Kinetic effects in strong Langmuir turbulence

Kinetic effects with regard to a one dimensional Langmuir soliton-like pulse are investigated. Though thus far mainly transit-time accelerations have been investigated regarding strong Langmuir turbulence, it is found that ponderomotive reflections (generalized nonlinear Landau damping) may play important roles also. The former may diffuse fast electrons up to relativistic energies, while the latter reflects slow electrons as well as ions that have speeds comparable with the group velocity of the pulse, and tend to form flat-top electron distributions at and around the quasi-soliton.Comment: 12th International Congress on Plasma Physics, 25-29 October 2004, Nice (France

Conformational Switching in Self-Assembling Mechanical Systems

A study of 1D self-assembly of a type of mechanical conformational switches, minus devices is presented where assembly occurs via the sequential mating of a random pair of parts selected from a part bin, referred to as sequential random bin-picking. The minus devices facilitate the robust yield of a desired assembly against the variation in the initial fraction of the part types, by specifying a fixed assembly sequence during the self-assembling process. It is also found that while the minus devices can encode" some assembly sequences, encoding other assembly sequences requires the use of another type of conformational switches, plus devices. It is proved that the local rules corresponding to the minus and plus devices, and three conformations per each component, can encode any assembly sequences of a 1D assembly of distinct components with arbitrary lengthPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87253/4/Saitou44.pd

Adapting Product and Supply Chain Systems under Severe Uncertainty

Currently, adaptation in a virtual enterprise is mostly reactive in response to variations that have already occurred. In order to remain profitable in the highly competitive global market, it is highly desirable to proactively adapt in anticipation of unplanned, but foreseeable high impact events, while still maintaining competitive product quality, cost, and lead-time. This paper approaches the problem by developing a unified model of product-supply chain systems based on networks of design-supplier pairs, and decision models of adaptation in the event of a jump based on real options theory. Application to a single component, single echelon supply chain is discussed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87248/4/Saitou59.pd

Multi-Period Production Capacity Planning for Integrated Product and Production System Design

This paper presents a simulation-based method to aid multi-period production capacity planning by quantifying the trade-off between product quality and production cost. The product quality is estimated as the statistical variation from the target performances obtained from the output tolerances of the production machines that manufacture the components. The production cost is estimated as the total cost of owning and operating a production facility during the planning horizon. Given demand forecasts in future production periods, a multi-objective genetic algorithm searches for the optimal types and quantity of the production machines to be purchased during each period, which simultaneously maximize the product quality and minimize the production cost during the entire planning horizon. Case studies on automotive valvetrain production are presented as a demonstrationPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87270/4/Saitou68.pd

Design for product-embedded disassembly pathways

This paper presents a computational method for designing an assembly with multiple built-in disassembly pathways, each of which can be activated to retrieve certain components. It is motivated by the global sales of consumer products whose optimal end-of-life options vary geographically due to local recycling/reuse infrastructures and regulatory requirements. Given the sets of components to be retrieved at each location, the method simultaneously determines the spatial configurations of components and locator features, such that each set of desired components is retrieved via a domino-like self-disassembly" process triggered by the removal of a fastener. A multi-objective generic algorithm is utilized to search for Pareto-optimal designs in terms of the realization of the desired disassembly pathways, the satisfaction of distance specifications among components, the minimization of disassembly cost at each location, and the efficient use of on-component locator features. A case study demonstrates the feasibility of the method.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87258/4/Saitou77.pd

Off-Line Error Prediction, Diagnosis and Recovery Using Virtual Assembly Systems

Automated assembly systems often stop their operation due to the unexpected failures occurred during their assembly process. Since these large-scale systems are composed of many parameters, it is difficult to anticipate all possible types of errors with their likelihood of occurrence. Several systems were developed in the literature, focusing on online diagnosing and recovering the assembly process in an intelligent manner based on the predicted error scenarios. However, these systems do not cover all of the possible errors and they are deficient in dealing with the unexpected error situations. The proposed approach uses Monte Carlo simulation of the assembly process with the 3D model of the assembly line to predict the possible errors in an offline manner. After that, these predicted errors can be diagnosed and recovered using Bayesian reasoning and genetic programming. A case study composed of a peg-in-hole assembly was performed and the results are discussed. It is expected that with this new approach, errors can be diagnosed and recovered accurately and costly downtime of robotic assembly systems will be reduced.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87271/4/Saitou102.pd

Conformational switching in self-assembling mechnical systems : theory and application

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1996.Includes bibliographical references (p. 170-174).by Kazuhiro Saitou.Ph.D

Image-based Automated Chemical Database Annotation with Ensemble of Machine-Vision Classifiers

This paper presents an image-based annotation strategy for automated annotation of chemical databases. The proposed strategy is based on the use of a machine vision-based classifier for extracting a 2D chemical structure diagram in research articles and converting them into standard chemical file formats, a virtual Chemical Expert" system for screening the converted structures based on the level of estimated conversion accuracy, and a fragment-based measure for calculation intermolecular similarity. In particular, in order to overcome limited accuracies of individual machine-vision classifier, inspired by ensemble methods in machine learning, it is attempted to use of the ensemble of machine-vision classifiers. For annotation, calculated chemical similarity between the converted structures and entries in a virtual small molecule database is used to establish the links. Annotation test to link 121 journal articles to entries in PubChem database demonstrates that ensemble approach increases the coverage of annotation, while keeping the annotation quality (e.g., recall and precision rates) comparable to using a single machine-vision classifier.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87266/4/Saitou55.pd