Relevant bibliographies by topics / Production control – Data processing

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Production control – Data processing'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Production control – Data processing"

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Lee, Hyeopgeon, Young-Woon Kim, and Ki-Young Kim. "Real-time Big Data Processing System to Improve Semiconductor Production Efficiency in Smart Factory." International Journal of Engineering & Technology 7, no. 3.33 (August 29, 2018): 243. http://dx.doi.org/10.14419/ijet.v7i3.33.21021.

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Semiconductor production efficiency is closely related to the defect rate in the production process. The temperature and humidity control in the production line are very important because these affect the defect rate. So many smart factory of semiconductor production uses sensor. It is installed in the semiconductor process, which send huge amounts of data per second to a central server to carry out temperature and humidity control in each production line. However, big data processing systems that analyze and process large-scale data are subject to frequent delays in processing, and transmitted data are lost owing to bottlenecks and insufficient memory caused by traffic concentrated in the central server. In this paper, we propose a real-time big data processing system to improve semiconductor production efficiency. The proposed system consists of a production line collection system, task processing system and data storage system, and improves the productivity of the semiconductor manufacturing process by reducing data processing delays as well as data loss and discarded data.
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Titov, Mikhail, Mikhail Borodin, Dmitry Golubkov, and Alexei Klimentov. "Advanced Analytics service to enhance workflow control at the ATLAS Production System." EPJ Web of Conferences 214 (2019): 03007. http://dx.doi.org/10.1051/epjconf/201921403007.

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Modern workload management systems that are responsible for central data production and processing in High Energy and Nuclear Physics experiments have highly complicated architectures and require a specialized control service for resource and processing components balancing. Such a service represents a comprehensive set of analytical tools, management utilities and monitoring views aimed at providing a deep understanding of internal processes, and is considered as an extension for situational awareness analytic service. Its key points are analysis of task processing, e.g., selection and regulation of key task features that affect its processing the most; modeling of processed data life-cycles for further analysis, e.g., generate guidelines for particular stage of data processing; and forecasting processes with focus on data and tasks states as well as on the management system itself, e.g., to detect the source of any potential malfunction. The prototype of the advanced analytics service will be an essential part of the analytical service of the ATLAS Production System (ProdSys2). Advanced analytics service uses such tools as Time-To-Complete (TTC) estimation towards units of the processing (i.e., tasks and chains of tasks) to control the processing state and to be able to highlight abnormal operations and executions. Obtained metrics are used in decision making processes to regulate the system behaviour and resources consumption.
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Liao, Wei Qiang, Li Ming Ling, and Jian Zhou. "Research of Roll Processing Instrument Upgrading and Improvement." Advanced Materials Research 684 (April 2013): 386–89. http://dx.doi.org/10.4028/www.scientific.net/amr.684.386.

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Introduce data extract from old Rolling processing measurement and control instrument. Research data transmission between administrative area and production field; achieve record, save, monitor and output of machine data. Research the relationship of administrative area and production field. Study control platform on PC, achieve the control of machine and operator by PC.
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Golubeva, Olesya, and Alina Pogorelova. "Development of a software module for quality control and statistical data processing in production." E3S Web of Conferences 217 (2020): 06008. http://dx.doi.org/10.1051/e3sconf/202021706008.

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the article considers the algorithmic and mathematical justification for the development of a new software module for product quality control and statistical data processing at the Auditor enterprises. The software is designed for automated calculation of product quality control and evaluation indicators. The program has a wide range of functions for statistical data processing and product quality control tools at the enterprise. The functional characteristics of the software include: comparing risks for a given set of factors for two cases, building a histogram of the distribution of cases over a given numerical interval, comparing objects for a given set of values using a generalized estimate, calculating global priorities for a given set of factors for several cases, calculating the I-th predicted value for a linear regression model, calculating the i-th predicted value for an exponential regression model, calculating the i-th predicted value for a parabolic regression model, calculating the consistency of experts for a given set of factors, calculating the n+1 value of a time series, and evaluating the level of employee satisfaction.
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Zhang, Jia Liang, Bei Zhi Li, Jian Guo Yang, and Han Yan Chen. "An Intelligent Control System of Candy Production Process." Advanced Materials Research 282-283 (July 2011): 658–61. http://dx.doi.org/10.4028/www.scientific.net/amr.282-283.658.

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Candy production processes involve many process variables. Operators often find it difficult to effectively monitor the process data, analyze current states, detect and diagnose process anomalies, and take appropriate actions to control the processes. The objective of this work is to develop an intelligent control system of candy production process to improve final candy quality and to increase production efficiency with good human-machine interfaces. The study is conducted by using virtual instrument, multi-sensor data fusion and fuzzy control technology to online detect and control typical parameters. Experiment results show that this system can reach requirements of processing accuracy and real-time property and is highly cost-efficient and practical.
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Wang, Yan Kun, Yun Xu Shi, and Hong Mei Fan. "Design of Mine Production Safety Monitoring System." Advanced Materials Research 503-504 (April 2012): 1330–33. http://dx.doi.org/10.4028/www.scientific.net/amr.503-504.1330.

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The mine safety monitoring system is a set of sensor technology, electronics technology, power electronics technology, computer technology, wireless communication and network technology in one of China's leading multi-functional computer network systems, including underground, Inoue environment and equipment the detection of network systems and the Inoue monitoring data processing system. Environment and equipment for testing network system to achieve underground, of Inoue environment physical monitoring and control; monitoring data processing system is a comprehensive treatment of the collected data in order to achieve the sub-station set up and control equipment or detection sensors, through LAN detection information sharing, may constitute the enterprise information system.
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Ahmad, Tanvir, Abdul Basit, Juveria Anwar, Olivier Coupiac, Behzad Kazemtabrizi, and Peter Matthews. "Fast Processing Intelligent Wind Farm Controller for Production Maximisation." Energies 12, no. 3 (February 10, 2019): 544. http://dx.doi.org/10.3390/en12030544.

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A practical wind farm controller for production maximisation based on coordinated control is presented. The farm controller emphasises computational efficiency without compromising accuracy. The controller combines particle swarm optimisation (PSO) with a turbulence intensity–based Jensen wake model (TI–JM) for exploiting the benefits of either curtailing upstream turbines using coefficient of power ( C P ) or deflecting wakes by applying yaw-offsets for maximising net farm production. Firstly, TI–JM is evaluated using convention control benchmarking WindPRO and real time SCADA data from three operating wind farms. Then the optimised strategies are evaluated using simulations based on TI–JM and PSO. The innovative control strategies can optimise a medium size wind farm, Lillgrund consisting of 48 wind turbines, requiring less than 50 s for a single simulation, increasing farm efficiency up to a maximum of 6% in full wake conditions.
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Himawan, Abdurrahman Faris Indriya, and Muhammad Abidhin Al Habtsi. "PENGENDALIAN KUALITAS PRODUK NPK PHONSKA DENGAN METODE STATISTICAL PROCESSING CONTROL PADA UNIT PRODUKSI 2A PT. PETROKIMIA GRESIK." MANAJERIAL 5, no. 1 (April 22, 2019): 75. http://dx.doi.org/10.30587/manajerial.v5i1.849.

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This study aims to determine the quality control of Phonska NPK fertilizer using Statistical Processing Control method. Statistical Processing Control to analyze and identify quality deviations in Phonska NPK products. There were five people in this study. Data collection techniques using observation, interviews and documentation. Data analysis techniques using Statistical Processing Control. PT. Petrokimia Gresik has Phonska NPK fertilizer products whose production has deviations but can be overcome using the SPC method (Statistical Processing Control).
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Kaban, Rendy. "Pengendalian Kualitas Kemasan Plastik Pouch Menggunakan Statistical Procces Control (SPC) di PT Incasi Raya Padang." Jurnal Optimasi Sistem Industri 13, no. 1 (April 25, 2016): 518. http://dx.doi.org/10.25077/josi.v13.n1.p518-547.2014.

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PT Incasi Raya is one of the major companies in Indonesia which produce edible oils. One of the stages in the production activities are packaging products. Used packaging made of plastic material, with the capacity and different type. Plastic pouch is one of the few types of packaging used in the packaging of edible oils. Quality packaging affects the distribution of production to the consumer. If the packaging is damaged, then the product can not be distributed to consumers. Therefore, the quality of the packaging must be kept for the successful marketing of the product. One way to implement a quality control methods Statistical Processing Control (SPC). The data used in this study is a secondary data provided by the company. Data collected is the number of production reject every month in packaging activities. The data processing of the data collection that is making control map p. The results of data processing show that many reject the production of packaging that are outside the control limits. Data that are outside the control limits indicates there is a problem in the quality control of the company. Of all types of packaging, only one or two months of production reject packs that are in the control limits. This suggests that the dominant packaging reject each month of production is outside the control limits. Reject the production was analyzed using a causal diagram. Factors influencing the presence reject packaging production is based on the analysis of human, machine, environment, materials, and methods within the company. After analyzing of the causal diagram, the data is revision. Making a map of the proposed p controls the data that has been revised is the end result of the data processing is done. Quality control companies are advised to be on the boundary control such as control map p recommended.Keyword : Reject Production, Packaging, Control Limits, Plastik, Edible OilsAbstrakPT Incasi Raya merupakan salah satu perusahaan besar di Indonesia yang memproduksi minyak goreng. Salah satu hal tahapan dalam kegiatan produksinya adalah pengemasan produk. Kemasan yang digunakan terbuat dari bahan plastik, dengan kapasitas dan jenis yang berbeda-beda. Plastik pouch merupakan salah satu dari beberapa jenis kemasan yang digunakan dalam pengemasan minyak goreng. Kualitas kemasan sangat berpengaruh terhadap pendistribusian hasil produksi kepada konsumen. Apabila kemasan mengalami kerusakan, maka produk tersebut tidak dapat didistribusikan kepada konsumen. Oleh karena itu, kualitas dari kemasan harus dijaga untuk keberhasilan pemasaran produk. Salah satu cara pengendalian kualitas menerapkan metode Statistical Processing Control (SPC). Data yang digunakan pada penelitian ini adalah data sekunder yang diberikan oleh perusahaan. Data yang dikumpulkan adalah jumlah reject produksi setiap bulan dalam kegiatan pengemasan. Pengolahan data dilakukan dari pengumpulan data yaitu pembuatan peta kontrol p. Hasil pengolahan data menunjukkan bahwa banyak kemasan reject produksi yang berada diluar batas kontrol. Data yang berada diluar batas kontrol menandakan terdapat masalah pada pengendalian kualitas perusahaan. Dari semua jenis kemasan, hanya satu atau dua bulan saja jumlah kemasan reject produksi yang berada dalam batas kontrol. Hal ini menunjukkan bahwa dominan tiap bulannya kemasan reject produksi berada diluar batas kontrol. Terjadinya reject produksi dianalisis menggunakan diagram sebab akibat. Faktorfaktor yang mempengaruhi adanya kemasan reject produksi berdasarkan analisis adalah manusia, mesin, lingkungan, material, dan metode dalam perusahaan. Setelah dilakukan analisis dengan diagram sebab akibat, dilakukan revisi data. Pembuatan peta kontrol p usulan dari data yang telah direvisi merupakan hasil akhir dari pengolahan data yang dilakukan. Pengendalian kualitas perusahaan disarankan berada pada batas kendali seperti peta kontrol p usulan.Kata Kunci : Reject Produksi, Kemasan, Batas Kontrol, Plastik, Minyak Goreng
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Niderla, Jonrad, Tomasz Rymarczyk, and Jan Sikora. "MANUFACTURING PLANNING AND CONTROL SYSTEM USING TOMOGRAPHIC SENSORS." Informatyka Automatyka Pomiary w Gospodarce i Ochronie Środowiska 8, no. 3 (September 25, 2018): 29–34. http://dx.doi.org/10.5604/01.3001.0012.5280.

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The article presents an idea of a production process control system. Advanced automation and control of production processes play a key role in maintaining competitiveness. The proposed solution consists of sensor networks for measurement process parameters, production resources and equipment state. The system uses wired and wireless communication, which gives possibility to acquisition data from existing in enterprise sensors and systems as well as acquisition data from new systems and sensors used to measure all processes, starting from production preparation to the final product. The solution contains process tomography sensors based on electrical capacitance tomography, electrical impedance tomography and ultrasound tomography. The use of tomographic methods enables to manage the intelligent structure of the companies in terms of processes and products. Industrial tomography enables observation of physical and chemical phenomena without the need to penetrate inside. It will enable the optimization and auto-optimization of design processes and production. Such solutions can operate autonomously, monitor and control measurements. All sensors return to the system continuous data about state of processes in some technologically closed objects like fermenters. Process tomography can also be used to acquisition data about a flow of liquids and loose ingredients in pipeline based on transport systems. Data acquired from sensors are collected in data warehouses in order to future processing and building the knowledge base. The results of the data analysis are showed in user control panels and are used directly in the control of the production process to increase the efficiency and quality of the products. Control methods cover issues related to the processing of data obtained from various sensors located at nodes. Monitoring takes place within the scope of acquired and processed data and parameter automation.
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Dissertations / Theses on the topic "Production control – Data processing"

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Moi, Havard. "Rule-based control of manufacturing systems." Thesis, Hong Kong : University of Hong Kong, 2000. http://sunzi.lib.hku.hk/hkuto/record.jsp?B22190168.

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Barr, Thomas W. "Development of a graphics interface for the Savannah River control program "Savres"." Thesis, Georgia Institute of Technology, 1992. http://hdl.handle.net/1853/20978.

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Zhang, Yaoen Lan. "An integrated intelligent shop control system." Thesis, Virginia Polytechnic Institute and State University, 1989. http://hdl.handle.net/10919/52095.

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Presently there is a trend in manufacturing system design from stand-alone, automatic operations to Computer Integrated Manufacturing (CIM). The success of the integration depends largely on the performance of system control software. This document presents research in the design and implementation of a shop control system, for a CIM facility, using a new method called the three-layer integrated approach. Two basic techniques used in this research are expert systems and object-oriented programming. The CIM system at VPI is an automated manufacturing and assembly system. In designing the control system for this CIM facility, the design of products, production facilities, and overall system must be taken into account. In order to manage this complex system, a control system called the “shop controller” has been developed using C++, an object-oriented programming language. In addition, three real-time simulators for the cell controllers have been developed for testing and debugging the production rules of the expert system. The basic approach taken for the shop control system has several advantages: applied intelligence, program efficiency, reusability of code, and ease of maintenance. Moreover, this approach has a new feature—modularity, which is the result of combining expert systems and object-oriented programming.
Master of Science
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容勁 and King Stanley Yung. "Application of multi-agent technology to supply chain management." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B31223886.

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Fan, Chi-kit, and 樊智傑. "Design and analysis of agent-based FMS control systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2005. http://hub.hku.hk/bib/B31580324.

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Roweis, Sam T. Hopfield John J. Abu-Mostafa Yaser S. Perona Pietro. "Data driven production models for speech processing /." Diss., Pasadena, Calif. : California Institute of Technology, 1999. http://resolver.caltech.edu/CaltechETD:etd-02272008-093303.

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Sabri, Dina O. "Process control using an optomux control board." Virtual Press, 1987. http://liblink.bsu.edu/uhtbin/catkey/484759.

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In this thesis process control concepts were used to develop software that could be adapted to a real world situation. The software was used to control a simple temperature regulating experiment. This experiment was used to demonstrate the use of OPTOMUX analog and digital input/output devices in controlling a process. The goal of this experiment was to use the input/output devices in controlling the temperature of the box within specified tolerances for a designated period of time. To accomplish optimal use of equipment and optimal control, a mathematical model was derived to predict the behavior of the process under control. The pattern observed while the temperature was increasing toward room temperature closely resembled an exponential function. For temperatures above room temperatures the curve then approximated a square root function. The pattern followed when decreasing the temperature-was exponential throughout. The time required to collect all the significant data in the case of increasing the temperature was two hours. In the case of decreasing temperature, one hour. Beyond these time limits the temperature remained essentially constant. The maximum temperature value that could be reached was six degrees above room temperature and the minimum two degrees below room temperature.
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Zhang, Luping, and 张路平. "Solving integrated process planning and scheduling problems with metaheuristics." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/208626.

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Process planning and scheduling are two important manufacturing planning functions which are closely related to each other. Usually, process planning and scheduling have to be performed sequentially, whereby the process plans are the input for scheduling. Many investigations have shown that the separate conduction of the two functions is much likely to ruin the effectiveness and feasibility of the process plans and schedules, and it is also difficult to cater for the occurrence of uncertainties in the dynamic manufacturing environment. The purpose of integrated process planning and scheduling (IPPS) is to perform the two functions concurrently. IPPS is a typical combinatorial optimization problem which belongs to the category of NP-hard problems. Research on IPPS has intensified in recent years. Researchers have reported various IPPS systems and solution approaches which are able to generate good solutions for specific IPPS problems. However, there is in general an absence of theoretical models for the IPPS problem representation, and research on the theoretical aspects of the IPPS is limited. The objective of this research is to establish a metaheuristic-based solution approach for the IPPS problem in flexible jobshop type of manufacturing systems. To begin with, a graph-based modeling approach for formulating the IPPS problem domain is proposed. This approach defines a way to use a category of AND/OR graphs to construct IPPS models. The graph-based IPPS model can be formulated using mathematical programming tools including polynomial mixed integer programming (PMIP) and mixed integer linear programming (MILP). The analytical mathematical programming approaches can be used to solve simple IPPS instances but they are not capable for large-scale IPPS problems. This research proposes a new IPPS modelling approach to incorporate metaheuristics in the solution strategy. Actually, the solution strategy comprises the metaheuristics and a mapping function. The metaheuristic is responsible for generating the operation sequences; a mapping function is then used to assign the operations to appropriate time slots on a schedule. General studies of applying constructive and improvement metaheuristics to solve the IPPS problem are conducted in this research. The ant colony optimization (ACO) is applied as a representative constructive metaheuristic, and a nonstandard genetic algorithm approach object-coding genetic algorithm (OCGA) is implemented as an improvement metaheuristic. The OCGA contains dedicated genetic operations to support the object-based genetic representation, and three particular mechanisms for population evolution. The metaheuristic-based solution approaches are implemented in a multi-agent system (MAS) platform. The hybrid MAS and metaheuristics based IPPS solution methodology is able to carry out dynamic rescheduling to cope with occurrence of uncertainties in practical manufacturing environments. Experiments have been carried out to test the IPPS solution approach proposed in this thesis. It is shown that both metaheuristics, ACO and OCGA, are having good performance in terms of solution quality and computational efficiency. In particular, due to the special genetic operations and population evolutionary mechanisms, the OCGA shows great advantages in experiments on benchmark problems. Finally, it is shown that the hybrid approach of MSA and metaheuristics is able to support real-time rescheduling in dynamic manufacturing systems.
published_or_final_version
Industrial and Manufacturing Systems Engineering
Doctoral
Doctor of Philosophy
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Yavuz, Mesut. "Batch production smoothing with variable setup and processing times." [Gainesville, Fla.] : University of Florida, 2005. http://purl.fcla.edu/fcla/etd/UFE0010066.

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Hamrouni, Nadia. "Structure and Processing in Tunisian Arabic: Speech Error Data." Diss., The University of Arizona, 2010. http://hdl.handle.net/10150/195969.

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This dissertation presents experimental research on speech errors in Tunisian Arabic (TA). The central empirical questions revolve around properties of `exchange errors'. These errors can mis-order lexical, morphological, or sound elements in a variety of patterns. TA's nonconcatenative morphology shows interesting interactions of phrasal and lexical constraints with morphological structure during language production and affords different and revealing error potentials linking the production system with linguistic knowledge.The dissertation studies expand and test generalizations based on Abd-El-Jawad and Abu-Salim's (1987) study of spontaneous speech errors in Jordanian Arabic by experimentally examining apparent regularities in data from real-time language processing perspective. The studies address alternative accounts of error phenomena that have figured prominently in accounts of production processing. Three experiments were designed and conducted based on an error elicitation paradigm used by Ferreira and Humphreys (2001). Experiment 1 tested within-phrase exchange errors focused on root versus non-root exchanges and lexical versus non-lexical outcomes for root and non-root errors. Experiments 2 and 3 addressed between-phrase exchange errors focused on violations of the Grammatical Category Constraint (GCC).The study of exchange potentials for the within-phrase items (experiment 1) contrasted lexical and non-lexical outcomes. The expectation was that these would include a significant number of root exchanges and that the lexical status of the resulting forms would not preclude error. Results show that root and vocalic pattern exchanges were very rare and that word forms rather than root forms were the dominant influence in the experimental performance. On the other hand, the study of exchange errors across phrasal boundaries of items that do or do not correspond in grammatical category (experiments 2 and 3) pursued two principal questions, one concerning the error rate and the second concerning the error elements. The expectation was that the errors predominantly come from grammatical category matches. That outcome would reinforce the interpretation that processing operations reflect the assignment of syntactically labeled elements to their location in phrasal structures. Results corroborated with the expectation. However, exchange errors involving words of different grammatical categories were also frequent. This has implications for speech monitoring models and the automaticity of the GCC.
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Books on the topic "Production control – Data processing"

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Computer-based production and inventory control. Englewood Cliffs, N.J: Prentice-Hall, 1989.

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1942-, Bailey James Edward, ed. Integrated production control systems: Management, analysis, design. 2nd ed. New York: Wiley, 1987.

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E, Bailey James, ed. Integrated production control systems: Management, analysis, design. 2nd ed. New York: Wiley, 1987.

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Bedworth, David D. Integrated production control systems: Management, analysis, design 2E. New York: Wiley, 1987.

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Council of Petroleum Accountants Societies (U.S.). Computer production control accounting guidelines. Tulsa, Okla. (P.O. Box 800, Tulsa 74101): Kraftbilt Products, 1992.

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Kang, Mujin. Entwicklung eines Werkstattsteuerungssystems mit simultaner Termin- und Kapazitätsplanung. München: Hanser, 1987.

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Shop Control '87 (1987 Cincinnati, Ohio). Shop Control '87: Conference proceedings, March 3-5, 1987, the Drawbridge Inn and Convention Center, Greater Cincinnati Airport Area. Cincinnati, Ohio (6600 Clough Pike, Cincinnati 45244-4090): Gardner Publications, 1987.

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Pabst, Hans-Jürgen. Analyse der betriebswirtschaftlichen Effizienz einer computergestützten Fertigungssteuerung mit CAPOSS-E, in einem Maschinenbauunternehmen mit Einzel- und Kleinserienfertigung. Frankfurt am Main: P. Lang, 1985.

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Micromaths: Mathematical problems and programs for your computer. London: Collins Educational, 1985.

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Lehmann, Frank. Störungsmanagement in der Einzel- und Kleinserienmontage: Ein Beitrag zur EDV-gestützten Montagesteuerung. Aachen: Shaker, 1992.

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Book chapters on the topic "Production control – Data processing"

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Yao, Shujie. "Data Processing." In Agricultural Reforms and Grain Production in China, 247–71. London: Palgrave Macmillan UK, 1994. http://dx.doi.org/10.1007/978-1-349-23553-7_10.

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Freakley, Philip K. "Process Control and Quality Control." In Rubber Processing and Production Organization, 183–265. Boston, MA: Springer US, 1985. http://dx.doi.org/10.1007/978-1-4613-2375-4_7.

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Rosato, Donald V., and Dominick V. Rosato. "Testing/Quality Control." In Plastics Processing Data Handbook, 326–51. Dordrecht: Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-010-9658-4_10.

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Feuer, Arie, and Graham C. Goodwin. "Sampled Data Control." In Sampling in Digital Signal Processing and Control, 343–95. Boston, MA: Birkhäuser Boston, 1996. http://dx.doi.org/10.1007/978-1-4612-2460-0_9.

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Palz, Wolfgang, and Jürgen Greif. "Quality control and data processing." In European Solar Radiation Atlas, 5–6. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/978-3-642-80237-9_5.

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Keviczky, László, Ruth Bars, Jenő Hetthéssy, and Csilla Bányász. "Sampled Data Control Systems." In Advanced Textbooks in Control and Signal Processing, 351–91. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8297-9_11.

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Yang, Bo, Yumin He, and Honghao Yin. "Data Analysis and Production Process Control." In Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems, 555–62. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-85874-2_59.

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Hill, Richard, and Stuart Berry. "Data for Production Planning and Control." In Texts in Computer Science, 65–83. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79104-9_4.

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Jacobs, D., C. T. Kuo, J. T. Lim, and S. M. Meerkov. "A System Theory for Production Lines." In Communications, Computation, Control, and Signal Processing, 463–80. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-6281-8_29.

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Siragusa, Gregory R., and Steven C. Ricke. "Probiotics as Pathogen Control Agents for Organic Meat Production." In Organic Meat Production and Processing, 329–49. Oxford, UK: Wiley-Blackwell, 2012. http://dx.doi.org/10.1002/9781118229088.ch20.

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Conference papers on the topic "Production control – Data processing"

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Altundogan, Goktug, Mehmet Karakose, Alisan Sarimaden, and Erhan Akin. "Edge control approach based on image processing in paper and packaging production." In 2017 International Artificial Intelligence and Data Processing Symposium (IDAP). IEEE, 2017. http://dx.doi.org/10.1109/idap.2017.8090300.

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Sun, Wen, Tao Ren, Xin Zhang, and Hong Song. "Optimization of intermittent oil production pattern based on data mining technology." In 2021 3rd International Conference on Intelligent Control, Measurement and Signal Processing and Intelligent Oil Field (ICMSP). IEEE, 2021. http://dx.doi.org/10.1109/icmsp53480.2021.9513394.

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Fair, Douglas C., and Jim Redifer. "Integration of Statistical Process Control Data Into Control and Information Systems for Production Optimization and Regulatory Compliance." In ASME 2004 Citrus Engineering Conference. American Society of Mechanical Engineers, 2004. http://dx.doi.org/10.1115/cec2004-5004.

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Data and Information from the plant floor is proliferating as more sophisticated machinery, instrumentation, and computer based devices are introduced into the manufacturing process. The use of Statistic Process Control to utilize this data goes beyond just measuring and analyzing product specific information. Food processing and manufacturing operations need to integrate real-time data and SPC data analysis into their operation in order to be a world-class manufacturer. To facilitate these goals, an organization must have a vision for an automation and information infrastructure as well as a data strategy. This discussion will touch on a number of key points in formulating that vision, as well as some specific functionalities using data and SPC that one would want to achieve. Paper published with permission.
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Jiao, Jianxin, Mitchell M. Tseng, Qinhai Ma, and Yi Zou. "Integrated Product and Production Data Management Based on Generic Bill of Materials and Operations to Support Mass Customization Production." In ASME 1999 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/detc99/eim-9026.

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Abstract This paper discusses the integrated product and production data management for mass customization production which is characterized by a large number of variety. A data structure, called Bill-of-Materials-and-Operations (BOMO), is proposed for the purpose of unifying BOMs and routings in order to facilitate better production planning and control, as well as order processing and engineering change control. To deal with variety effectively, a generic BOMO concept is put forward based on an understanding of a generic variety structure developed in the paper for characterizing variety. The merits of the generic BOMO for integrated product and production data management are detailed in terms of customer order processing, engineering change control, production job planning, costing, and integrated material and capacity planning. A prototype implementation of the proposed generic BOMO methodology in souvenir clock manufacturing is also reported.
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Zou, Jing, Qing Chang, Yong Lei, Jorge Arinez, and Guoxian Xiao. "Modeling and Performance Identification for General Production System Using Sensor Data." In ASME 2016 11th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/msec2016-8506.

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The productivity and efficiency of production systems are greatly influenced by their configuration and complex dynamics subject to constant changes caused by technology insertion, engineering modification, as well as disruption events. In this paper, we develop a mathematical model of production systems with general structure (tandem line, parallel, and etc.) to estimate the status of the system (production counts and processing speeds of the stations, buffer levels and production loss) by using sensor data of disruption events. Real-time production system performance such as effective disruption events, opportunity window, and permanent production loss are identified, which is very useful in real-time control to increase overall system efficiency.
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Zhiqiang, Zhao, Chua Wei Quan, Ding Xiaoming, and Prabhu Vinayak Ashok. "Smart Factory of Industry 4.0: Connection Infrastructure, Data Acquisition, Data Processing, and Applications." In ASME 2019 14th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/msec2019-2703.

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Abstract Smart factory adopts cyber-physical technologies integrating independent discrete systems into a context-sensitive manufacturing environment to optimize manufacturing processes using decentralized information and real-time communication. This paper presents our work in the realization of a smart factory, which comprises of a four-layer hierarchical architecture, i.e. connection infrastructure, data acquisition, data processing and smart applications. In the connection infrastructure layer, all shopfloor machines are connected through diverse protocols, IoT sensors, PLC interfaces and DNC connectors. A centralized IoT gateway supports such a scalable and adaptable connection and ensures a reliable communication among all heterogeneous manufacturing systems. In the data acquisition layer, the real-time machine and job data are acquired from shopfloor systems. Machine data indicates machines’ working condition and job data reveals the production information. The data processing layer comprises of three modules, i.e. shopfloor monitoring, data visualization and data analytics, which monitor and visualize shopfloor activities and analyze the semantics of various data using AI-based TPM engines providing the scientific indicators for next-step decisions. The smart application layer provides with several decision-making and remote control functions for shopfloor productivity and efficiency, such as predictive maintenance, shopfloor management, machine & job optimization and digital twin. The smart factory system has been implemented in the manufacturing shopfloor at Nanyang Polytechnic. The results and validation show that the system can simultaneously collect and analyze the manufacturing data from shopfloor systems, and further communicate with and control the shopfloor systems with decision-support functions. The overall shopfloor efficiency and flexibility can be significantly improved towards a smart factory of Industry 4.0.
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Martinez, R., J. S. Uhlman, C. M. Ting, B. S. Paul, J. M. Anderson, M. C. Goody, and D. O. Stewart. "Understanding Roughness Noise: Progress in Analytical Modeling and Testing, Part 2—Comparison of Calculations to Data." In ASME 2008 Noise Control and Acoustics Division Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/ncad2008-73091.

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This Part-2 paper applies Part 1’s theory of sheared rapid distortions to compute broadband noise from flow over large roughness elements, and compares those calculations to recent wind-tunnel measurements. The calculations suggest that shear effects are subdominant in the sound-production process. Post-processing of computed results brings out key features of the theory’s non-equilibrium distorting turbulence. A follow-up analysis makes possible the physical interpretation of the measured acoustic spectral densities in terms of the kinematics of the spatially non-uniform carrier flow.
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Zheng, Wei, Yong Lei, and Qing Chang. "Reinforcement Learning Based Real-Time Control Policy for Two-Machine-One-Buffer Production System." In ASME 2017 12th International Manufacturing Science and Engineering Conference collocated with the JSME/ASME 2017 6th International Conference on Materials and Processing. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/msec2017-2771.

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It is attractive to reduce the total cost of a manufacture system with real-time control of the production. The total cost mainly consists of the production cost, the penalty of the permanent production loss, and the Work-In-Process (WIP) inventory level cost. However, it is difficult to derive an analytical model of manufacture system due to the complexity of starved and blocked phenomena, the random failure and maintenance processes. Therefore, finding a real-time control policy for the manufacture system without exact analytical model is dearly needed. In this paper, a novel reinforcement learning based control decision policy is proposed based on the action of switching the machines on or off at the start of each time slot. Firstly, a simulation model is developed with MTBF and MTTR evaluated from the history data to collect samples. Then, a reinforcement learning method, specifically, Least-Square-Policy-Iteration method, is applied to obtain a sub-optimal policy. The simulation results show that the proposed method performs well in reducing the total cost.
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Spiric, Zdravko. "Innovative Approach to the Mercury Control During Natural Gas Processing." In ASME 2001 Engineering Technology Conference on Energy. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/etce2001-17085.

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Abstract Natural gas, being produced from gas fields around the globe, along with a large number of other harmful substances (CO2, H2S, RSH, COS, etc.), often contains mercury. Mercury’s potentially harmful effect on humans and on the ecological system as a whole as well as the risk regarding mercury’s corrosive effects to the very sophisticated and expensive process material, equipment and catalysts is making its removal an imperative. The frequently applied procedure to remove mercury as an impurity and environment pollutant from process streams utilizes adsorption on a fixed bed consisting of sulfur impregnated activated carbon. This paper deals with data, results and more than seven years of practical field experience obtained by research of mercury removal unit efficiency during production and enhancement of natural gas at Molve, Croatia. Paper details the operating implications of handling and processing natural gas containing mercury, showing the results of the innovative approach in the process control, resulting in safety reliability and process efficiency improvements by plant modification due to change of gas flow direction.
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Pham, Vuong, Amirmasoud Dahaghi, Shahin Negahban, William Fincham, and Aydin Babakhani. "I-GeoSensing Fracture Diagnostic I-GSFD for Fast Processing of the Smart Microchip Proppants Data." In SPE Annual Technical Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/206196-ms.

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Abstract Unconventional oil and gas reservoir development requires an understanding of the geometry and complexity of the hydraulic fractures. The current categories of fracture diagnostic approaches include methods for near-wellbore (production & temperature logs, tracers, and borehole imaging) and far-field techniques (micro-seismic fracture mapping). These techniques provide an indirect and interpreted fracture geometry. Therefore, none of these methods consistently provides a fully detailed and accurate description of the characteristic of the subsurface hydraulic fractures. This study proposes a novel approach that uses direct data from the injected fine size (proppant Mesh size equivalence) and battery-less, Smart MicroChip Proppants (SMPs), to map the fracture geometry. This novel approach enables direct, fast, smart, and real-time processing of the received high-resolution geo-sensor data from the SMPs collected in high pressure and high-temperature environment and maps the fracture network using the proposed i-Geosensing Fracture Diagnostic (i-GSFD), which is a closed-loop architecture. i-GSFD is based on multi-dimensional projection unsupervised clustering, and integrated Bayesian optimizer to control the stochastic nature of any components in the loop.
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Reports on the topic "Production control – Data processing"

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Dogruel, David, and William Kirk Hollis. LANL Hydrogen Processing Laboratory (HPL), Data acquisition and control system upgrade. Office of Scientific and Technical Information (OSTI), March 2016. http://dx.doi.org/10.2172/1244320.

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Beer, Randall D. Neural Networks for Real-Time Sensory Data Processing and Sensorimotor Control. Fort Belvoir, VA: Defense Technical Information Center, December 1992. http://dx.doi.org/10.21236/ada259120.

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Beer, Randall D. Neural Networks for Real-Time Sensory Data Processing and Sensorimotor Control. Fort Belvoir, VA: Defense Technical Information Center, June 1992. http://dx.doi.org/10.21236/ada251567.

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Levitan, Herbert. Microcomputer-Based Data Acquisition, Analysis and Control of Information Processing by Neural Networks. Fort Belvoir, VA: Defense Technical Information Center, November 1986. http://dx.doi.org/10.21236/ada177170.

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Hall, Candice, and Robert Jensen. Utilizing data from the NOAA National Data Buoy Center. Engineer Research and Development Center (U.S.), March 2021. http://dx.doi.org/10.21079/11681/40059.

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This Coastal and Hydraulics Engineering Technical Note (CHETN) guides users through the quality control (QC) and processing steps that are necessary when using archived U.S. National Oceanic and Atmospheric Administration (NOAA) National Data Buoy Center (NDBC) wave and meteorological data. This CHETN summarizes methodologies to geographically clean and QC NDBC measurement data for use by the U.S. Army Corps of Engineers (USACE) user community.
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Wierup, Martin, Helene Wahlström, and Björn Bengtsson. How disease control and animal health services can impact antimicrobial resistance. A retrospective country case study of Sweden. O.I.E (World Organisation for Animal Health), April 2021. http://dx.doi.org/10.20506/bull.2021.nf.3167.

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Data and experiences in Sweden show that it is possible to combine high productivity in animal production with the restricted use of antibiotics. The major key factors that explain Sweden’s success in preventing AMR are: Swedish veterinary practitioners were aware of the risk of AMR as early as the 1950s, and the need for prudent use of antibiotics was already being discussed in the 1960s. Early establishment of health services and health controls to prevent, control and, when possible, eradicate endemic diseases reduced the need for antibiotics. Access to data on antibiotic sales and AMR made it possible to focus on areas of concern. State veterinary leadership provided legal structures and strategies for cooperation between stakeholders and facilitated the establishment of coordinated animal health services that are industry-led, but supported by the State.
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R. Will Grimes, Norman Merriam, L.J. Fahy, C.G. Mones, Jr L.A. Johnson, F.M. Carlson, T.F. Turner, et al. 1.PRELIMINARY EVALUATION OF A PROCESS USING PLASMA REACTIONS TO DESULFURIZE HEAVY OILS; 2.PROCESS SUPPORT AND DEVELOPMENT FOR COMPCOAL; 3.MISCIBLE/IMMISCIBLE GAS INJECTION PROCESSES; 4.COMPCOAL: A PROFITABLE PROCESS FOR PRODUCTION OF A STABLE HIGH-BTU FUEL FROM POWDER RIVER BASIN COAL; 5.EVALUATION OF ALTERNATE FREE RADICAL INITIATORS FOR HEAVY OIL/PLASTICS CO-PROCESSING; 6.DEVELOPMENT OF AN ON-LINE ALKALI MONITORING PROBE; 7.DEVELOPMENT OF A PORTABLE DATA ACQUISITION SYSTEM; 8.BENCH-SCALE TESTING AND VERIFICATION OF PYROLYSIS CONCEPT FOR REMEDIATION OF TANK BOTTOMS; 9.HAZ-FLOTE: EX-SITU DECONTAMINATION OF MATERIALS; 10.IN-SITU AMELIORATION OF ACID MINE DRAINAGE PROBLEMS; 11.THE SYNAG PROCESS: COAL COMBUSTION ASH MANAGEMENT OPTION; 12.CONDITIONING AND HYDRATION REACTIONS ASSOCIATED WITH CLEAN COAL TECHNOLOGY ASH DISPOSAL/HYDRATION. Office of Scientific and Technical Information (OSTI), October 1999. http://dx.doi.org/10.2172/767235.

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Gates, Allison, Michelle Gates, Shannon Sim, Sarah A. Elliott, Jennifer Pillay, and Lisa Hartling. Creating Efficiencies in the Extraction of Data From Randomized Trials: A Prospective Evaluation of a Machine Learning and Text Mining Tool. Agency for Healthcare Research and Quality (AHRQ), August 2021. http://dx.doi.org/10.23970/ahrqepcmethodscreatingefficiencies.

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Background. Machine learning tools that semi-automate data extraction may create efficiencies in systematic review production. We prospectively evaluated an online machine learning and text mining tool’s ability to (a) automatically extract data elements from randomized trials, and (b) save time compared with manual extraction and verification. Methods. For 75 randomized trials published in 2017, we manually extracted and verified data for 21 unique data elements. We uploaded the randomized trials to ExaCT, an online machine learning and text mining tool, and quantified performance by evaluating the tool’s ability to identify the reporting of data elements (reported or not reported), and the relevance of the extracted sentences, fragments, and overall solutions. For each randomized trial, we measured the time to complete manual extraction and verification, and to review and amend the data extracted by ExaCT (simulating semi-automated data extraction). We summarized the relevance of the extractions for each data element using counts and proportions, and calculated the median and interquartile range (IQR) across data elements. We calculated the median (IQR) time for manual and semiautomated data extraction, and overall time savings. Results. The tool identified the reporting (reported or not reported) of data elements with median (IQR) 91 percent (75% to 99%) accuracy. Performance was perfect for four data elements: eligibility criteria, enrolment end date, control arm, and primary outcome(s). Among the top five sentences for each data element at least one sentence was relevant in a median (IQR) 88 percent (83% to 99%) of cases. Performance was perfect for four data elements: funding number, registration number, enrolment start date, and route of administration. Among a median (IQR) 90 percent (86% to 96%) of relevant sentences, pertinent fragments had been highlighted by the system; exact matches were unreliable (median (IQR) 52 percent [32% to 73%]). A median 48 percent of solutions were fully correct, but performance varied greatly across data elements (IQR 21% to 71%). Using ExaCT to assist the first reviewer resulted in a modest time savings compared with manual extraction by a single reviewer (17.9 vs. 21.6 hours total extraction time across 75 randomized trials). Conclusions. Using ExaCT to assist with data extraction resulted in modest gains in efficiency compared with manual extraction. The tool was reliable for identifying the reporting of most data elements. The tool’s ability to identify at least one relevant sentence and highlight pertinent fragments was generally good, but changes to sentence selection and/or highlighting were often required.
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Mazari, Mehran, Siavash F. Aval, Siddharth M. Satani, David Corona, and Joshua Garrido. Developing Guidelines for Assessing the Effectiveness of Intelligent Compaction Technology. Mineta Transportation Institute, January 2021. http://dx.doi.org/10.31979/mti.2021.1923.

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Many factors affect pavement compaction quality, which can vary. Such variability may result in an additional number of passes required, extended working hours, higher energy consumption, and negative environmental impacts. The use of Intelligent Compaction (IC) technology during construction can improve the quality and longevity of pavement structures while reducing risk for contractors and project owners alike. This study develops guidelines for the implementation of IC in the compaction of pavement layers as well as performing a preliminary life-cycle cost analysis (LCCA) of IC technology compared to the conventional compaction approach. The environmental impacts of the improved construction process were quantified based on limited data available from the case studies. The LCCA performed in this study consisted of different scenarios in which the number of operating hours was evaluated to estimate the cost efficiency of the intelligent compaction technique during construction. The analyses showed a reduction in energy consumption and the production of greenhouse gas (GHG) emissions with the use of intelligent compaction. The LCCA showed that the use of IC technology may reduce the construction and maintenance costs in addition to enhancing the quality control and quality assurance (QC/QA) process. However, a more comprehensive analysis is required to fully quantify the benefits and establish more accurate performance indicators. A draft version of the preliminary guidelines for implementation of IC technology and long-term monitoring of the performance of pavement layers compacted thereby is also included in this report.
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Berney, Ernest, Andrew Ward, and Naveen Ganesh. First generation automated assessment of airfield damage using LiDAR point clouds. Engineer Research and Development Center (U.S.), March 2021. http://dx.doi.org/10.21079/11681/40042.

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This research developed an automated software technique for identifying type, size, and location of man-made airfield damage including craters, spalls, and camouflets from a digitized three-dimensional point cloud of the airfield surface. Point clouds were initially generated from Light Detection and Ranging (LiDAR) sensors mounted on elevated lifts to simulate aerial data collection and, later, an actual unmanned aerial system. LiDAR data provided a high-resolution, globally positioned, and dimensionally scaled point cloud exported in a LAS file format that was automatically retrieved and processed using volumetric detection algorithms developed in the MATLAB software environment. Developed MATLAB algorithms used a three-stage filling technique to identify the boundaries of craters first, then spalls, then camouflets, and scaled their sizes based on the greatest pointwise extents. All pavement damages and their locations were saved as shapefiles and uploaded into the GeoExPT processing environment for visualization and quality control. This technique requires no user input between data collection and GeoExPT visualization, allowing for a completely automated software analysis with all filters and data processing hidden from the user.
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