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Journal articles on the topic 'Production control – Data processing'
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1
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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Brandmeier, Markus, Norbert Eckl, Daniel Weberling, and Jörg Franke. "Transparent Acquisition and Processing of Energy Data in the Field of Industrial Production - Requirements and Applications." Applied Mechanics and Materials 882 (July 2018): 81–89. http://dx.doi.org/10.4028/www.scientific.net/amm.882.81.
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Energy efficiency becomes a critical production factor due to legal regulations, sustainable customer-side production requirements and the increasingly volatile supply situation. Energy transparency is of crucial importance for the definition of strategic measures to increase energy efficiency. However, the transparent collection and processing of energy data in production not only forms the basis of industrial energy management, but also facilitates the additional optimization of subareas in the production environment. Especially in the context of production-related data, such as process and product quality data and production planning and control information, as well as combined with expert knowledge, energy data provides a wide range of application fields. This paper analyzes the requirements for a holistic, transparent collection and processing of energy data and identifies possible applications for the optimization of production and production-related areas.
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I.J Agabi and J.S Ibrahim. "Energy Evaluation and Processing Cost Reduction in Agudu Maize Processing Industry." International Journal of Engineering and Management Research 11, no. 1 (February 27, 2021): 142–55. http://dx.doi.org/10.31033/ijemr.11.1.20.
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This study evaluated energy consumption by Agudu Farms Limited (AFL) that processes maize and cassava into flour for human consumption. The objectives of study included to determine energy contribution to processing cost, to minimize the processing cost and to propose a new selling price per unit of sale of the product. The study materials included; a multi-meter, stopwatch, electrical appliances’ nameplates and bills, fuel purchased receipts, and production records. Data was collected through detailed energy audits and measurements of present electricity consumption. This data was converted into energy intensities, rates and costs, and analyzed. The monthly energy intensity plotted on bar charts using Microsoft excel and the results showed that diesel had the highest consumption variation of 3500 kWh/t, electricity 200kWh/t and labor 110 kWh/t. The percentage of energy contribution to processing cost was 33%. In monetary terms, the processing cost per hour of operation showed average value of ₦830. Whereas, the minimum production cost per hour using Tora software showed ₦767. The new product price per ten-kilogram (10kg) unit of sale of maize flour, using break-even analysis, showed ₦2864. The study observed that diesel contributed more to production cost than electricity and labor and therefore, recommended the setting up of an energy monitoring team to monitor procurement and control utilization of diesel to reduce production cost.
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FILIPPI, ROBERTO, THEMIS KARAMINIS, and MICHAEL S. C. THOMAS. "Language switching in bilingual production: Empirical data and computational modelling." Bilingualism: Language and Cognition 17, no. 2 (October 30, 2013): 294–315. http://dx.doi.org/10.1017/s1366728913000485.
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One key issue in bilingualism is how bilinguals control production, particularly to produce words in the less dominant language. Language switching is one method to investigate control processes. Language switching has been much studied in comprehension, e.g., in lexical decision task, but less so in production. Here we first present a study of language switching in Italian–English adult bilinguals in a naming task for visually presented words. We demonstrate an asymmetric pattern of time costs to switch language, where participants incurred a greater time cost to switch into naming in their dominant language (Italian). In addition, costs were greater where the stimuli were interlingual cognates or homographs than words existing in only one language, implicating lexical competition as a source of the cost. To clarify the operation of control processes, we then present two connectionist models of bilingual naming, based on the previous models of Seidenberg and McClelland (1989), Cohen, Dunbar and McClelland (1990), Gilbert and Shallice (2002), and Karaminis and Thomas (2010). Crucially, both models acquired their differential language dominance via an experience-dependent learning process. The models embody different assumptions about the language control processes that produce the switch cost. We consider which processing assumptions are sufficient to explain asymmetric language switch costs and word class effects on language switching in individual word reading, as well as generating novel predictions for future testing.
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Stankov, Stanko. "Modern control of mineral wool production process." Chemical Industry 67, no. 2 (2013): 375–84. http://dx.doi.org/10.2298/hemind120428069s.
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In this paper, the control of the plant for mineral wool production consisting of a number of the technological units of different sizes and complexity is considered. The application of modern equipment based on PLC (Programmable Logic Controller) and SCADA (Supervisory Control And Data Acquisition) configuration provides optimal control of technological process. Described supervisory and control system is consisting of a number of units doing decentralized distributed control of technological entities where all possible situation are considered during work of machines and devices, which are installed in electric drive and are protected from technological and electrical accident. Transformer station and diesel engine, raw materials transport and dosage, processes in dome oven, centrifuges, polycondensation (PC) chamber, burners, compressor station, binder preparation and dosage, wool cutting, completed panel packing and their transport to storehouse are controlled. Process variables and parameters like as level, flow, velocity, temperature, pressure, etc. are controlled. Control system is doing identification of process states changes, diagnostic and prediction of errors and provides prediction of behavior of control objects when input flows of materials and generates optimal values of control variables due to decreasing downtime and technic - economical requires connected to wool quality to be achieved. Supervisory and control system either eliminates unwanted changes in the production line or restricts them within the allowable limits according to the technology. In this way, the optimization of energy and raw materials consumption and appropriate products quality is achieved, where requirements are satisfied in accordance with process safety and environmental standards. SCADA provides a visual representation of controlled and uncontrolled parts of the technological process, processing alarms and events, monitoring of the changes of relevant variables, data archiving, choice of either automatic or manual control. Supervison of the production process by intuitive screens on monitors, and display terminal is allowed to the operator. Certain objects of plant are represented by the appropriate symbols whose color is changed depending on status (working, inactive status, stand by, failure, etc.). Symbols are associated with characteristic parameters and the variables whose current values are monitored by graphics and/or tables. Special attention is paid to alarm conditions occurring in the case of failure or exceeding the set limits of certain values. Alarm signal is manifested by sound and signal light, with a corresponding text message on the screen, with the date and time of occurrence and the request to the operator to confirm the alarm in some way. Alarms and other important data are stored in the database, including information about the time of removing the causes of the alarm emergence. Beside data acqusition and processing data of process variables and installed equipment state, the system also provides data archiving and generating and printing of daily, weekly and monthly reports. Based on these reports, analysis and appropriate corrections are being done to increase productivity. Specific data of drive functionality, raw materials and amounts of final products are available to management at any moment via Internet. Information about status of embedded equipment, devices and protective elements provide planning periodical reviews and remont some lines or whole plant. Then replacement of certain parts significantly contributes to efficienty of current, preventive and investment maintenance. In this way, reliability and safety of production plant are increased. With complete automatization of production process that is complex and multidisciplinary, demages and energy consumption are considerably decreasing, workforce is optimized, good quality of final product is achieved and plant work with full capacity is provided. Some technical solutions (diesel engine and transformer station supervisory, compressor station supervisory, electric drive regulation, dedusting system control, HVAC (heating, ventilation, and air conditioning) system control, transport and dosage system control) applied at realization of supervisory and control system for mineral wool production process, can be also applied to regulation large number of industrial processes.
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Dong, Hai, Qing Quan Tong, and Yi Kai Wang. "Study on Quality Control Method in Multi-Specification and Small-Batch Production." Advanced Materials Research 1006-1007 (August 2014): 363–66. http://dx.doi.org/10.4028/www.scientific.net/amr.1006-1007.363.
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Aiming at the problem of less quality characteristics data in multi-specification and small-batch production, matter-element theory was applied to adjust similarity of factors affecting the quality during the processing, thus similar processes was divided and data shortage problem was resolved. In addition, the relative range method was applied to translate characteristics data, thus drawing the control chart to judge process control state.Through the analysis of a case,the validity of quality control method was verified in the multi-specification and small-batch production.
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García Plaza, E., P. Núñez López, and E. Beamud González. "Multi-Sensor Data Fusion for Real-Time Surface Quality Control in Automated Machining Systems." Sensors 18, no. 12 (December 11, 2018): 4381. http://dx.doi.org/10.3390/s18124381.
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Multi-sensor data fusion systems entail the optimization of a wide range of parameters related to the selection of sensors, signal feature extraction methods, and predictive modeling techniques. The monitoring of automated machining systems enables the intelligent supervision of the production process by detecting malfunctions, and providing real-time information for continuous process optimization, and production line decision-making. Monitoring technologies are essential for the reduction of production times and costs, and an improvement in product quality, discarding the need for post-process quality controls. In this paper, a multi-sensor data fusion system for the real-time surface quality control based on cutting force, vibration, and acoustic emission signals was assessed. A total of four signal processing methods were analyzed: time direct analysis (TDA), power spectral density (PSD), singular spectrum analysis (SSA), and wavelet packet transform (WPT). Owing to the nonlinear and stochastic nature of the process, two predictive modeling techniques, multiple regression and artificial neural networks, were evaluated to correlate signal parametric characterization with surface quality. The results showed a high correlation of surface finish with cutting force and vibration signals. The signal processing methods based on signal decomposition in a combined time and frequency domain (SSA and WPT) exhibited better signal feature extraction, detecting excitation frequency ranges correlated to surface finish. The artificial neural network model obtained the highest predictive power, with better behavior for the whole data range. The proposed on-line multi-sensor data fusion provided significant improvements for in-process quality control, with excellent predictive power, reliability, and response times.
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Fomin, S. Ya. "OPERATING DATA PROCESSING CONSOLE SYSTEM AUTOMATED COMMAND PROCESSOR DEVELOPMENT FOR LARGE-SCALE OPERATION PRODUCTION CONTROL. REPORT 1." Izvestiya Visshikh Uchebnykh Zavedenii. Chernaya Metallurgiya = Izvestiya. Ferrous Metallurgy 56, no. 3 (March 21, 2015): 48. http://dx.doi.org/10.17073/0368-0797-2013-3-48-55.
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Slevc, L. Robert, and Jared M. Novick. "Memory and cognitive control in an integrated theory of language processing." Behavioral and Brain Sciences 36, no. 4 (June 24, 2013): 373–74. http://dx.doi.org/10.1017/s0140525x12002683.
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AbstractPickering & Garrod's (P&G's) integrated model of production and comprehension includes no explicit role for nonlinguistic cognitive processes. Yet, how domain-general cognitive functions contribute to language processing has become clearer with well-specified theories and supporting data. We therefore believe that their account can benefit by incorporating functions like working memory and cognitive control into a unified model of language processing.
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Han, Qiang, and Wei Huang. "Control Method for Improving Efficiency of Digital Inkjet Printing." Advanced Materials Research 816-817 (September 2013): 467–70. http://dx.doi.org/10.4028/www.scientific.net/amr.816-817.467.
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Improving speed of digital inkjet printing is most important to put the digital inkjet printing over for industrial mass production. The factors that impact the speed of digital inkjet printing are data analyzed. A new high-efficiency control method that improving the data processing algorithm efficiency is described in this paper.
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Creamer, Nancy G., and Mark A. Bennett. "008 COVER CROP MANAGEMENT FOR PROCESSING TOMATO PRODUCTION." HortScience 29, no. 5 (May 1994): 428e—428. http://dx.doi.org/10.21273/hortsci.29.5.428e.
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A mixture of rye, hairy vetch, barley, and crimson clover was seeded on raised beds at two locations in Ohio in August, 1992. The following May, the mixture was killed with an undercutter and left on the surface as a mulch. Processing tomatoes (OH 8245) were planted into the killed cover crop mulch immediately following undercutting. Four systems of production were evaluated including: conventional (without cover crop mulch), integrated (with reduced chemical input), organic, and no additional input. At the Columbus site, above ground biomass (AGB) was 9,465 kg ha-1 with 207 kg ha-1 N in to AGB. In Fremont, the AGB was 14,087 kg ha-1 with 382 kg ha-1 N in the AGB. Annual weeds were suppressed by the killed cover crop mulch, and no additional weed control for the annual weeds was necessary. Weed suppression by the mulch was equivalent to weed suppression by the herbicides used in the conventional system. Other data that will be reported include soil moistures and temperatures; impact on insects end diseases; and, tomato growth, development, and yield.
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Jiang, Jun Hai, and Qian Zhang Zhuang. "A Study of Beer Fermentation Control System Based on the Technology of Computer Control." Applied Mechanics and Materials 713-715 (January 2015): 719–22. http://dx.doi.org/10.4028/www.scientific.net/amm.713-715.719.
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By analyzing the structure characteristics of fermented beer and has the function of system analysis, introduced in the fermentation process of beer, the use of computer technology, the real-time processing of beer fermentation temperature, pressure, the collection of data signal level etc.. The computer system to realize the automatic control and management on the beer fermentation process of beer fermentation, production management and cost will be greatly improved.
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Li, Xue Fen. "Research and Application of Tabular Processing Method of Serial Communicaiton Data in Excel." Applied Mechanics and Materials 241-244 (December 2012): 2934–39. http://dx.doi.org/10.4028/www.scientific.net/amm.241-244.2934.
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Connected with the Serial Communications data manage needed in the industry control, based on the methods of the Serial Communications program and circular queue data sink, with the introduction to Excel interactive objects and objects’s methods, this paper studies the EXCEL tabular methods through Visual C++. Through the electronic controlled high-pressure common-rail part production quality management system, the reliability and stability of the Serial Communications data Excel tabular have been verified.
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Lechner, Michael, Tassilo Christ, Philipp Frey, Simon Wituschek, Alexander Arzhanov, Fedor Petrov, and Marion Merklein. "Blockchain in der Blechverarbeitung/Blockchain in sheet metal processing." wt Werkstattstechnik online 110, no. 10 (2020): 704–8. http://dx.doi.org/10.37544/1436-4980-2020-10-60.
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Die Verfolgung von Bauteilen und Zwischenprodukten sowie die Erfassung eines vollständigen Produktionsdatensatzes sind in modernen Fertigungsketten eine wichtige Voraussetzung für die durchgängig digitale Produktion. Dieser Beitrag stellt die Lösung dieser Herausforderungen durch die Kombination zweier Systeme vor: Während eine blockchain-basierte Austauschplattform die Einhaltung der Anforderungen an die prozessübergreifende Vernetzung sicherstellt, kommt eine optische Technologie für die markierungsfreie Bauteilidentifizierung zum Einsatz. The ability to both track physical products and to gather a production data record are important elements of modern manufacturing processes and crucial requirements for an end-to-end digital production. This work presents a solution for both challenges based on the combination of two systems: While a blockchain-based data exchange platform ensures that the requirements towards networked processes are met, an optical technology for marker-free identification of component parts is used.
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TOMPKIN, R. B. "Control of Listeria monocytogenes in the Food-Processing Environment." Journal of Food Protection 65, no. 4 (April 1, 2002): 709–25. http://dx.doi.org/10.4315/0362-028x-65.4.709.
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The purpose of this paper is to provide guidance to food processors in controlling Listeria monocytogenes in food-processing environments. Of particular concern are outbreaks of a few to several hundred scattered cases involving an unusually virulent strain that has become established in the food-processing environment and contaminates multiple lots of food over days or months of production. The risk is highest when growth occurs in a food before it is eaten by a susceptible population. The information presented in this paper provides the basis for the establishment of an environmental sampling program, the organization and interpretation of the data generated by this program, and the response to Listeria–positive results. Results from such a program, including examples of niches, are provided. Technologies and regulatory policies that can further enhance the safety of ready-to-eat foods are discussed.
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Niu, Xiang Jie. "Data Acquisition and Transmission Method of the Quality Traceability for Poultry Processing." Applied Mechanics and Materials 380-384 (August 2013): 3561–65. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.3561.
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Traceable system, which is an effective way to control the quality and safety of agricultural products receives increasingly attention globally. Using the food safety of poultry processing as the research object, the paper builds a safety production management and quality trace system in order to achieve the goal of quality trace. Making detail analysis of the RFID data acquisition and compression delivery method, the author using wavelet compression technology to complete efficient delivery issues of tag identification and ensure delivery efficiency. This paper achieves the function of efficient transmission and tag-data acquisition in quality traceability system for poultry processing.
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Cheng, Huan Xin, Kai Zhang, and Li Cheng. "Design a Temperature Control System Based on Labview." Applied Mechanics and Materials 644-650 (September 2014): 95–98. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.95.
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Temperature is the main environment parameter to industrial and agricultural production. To timely and accurate measurement is having great significance. A lot of production equipment, thermal equipment and large warehouse need for temperature measurement. Therefore, design a kind of ability of temperature automatic detection system has widely application value. This design is mainly on the Labview virtual instrument platform to develop a temperature acquisition system. We use good interface of Labview for data acquisition which is real-time display data in Labview. It can realize serial port function and will transfer to PC owners system. The data collected in the Labview environment for data processing and analysis, and it can accord the analysis of the results to control the singlechip microcomputer temperature.
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Takács, Sándor, Istvánné Rácz, Erzsébet Csengeri, and Tibor Bíró. "Biomass production estimation of processing tomato using AquaCrop under different irrigation treatments." Acta Agraria Debreceniensis, no. 2 (December 15, 2019): 131–36. http://dx.doi.org/10.34101/actaagrar/2/3691.
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The wiser usage of irrigation water is inevitable in the future. Irrigation has very high input cost; therefore, farmers must carry out irrigation with care. Also, the effect of irrigation on crops has a big role in decision making. Modeling provides a possibility to evaluate this effect. AquaCrop, as a crop production simulation model has great potential in this field. The accuracy of tomato biomass yield prediction of the model was tested in this research. For collecting the necessary data, a field experiment was conducted at Szarvas on processing tomato with different water supplies, such as 100% (I100), 75% (I75), 50% (I50) of potential evapotranspiration and a control with basic water supply (C). The relation of the simulation and actual biomass yields was evaluated during the season. Very good correlation was found between the modelled and the actually harvested data. The data for the control and I100 treatments showed higher correlation than the I75 and I50. The relationship for all of the data was moderately strong. Miscalculations occur mostly when the dry biomass yield reaches 7 t ha-1. The accuracy of the model was evaluated with the use of mean absolute error (MAE) and root mean squared error (RMSE) values. The least error was found in the C treatment, which means 0.34 MAE and 0.45 t ha-1 RMSE. The simulation resulted in higher errors in the I75 and I50 treatments.
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Teutsch, C., and M. Prof Schenk. "Qualitätsdatengesteuerte Produktion*/Quality-driven Production - Technological trends in production." wt Werkstattstechnik online 107, no. 11-12 (2017): 793–97. http://dx.doi.org/10.37544/1436-4980-2017-11-12-17.
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Das konsequente Nutzen von Informationen aus dem Produktionsprozess für die optimale Steuerung von Maschinen und Anlagen ist einer der grundlegenden Ansätze der Industrie 4.0. Die Qualitätsdaten des resultierenden Produktes haben diesbezüglich eine besonders hohe Aussagekraft, denn diese lassen zuverlässige Rückschlüsse auf Abweichungen im Produktionsprozess zu. Setzt man die Daten des laufenden Produktionsprozesses in Korrelation zur produktindividuellen Qualität am Prozessende können qualitätskritische Prozessparameter und deren Schwankungen ermittelt und Qualitätsabweichungen, zum Beispiel durch Verschleiß, rechtzeitig prognostiziert werden. Darüber hinausgehend ermöglichen beispielsweise kontinuierlich ermittelte geometrische Qualitätsdaten und Formabweichungen die adaptive Berechnung optimaler Steuerungsparameter für NC-Bearbeitungsmaschinen, wodurch sich prädiktive Ansätze der Verschleißermittlung in neue präskriptive Ansätze zur adaptiven Steuerung wandeln. Daher ist die präzise Kenntnis dieser Ursache-Wirkung-Zusammenhänge heute ein entscheidender Wettbewerbsvorteil und eröffnet neue wirtschaftliche Potentiale. Am Beispiel der NC-Bearbeitung von Aluminiumrädern wird die praktische Umsetzung des Konzeptes diskutiert. The utilization of information from the production process for the optimal control of machines is one of the fundamentals of Industrie 4.0. The quality data of the resulting product allows to draw conclusions on production process deviations. By correlating continuous process data with the product‘s individual quality at the process end, dependencies can be determined that are critical to the quality or that lead to unwanted quality variations. The data dependencies can then be used to forecast process deviations, e.g. due to wear of tools. Furthermore, the geometric quality data can be used to adaptively reconstruct control parameters for NC machine tools and predictive approaches are transformed into new prescriptive approaches. A precise knowledge about the cause-effect relationship is a vital competitive advantage and provides new economic potentials. At the example of the NC processing of aluminum wheels the practical application of this concept is discussed.
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Tarkowski, Paweł, Ireneusz Malujda, Krzysztof Talaśka, Jan Górecki, Mateusz Kukla, and Dominik Wilczyński. "Recognition of Seat Elements during Production through Image Processing." Applied Mechanics and Materials 816 (November 2015): 35–42. http://dx.doi.org/10.4028/www.scientific.net/amm.816.35.
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The primary aim of the research, whose results are presented in this article, was to investigate the process of visual identification of objects. The objects recognised under this research were passenger seats for mass transit applications. The system presented in this paper is intended to be incorporated in the production process control system. The problem under analysis is based on the need to recognise (identify) an object located in the process area of the machine before proceeding with the process. Neural network was chosen as the adaptive element due to a high degree of similarity between the semi-products. The function of the network was to check if correct element had been fed. The input data fed to the network was the information from processing the photo images of these elements. The results of research as presented in this article are based on a limited set of elements and present the method used for solving the task of identification.
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Oborski, Przemysław. "Integrated Monitoring System of Production Processes." Management and Production Engineering Review 7, no. 4 (December 1, 2016): 86–96. http://dx.doi.org/10.1515/mper-2016-0039.
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Abstract Integrated monitoring system for discrete manufacturing processes is presented in the paper. The multilayer hardware and software reference model was developed. Original research are an answer for industry needs of the integration of information flow in production process. Reference model corresponds with proposed data model based on multilayer data tree allowing to describe orders, products, processes and save monitoring data. Elaborated models were implemented in the integrated monitoring system demonstrator developed in the project. It was built on the base of multiagent technology to assure high flexibility and openness on applying intelligent algorithms for data processing. Currently on the base of achieved experience an application integrated monitoring system for real production system is developed. In the article the main problems of monitoring integration are presented, including specificity of discrete production, data processing and future application of Cyber-Physical-Systems. Development of manufacturing systems is based more and more on taking an advantage of applying intelligent solutions into machine and production process control and monitoring. Connection of technical systems, machine tools and manufacturing processes monitoring with advanced information processing seems to be one of the most important areas of near future development. It will play important role in efficient operation and competitiveness of the whole production system. It is also important area of applying in the future Cyber-Physical-Systems that can radically improve functionally of monitoring systems and reduce the cost of its implementation.
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Zhang, Jing, Na Li, Jie Yang, and Na Lv. "The Application of OLAP in Logistics System of Steel-Production." Applied Mechanics and Materials 577 (July 2014): 1296–99. http://dx.doi.org/10.4028/www.scientific.net/amm.577.1296.
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The cost control of Enterprises, logistics cost has become one of the important components. In this paper, based on SQL Server2000 database steel production logistics information multi-dimensional data set is established based on the on-line analytical processing (OLAP) base. The production logistics information data of steelmaking workshop in the data mining process come true, which will help enterpriser to make decisions.
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Xin-chun, Chen, Ding Peng, Yan Nai-qing, and Bi Meng-xue. "Study on Discrete Manufacturing Quality Control Technology Based on Big Data and Pattern Recognition." Mathematical Problems in Engineering 2021 (February 19, 2021): 1–10. http://dx.doi.org/10.1155/2021/8847094.
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Aiming at the quality control problems in the discrete manufacturing process of large and superlarge equipment, which cannot meet the urgent needs of production, a quality control method based on big data and pattern recognition is proposed. A large amount of data is collected through the test equipment developed in the discrete manufacturing process; a database of typical working conditions and an information tracking system relying on the cloud platform were formed. The working conditions were divided by the principal component analysis (PCA) and improved K-means algorithm. The Markov prediction model predicts the working conditions, recognizes the pattern with typical working conditions, regulates the processing parameters, and achieves quality control. Taking the quality control of the hydraulic cylinder manufacturing process above 5 m as an example for experimental verification, the experiments indicated that working conditions can be automatically identified and classified through pattern recognition technology. The process capability index Cpk increased from 0.6 to 1, which proved the effectiveness of quality control and the improvement of processing capabilities.
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Zhong, Tao, Pei Jie Lou, Hong Xin Ruan, and Bo Zhang. "Construction of Coal Mine Comprehensive Informatization Based on Kilomega Fiber-Optic Industry Ether Ring Network." Applied Mechanics and Materials 88-89 (August 2011): 448–53. http://dx.doi.org/10.4028/www.scientific.net/amm.88-89.448.
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Based on the enhancement of coal mine integrated automation, building safety in automatical production and scheduling control system are increasingly improving with advanced technology, higher informatization level and powerful processing ability. This paper foucs on the comprehensive industry network of kilomega fiber-optic industry ether ring network, and presents synthesized automation software platform which is object-oriented and possesses the function of distributed processing, which aims to achieve data collection, processing, storage and browsing for every subsystem of coal mine production. On this basis, we design a set of scheduling control system in terms of comprehensive display for monitor information of coal mine production and various kinds of office equipment applied to scheduling control centre. It provides a high quality platform for coal mine comprehensive informatization in Bao Dian.
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Мельников, Владимир, Vladimir Mel'nikov, Светлана Демина, and Svetlana Demina. "ANOMALIES IN AUTOMATION CONTROL OF MODERL HUMAN LABOR ACTIVITIES." Bulletin of Bryansk state technical university 2018, no. 7 (October 4, 2018): 82–90. http://dx.doi.org/10.30987/article_5ba8a18e7ba2b6.07654141.
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The purpose of this work consisted in the study of trends and automation problems in separate spheres of human labor activities and in search of possible me-thods and means of production robotization control in Russia.
As a result of the use of the data statistical processing method and a comparative analysis of re-sults the authors have got revealed anomalies and structural disproportions in automation processes of human labor activities conditioned on man substitution by a machine to save labor as a factor of production.
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Звягинцева, Алла, Alla Zvyaginceva, Светлана Сазонова, Svetlana Sazonova, Виктор Асминин, and Viktor Asminin. "PROCESS MODELING AND IMPROVEMENT OF MEASURES TO IMPROVE WORKING CONDITIONS AT THE MINING AND PROCESSING PLANT." Modeling of systems and processes 12, no. 2 (October 24, 2019): 10–16. http://dx.doi.org/10.12737/article_5db1e3e5eab7b3.03295200.
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The data of field measurements of harmful production factors at JSC "Lebedinsky GOK" in the working areas and at the enterprise as a whole are given. The data correspond to the types of official control and monitoring of the current state of the situation in the enterprise. The impact of harmful production factors in the workplace on the health of personnel, as well as the dust released during the work on environmental pollution of the adjacent territories is considered. The analysis of the results of control activities and existing environmental measures with a view to their improvement. The proposed types of control have been proposed to be used to improve working conditions in industries with increased exposure to harmful production factors due to the improvement of the types of control carried out and the necessary measures.
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Valeriani, Davide, and Kristina Simonyan. "The dynamic connectome of speech control." Philosophical Transactions of the Royal Society B: Biological Sciences 376, no. 1836 (September 6, 2021): 20200256. http://dx.doi.org/10.1098/rstb.2020.0256.
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Speech production relies on the orchestrated control of multiple brain regions. The specific, directional influences within these networks remain poorly understood. We used regression dynamic causal modelling to infer the whole-brain directed (effective) connectivity from functional magnetic resonance imaging data of 36 healthy individuals during the production of meaningful English sentences and meaningless syllables. We identified that the two dynamic connectomes have distinct architectures that are dependent on the complexity of task production. The speech was regulated by a dynamic neural network, the most influential nodes of which were centred around superior and inferior parietal areas and influenced the whole-brain network activity via long-ranging coupling with primary sensorimotor, prefrontal, temporal and insular regions. By contrast, syllable production was controlled by a more compressed, cost-efficient network structure, involving sensorimotor cortico-subcortical integration via superior parietal and cerebellar network hubs. These data demonstrate the mechanisms by which the neural network reorganizes the connectivity of its influential regions, from supporting the fundamental aspects of simple syllabic vocal motor output to multimodal information processing of speech motor output. This article is part of the theme issue ‘Vocal learning in animals and humans’.
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Romanenko, N. "PRODUCTION HAZARDS ASSESSMENT IN THE OPERATION OF FOOD PROCESSING EQUIPMENT." Labour protection problems in Ukraine 35, no. 1 (July 2, 2019): 25–30. http://dx.doi.org/10.36804/nndipbop.35-1.2019.25-30.
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According to official statistics, the food industry is characterized by high rates of injury. An important role in preventing occupational injuries is played by the analysis of the causes and circumstances of accidents and, first of all, the bringing of its results to all structural units and employees. The purpose of the article is research and evaluation of industrial hazards during the operation of food industry equipment, scientific substantiation of priority directions of the prevention of traumatism at food enterprises. On the basis of the data of the special investigation of accidents at the Ukrainian industry, an injury analysis was conducted at food industry enterprises. Identified hazardous factors in the operation of food industry equipment. It has been determined that more than a third of injured people were injured when using cars. The second position is accidents related to technological equipment for the food, meat, dairy and fish industry. The main types of events that resulted in injuries include traffic accidents, including traffic accidents on public roads (roads) and on the territory of the enterprise, the effect of moving objects, flying, turning and falling of the victim. The state of professional training in the field of occupational safety of the victims was investigated. Distribution of accidents on causes of occurrence taking into account types of productions has been carried out. It was found that the most traumatic are the production of dairy products and the production of bread, bakery and flour products. The areas of injury in both types of production are: violations of traffic safety rules, violations of labor and production discipline, including non-fulfillment of official duties, requirements of instructions for occupational safety, unsatisfactory technical condition of industrial objects, buildings, structures of engineering communications, territories, means production, vehicles. In order to prevent injuries among food industry workers it is expedient: to provide the proper technical condition of production equipment; to strengthen control over the observance of the requirements of the technological process, the rules of labor protection in the performance of work of increased danger; to ensure the availability of modern means of individual and collective protection and to strengthen control over their use; to implement effective methods of teaching safe working methods.
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Scanlon, Michael, Vikram Sharma, and Georg Zangl. "Model centric production management systemsy—opportunity and challenges." APPEA Journal 50, no. 2 (2010): 690. http://dx.doi.org/10.1071/aj09054.
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While modelling technology is routinely used in oil and gas to control and optimise process facilities and downstream plants, the upstream sector has been slow to adopt model-based control systems, or the models are very coarse and mono-dimensional, reducing confidence in their predictive capability. Further, the models are discipline specific, and the interdependence between the subsurface and the surface is poorly evaluated. This is particularly relevant to coal seam gas developments, where well productivity planning and management needs to be considered in the context of the complete production value chain, and the dependencies between the gathering system and the processing plants considered in optimising the contract nominations. A key breakthrough technology will be a model-based control system that can assimilate all the available data, put the data into context, represent the full value chain, assess the relative impact of the components of the production train, and then assess the decision alternatives in the context of deliverability, processing cost, HSE and market opportunity in sufficient time to have an impact. Advances in data acquisition, transmission and storage, coupled with advances in computational efficiency and software engineering, mean that integrated modelling systems are realisable today.Collaboration between technology providers has delivered software tools that offer a unified perspective across the subsurface, surface gathering systems and facility worlds. The presentation will explore the technology capability, the application opportunity and organisational requirement to fully realise the potential of integrated asset models.
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Mazak, Alexandra, Arndt Lüder, Sabine Wolny, Manuel Wimmer, Dietmar Winkler, Konstantin Kirchheim, Ronald Rosendahl, Hessamedin Bayanifar, and Stefan Biffl. "Model-based generation of run-time data collection systems exploiting AutomationML." at - Automatisierungstechnik 66, no. 10 (October 25, 2018): 819–33. http://dx.doi.org/10.1515/auto-2018-0022.
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Abstract Production system operators need support for collecting and pre-processing data on production systems consisting of several system components, as foundation for optimization and defect detection. Traditional approaches based on hard-coded programming of such run-time data collection systems take time and effort, and require both domain and technology knowledge. In this article, we introduce the AML-RTDC approach, which combines the strengths of AutomationML (AML) data modeling and model-driven engineering, to reduce the manual effort for realizing the run-time data collection (RTDC) system. We evaluate the feasibility of the AML-RTDC approach with a demonstration case about a lab-sized production system and a use case based on real-world requirements.
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Hanson, Eric N., and Jennifer Widom. "An overview of production rules in database systems." Knowledge Engineering Review 8, no. 2 (June 1993): 121–43. http://dx.doi.org/10.1017/s0269888900000126.
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AbstractDatabase researchers have recognized that integrating a production rules facility into a database system provides a uniform mechanism for a number of advanced database features including integrity constraint enforcement, derived data maintenance, triggers, protection, version control, and others. In addition, a database system with rule processing capabilities provides a useful platform for large and efficient knowledge-base and expert systems. Database systems with production rules are referred to as active database systems, and the field of active database systems has indeed been active. This paper summarizes current work in active database systems, and suggests future research directions. Topics covered include database rule languages, rule processing semantics, and implementation issues.
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Bruce, George J., and Kenneth Reay. "Cost-Effective Planning and Control." Journal of Ship Production 7, no. 03 (August 1, 1991): 183–87. http://dx.doi.org/10.5957/jsp.1991.7.3.183.
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Situations have frequently been encountered where It Is necessary to reestablish control of a shipbuilding contract when it has been lost. This has to be done quickly, and requires a combination of an effective planning and control system with a computer for data processing. Expediency dictates the use of readily available PCs and proprietary software. The approach adopted was found to be robust and effective, and has been used as a basis for development of more formal planning and control systems. These are now in use as the means of planning and implementing ship production.
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Li, Xilin, Malcolm S. Powell, and Tim Horberry. "Human Factors in Control Room Operations in Mineral Processing." Journal of Cognitive Engineering and Decision Making 6, no. 1 (January 5, 2012): 88–111. http://dx.doi.org/10.1177/1555343411432340.
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This study applied human factors research approaches to the complex and dynamic environment of mineral processing plants. In this domain, little formal human factors research has previously been undertaken, despite that human performance limitations are frequently noted as a bottleneck to effective production. This article presents a broad, operator-centered investigation on the current status of control room operations and explores the underlying barriers in the operators’ work environment. A total of 20 operators working at two types of Australian mineral processing plants were involved. Multiple data collection methods, including in situ observations and interviews, surveys, and reviews of documentation, were used. The findings revealed that operator control was essentially in a reactive mode, with operators often lacking the will or ability to engage in process optimization. A simplified work domain analysis was used to highlight the essential elements involved in operator control and to explore the gaps between the observed reactive behavior and the required proactive control employed by operators. Also, this study uncovered deficiencies in the current information and organizational environments constraining operator control ability. These deficiencies included poorly designed human-machine interface and alarms, insufficient operator training, and inappropriate task allocations. Further research for enhancing operator capacity is recommended and highlighted.
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Francaviglia, Rosa, and Claudia Di Bene. "Deficit Drip Irrigation in Processing Tomato Production in the Mediterranean Basin. A Data Analysis for Italy." Agriculture 9, no. 4 (April 19, 2019): 79. http://dx.doi.org/10.3390/agriculture9040079.
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In this study, the effects of deficit irrigation (DI) on crop yields and irrigation water utilization efficiency (IWUE) of processing tomato are contrasting. This study aimed at analyzing a set of field experiments with drip irrigation available for Mediterranean Italy in terms of marketable yields and IWUE under DI. Both yields and IWUE were compared with the control treatment under full irrigation, receiving the maximum water restoration (MWR) in each experiment. The study also aimed at testing the effect of climate (aridity index) and soil parameters (texture). Main results indicated that yields would marginally decrease at 70–80% of MWR and variable irrigation regimes during the crop cycle resulted in higher crop yields. However, results were quite variable and site-dependent. In fact, DI proved more effective in fine textured soils and semiarid climates. We recommend that further research should address variable irrigation regimes and soil and climate conditions that proved more unfavorable in terms of crop response to DI.
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Pruin, B., A. Martini, P. Shanmugam, and C. Lopes. "The Swarm Archiving Payload Data Facility, an Instance Configuration of the ESA Multi-Mission Facility." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W3 (April 29, 2015): 685–89. http://dx.doi.org/10.5194/isprsarchives-xl-7-w3-685-2015.
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The Swarm mission consists of 3 satellites, each carrying an identical set of instruments. The scientific algorithms for processing are organized in 11 separate processing steps including automated product quality control. In total, the mission data consists of data products of several hundred distinct types from raw to level 2 product types and auxiliary data. The systematic production for Swarm within the ESA Archiving and Payload Data Facility (APDF) is performed up to level 2. The production up to L2 (CAT2-mature algorithm) is performed completely within the APDF. A separate systematic production chain from L1B to L2 (CAT1-evolving algorithm) is performed by an external facility (L2PS) with output files archived within the APDF as well. The APDF also performs re-processing exercises. Re-processing may start directly from the acquired data or from any other intermediate level resulting in the need for a refined product version and baseline management. <br><br> Storage, dissemination and circulation functionality is configurable in the ESA generic multi-mission elements and does not require any software coding. The control of the production is more involved. While the interface towards the algorithmic entities is standardized due to the introduction of a generic IPF interface by ESA, the orchestration of the individual IPFs into the overall workflows is distinctly mission-specific and not as amenable to standardization. The ESA MMFI production management system provides extension points to integrate additional logical elements for the build-up of complex orchestrated workflows. These extension points have been used to inject the Swarm-specific production logic into the system. A noteworthy fact about the APDF is that the dissemination elements are hosted in a high bandwidth infrastructure procured as a managed service, thus affording users a considerable access bandwidth. <br><br> This paper gives an overview of the Swarm APDF data flows. It describes the elements of the solution with particular focus on how the available generic multi-mission functionality of the ESA MMFI was utilized and where there was a need to implement missionspecific extensions and plug-ins. The paper concludes with some statistics on the system output during commissioning and early operational phases as well as some general considerations on the utilization of a framework like the ESA MMFI, discussing benefits and pitfalls of the approach.
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Darno, Darno, Anita Anita, Jaya Adi Gama Tengtarto, Kuswana Rama, and Camelia Dewi R. "EVALUASI SISTEM PENGENDALIAN INTERNAL BAHAN BAKU PRODUKSI PADA UD. XYZ DI SIDOARJO." Jurnal Logistik Indonesia 5, no. 1 (December 1, 2020): 65–72. http://dx.doi.org/10.31334/logistik.v5i1.1187.
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The era of globalization, the industrial world is increasingly developing, there are many companies engaged in the industry that manage various kinds of products, there will be more competitive competition. The development of the company is increasing rapidly, with the level of use and need for raw materials that are relatively large and increasing consumer demand. Raw material inventory control system for its role is needed in companies with existing theories. The author intends to analyze "Evaluation Of The Internal Control System For Raw Material For The Smoothness Of The Production Prosess (Case Study at UD. XYZ di Sidoarjo)". The purpose of this study is to find out how the internal control system for raw material inventory can be used to facilitate all production processes or processing of raw materials at UD. Light Plastic Sidoarjo. The data analysis technique used and carried out is a qualitative descriptive technique, which is to compare the collected data on a theoretical basis as a reference material that provides several suggestions for problem solvers in writing. Based on the results of research that can be done that the processing process in the company includes: the stage of purchasing raw materials, the stage of storing raw materials, the processing stage, the distribution stage. The research was conducted using a case study approach with qualitative methods. Data collection methods are carried out, namely interviews, observation and documentation. Based on the analysis, it is concluded that the internal control system for raw material inventory can expedite the processing or production process in the company which is said to be good, but there are still some weaknesses, namely concurrency in work, lack of monitoring of the production process or processing time and the entry and exit of goods in the company.
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Alkadi, Ihssan. "Data Mining." Review of Business Information Systems (RBIS) 12, no. 1 (January 1, 2008): 17–24. http://dx.doi.org/10.19030/rbis.v12i1.4394.
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Recently data mining has become more popular in the information industry. It is due to the availability of huge amounts of data. Industry needs turning such data into useful information and knowledge. This information and knowledge can be used in many applications ranging from business management, production control, and market analysis, to engineering design and science exploration. Database and information technology have been evolving systematically from primitive file processing systems to sophisticated and powerful databases systems. The research and development in database systems has led to the development of relational database systems, data modeling tools, and indexing and data organization techniques. In relational database systems data are stored in relational tables. In addition, users can get convenient and flexible access to data through query languages, optimized query processing, user interfaces and transaction management and optimized methods for On-Line Transaction Processing (OLTP). The abundant data, which needs powerful data analysis tools, has been described as a data rich but information poor situation. The fast-growing, tremendous amount of data, collected and stored in large and numerous databases. Humans can not analyze these large amounts of data. So we need powerful tools to analyze this large amount of data. As a result, data collected in large databases become data tombs. These are data archives that are seldom visited. So, important decisions are often not made based on the information-rich data stored in databases rather based on a decision maker's intuition. This is because the decision maker does not have the tools to extract the valuable knowledge embedded in the vast amounts of data. Data mining tools which perform data analysis may uncover important data patterns, contributing greatly to business strategies, knowledge bases, and scientific and medical research. So data mining tools will turn data tombs into golden nuggets of knowledge.
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JONES, F. T., R. C. AXTELL, D. V. RIVES, S. E. SCHEIDELER, F. R. TARVER, R. L. WALKER, and M. J. WINELAND. "A Survey of Campylobacter jejuni Contamination in Modern Broiler Production and Processing Systems." Journal of Food Protection 54, no. 4 (April 1, 1991): 259–62. http://dx.doi.org/10.4315/0362-028x-54.4.259.
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Campylobacter jejuni contamination was surveyed in samples collected from the breeder-multiplier houses, broiler houses, feed mills, hatcheries, and processing plants of two integrated broiler firms. Insects and mice were also trapped at each location. C. jejuni was most frequently found in samples collected from processing plants, followed by samples collected from broiler houses, and breeder-multiplier houses. Samples obtained from feed mills and hatcheries were negative, suggesting that the C. jejuni was not transmitted by either feed or eggs. C. jejuni was also not isolated from insect or mouse samples. However, the external surfaces of insects were sanitized with a chlorine solution, prior to analysis. Thus, these data suggest any contamination of insects with C. jejuni is generally external not internal. Contamination in broilers apparently originated from some unknown source(s) in broiler houses. C. jejuni was isolated from 20% of the cloacal swabs taken as birds entered the plant, 52% of the carcasses sampled following immersion chilling, and 31.6% of whole broiler carcasses sampled at retail outlets. While these data suggest that cross-contamination occurred within processing plants, field control methods would appear to be necessary for control of C. jejuni in modern broiler production and processing systems. The frequent C. jejuni isolations from dead birds in broiler houses suggested the regular collection of normal mortality as one farm management procedure that might help reduce Campylobacter contamination in broilers.
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Owusu-Mensah, Daniel, Ren Naifei, Lydia Brako, Priscilla Boateng, and Williams Kweku Darkwah. "Analysis of Production System Management of Ghana’s Food and Beverage Industry: Empirical evidence from Spare Parts Inventory Control, Production Quality and Maintenance Modeling." Journal of Food Industry 4, no. 1 (April 13, 2020): 1. http://dx.doi.org/10.5296/jfi.v4i1.16511.
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The production systems of various industries have increasingly become a strategic business management function that drives differentiation and competitive edge. Production plant maintenance is therefore an integral part of an entire production system management function, which should encapsulate spare part inventory control systems, total quality assurance, improvement measures and cost control measures. This project sought to understand the production process of firms in Ghana’s food and beverage industry, assess the spare part inventory management practices, production quality control practices and maintenance management strategies implemented in order to recommend a maintenance optimization modeling system towards ensuring an optimal operation cost and production quality. Using both the inductive and deductive research approaches, the research project was exploratory and explanatory in nature. Three major players in Ghana’s food and beverage industry: GIHOC-DCL (Ghana Industrial Holding Corporation Distillery Limited), Heathy-Life Ghana Limited (Healthy-Life) and Parlays Ghana Limited (Parlays) were purposively sampled as industrial case studies to generate data from documentary secondary data and survey based sources. The functionality tools available in MATLAB/Simulink software assisted in formulating the maintenance optimization problem, modeling, analyzing and deriving solutions. The study found that the food and beverage processing business in Ghana has a positive correlation with the main agricultural produce of the country and involves a series of activities including processing and preservation of meat, fish, fruit, vegetables, starch products, bread and sugar. Spare part inventory management and quality control tools mainly applied include Statistical Control Charts and Check Sheet rather than optimization models and software.
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JONES, F. T., R. C. AXTELL, D. V. RIVES, S. E. SCHEIDELER, F. R. TARVER, R. L. WALKER, and M. J. WINELAND. "A Survey of Salmonella Contamination in Modern Broiler Production." Journal of Food Protection 54, no. 7 (July 1, 1991): 502–7. http://dx.doi.org/10.4315/0362-028x-54.7.502.
Full textAbstract:
A survey of contamination with Salmonella was done in the breeder/multiplier and broiler houses, feed mills, hatcheries, and processing plants of two integrated broiler firms. Samples of insects and mice were also collected at each location. Sixty percent (60%) of the meat and bone meal samples collected at feed mills were contaminated. Salmonella was isolated from 35% of the mash feed samples tested. The pelleting process reduced Salmonella isolation rates by 82.0%. Data collected from breeder/multiplier houses suggested that feed was the ultimate source of Salmonella contamination in that environment. Salmonella was found in 9.4% of the yolk sac samples collected from day-old chicks in hatcheries. Fecal dropping samples collected in broiler houses about one week prior to slaughter were contaminated at a rate of 5.2%. Salmonella was found in 33% of the samples collected from live haul trucks and 21.4% of the whole processed broiler carcasses sampled at processing plants. Salmonella typhimurium was the serotype most commonly isolated. The gastrointestinal tract of one of 19 mice sampled was contaminated with Salmonella. Data suggest that insects were primarily mechanical carriers. Results suggest Salmonella contamination in the U.S. broiler production and processing system has changed little since 1969. The data also underline the contention that effective Salmonella control efforts must be comprehensive.
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Zhang, Chong Shan, Shao Hong Jing, Qi Long Ma, and Liu Gang Shi. "The Design and Implementation of Remote Optimization and Control System of Cement Industry." Applied Mechanics and Materials 631-632 (September 2014): 698–701. http://dx.doi.org/10.4028/www.scientific.net/amm.631-632.698.
Full textAbstract:
With the rapid development of cement industry in China, looseness of information management and hardness of production line optimization control have became an utmost important issue. In this paper, we design and implement a remote optimization and control system via B/S architecture, which is under the model of ASP.NET MVC. Conclusively,this system implements the functions which are data analysis and processing of cement enterprises,optimization control of production line and meta-analysis of enterprise information.