Academic literature on the topic 'Production planning Australia Data processing Case studies'
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Journal articles on the topic "Production planning Australia Data processing Case studies"
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Sugimura, Nobuhiro, Koji Iwamura, and Tomohiko Maeda. "Special Issue on Production Planning and Scheduling." International Journal of Automation Technology 9, no. 3 (May 5, 2015): 209. http://dx.doi.org/10.20965/ijat.2015.p0209.
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This issue focuses on production planning and scheduling for production system and the related problems that have arisen in these areas in the last half century as digital computer systems developed. These problems relate to production management, production planning, shop floor control, product design and process planning. In the first stage of production planning and scheduling systems R&D, optimization is a key issue that has been widely discussed and many theories and optimization algorithms proposed. Rule-based methods are discussed as potential solutions to these problems. With rapid advances in computer and information processing technologies and performance, tremendous progress has been made in the areas of production systems such as production planning, production scheduling, advances production systems (APS), enterprise resource planning (ERP), just-in time (JIT) processes, the theory of constraint (TOC), product data management (PDM) and computer-aided design / manufacturing / engineering (CAD/CAM/CAE). This special issue addresses the latest research advances, applications, and case studies in production planning and scheduling covering such as decentralized and autonomous production systems, distributed simulation models, robust capacity planning models, wireless sensor networks for production systems and applications to automotive component and steel production. We hope that learning about these advances will enable readers to share their own experience and knowledge in technology, new developments and the potential applications of production planning and scheduling methods and solutions.
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Campos-Andaur, Paulina, Karen Padilla-Lobo, Nicolás Contreras-Barraza, Guido Salazar-Sepúlveda, and Alejandro Vega-Muñoz. "The Wine Effects in Tourism Studies: Mapping the Research Referents." Sustainability 14, no. 5 (February 23, 2022): 2569. http://dx.doi.org/10.3390/su14052569.
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This research provides an empirical overview of articles and authors referring to research on wine tourism, analyzed from 2000 to 2021, and what they contribute to deepening the Sustainable Development Goals (SDGs) 8. The articles were examined through a bibliometric approach based on data from 199 records stored in the Web of Science (JCR), applying traditional bibliometric laws, and using VOSviewer for data processing and metadata. The results highlight an exponential increase in scientific production without interruptions between 2005 and 2020, with a concentration in only 35 highly cited authors, where the hegemony is held by Australia, among the co-authorship networks of worldwide relevance. The main topics observed in the literature are local development through wine tourism, sustainability and nature conservation, and strategies for sustainable development. Finally, there are six articles with great worldwide influence in wine tourism studies that maintain in their entirety the contribution made by researchers affiliated with Australian universities.
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Hoffman, Ralph E. "Verbal hallucinations and language production processes in schizophrenia." Behavioral and Brain Sciences 9, no. 3 (September 1986): 503–17. http://dx.doi.org/10.1017/s0140525x00046781.
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AbstractHow is it that many schizophrenics identify certain instances of verbal imagery as hallucinatory? Most investigators have assumed that alterations in sensory features of imagery explain this. This approach, however, has not yielded a definitive picture of the nature of verbal hallucinations. An alternative perspective suggests itself if one allows the possibility that the nonself quality of hallucinations is inferred on the basis of the experience of unintendedness that accompanies imagery production. Information-processing models of “intentional” cognitive processes call for abstract planning representations that are linked to goals and beliefs. Unintended actions - and imagery - can reflect planning disruptions whereby cognitive products do not cohere with concurrent goals. A model of schizophrenic speech disorganization is presented that postulates a disturbance of discourse planning. Insofar as verbal imagery can be viewed as inwardly directed speech, a consequence of such planning disturbances could be the production of unintended imagery. This link between the outward disorganization of schizophrenic speech and unintended verbal imagery is statistically supported by comparing the speech behavior of hallucinating and nonhallucinating schizophrenics. Studies of “borderline” hallucinations during normal, “goal-less” relaxation and drowsiness suggest that experiential unintendedness leads to a nonpathological variant of hallucinatory otherness that is correctable upon emerging from such passive cognitive states. This contrasts with the schizophrenic case, where nonconcordance with cognitive goals reinforces the unintendedness of verbal images and sustains the conviction of an external source. This model compares favorably with earlier models of verbal hallucinations and provides further evidence for a language production disorder in many schizophrenics.Short Abstract: How is it that many schizophrenics identify certain instances of verbal imagery as hallucinatory? This paper proposes that the critical feature identifying hallucinations is the experience of unintendedness. This experience is nonpathological during passive conscious states but pathological if occurring during goal-directed cognitive processing. A model of schizophrenic speech disorganization is presented that postulates a disturbance of discourse planning that specifies communicative intentions. These alterations could generate unintended verbal imagery as well. Statistical data are offered to support the model, and relevant empirical studies are reviewed.
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Wrigley, CW. "Developing better strategies to improve grain quality for wheat." Australian Journal of Agricultural Research 45, no. 1 (1994): 1. http://dx.doi.org/10.1071/ar9940001.
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There are opportunities to improve the quality and-market value of wheat grain at all stages of production, storage and transport. An essential pre-requisite is a thorough knowledge of market requirements, both for the coming crop season and well into the future in the case of breeding programs and research planning. Elucidation of the molecular basis of grain quality is an important part of the overall strategy of quality improvement. The outcome expected from such studies will be the identification of key chemical components that can serve as markers for specific aspects of grain quality. The provision of screening tests for these marker compounds then permits intelligent quality testing at harvest, planning of genotype and environment to maximize quality, and selection of suitable genotypes at an early stage of breeding. This review describes the state of our present knowledge of grain quality at the molecular/chemical level (with particular references to dough quality for wheat), and it indicates how this knowledge can be put to practical use in better suiting wheat grain for processing requirements both in Australia and overseas.
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Lu, Ming, Fei Dai, and Wu Chen. "Real-time decision support for planning concrete plant operations enabled by integrating vehicle tracking technology, simulation, and optimization algorithms." Canadian Journal of Civil Engineering 34, no. 8 (August 1, 2007): 912–22. http://dx.doi.org/10.1139/l07-029.
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By integrating the vehicle tracking system, discrete-event simulation algorithm, and evolutionary optimization algorithm, we developed HKCONSIM-Realtime, a decision-support platform created specifically for handling ready-mixed concrete operations. This platform is capable of (1) tracking the positions of concrete trucks and monitoring the motion and status of concrete deliveries in real time, (2) transforming the tracking records into data that provide updated input to simulation, and (3) optimizing the operations and logistics of concrete production based on simulation of the production system using the most current data. This paper presents an overview of the design and development of (1) the hardware and software modules, (2) the data flow and processing throughout the system, and (3) the role of the system in providing interactive, effective support for the human operator to attain cost efficiency. Case studies are given to demonstrate the functionality and application of the prototype system. Key words: simulation, optimization, vehicle tracking, construction planning, ready-mixed concrete, Hong Kong.
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Slepnev, Mihail A., and Anwar Sabeeh Al-qatrany. "Development of an urban planning information system for settlements located in oil production areas: the case of Al-Zubair district in Basra governorate." Vestnik MGSU, no. 5 (May 2022): 559–68. http://dx.doi.org/10.22227/1997-0935.2022.5.559-568.
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Introduction. Oil production areas are highly damaged in Al-Zubair district. However, they border residential and industrial zones, water areas, and farmlands. The local transport infrastructure demonstrates rapid growth. Al-Zubair district is also home to a largest oilfield in Basra governorate. The oilfield is an important factor of the country’s economic development and an employer for the residents of Basra and other Iraqi governorates. The programme, focused on the development of an urban planning information system, proposed by the authors for oil production areas, encompasses information gathering and processing, database provisioning, data analyzing and processing. The ArcGIS cartographic system will be used to make base maps of urban environments. Field studies have been conducted in the areas of environmental degradation, intervention and imbalance. The preparatory work included information gathering, photographing, and using GPS to determine the location of the areas under research. The purpose of the study is to identify the areas, that are potentially fit for human habitation, and analyze alternative inventory accounting models of oil production areas using three project proposals.
Materials and methods. Standard measuring instruments and navigation devices, such as Garmin GPS controller, were used to collect the information to be further added to the database and processed using statistical methods. GIS systems (Arc Map 10.3) and Microsoft excel were used to make digital maps; the remote sensing method and open data were also employed. A camera was used to make photos of particular objects. Firstly, the information was collected and added to the controller database, then it was forwarded to a computer system as vector data to make a digital map and develop design solutions.
Results. The purpose of the new urban planning information system is to assess the local living conditions and ensure the sustainable development of populated areas in the Al-Zubair district of Basra Governorate, the Republic of Iraq.
Conclusions. The proposed method of using an ecological mapping system to identify the areas potentially fit for human habitation will improve the quality of urban planning, enhance the environment in oil production areas and ensure their sustainable development. These areas need area development plans, that comply with the standards for residential areas located in oil production neighbourhoods.
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Šulyová, Dominika, and Gabriel Koman. "The Significance of IoT Technology in Improving Logistical Processes and Enhancing Competitiveness: A Case Study on the World’s and Slovakia’s Wood-Processing Enterprises." Sustainability 12, no. 18 (September 21, 2020): 7804. http://dx.doi.org/10.3390/su12187804.
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The wood-processing industry currently does not sufficiently use modern technologies, unlike the automotive sector. The primary motive for writing this article was in cooperation with a Slovak wood processing company, which wanted to improve its logistics processes and increase competitiveness in the wood processing sector through the implementation of new technologies. The aim of this article was to identify the positives and limitations of the implementation of Internet of Things (IoT) technology into the wood processing industry, based on a secondary analysis of case studies and the best practice of American wood processing companies such as West Fraser Timber in Canada, and Weyerhaeuser in the USA. The selection of case studies was conditional on criteria of time relevance, size of the sawmills, and production volume in m3. These conditional criteria reflected the conditions for the introduction of similar concepts for wood-processing enterprises in Slovakia. The implementation of the IoT can reduce operating costs by up to 20%, increase added value for customers, and collect real-time data that can serve as the basis for support of management and decision-making at the operational, tactical, and strategic levels. In addition to the secondary analysis, methods of comparison of global wood processing companies, synthesis of knowledge, and summarization of positives and limitations of IoT implementation or deduction were used to reach our conclusions. The results were used as the basis for the design of a general model for the implementation of IoT technology for Slovak wood processing enterprises. This model may represent best practice for the selected locality and industry. The implications and verification of the designed model in practice will form part of other research activities, already underway in the form of a primary survey.
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Hanafie, Ahmad, Rizal Syarifuddin, and Arisman D. "PENJADWALAN DISTRIBUSI DENGAN MENGGUNAKAN METODE DISTRIBUTION RESOURCES PLANNING (DRP) (Studi kasus PT.Biota Laut Ganggang)." Journal Industrial Engineering and Management (JUST-ME) 1, no. 02 (December 21, 2020): 31–36. http://dx.doi.org/10.47398/justme.v1i02.7.
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Perkembangan dunia usaha atau industry mengalami persaingan yang begitu ketat dan peningkatan permintaan. Aktivitas pendistribusian merupakan salah satu factor yang sangat penting dari akhir sebuah proses produksi. Distribusi ini sangat menentukan untuk penjadwalan dan tingkat biaya yang dibutuhkan untuk mendistribusikan sebuah produk. Metode yang digunakan dalam hal ini adalah metode Distribution Resorces Planning (DRP) dan data yang didapatkan berdasar data histori selama 1 tahun dengan tujuan penelitian yaitu, mengoptimalkan penjadwalan aktivitas distribusi dan melakukan distribusi dengan biaya yang efisien. Berdasarkan hasil penelitian dan pengolahan data yang dilakukan pada distribusi ke 3 negara yakni China,USA,dan Australia sesuai distribusi yang dilakukan oleh perusahaan total biaya distribusi sebesar Rp. 91.071.776.880,00 dengan total frekuensi pengiriman sebanyak 12 kali. Berdasarkan metode Distribution Resources Planning (DRP) dengan menggunakan teknik forecasting (peramalan) linear regression, menghitung lot sizing (ukuran lot), dan safety stock (stok pengaman) maka, biaya distribusi yang dihasilkan sebesar Rp. 90.879.778.846,74 dengan total frekuensi pengiriman sebanyak 12 kali. Dengan menggunakan metode Distribution Resources Planning (DRP) ini maka didapatkan penurunan biaya distribusi sebesar 21,08% atau sebanyak Rp.191.998.411,26 dari biaya distribusi yang dilakukan tanpa menggunakan metode Distribution Resources Planning (DRP).
The development of the business world or industry is experiencing intense competition and increased demand. Distribution activity is one of the most important factors at the end of a production process. This distribution is very decisive for scheduling and the level of the cost required to distribute a product. The method used in this case is the Distribution Resources Planning (DRP) method and data obtained based on historical data for 1 year with the purpose of research, namely, optimizing the scheduling of distribution activities and distributing at an efficient cost. Based on the results of research and data processing conducted in distribution to 3 countries namely China, USA, and Australia in accordance with the distribution carried out by the company's total distribution cost of Rp. 91,071,776,880.00 with a total shipping frequency of 12 times. Based on Distribution Resources Planning (DRP) method by using the linear regression forecasting technique, calculating lot sizing (lot size), and safety stock (safety stock), the resulting distribution cost is Rp. 90,879,778,846.74 with a total shipping frequency of 12 times. By using the distribution resources planning (DRP) method, distribution costs decreased by 21.08% or as much as Rp.191,998,411.26 from distribution costs carried out without using the distribution resources planning (DRP) method.
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Mudd, Gavin M. "Assessing the Availability of Global Metals and Minerals for the Sustainable Century: From Aluminium to Zirconium." Sustainability 13, no. 19 (September 29, 2021): 10855. http://dx.doi.org/10.3390/su131910855.
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Mining supplies metals and minerals to meet the material and energy needs of the modern world. Typically, mineral resources are widely considered to be ‘finite’ in nature, yet, paradoxically, global production and reported reserves and resources continue to grow. This paper synthesizes an extensive array of data on the long-term trends in cumulative mine production, reserves and resources at a global level as well detailed case studies of Australia, a global leader in many sectors of mining, and lithium, a new metal with rapidly growing demand. Overall, the paper shows that growing mine production has been clearly matched by growing reserves and resources, although there are numerous complex social, environmental and governance factors which are already affecting mines and are expected to increasingly affect mining into the future. Thus it is not possible at present to determine the ‘ultimately recoverable resource’, especially as this is a dynamic quantity dependent on a variety of inter-related factors (e.g., exploration, social issues, technology, market dynamics, environmental risks, governance aspects, etc.). This finding reinforces the need for continuing detailed studies of all metals and minerals to understand their individual supply and use dynamics to help modern society meet its needs and sustainable development goals.
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Pereira, Luísa Gomes, Paulo Fernandez, Sandra Mourato, Jorge Matos, Cedric Mayer, and Fábio Marques. "Quality Control of Outsourced LiDAR Data Acquired with a UAV: A Case Study." Remote Sensing 13, no. 3 (January 26, 2021): 419. http://dx.doi.org/10.3390/rs13030419.
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Over the last few decades, we witnessed a revolution in acquiring very high resolution and accurate geo-information. One of the reasons was the advances in photonics and LiDAR, which had a remarkable impact in applications requiring information with high accuracy and/or elevated completeness, such as flood modelling, forestry, construction, and mining. Also, miniaturization within electronics played an important role as it allowed smaller and lighter aerial cameras and LiDAR systems to be carried by unmanned aerial vehicles (UAV). While the use of aerial imagery acquired with UAV is becoming a standard procedure in geo-information extraction for several applications, the use of LiDAR for this purpose is still in its infancy. In several countries, companies have started to commercialize products derived from LiDAR data acquired using a UAV but not always with the necessary expertise and experience. The LIDAR-derived products’ price has become very attractive, but their quality must meet the contracted specifications. Few studies have reported on the quality of outsourced LiDAR data acquired with UAV and the problems that need to be handled during production. There can be significant differences between the planning and execution of a commercial project and a research field campaign, particularly concerning the size of the surveyed area, the volume of the acquired data, and the strip processing. This work addresses the quality control of LiDAR UAV data through outsourcing to develop a modelling-based flood forecast and alert system. The contracted company used the Phoenix Scout-16 from Phoenix LiDAR Systems, carrying a Velodyne VLP-16 and mounted on a DJI Matrice 600 PRO Hexacopter for an area of 560 ha along a flood-prone area of the Águeda River in Central Portugal.
Books on the topic "Production planning Australia Data processing Case studies"
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Kaewert, Julie Wallin. Developing expert systems for manufacturing: A case study approach. New York: McGraw-Hill, 1990.
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M, Aarup, Zweben Monte, and Fox Mark 1952-, eds. Intelligent scheduling. San Francisco, Calif: Morgan Kaufmann, 1994.
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(Editor), Monte Zweben, and Mark Fox (Editor), eds. Intelligent Scheduling. Morgan Kaufmann, 1998.
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Wegrzyn, Michael S. Implementation of core modules in MAPICS II: A case study. 1989.
Find full textConference papers on the topic "Production planning Australia Data processing Case studies"
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Kuzmichev, Dmitry, Babak Moradi, Yulia Mironenko, Negar Hadian, Raffik Lazar, Laurent Alessio, and Faeez Rahmat. "Case Studies of Digitalized Locate the Remaining Oil Workflows Powered by Hybrid Data & Physics Methods." In Abu Dhabi International Petroleum Exhibition & Conference. SPE, 2021. http://dx.doi.org/10.2118/207958-ms.
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Abstract Mature fields already account for about 70% of the hydrocarbon liquids produced globally. Since the average recovery factor for oil fields is 30 to 35%, there is substantial quantities of remaining oil at stake. Conventional simulation-based development planning approaches are well established, but their implementation on large, complex mature oil fields remains challenging given their resource, time, and cost intensity. In addition, increased attention towards reduce carbon emissions makes the case for alternative, computationally-light techniques, as part of a global digitalisation drive, leveraging modern analytics and machine learning methods. This work describes a modern digital workflow to identify and quantify by-passed oil targets. The workflow leverages an innovative hybrid physics-guided data-driven, which generates historical phase saturation maps, forecasts future fluid movements and locate infill opportunities. As deliverables, a fully probabilistic production forecast is obtained for each drilling location, as a function of the well type, its geometry, and position in the field. The new workflow can unlock remaining potential of mature fields in a shorter time-frame and generally very cost-effectively compared to the advanced dynamic reservoir modelling and history-match workflows. Over the last 5 years, this workflow has been applied to more than 30 mature oil fields in Europe, Africa, the Middle East, Asia, Australia, and New Zealand. Three case studies’ examples and application environments of applied digital workflow are described in this paper. This study demonstrates that it is now possible to deliver digitalized locating the remaining oil projects, capturing the full uncertainty ranges, including leveraging complex multi-vintage spatial 4D datasets, providing reliable non-simulation physics-compliant data-driven production forecasts within weeks.
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Grigoriev, Gleb, Vladimir Gulin, Alexei Nikitin, Nikita Sivoy, Eugene Bondarev, Marat Islamuratov, Oksana Zakharova, Igor Karpov, Evgenii Liubimov, and Vladislav Votsalevskiy. "Integrated Droneborne Geophysics Application as a Tool for Exploration Optimization. Case Studies." In SPE Annual Technical Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/206250-ms.
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Abstract Unmanned aerial vehicles (UAV) have a great potential for geological exploration optimization at all stages. This study considers UAV implementation at different exploration stage. Integrated approach using unmanned aerial systems shows great effectiveness based on the completed surveys. Low-depth electrical exploration using the shallow electrical exploration method is one of the possible UAVs technologies with great potential. In this study there are several cases describing main field data acquisition, models and cross-sections processing. Unmanned aerial systems are applicable at all stages of the oil and gas value chain and are already an integral part of oil&gas production process. Now there are more than 70 unmanned aerial systems application scenarios. The main advantages of drones are that the use of this operational data collection tool allows: – to reduce the duration of collecting geospatial data by 70%, and the cost by 3 times; – make the best decisions quickly; – to realize additional potential for increasing efficiency (application at all stages of the production chain) – increase the production processes safety level The most promising and actively developing areas of technology application are: Geophysical surveys at different stages of geological exploration. Drones have great potential for application in non-seismic exploration methods in the early stages of geological exploration. In addition, UAV surveys are suitable for planning geological exploration and working out the conceptual arrangement of the terrain. The presence of an accurate digital elevation model at the start of work of the project team makes it possible to remove a number of uncertainties and questions about conducting field work on seismic exploration, the placement of infrastructure and corridor communications. Objective control of the capital construction progress. Another important area of drones application is aerial photography at all stages of capital construction. With the help of UAVs, it is possible to control such parameters as the status and quality of construction and installation works, equipment of contractors, compliance with safety and environmental standards, and others. To do this, the unmanned vehicle flies around the object with a given regularity, filming it from different angles. After aerial photography, special software stitches the results into photogrammetric products (digital terrain model, orthophotomaps, 3D models) with an accuracy of 4–6 centimeters. On the constructed models, you can calculate the dynamics by one or another parameter. Operational fieldwork and intrastructure monitoring. At the same time, one of the key goals of technology application is the creation of a network of autonomous stations with drones at all assets for remote control of the company's production processes. The first step in this direction was the joint pilot testing of an automated take-off and landing station with an unmanned aerial vehicle of a multi-rotor type. The use of the station will reduce the time and cost of collecting data on capital construction and infrastructure. Project teams will be able to react faster to changes. An automated take-off and landing station allows the use of unmanned aerial vehicles without human intervention. The drone can independently take off, perform the necessary operations, land and recharge. Thus, flight operations and data collection can be performed remotely without the constant presence of a specialist on site.
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Kessy, Dillon, Jose Ignacio Sierra Castro, Jose Chirinos, Giorgio De Paola, and Maria Jose Lopez Perez-Valiente. "How Artificial Intelligence can Guide Marcellus Development." In SPE Eastern Regional Meeting. SPE, 2021. http://dx.doi.org/10.2118/201786-ms.
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Abstract The application of Artificial Intelligence for planning has received increased attention in the energy industry in the past few years, particularly for the increased production efficiency requirements and environmental standards. The objective of this paper is to show the successful integration of production, completion, subsurface and spatial data using machine-learning algorithms to predict production performance for future development wells. The internal Marcellus Business Unit (MBU) well database, populated with data of 500+ historical wells, has been used in this study. Production data, treated as timeseries, has been processed using functional Principal Component Analysis (PCA) to allow removal of outliers and mode detection. Utilizing this data, a suite of machine-learning algorithms has been applied to reconstruct gas production from available and target well data. Uncertainty quantification has been provided for production curves to identify the quality of prediction. During the study, the sensitivity analysis on input variables has been performed iteratively to screen and rank the most important variables for prediction. The workflow, Unconventional Reservoir Assistant (URA), has been implemented in a proprietary cloud-based platform providing the necessary means for data upload, integration, pre-processing, and finally model training and deployment. This allows the user to focus on the evaluation of model output quality, data filter and workspace generation for continuous model testing and improvement. The full well dataset, split into trained and tested data, has been used for prediction as a preliminary guide to where the most prolific areas of development are located. Results were ranked based on production expected by pad and based on normalized performance. The information was then used to compare with type curves and original development order. In parallel, economic evaluation of break-even was performed to rank all future pads. Consequently, integration of the model prediction and breakeven ranking were used to generate the final development order for the MBU. The URA tool has shown preliminary success in predicting production performance for the pilot development area. Multiple case studies have been run achieving blind test results with high accuracy for historical prediction. Results show some dependency of predictor variable ranking on the field development area, providing insight on how subsurface may affect well dynamic behavior. This paper describes how the integration of URA can complement the development workflow for unconventional reservoirs and be used to predict performance based on complex data integration. The methodology used is superior to standard machine learning models providing only production indicators, as it gives the user the possibility to evaluate economics and completion design sensitivity for future well activities. The methodology can be further extended as a proxy model for well schedule optimization in planning or for better insight into well refrac selection.