first explore the principles of System Dynamics and how they differ from Discrete Event Simulation. The opportunity for System Dynamics is then explored, and this leads to defining the capabilities that a suitable tool would need. This specification is then transformed into a computer modelling tool, which is then assessed by applying this tool to model an engine production facility. Read More: http://www.worldscientific.com/doi/abs/10.1142/S0219686703000228

Automatic summary assessment for intelligent tutoring systems

Summary writing is an important part of many English Language Examinations. As grading students' summary writings is a very time-consuming task, computer-assisted assessment will help teachers carry out the grading more effectively. Several techniques such as latent semantic analysis (LSA), n-gram co-occurrence and BLEU have been proposed to support automatic evaluation of summaries. However, their performance is not satisfactory for assessing summary writings. To improve the performance, this paper proposes an ensemble approach that integrates LSA and n-gram co-occurrence. As a result, the proposed ensemble approach is able to achieve high accuracy and improve the performance quite substantially compared with current techniques. A summary assessment system based on the proposed approach has also been developed.

Analogical Reasoning Techniques in Intelligent Counterterrorism Systems

The paper develops a set of ideas and techniques supporting analogical reasoning throughout the life-cycle of terrorist acts. Implementation of these ideas and techniques can enhance the intellectual level of computer-based systems for a wide range of personnel dealing with various aspects of the problem of terrorism and its effects. The method combines techniques of structure-sensitive distributed representations in the framework of Associative-Projective Neural Networks, and knowledge obtained through the progress in analogical reasoning, in particular the Structure Mapping Theory. The impact of these analogical reasoning tools on the efforts to minimize the effects of terrorist acts on civilian population is expected by facilitating knowledge acquisition and formation of terrorism-related knowledge bases, as well as supporting the processes of analysis, decision making, and reasoning with those knowledge bases for users at various levels of expertise before, during, and after terrorist acts.

Knowledge Learning Technology for Intelligent Tutoring Systems

In this work we suggest the technology of creation of intelligent tutoring systems which are oriented to teach knowledge. It is supposed the acquisition of expert’s knowledge by using of the Formal Concept Analysis method, then construction the test questions which are used for verification of the pupil's knowledge with the expert’s knowledge. Then the further tutoring strategy is generated by the results of this verification.

Analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing

Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others.

Analytical Approximations to Predict Performance Measures of Manufacturing Systems with Job Failures and Parallel Processing

Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others.

Comparing architectural styles for distributed expert knowledge modules in intelligent tutoring systems

Intelligent Tutoring Systems (ITSs) are computerized systems for learning-by-doing. These systems provide students with immediate and customized feedback on learning tasks. An ITS typically consists of several modules that are connected to each other. This research focuses on the distribution of the ITS module that provides expert knowledge services. For the distribution of such an expert knowledge module we need to use an architectural style because this gives a standard interface, which increases the reusability and operability of the expert knowledge module. To provide expert knowledge modules in a distributed way we need to answer the research question: ‘How can we compare and evaluate REST, Web services and Plug-in architectural styles for the distribution of the expert knowledge module in an intelligent tutoring system?’. We present an assessment method for selecting an architectural style. Using the assessment method on three architectural styles, we selected the REST architectural style as the style that best supports the distribution of expert knowledge modules. With this assessment method we also analyzed the trade-offs that come with selecting REST. We present a prototype and architectural views based on REST to demonstrate that the assessment method correctly scores REST as an appropriate architectural style for the distribution of expert knowledge modules.

FY2010 Annual Report Research, Intelligent Transportation Systems, and Technology Transfer Activities, October 18, 2011

Transportation research makes a difference for Iowans and the nation. Implementation of cost effective research projects contributes to a transportation network that is safer, more efficient, and longer lasting. Working in cooperation with our partners from universities, industry, other states, and FHWA, as well as participation in the Transportation Research Board (TRB), provides benefits for every facet of the DOT. This allows us to serve our communities and the traveling public more effectively. Pooled fund projects allow leveraging of funds for higher returns on investments. In 2010, Iowa led fifteen active pooled fund studies, participated in twenty-two others, and was wrapping-up, reconciling, and closing out an additional 6 Iowa Led pooled fund studies. In addition, non-pooled fund SPR projects included approximately 20 continued, 9 new, and over a dozen reoccurring initiatives such as the technical transfer/training program. Additional research is managed and conducted by the Office of Traffic and Safety and other departments in the Iowa DOT.