Distributed Artificial Intelligence in manufacturing systems control

This research uses a Distributed Artificial Intelligence (DAI) framework to efficiently utilize the infrastructure available for process planning in a batch processing PWB assembly facility. The DAI approach decomposes the entire production control task into several sub-tasks. Then, the sub-tasks are implemented by the basic elements of the DAI system called ‘intelligent agents’. By working collectively, the intelligent agents of the DAI system can arrive at a solution for the problem. The DAI system initially proposes all possible solutions generated by the intelligent agents. Then, a fuzzy coordination technique is utilized to evaluate the solutions and to find the most appropriate one for shopfloor implementation. Using inputs such as the short-term production plan, design data, shopfloor observation data, and CAD information, the DAI system provides applicable production plans with ranks for the feasibility of current assembly activities.     

Simulation based alternatives for overall process improvement at the cardiac catheterization lab

Cardiac catheterization is one of the critical procedures in patient care. It is pertinent for all process related issues in this department to be handled with due priority. This research is a cross-functional effort with a leading hospital that was in its planning stage to implement an overall process improvement at its cardiac catheterization lab department. It has been determined that significant process delays exist in this department. One of the identified key factors to process improvement was to reduce patient turnaround time. Process mapping was used to study the system and identify potential sources of delays in the system. A set of qualitative recommendations were put forward. These recommendations, include the reduction of wait time of outpatients and inpatients and the reduction of non-value-added times such as transfer time of patients, were evaluated using a discrete event simulation approach. The simulation study shows that the daily operating hours at the catheterization lab could be reduced, aiding to reallocate staff for discharging other duties, as the hospital may require.     

Automated process planning method to machine A B-Spline free-form feature on a mill–turn center

In this paper, we present a methodology for automating the process planning and NC code generation for a widely encountered class of free-form features that can be machined on a 3-axis mill–turn center. The free-form feature family that is considered is that of extruded protrusions whose cross-section is a closed, periodic B-Spline curve. In this methodology, for machining a part with B-Spline protrusion located at the free end, the part is first rough turned to the maximum profile diameter of the B-Spline, followed by rough profile cutting and finish profiling with axially mounted end mill tools. The identification and sequencing of machining volumes is completely automated, as is the generation of actual NC code. The approach supports both convex and non-convex profiles. In the case of non-convex profiles, the process planning algorithm ensures that there is no gouging of the work piece by the tool. The algorithm also identifies when sections of the tool path lie outside the work piece and utilizes rapid traverses in these regions to reduce cutting time. This methodology presents an integrated turn–mill process planning where by making the process fully automated from design with no user intervention making the overall process planning efficient. The algorithm was tested on several examples and test parts using the unmodified NC code obtained from the implementation were run on a Moriseiki mill–turn center. The parts that were produced met the dimensional specifications of the desired part.     

An integrated algorithm for text recognition: comparison with a cascaded algorithm

The use of diverse knowledge sources in text recognition and in correction of letter substitution errors in words of text is considered. Three knowledge sources are defined: channel characteristics as probabilities that observed letters are corruptions of other letters, bottom-up context as letter conditional probabilities (when the previous letters of the word are known), and top-down context as a lexicon. Two algorithms, one based on integrating the knowledge sources in a single step and the other based on sequentially cascading bottom-up and top-down processes, are compared in terms of computational/storage requirements and results of experimentation.     

Experiments in Text Recognition with Binary n-Gram and Viterbi Algorithms

The binary n-gram and Viterbi algorithms have been suggested as alternative approaches to contextual postprocessing for text produced by a noisy channel such as an optical character recognizer. This correspondence describes the underlying theory of each approach in unified terminology, and presents new implementation algorithms for each approach. In particular, a storage efficient data structure is proposed for the binary n-gram algorithm and a recursive formulation is given for the Viterbi algorithm. Results of extensive experiments with each algorithm are described.     

Boundary detection in multidimensions

The development of image processing algorithms for time-varying imagery and computerized tomography data calls for generalization of the concepts of adjacency, connectivity, boundary, etc., to three and four-dimensional discrete spaces. This paper defines these basic concepts in unified terminology and presents algorithms for a boundary detection task in multidimensional space. The performance of these algorithms is discussed with respect to theoretical maximum complexity, and is illustrated with simulated computerized tomography data.     

Document image-processing system for name and address recognition

This article describes a real-time document image processing system. Its objective is to recognize names and addresses from scanned address block images extracted from various tax forms of the United States Internal Revenue Service. The Name and Address Block Reader (NABR) system accepts both machine- and hand-printed address block images as input. Salient aspects of the system are presented, including document analysis (connected component analysis, address block extraction, label detection, hand-print/machine-print discrimination) and document recognition. Document recognition is performed in two nonidentical streams for machine-and hand-print; key steps are address parsing, character recognition, word recognition, and postal data base lookup (ZIP+4 and city-state-ZIP files). System output is a packet containing the results of recognition together with data base access status file. Real-time throughput (8500 forms/h) is achieved by employing a loosely coupled multiprocessing architecture where successive input images are distributed to available address recognition processors. The functional architecture, software design, system architecture, and the hardware implementation are described. Performance evaluation on machine- and hand-written addresses are presented. © 1996 John Wiley & Sons, Inc.     

Postal address reading in real time

In 1994, the U.S. Postal Service (USPS) delivered 177 billion pieces of mail to 125 million delivery addresses. To assist in processing this large volume of mail, USPS and the Center for Document Analysis and Recognition (CEDAR) have been exploring automation methods for processing letter mail with handwritten addresses. The CEDAR system for locating and reading destination address blocks on letter mail pieces operates at real-time rates. The system architecture uses a variety of pipelining and multiprocessor techniques to achieve the required processing speed and minimize latency. Image processing operations are performed using specialized hardware operating at 103 ns/pixel. This hardware includes CCITT Group 3 (FAX) decompression, image enhancement, and conversion of the image representation from pixel-based representation to symbolic representation. This symbolic representation of the image can be processed in real time using software running on general-purpose processors. This software performs the address block location (ABL), handwritten address interpretation (HWAI), and data base querying needed to determine the delivery point of the mail piece. The current system can correctly locate and produce a five-digit ZIP code with an accuracy of 66% on a test set of 1566 handwritten mail pieces. A unique delivery point (e.g., ZIP + 4 code) can be determined on these same mail pieces 26% of the time. © 1996 John Wiley & Sons, Inc.     

Reading handwritten phrases on U.S. census forms

Commercial form-reading systems for extraction of data from forms do not meet acceptable accuracy requirements on forms filled out by hand. Several important form-processing applications involve the automated reading of handwritten responses. U.S. Census forms are a case in point. A database of form images containing actual responses received by the U.S. Census Bureau was made available by National Institute of Standards and Technology (NIST) in December 1993. A number of factors combine to make the task of reading these forms a challenging one. The quality of form images is often poor, and the handwritten responses are very loosely constrained in terms of writing style, format of response, and choice of text. The sizes of the lexicons provided are large (10,000-50,000 entries) and yet the coverage is incomplete (60%-70%). In this article we discuss our approach to automate the task of reading the census forms. The subtasks of field extraction and phrase recognition are described and multiclassifier control strategies for phrase recognition are presented. The error rate of the system when no rejects are allowed is 59%, with a lower bound of 40% being imposed by the incomplete coverage of the lexicon. The article concludes with a discussion of experimental results and directions for future research. © 1996 John Wiley & Sons, Inc.     

Evidence of low-symmetry phases in pressure-dependent Raman spectroscopic study of BaTiO<Subscript>3</Subscript>

In the earlier pressure-dependent Raman spectroscopic studies, it has been reported that BaTiO₃ undergoes a tetragonal to cubic phase transition above ~ 2 GPa, whereas pressure-dependent X-ray absorption, X-ray diffuse scattering studies and pair distribution function studies have reported the presence of a low-symmetry rhombohedral phase above ~ 2.3 GPa. In this report, we present our pressure-dependent Raman spectroscopic studies on polycrystalline BaTiO₃ which shows that it first undergoes a transition from tetragonal to orthorhombic/rhombohedral phase above ~ 2.6 GPa and then finally goes to the cubic phase above 8.4 GPa. Pressure-dependent synchrotron X-ray diffraction (SXRD) studies have also been carried out that provided rate of change of volume as a function of pressure resulting in bulk modulus of 215 ± 9 GPa.