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215results about How to "Lightweight production" patented technology

Method of producing, selling, and distributing articles of manufacture

A method of selling articles of manufacture which utilizes an electronic communication system to identify a plurality of articles of manufacture, from a plurality of manufacturing entities, which are available for purchase by said plurality of potential purchasers. The steps of the method include: Identifying pricing milestones in each of (1) a manufacturing phase and (2) a distribution phase, which correspond to an increase in commercial risk. Determining a separate price for each of said pricing milestones to establish a range of prices for said selected ones of said plurality of articles of manufacture, taking into account a change in said commercial risk as said pricing milestones are experienced. Making conditional offers for sale to potential purchasers at each of the pricing milestones, with the conditional offers specifying at least a minimum number of articles which must be ordered in aggregate before the conditional offer becomes binding upon a manufacturing entity. Communicating with potential purchasers and aggregating commercial commitments from potential purchasers for each pricing milestones and thereby selling articles of manufacture. Such that each pricing milestone corresponds to a period of availability in which costs of future supply chain activities or savings related to avoidance of future supply chain activities are reflected in an offer price. The method may also include the use of a trusted intermediary, which may use a virtual exchange.
Owner:LAKESOUTH HLDG LLC

Intelligent electronically-controlled suspension system based on soft computing optimizer

InactiveUS20060293817A1Near-optimal FNNMaximises informationDigital data processing detailsAnimal undercarriagesInput/outputSoft computing
A Soft Computing (SC) optimizer for designing a Knowledge Base (KB) to be used in a control system for controlling a suspension system is described. The SC optimizer includes a fuzzy inference engine based on a Fuzzy Neural Network (FNN). The SC Optimizer provides Fuzzy Inference System (FIS) structure selection, FIS structure optimization method selection, and teaching signal selection and generation. The user selects a fuzzy model, including one or more of: the number of input and/or output variables; the type of fuzzy inference model (e.g., Mamdani, Sugeno, Tsukamoto, etc.); and the preliminary type of membership functions. A Genetic Algorithm (GA) is used to optimize linguistic variable parameters and the input-output training patterns. A GA is also used to optimize the rule base, using the fuzzy model, optimal linguistic variable parameters, and a teaching signal. The GA produces a near-optimal FNN. The near-optimal FNN can be improved using classical derivative-based optimization procedures. The FIS structure found by the GA is optimized with a fitness function based on a response of the actual suspension system model of the controlled suspension system. The SC optimizer produces a robust KB that is typically smaller that the KB produced by prior art methods.
Owner:YAMAHA MOTOR CO LTD
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