888 resultados para Medical instruments and apparatus
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Mode of access: Internet.
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Mode of access: Internet.
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"October 1979."
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Current technology trends in medical device industry calls for fabrication of massive arrays of microfeatures such as microchannels on to nonsilicon material substrates with high accuracy, superior precision, and high throughput. Microchannels are typical features used in medical devices for medication dosing into the human body, analyzing DNA arrays or cell cultures. In this study, the capabilities of machining systems for micro-end milling have been evaluated by conducting experiments, regression modeling, and response surface methodology. In machining experiments by using micromilling, arrays of microchannels are fabricated on aluminium and titanium plates, and the feature size and accuracy (width and depth) and surface roughness are measured. Multicriteria decision making for material and process parameters selection for desired accuracy is investigated by using particle swarm optimization (PSO) method, which is an evolutionary computation method inspired by genetic algorithms (GA). Appropriate regression models are utilized within the PSO and optimum selection of micromilling parameters; microchannel feature accuracy and surface roughness are performed. An analysis for optimal micromachining parameters in decision variable space is also conducted. This study demonstrates the advantages of evolutionary computing algorithms in micromilling decision making and process optimization investigations and can be expanded to other applications
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Section "A": Dissecting and Post-Mortem Instruments Diagnostic Instruments and Apparatus Microscopes and Microscopic Accessories Laboratory Apparatus and Glass Ware Apparatus for Blood and Urine Analysis Apparatus for Phlebotomy, Cupping and Leeching Apparatus for Infusion and Transfusion Syringes for Aspiration and Injection Osteological Preparations Section "B": Anaesthetic, General Operating, Osteotomy, Trepanning, Bullet, Pocket Case, Cautery, Ligatures, Sutures, Dressings, Etc. Section "B" continued Section "C": Eye, Ear, Nasal, Dermal, Oral, Tonsil, Tracheal, Laryngeal,Esophageal, Stomach, Intestinal, Gall Bladder Section "C": continued Section "D": Rectal, Phimosis, Prostatic, Vesical, Urethral, Ureteral, Instruments Section "E": Gynecic, Hysterectomy, Obstetrical, Instrument Satchels, Medicine Cases Section "F": Electric Cautery Transformers, Electro-Cautery Burners and Accessories, Electric Current Controllers, Electro-Diagnostic Outfits, Electrolysis Instruments Electro-Therapeutic Lamps, Faradic Batteries, Galvanic Batteries Section "G": Office Furniture, Office Sterilizing Apparatus, Hospital Supplies, Surgical Rubber Goods, Sick Room Utensils, Invalid Rolling Chairs, Invalid Supplies Section "H": Artificial Limbs, Deformity Apparatus, Fracture Apparatus, Splints, Splint Material, Elastic Hosiery, Abdominal Supporters, Crutches, Trusses, Suspensories, Etc. Index
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Item 215
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"December 1989."
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"September 1987."
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The paper discusses maintenance challenges of organisations with a huge number of devices and proposes the use of probabilistic models to assist monitoring and maintenance planning. The proposal assumes connectivity of instruments to report relevant features for monitoring. Also, the existence of enough historical registers with diagnosed breakdowns is required to make probabilistic models reliable and useful for predictive maintenance strategies based on them. Regular Markov models based on estimated failure and repair rates are proposed to calculate the availability of the instruments and Dynamic Bayesian Networks are proposed to model cause-effect relationships to trigger predictive maintenance services based on the influence between observed features and previously documented diagnostics
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The paper discusses maintenance challenges of organisations with a huge number of devices and proposes the use of probabilistic models to assist monitoring and maintenance planning. The proposal assumes connectivity of instruments to report relevant features for monitoring. Also, the existence of enough historical registers with diagnosed breakdowns is required to make probabilistic models reliable and useful for predictive maintenance strategies based on them. Regular Markov models based on estimated failure and repair rates are proposed to calculate the availability of the instruments and Dynamic Bayesian Networks are proposed to model cause-effect relationships to trigger predictive maintenance services based on the influence between observed features and previously documented diagnostics
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Cover title.
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Loose-leaf for updating.
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Pós-graduação em Enfermagem (mestrado profissional) - FMB
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Mode of access: Internet.
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Mode of access: Internet.