Application of Neural Networks to Evaluate Factors Affecting Drilling Performance

Achieving the highest Rate of Penetration (ROP) with the least possible Bit Tooth Wear Rate (BTWR) is the aim of every drilling engineer when selecting a drilling bit. Predicting the optimal ROP has become increasingly important given the rise in expenses involved in drilling a well. This has meant that oil companies engage in a perpetual struggle to predict the optimum rock mechanical property parameters. Predicting optimal rock mechanical property parameters, specifically Rate of Penetration (ROP), has become increasingly important given the rise in expenses involved in drilling a well. The prediction of ROP from the current available data is an important criterion for reduction of drilling costs. ROP represents rock bit interaction which relates rock compressive strength and bit aggressivity. ROP prediction is complex because of the numerous variables which lead to difficulties in evaluating drilling parameters. Several models and methods have been published for predicting, and therefore potentially optimizing rate of penetration. However, these models and methods have limitations, too many variables are included, their input parameters are often not readily available, and their relationships are complex and not easily modeled. Therefore, the application of Neural Network is suggested in this study. A new methodology has been developed to predict the rate of penetration using the Artificial Neural Network (ANN). Three case studies representing different formations in Kuwait have been conducted to investigate ROP prediction for various applications. These cases have investigated the prediction of ROP for a specific heterogeneous formation (CASE I); a semihomogenous formation (CASE II); a drilling section composed of a heterogeneous formation and for a drilling section composed of a complex heterogeneous set of formations (CASE III). Predicting ROP parameters is of particular interest, therefore finding a new method to predict ROP for the cases investigated in this study will be a valuable achievement. Application of the new network models would then be used for selecting the best parameters for an optimal drilling strategy based on field data. In addition to the prediction of ROP, several runs were carried out to predict Tooth Wear Rate (TWR) for a drilling section in case III. Rock bit interactions in the field as a function of rock mechanical property parameters was achieved by predicting ROP which relates to rock compressive strength and bit aggressivity; as well as TWR which relates to rock abrasiveness and wear resistance. History of bit runs, mud logging data, geological information, offset well bit records, drill bit characteristics, and wireline data all play an important role in the prediction of rock bit interactions in this study. Based on field data, the prediction of rock mechanical property parameters can be accomplished by the use of a neural network as an alternative prediction and optimization method. Neural network offers a new form of information processing that is fundamentally different from a traditional processing system. The system uses a knowledge base of various drilling parameters, to produce a “correlation” description of the optimal Rate of Penetration

Robotics in Dentistry : A Narrative Review

Background: Robotics is progressing rapidly. The aim of this study was to provide a comprehensive overview of the basic and applied research status of robotics in dentistry and discusses its development and application prospects in several major professional fields of dentistry. Methods: A literature search was conducted on databases: MEDLINE, IEEE and Cochrane Library, using MeSH terms: [“robotics” and “dentistry”]. Result: Forty-nine articles were eventually selected according to certain inclusion criteria. There were 12 studies on prosthodontics, reaching 24%; 11 studies were on dental implantology, accounting for 23%. Scholars from China published the most articles, followed by Japan and the United States. The number of articles published between 2011 and 2015 was the largest. Conclusions: With the advancement of science and technology, the applications of robots in dental medicine has promoted the development of intelligent, precise, and minimally invasive dental treatments. Currently, robots are used in basic and applied research in various specialized fields of dentistry. Automatic tooth-crown-preparation robots, tooth-arrangement robots, drilling robots, and orthodontic archwire-bending robots that meet clinical requirements have been developed. We believe that in the near future, robots will change the existing dental treatment model and guide new directions for further development

Learning about tooth removal with robot technology

Deze PhD-thesis richt zich op een fundamenteel onderzoek van de extractieleer en maakt daarbij gebruik van robottechnologie. Het onderzoek omvat zes inhoudelijke hoofdstukken, waarin verschillende aspecten van dit onderwerp worden behandeld. Het tweede hoofdstuk analyseert de literatuur over robottechnologie in de tandheelkunde en wijst op de matige kwaliteit van beschikbare literatuur, zeker als het op klinische toepassingen aankomt. Hoofdstuk 3 biedt een overzicht van robotsystemen in alle deelgebieden van de tandheelkunde sinds 1985. Hoofdstuk 4 introduceert een meetopstelling om krachten en bewegingen bij tandextracties nauwkeurig vast te leggen, terwijl hoofdstuk 5 de resultaten van een serie experimenten voor wat betreft krachten en momenten weergeeft. Hoofdstuk 6 beschrijft het bewegingsbereik en de snelheden tijdens tandheelkundige extracties, zoals gemeten met een robotarm. Hoofdstuk 7 beschrijft de ontwikkeling en eigenschappen van een classificatiemodel voor extracties op basis van kracht- en bewegingsgegevens. De conclusie benadrukt de toenemende interesse in robotinitiatieven in de tandheelkunde, de behoefte aan wetenschappelijke validatie van de toegevoegde waarde daarvan en het potentieel van robottechnologie om ons fundamentele begrip van de extractieleer te vergroten. De studies benadrukken het belang van gegevensverzameling, analyse en samenwerking tussen verschillende disciplines om ons fundamentele begrip van extracties te verbeteren, met een focus op tandheelkundig onderwijs en uiteindelijk de patiëntenzorg

Aeronautical Engineering: A special bibliography with indexes, supplement 54

This bibliography lists 316 reports, articles, and other documents introduced into the NASA scientific and technical information system in January 1975

Odontology & artificial intelligence

Neste trabalho avaliam-se os três fatores que fizeram da inteligência artificial uma tecnologia essencial hoje em dia, nomeadamente para a odontologia: o desempenho do computador, Big Data e avanços algorítmicos. Esta revisão da literatura avaliou todos os artigos publicados na PubMed até Abril de 2019 sobre inteligência artificial e odontologia. Ajudado com inteligência artificial, este artigo analisou 1511 artigos. Uma árvore de decisão (If/Then) foi executada para selecionar os artigos mais relevantes (217), e um algoritmo de cluster k-means para resumir e identificar oportunidades de inovação. O autor discute os artigos mais interessantes revistos e compara o que foi feito em inovação durante o International Dentistry Show, 2019 em Colónia. Concluiu, assim, de forma crítica que há uma lacuna entre tecnologia e aplicação clínica desta, sendo que a inteligência artificial fornecida pela indústria de hoje pode ser considerada um atraso para o clínico de amanhã, indicando-se um possível rumo para a aplicação clínica da inteligência artificial.There are three factors that have made artificial intelligence (AI) an essential technology today: the computer performance, Big Data and algorithmic advances. This study reviews the literature on AI and Odontology based on articles retrieved from PubMed. With the help of AI, this article analyses a large number of articles (a total of 1511). A decision tree (If/Then) was run to select the 217 most relevant articles-. Ak-means cluster algorithm was then used to summarize and identify innovation opportunities. The author discusses the most interesting articles on AI research and compares them to the innovation presented during the International Dentistry Show 2019 in Cologne. Three technologies available now are evaluated and three suggested options are been developed. The author concludes that AI provided by the industry today is a hold-up for the praticioner of tomorrow. The author gives his opinion on how to use AI for the profit of patients

A scoping review of the use and application of virtual reality in pre-clinical dental education

Introduction Virtual reality (VR) is gaining recognition as a valuable tool for training dental students and its use by dental schools around the world is growing. It is timely to review the literature relating to the use of VR in dental education, in order to ensure that educators are well-informed of current areas of inquiry, and those requiring further investigation, to enable appropriate decisions about whether to employ VR as a teaching tool. Method A scoping review using the method outlined by Arksey and O'Malley was conducted. Both Web of Science and ERIC databases were searched. Inclusion and exclusion criteria were established to filter results. The data were collected and categorised using a custom data collection spreadsheet. Results The review identified 68 relevant articles. Following review, four educational thematic areas relating to the 'simulation hardware', the 'realism of the simulation', 'scoring systems' and 'validation' of the systems emerged. Conclusion This paper summarises and draws out themes from the current areas of inquiry in the literature, uncovering a number of weaknesses and assumptions. It recommends areas where additional investigation is required in order to form a better evidence base for the utility of VR in dental education, as well as to inform its future development

The use of mechanical redundancy for fault detection in non-stationary machinery

The classical approach to machinery fault detection is one where a machinery’s condition is constantly compared to an established baseline with deviations indicating the occurrence of a fault. With the absence of a well-established baseline, fault detection for variable duty machinery requires the use of complex machine learning and signal processing tools. These tools require extensive data collection and expert knowledge which limits their use for industrial applications. The thesis at hand investigates the problem of fault detection for a specific class of variable duty machinery; parallel machines with simultaneously loaded subsystems. As an industrial case study, the parallel drive stations of a novel material haulage system have been instrumented to confirm the mechanical response similarity between simultaneously loaded machines. Using a table-top fault simulator, a preliminary statistical algorithm was then developed for fault detection in bearings under non-stationary operation. Unlike other state of the art fault detection techniques used in monitoring variable duty machinery, the proposed algorithm avoided the need for complex machine learning tools and required no previous training. The limitations of the initial experimental setup necessitated the development of a new machinery fault simulator to expand the investigation to include transmission systems. The design, manufacturing and setup of the various subsystems within the new simulator are covered in this manuscript including the mechanical, hydraulic and control subsystems. To ensure that the new simulator has successfully met its design objectives, extensive data collection and analysis has been completed and is presented in this thesis. The results confirmed that the developed machine truly represents the operation of a simultaneously loaded machine and as such would serve as a research tool for investigating the application of classical fault detection techniques to parallel machines in non-stationary operation.Master's These

Objective assessment and feedback generation in dental surgical simulation : a framework based on correlating procedure and outcome

Fine motor skill is indispensable for a dentist. As in many other medical fields of study, the traditional surgical master-apprentice model is widely adopted in dental education. Recently, virtual reality (VR) simulators have been employed as supplementary components to the traditional skill-training curriculum, and numerous dental VR systems have been developed academically and commercially. However, the full promise of such systems has yet to be realized due to the lack of sufficient support for formative feedback. Without such a mechanism, evaluation still demands dedicated time of experts in scarce supply. With the aim to fill the gap of formative assessment using VR simulators in skill training in dentistry, this thesis presents a framework to objectively assess the surgical skill and generate formative feedback automatically. VR simulators enable collecting detailed data on relevant metrics throughout a procedure. Our approach to formative feedback is to correlate procedure metrics with the procedure outcome in order to identify the portions of a procedure that need to be improved. Prior to the correlation, the procedure outcome needs to be evaluated. The scoring algorithm designed in this thesis provides an overall score and identifies specific errors and their severity. Building upon this, we developed techniques to identify the portion of the procedure responsible for the errors. Specifically, for the errors in the outcome the responsible portions of the procedure are identified based on correlation of location of the error. For some types of feedback one mode may be more suitable than another. Tutoring formative feedback are provided using the video- and haptic- modalities. The effectiveness of the feedback systems have been evaluated with the dental students with randomized controlled trials and the findings show the feedback mechanisms to be effective and have potentials to use as valuable supplemental training resources

Advanced Applications of Rapid Prototyping Technology in Modern Engineering

Rapid prototyping (RP) technology has been widely known and appreciated due to its flexible and customized manufacturing capabilities. The widely studied RP techniques include stereolithography apparatus (SLA), selective laser sintering (SLS), three-dimensional printing (3DP), fused deposition modeling (FDM), 3D plotting, solid ground curing (SGC), multiphase jet solidification (MJS), laminated object manufacturing (LOM). Different techniques are associated with different materials and/or processing principles and thus are devoted to specific applications. RP technology has no longer been only for prototype building rather has been extended for real industrial manufacturing solutions. Today, the RP technology has contributed to almost all engineering areas that include mechanical, materials, industrial, aerospace, electrical and most recently biomedical engineering. This book aims to present the advanced development of RP technologies in various engineering areas as the solutions to the real world engineering problems

Research and Technology, 1994

This report selectively summarizes the NASA Lewis Research Center's research and technology accomplishments for the fiscal year 1994. It comprises approximately 200 short articles submitted by the staff members of the technical directorates. The report is organized into six major sections: Aeronautics, Aerospace Technology, Space Flight Systems, Engineering and Computational Support, Lewis Research Academy, and Technology Transfer. A table of contents and author index have been developed to assist the reader in finding articles of special interest. This report is not intended to be a comprehensive summary of all research and technology work done over the past fiscal year. Most of the work is reported in Lewis-published technical reports, journal articles, and presentations prepared by Lewis staff members and contractors. In addition, university grants have enabled faculty members and graduate students to engage in sponsored research that is reported at technical meetings or in journal articles. For each article in this report a Lewis contact person has been identified, and where possible, reference documents are listed so that additional information can be easily obtained. The diversity of topics attests to the breadth of research and technology being pursued and to the skill mix of the staff that makes it possible