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Kembro, Joakim Hans, and Andreas Norrman. "Warehouse configuration in omni-channel retailing: a multiple case study." International Journal of Physical Distribution & Logistics Management 50, no. 5 (December 20, 2019): 509–33. http://dx.doi.org/10.1108/ijpdlm-01-2019-0034.
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Purpose The purpose of this study is to explore warehouse configuration in omni-channel retailing. Design/methodology/approach A multiple case study is conducted with six large omni-channel retailers from three different sectors. Findings The study shows an increase in the number, variation and frequency of flows passing through omni-channel warehouses. Along with an increased variety of stock keeping units (including singles vs multipacks), there is an increase in the complexity of planning and coordination of order fulfillment. Retailers test a mix of different solutions for storage and picking and partly shift focus to advanced sorting operations. The companies already have or plan to invest in substantial automation systems, which emphasize the importance of capturing and using accurate master data. Research limitations/implications The study highlights the need to understand the interrelations and co-development of configuration elements in omni-channel warehousing. The findings also suggest that a successful transformation requires increased collaboration with upstream and downstream partners. Conceptual models are developed to illustrate strategies and development paths in omni-channel warehousing, and suggestions for future research are summarized in a research agenda. A research limitation is the focus on Swedish retailers in three sectors (fashion, consumer electronics and DIY/construction material). Future studies can include additional sectors, extend the geographical scope and explore cross-regional differences. Practical implications As one of the few deeper case studies on omni-channel warehousing, practitioners will find new configurations described and analyzed here. Along with conceptual models, a synthesis of challenges and potential solutions are presented to support retailers’ practical analysis and decision making. Originality/value This is one of the first multiple case studies that go deeper into omni-channel warehouse configuration, which is of increasing importance to both scholars and practitioners in the field.
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Azzi, Anna, Daria Battini, Maurizio Faccio, Alessandro Persona, and Fabio Sgarbossa. "Inventory holding costs measurement: a multi-case study." International Journal of Logistics Management 25, no. 1 (May 6, 2014): 109–32. http://dx.doi.org/10.1108/ijlm-01-2012-0004.
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Purpose – Logisticians in the worldwide industry are frequently faced with the problem of measuring the total cost of holding inventories with simple and easy-to-use methodologies. The purpose of this paper is to look at the problem, and in particular illustrate the inventory holding cost rate computation, when different kind of warehousing systems are applied. Design/methodology/approach – A multiple case study analysis is here developed and supported by a methodological framework directly derived from the working group discussions and brainstorming activities. Two different field of application are considered: one related to five companies with manual warehousing systems operating with traditional fork lift trucks; the other is among five companies operating with automated storage/retrieval systems (AS/RS) to store inventories. Findings – The multi-case study helps to understand how the holding cost parameter is currently computed by industrial managers and how much the difference between manual and automated/automatic warehousing systems impacts on the inventory cost structure definition. The insights from the ten case studies provide evidence that the kind of storage system adopted inside the factory can impact on the holding cost rate computation and permit to derive important considerations. Practical implications – The final aim of this work is to help industrial engineers and logisticians in correctly understanding the inventory costs involved in their systems and their cost structure. In addition, the multi-case analysis leads to considerations, to be applied in different industrial contexts. As other industrial applications are identified, they may be analyzed by using the presented methodology, and with aid from the data from this paper. Originality/value – The relevance of this work is to help industrial engineers and logisticians in understanding correctly the inventory costs involved in their logistics systems and their cost structure. In addition, the multi-case analysis lead to interesting final considerations, easily to be applied in different industrial contexts. As other industrial applications are identified, they may be analyzed by using the methodology and extrapolating the data from this paper.
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You, Jane, Qin Li, and Jinghua Wang. "On Hierarchical Content-Based Image Retrieval by Dynamic Indexing and Guided Search." International Journal of Cognitive Informatics and Natural Intelligence 4, no. 4 (October 2010): 18–36. http://dx.doi.org/10.4018/jcini.2010100102.
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This paper presents a new approach to content-based image retrieval by using dynamic indexing and guided search in a hierarchical structure, and extending data mining and data warehousing techniques. The proposed algorithms include a wavelet-based scheme for multiple image feature extraction, the extension of a conventional data warehouse and an image database to an image data warehouse for dynamic image indexing. It also provides an image data schema for hierarchical image representation and dynamic image indexing, a statistically based feature selection scheme to achieve flexible similarity measures, and a feature component code to facilitate query processing and guide the search for the best matching. A series of case studies are reported, which include a wavelet-based image color hierarchy, classification of satellite images, tropical cyclone pattern recognition, and personal identification using multi-level palmprint and face features. Experimental results confirm that the new approach is feasible for content-based image retrieval.
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Ubaid, Ayesha, Farookh Hussain, and Muhammad Saqib. "Container Shipment Demand Forecasting in the Australian Shipping Industry: A Case Study of Asia–Oceania Trade Lane." Journal of Marine Science and Engineering 9, no. 9 (September 6, 2021): 968. http://dx.doi.org/10.3390/jmse9090968.
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Demand forecasting has a pivotal role in making informed business decisions by predicting future sales using historical data. Traditionally, demand forecasting has been widely used in the management of production, staffing and warehousing for sales and marketing data. However, the use of demand forecasting has little been studied in the container shipping industry. Improved visibility into the demand for container shipments has been a long-held objective of industry stakeholders. This paper addresses the shortcomings of both short-term and long-term shipment demand forecasting for the Australian container shipping industry. In this study, we compare three forecasting models, namely, the seasonal auto-regressive integrated moving average (SARIMA), Holt–Winters’ seasonal method and Facebook’s Prophet, to find the best fitting model for short-term and long-term import demand forecasting in the Australian shipping industry. Demand data from three years, i.e., 2016–2018, is used for the Asia–Oceania trade lane. The mean absolute percentage error (MAPE), root mean squared error (RMSE) and 2-fold walk-forward cross-validation are used for the model evaluation. The experiment results observed from the selected metrics suggest that Prophet outperforms the other models in its comparison for container shipment demand forecasting.
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Azanha, Adrialdo, Mauro Vivaldini, Silvio R. I. Pires, and João Batista de Camargo Junior. "Voice picking: analysis of critical factors through a case study in Brazil and the United States." International Journal of Productivity and Performance Management 65, no. 5 (June 13, 2016): 723–39. http://dx.doi.org/10.1108/ijppm-11-2015-0163.
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Purpose – The purpose of this paper is to identify and analyse the difficulties encountered in the implementation of a voice picking system at a large multinational company of the tractor industrial segment, outlining a comparison related to the main critical factors concerning the system implementation at a Brazilian and a USA plant. Design/methodology/approach – The methodology utilised was qualitative and exploratory conducted through case studies in the two plants of the multinational company. The main data were collected through interviews with key managers directly involved in the project of voice picking system implementation. Findings – The results indicate that the picking processes in the two plants were similar, since both were designed for the production line and conducted using bar-code readers and paper lists. Nevertheless, the internal warehousing process in the USA was more mature and computerised, whereas the Brazilian process still had opportunity for improvement, such as, the visual storage process, where the operator was responsible for locating an empty position. Research limitations/implications – Since this research is an exploratory case study, its results cannot be generalised. Practical implications – The paper provides relevant practical information and experiences to managers interested in implementing voice picking systems, as well as interested in improving the accuracy and productivity of logistics processes within warehouses. Originality/value – The voice picking systems are more widespread in the USA than in Brazil, and therefore, companies around the world can use this studied case to better understand about the voice picking systems implementation process in both emerging and mature marketplaces.
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He, Wenjun, Katie G. Kirchoff, Royce R. Sampson, Kimberly K. McGhee, Andrew M. Cates, Jihad S. Obeid, and Leslie A. Lenert. "Research Integrated Network of Systems (RINS): a virtual data warehouse for the acceleration of translational research." Journal of the American Medical Informatics Association 28, no. 7 (March 17, 2021): 1440–50. http://dx.doi.org/10.1093/jamia/ocab023.
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Abstract Objective Integrated, real-time data are crucial to evaluate translational efforts to accelerate innovation into care. Too often, however, needed data are fragmented in disparate systems. The South Carolina Clinical & Translational Research Institute at the Medical University of South Carolina (MUSC) developed and implemented a universal study identifier—the Research Master Identifier (RMID)—for tracking research studies across disparate systems and a data warehouse-inspired model—the Research Integrated Network of Systems (RINS)—for integrating data from those systems. Materials and Methods In 2017, MUSC began requiring the use of RMIDs in informatics systems that support human subject studies. We developed a web-based tool to create RMIDs and application programming interfaces to synchronize research records and visualize linkages to protocols across systems. Selected data from these disparate systems were extracted and merged nightly into an enterprise data mart, and performance dashboards were created to monitor key translational processes. Results Within 4 years, 5513 RMIDs were created. Among these were 726 (13%) bridged systems needed to evaluate research study performance, and 982 (18%) linked to the electronic health records, enabling patient-level reporting. Discussion Barriers posed by data fragmentation to assessment of program impact have largely been eliminated at MUSC through the requirement for an RMID, its distribution via RINS to disparate systems, and mapping of system-level data to a single integrated data mart. Conclusion By applying data warehousing principles to federate data at the “study” level, the RINS project reduced data fragmentation and promoted research systems integration.
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Filippi, Amanda Cristina Gaban, Patricia Guarnieri, José Márcio Carvalho, Silvia Araújo Reis, and Cleyzer Adrian da Cunha. "New configurations in Brazilian agribusiness: rural warehouse condominiums." Journal of Agribusiness in Developing and Emerging Economies 10, no. 1 (December 30, 2019): 41–63. http://dx.doi.org/10.1108/jadee-12-2018-0178.
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Purpose The purpose of this paper is to analyze the development of rural warehouses condominiums (or “condos”) as new rural configurations in the Brazilian agribusiness from the perspective of the theory of collective action. Design/methodology/approach A systematic literature review was complemented with multiple case studies based on interviews and direct observation. Content analysis was used to interpret the secondary and primary data. Findings Rural warehouse condos can be characterized as a collective action which is a new business model in Brazilian agribusiness. This new initiative has several advantages: reduction of the warehouse deficit and other logistical bottlenecks; strategic commercialization of production; reduction of logistical costs; inclusion of smallholders in the economy and, consequently, the generation of income for smallholders and their participation in the market. Research limitations/implications The study used a qualitative approach and findings and discussion are inherently interpretative. Social implications Understanding the organization of rural warehouse condos supports the inclusion of smallholding farmers and income generation. This creates a social benefit through rural growth and economic development. Some constraints related to the lack of public policies, specific credit lines in financial institutions, the problem of non-regularized rural areas, lack of transparency and conflicts among the members can limit expansion. Originality/value Rural warehouse condos are expanding mainly in the south region of Brazil, where smallholders are concentrated. In this new configuration, they can engage in an association to obtain several benefits, such as reduced logistics costs, better access to financing and increased bargaining power with suppliers. As this research dealt with a relatively new and poorly studied topic, it contributes to the development of new studies to map innovative warehousing practices.
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Ahmad, Shafiq, Muhammad Arfan Hadyait, and Muhammad Mohsin Rashid. "Effect Of Supply Chain Risk Management On Organization Performance: A Case Study Of National Foods Manooabad Muridke District Sheikhupura." International Journal of social Sciences and Economic Review 1, no. 1 (May 19, 2019): 1–7. http://dx.doi.org/10.36923/ijsser.v1i1.22.
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Purpose: Previously there are many studies that focused on risk management in general context and little attention was paid on how supply chain risks management effects an organization profit and performance. The main aim of our study to explore the effect of supply chain risk management on organization performance in national foods Manooabad Muridke district Sheikhupura.
Methodology: This study conducted in National foods Manooabad Muridke. Data were collected by using questioner from the employees of National foods Manooabad Muridke. SPSS 22 (Statistical package for social sciences) was used to analyze the collected data.
Main Findings: This study is an attempt to check the effects of supply chain risk management variables to the performance of the organization. Three main supply chain risk management variables were identified namely, supply chain risk identification, supply chain risk sources and supply chain risk mitigation. We find that risk register method is mainly used for the identification of risks in the supply chain at any level. The most important risks of our study that are supplier risks, environmental risks, political risks, markets risks, warehousing risks, and financial risks. In mitigation strategies that are good to mitigate the risk in supply chain risk avoidance measures, risk control measures and risk cooperation measures.
Applications: We concluded that it is important for an organization to identify risks proactively as early as possible in the decision-making process. Different types of risks need to be identified in all process of supply chains. After all the identification of risks, the organization needs to be mitigated these risks by using different mitigate strategies plan.
Originality: In the future, this study will be helpful for many organizations which deal with food items consumed by people. As in this study, we worked on supply chain risks and their management before many studies were conducted generally on risk management so this study especially focused on supply chain risks. There is a need to conduct more study in this regard in different industries so better information available to people to control risks in supply chain management.
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Akkad, Mohammad Zaher, Sameh Haidar, and Tamás Bányai. "Design of Cyber-Physical Waste Management Systems Focusing on Energy Efficiency and Sustainability." Designs 6, no. 2 (April 13, 2022): 39. http://dx.doi.org/10.3390/designs6020039.
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Industry 4.0 tools, such as the Internet of Things, artificial intelligence, digital twinning, and cloud computing, create a technological revolution that accelerates efforts to optimize the efficiency of cyber-physical operations and services. The waste management system requires a critical share of city logistics optimization, especially when using cyber-physical systems. Modern tools reduce the required municipal waste handling, such as loading and unloading, transportation, and warehousing, which leads to an increase in efficiency and flexibility, saving energy and time, and protecting the environment. In this paper, we present a cyber-physical waste management system solution by providing a cyber-physical model design and description, mathematical modeling, and two cases to investigate the impact on energy consumption and emissions. After an introduction and literature review, we describe the design of the cyber-physical model and tackle the first echelon. The designed system incorporates the IoT, smart bins with multi-percentage sensors, data and information analysis, vehicles’ actual routes, energy and emissions optimization, multi-echelon systems, time windows, and flexibility. Mathematical modeling equations for the optimized total energy consumption are presented. Thirty and twenty smart bins located in VIII District in Budapest are detailed as two case studies, where solutions for the optimized real routes and energy consumption are found using three metaheuristic algorithms: genetic, particle swarm, and simulated annealing optimization algorithms. The accrued emissions of CO, NMHC, CH4, NOx, and PM for the optimized solutions are calculated. Finally, the results are compared with a random traditional solution to measure the effectiveness.
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Nag, Barin, Chaodong Han, and Dong-qing Yao. "Mapping supply chain strategy: an industry analysis." Journal of Manufacturing Technology Management 25, no. 3 (April 1, 2014): 351–70. http://dx.doi.org/10.1108/jmtm-06-2012-0062.
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Purpose – In manufacturing industries, the levels of inventories at all stages (i.e. raw material, work-in-process and finished goods inventories) indicate the firm's competitive positioning, strategies, internal processes and relationships with suppliers and downstream customers. The authors identify patterns of manufacturing industries based on levels of raw material and finished goods inventories to classify inbound and outbound supply chain strategies. Design/methodology/approach – The authors review literature on supply chain inventory strategy and perform cluster analysis to analyze patterns of manufacturing industries based on manufacturing industry data collected from US Census of Bureau. Following Porter's Five Forces Model, the authors perform in-depth case studies of four representative industries to analyze factors driving supply chain strategies, including industry intensity of rivalry, threat of new entrants, threat of substitutes, bargaining power of suppliers, and bargaining power of buyers. Findings – This study identifies three streams of research on supply chain strategy: Fisher's model and its variations, lean and agile paradigms, and push/pull systems. It finds that whether an industry shows low or high raw materials or finished goods inventories depending on its products, processes, and the dynamics of all forces described in the Five Forces Model. Research limitations/implications – This study is not able to include supplier selection, production strategies, warehousing and distribution, and even product design into the analysis of supply chain strategy due to data limitation. This study classifies industries based on average inventory levels of raw materials and finished goods, while inventory levels and supply chain strategies for specific firms may vary significantly within each industry. Originality/value – This study contributes to the supply chain management literature by providing a parsimonious framework of mapping inbound and outbound supply chain inventory strategies, and the results based on the analyses of all US manufacturing industries provide a baseline picture for supply chain management professionals with manufacturing firms.
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Suknovic, Milija, Milutin Cupic, Milan Martic, and Darko Krulj. "Data warehousing and data mining: A case study." Yugoslav Journal of Operations Research 15, no. 1 (2005): 125–45. http://dx.doi.org/10.2298/yjor0501125s.
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This paper shows design and implementation of data warehouse as well as the use of data mining algorithms for the purpose of knowledge discovery as the basic resource of adequate business decision making process. The project is realized for the needs of Student's Service Department of the Faculty of Organizational Sciences (FOS), University of Belgrade, Serbia and Montenegro. This system represents a good base for analysis and predictions in the following time period for the purpose of quality business decision-making by top management. Thus, the first part of the paper shows the steps in designing and development of data warehouse of the mentioned business system. The second part of the paper shows the implementation of data mining algorithms for the purpose of deducting rules, patterns and knowledge as a resource for support in the process of decision making.
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Shin, Bongsik. "A case of data warehousing project management." Information & Management 39, no. 7 (July 2002): 581–92. http://dx.doi.org/10.1016/s0378-7206(01)00137-9.
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AhmedButt, Muheet, and Majid Zaman. "Data Quality Tools for Data Warehousing: Enterprise Case Study." International Journal of Computer Applications 62, no. 10 (January 18, 2013): 22–24. http://dx.doi.org/10.5120/10117-4788.
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Ahmed Butt, Er Muheet. "Data Quality Tools for Data Warehousing: Enterprise Case Study." IOSR Journal of Engineering 3, no. 01 (January 2013): 75–76. http://dx.doi.org/10.9790/3021-03117576.
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Singbal, Vishwesh, Gajendra K. Adil, and Rakesh Venkitasubramony. "Case Article—Forward-Reserve Storage Design: A Case of Carriage Repair Workshop, Indian Railways." INFORMS Transactions on Education 21, no. 1 (September 2020): 30–34. http://dx.doi.org/10.1287/ited.2019.0228ca.
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Case studies are useful in imparting decision-making skills to students. Warehousing is a critical part of most supply chains, but case studies based on warehousing methods and operations therein are rare. Recognizing the need to bridge this gap, a case study is designed to present a real-life scenario at the carriage repair workshop of Indian Railways. The case study facilitates the learning of students regarding operations in automated warehousing and relevant storage strategies. Additionally, the case encourages the students to explore the use of heuristics and optimization models. This case article highlights the major learning objectives of the case study and discusses the classroom teaching experience. This case can be used in various courses and the case questions can be selected based on the teaching objectives and/or the educational background of the students.
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Bose, Indranil, and Ben Hui Siu Bun. "A Case-Based Analysis of Active Data Warehousing." IT Professional 16, no. 3 (May 2014): 52–60. http://dx.doi.org/10.1109/mitp.2013.63.
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Johnson, Ralph J. "A Comprehensive Research Study Literature Review of EPIC© in Terms of Enabling Healthcare Agility: A Report Card." Journal of Medical Informatics and Decision Making 1, no. 4 (February 20, 2021): 1–21. http://dx.doi.org/10.14302/issn.2641-5526.jmid-21-3739.
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Background As healthcare markets have become more dynamic and turbulent, healthcare organizations have evolved by becoming increasingly “Smart-Agile” in their business practices. Smart-Agility definition-ally ensures success due to its inherent ability to rapidly detect and react appropriately to varied and evolving unclear, complex, and seemingly tumultuous situations and produce high-quality, low-cost goods and services with high customer satisfaction. Thus, there is a vital need for Smart-Agile healthcare IT systems for collection, analyses, and reporting of substantial quantities of healthcare data to inform patient treatment and organizational decisions. EPIC® and its meaningful-use components appear increasingly popular, capturing a majority portion of the healthcare Electronic Healthcare Records (EHR) IT market (>~30%).Yet, there are few, if any, studies reporting on EPIC in terms of Smart-Agility. Aim The intent of this article is to report a systematic review of scientific literature regarding EPIC’s healthcare IT systems meaningful-use features cross-compared with Smart-Agility aspects to produce a positive vs. negative report card—and whether its features are critical vs. non-critical in terms of Smart-Agility. Method Findings reported herein derive from a grounded, iterative review of open-source, peer-reviewed scientific literature following PRISMA. Findings Report card results were mixed. EPIC clearly succeeds and excels (better than average) on Smart-Agile healthcare IT system core aspects that are the most central, critical and valuable in terms of informing healthcare organizations’ decisions and their patients’ care (6 out of 7; B+, -A), specifically: Standardized Data Collection / Connectivity, Real-Time Data Warehousing/Outcome Measures, Enhanced Patient Safety, Patient Tracking and Follow-up (Continuity of Care), Patient Involvement, and Potential Use in Medical Education. The only critical core criterion it failed on was End-User Satisfaction, and some of that appears to dissipate with new users’ software familiarity. Conclusion EPIC provides a solid and relatively inexpensive foundation with great potential for enabling Smart Agility in healthcare organizations with its high-quality collection and management of vast amounts of inter-connected raw data, auto-analysis, and fast report generation. But it does so with hidden costs and inefficiencies. Avenues of further inquiry are suggested.
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Jukic, Nenad, and Miguel Velasco. "Data Warehousing Requirements Collection and Definition." International Journal of Business Intelligence Research 1, no. 3 (July 2010): 66–76. http://dx.doi.org/10.4018/jbir.2010070105.
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Defining data warehouse requirements is widely recognized as one of the most important steps in the larger data warehouse system development process. This paper examines the potential risks and pitfalls within the data warehouse requirement collection and definition process. A real scenario of a large-scale data warehouse implementation is given, and details of this project, which ultimately failed due to inadequate requirement collection and definition process, are described. The presented case underscores and illustrates the impact of the requirement collection and definition process on the data warehouse implementation, while the case is analyzed within the context of the existing approaches, methodologies, and best practices for prevention and avoidance of typical data warehouse requirement errors and oversights.
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He, Xin James, and Myron Sheu. "Data warehousing for supply chain management with case analysis." International Journal of Management and Enterprise Development 3, no. 5 (2006): 438. http://dx.doi.org/10.1504/ijmed.2006.009569.
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Azaiez, Noura, and Jalel Akaichi. "The Model-Driven Architecture for the Trajectory Data Warehouse Modeling." International Journal of Data Warehousing and Mining 16, no. 4 (October 2020): 26–43. http://dx.doi.org/10.4018/ijdwm.2020100102.
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Business Intelligence includes the concept of data warehousing to support decision making. As the ETL process presents the core of the warehousing technology, it is responsible for pulling data out of the source systems and placing it into a data warehouse. Given the technology development in the field of geographical information systems, pervasive systems, and the positioning systems, the traditional warehouse features become unable to handle the mobility aspect integrated in the warehousing chain. Therefore, the trajectory or the mobility data gathered from the mobile object movements have to be managed through what is called the trajectory ELT. For this purpose, the authors emphasize the power of the model-driven architecture approach to achieve the whole transformation task, in this case transforming trajectory data source model that describes the resulting trajectories into trajectory data mart models. The authors illustrate the proposed approach with an epilepsy patient state case study.
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Sardar, Souryajyoti, Pulastya Bandyopadhyay, and Anirban Sanyal. "A Comprehensive Data and Project Management Platform: A Case Study of a Central Bank." Journal of Information & Knowledge Management 15, no. 03 (July 26, 2016): 1650026. http://dx.doi.org/10.1142/s021964921650026x.
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This study considers an efficient way to manage different aspects of a Central Bank’s Data Warehousing project using a custom built data and project management platform. Although the key aspect of managing a Data Warehouse is of course data management, but simultaneously the management of on-going projects related to data integration, website, internal and external human resources, etc. are also important. Data Warehousing in Central Banks is strategically different with other Commercial Bank/Corporate Data Warehousing project in terms of functionality/purpose. A typical Data Warehouse of a Commercial Bank or Corporate body primarily consists of the data generated out of their business operations. On the other hand, a Central Bank collects data from such Commercial Banks, Corporate bodies or Regulatory bodies for regulatory or supervisory purpose along with data on various subject domains allied to central banking compiled within the organisation. As a result, management of such diverse data sources is a major challenge for every central bank. Further, the traditional project management concepts are not applicable as-it-is in the context of a Central Bank. Keeping in view these particularities, and the shortcomings of available commercial project management tools, a comprehensive Information Management System has been built in Reserve Bank of India. The development was done in-house and based on open source platform. The salient features of this system are: (1) An all-in-one monitoring platform to monitor different aspects of Data Warehousing and Data Management project through a single window. (2) Scalability. (3) Cross-platform usability. This study presents the background, design and development of the system in detail.
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Jefferys, Benjamin R., Iheanyi Nwankwo, Elias Neri, David C. W. Chang, Lev Shamardin, Stefanie Hänold, Norbert Graf, Nikolaus Forgó, and Peter Coveney. "Navigating legal constraints in clinical data warehousing: a case study in personalized medicine." Interface Focus 3, no. 2 (April 6, 2013): 20120088. http://dx.doi.org/10.1098/rsfs.2012.0088.
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Personalized medicine relies in part upon comprehensive data on patient treatment and outcomes, both for analysis leading to improved models that provide the basis for enhanced treatment, and for direct use in clinical decision-making. A data warehouse is an information technology for combining and standardizing multiple databases. Data warehousing of clinical data is constrained by many legal and ethical considerations, owing to the sensitive nature of the data being stored. We describe an unconstrained clinical data warehousing architecture, some of the legal constraints that have led us to reconsider this architecture, and the legal and technical solutions to these constraints developed for the clinical data warehouse in the personalized medicine project p-medicine. We also propose some changes to the legal constraints that will further enable clinical research.
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Smith, Brian L., David C. Lewis, and Ryan Hammond. "Design of Archival Traffic Databases: Quantitative Investigation into Application of Advanced Data Modeling Concepts." Transportation Research Record: Journal of the Transportation Research Board 1836, no. 1 (January 2003): 126–31. http://dx.doi.org/10.3141/1836-16.
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Given the enormous quantities of data collected by intelligent transportation systems (ITS), transportation professionals recently have focused on developing archived data user services (ADUS) to facilitate efficient use of these data in myriad transportation analyses. Most ITS systems were designed by using a transactional database design, which is not well suited to support the ad hoc queries required by ADUS. Research investigated the application of data-warehousing concepts to better support the requirements of ADUS. A case study is presented in which an ADUS for the Hampton Roads Smart Traffic Center, the regional freeway management system, was redesigned from a transactional approach to one based on data warehousing. Test queries run by using both approaches demonstrated that dramatic increases in efficiency are achievable through the use of data-warehousing concepts in ADUS.
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Steven and Yugih Setyanto. "Perubahan Komunikasi Interpersonal dalam Hubungan Rekan Bisnis Selama Masa Pandemi (Studi Kasus di PT Jassendo Mandiri Sentosa)." Kiwari 1, no. 3 (August 29, 2022): 493–500. http://dx.doi.org/10.24912/ki.v1i3.15807.
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Communication is a basic activity that is needed and carried out by every human being. Through communication, humans can relate to each other both in daily life at home at work, in the market, in society, or wherever humans are. Interpersonal relationships where when we communicate, we not only convey the content of the message, but also determine the level of interpersonal relationships. So when we communicate we not only determine the content but also determine the relationship. The existence of the Covid-19 pandemic has made major changes in communication patterns that occur within the company as well as communication relationships with company clients. PT Jassendo Mandiri Sentosa is a fishery company founded on September 14, 2016 by Agustono. PT Jassendo Mandiri Sentosa is engaged in warehousing related to the sale and purchase of marine fauna, especially fish. The development of communication technology, especially the development of mass media can be seen from the diversity of media. This is used by most companies in running their business or business. Like wise with the communication patterns that occur at PT Jassendo Mandiri Sentosa. The pattern of communication carried out with clients or company business partners that was previously done face-to-face or directly was forced to turn online due to Covid-19 pandemic. The intention of this research to determine the pattern of interpersonal communication in business partner relationships during the pandemic that took place at PT Jassendo Mandiri Sentosa. This research using the theory of interpersonal communication. This research uses qualitative research methods and case studies at PT Jassendo Mandiri Sentosa. In collecting data, the researcher used interview, observation and documentation methods. Researchers processed and analyzed data using the Miles and Huberman model which consisted of data reduction, data display and conclusion drawing and tested the validity of the data using data triangulation techniques. Komunikasi merupakan aktivitas dasar yang dibutuhkan dan dilakukan oleh setiap manusia. Melalui komunikasi, manusia dapat saling berhubungan satu sama lain baik dalam kehidupan sehari - hari di rumah di tempat kerja, pasar, masyarakat, atau di manapun manusia berada. Hubungan interpersonal dimana ketika kita berkomunikasi, kita bukan sekedar menyampaikan isi pesan, tetapi juga menentukan kadar hubungan interpersonalnya. Jadi ketika kita berkomunikasi kita tidak hanya menentukan content melainkan juga menentukan relationship. Adanya pandemi Covid-19 membuat perubahan besar dalam pola komunikasi yang terjadi di dalam perusahaan maupun hubungan komunikasi dengan klien perusahaan. PT Jassendo Mandiri Sentosa merupakan salah satu perusahaan perikanan yang didirikan pada 14 september 2016 oleh Agustono. PT Jassendo Mandiri Sentosa bergerak di bidang pergudangan terkait penjualan dan pembelian fauna laut terutama ikan. Perkembangan teknologi komunikasi, khususnya perkembangan media massa terlihat dari keberagaman media. Hal ini dimanfaatkan oleh sebagian besar perusahaan dalam menjalankan bisnis atau usahanya. Begitu pula dengan pola komunikasi yang terjadi di PT Jassendo Mandiri Sentosa. Pola komunikasi yang dilakukan dengan klien atau rekan bisnis perusahaan yang sebelumnya dilakukan secara tatap muka atau secara langsung terpaksa berubah mejadi online dikarenakan pandemi Covid-19. Penelitian ini bertujuan untuk mengetahui pola komunikasi interpersonal dalam hubungan rekan bisnis selama masa pandemi yang berlangsung di PT Jassendo Mandiri Sentosa. Teori yang digunakan dalam penelitian ini yakni teori komunikasi interpersonal. Penelitian ini menggunakan metode penelitian kualitatif dan studi kasus pada PT Jassendo Mandiri Sentosa. Dalam mengumpulkan data, peneliti menggunakan metode wawancara, observasi, dan dokumentasi. Peneliti mengolah dan menganalisis data dengan menggunakan model Miles dan Huberman yang terdiri dari reduksi data, display data, dan penarikan kesimpulan serta menguji keabsahan data dengan menggunakan teknik triangulasi data.
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Ranjan, Jayanthi, and Saani Khalil. "Data Warehousing and Business Intelligence at Shoppers' Stop: a case study." International Journal of Business Excellence 1, no. 3 (2008): 282. http://dx.doi.org/10.1504/ijbex.2008.017884.
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Irtaimeh, Hani J., Abdallah Mishael Obeidat, Shadi H. Abualloush, and Amineh A. Khaddam. "Impact of Business Intelligence on Technical Creativity: A Case Study on AlHekma Pharmaceutical Company." European Scientific Journal, ESJ 12, no. 28 (October 31, 2016): 502. http://dx.doi.org/10.19044/esj.2016.v12n28p502.
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Business Intelligence, through its dimensions (data warehousing, data mining, direct analytical processing), helps the members of an organization to perceive and interpret their role in the organization’s creativity. For this reason, we may assume that Business Intelligence has an impact on Technical Creativity, and that matching of Business Intelligence and Technical Creativity will improve and achieve excellence in an organization. The aim of this study is to explore the impact of business intelligence dimensions (data warehousing, data mining, direct analytical processing) on Technical Creativity in AlHekma Pharmaceutical Company as a case study. For this purpose, a questionnaire was developed to collect data from the study population which consists of 50 employees. This is aimed at testing the hypotheses and achieving the objectives of the study. The most important results that the study achieved were that there was a statistically significant impact of business intelligence with its dimensions (data warehousing, data mining, and direct analytical processing) in technical creativity. The most important recommendations of the study were the necessity of organizations dependence on modern technology in order to develop their works. Thus, this is because this technology is recognized by its high accuracy on a completion of the work, as well as deepening the concept of technical creativity which gives them a competitive advantage in the marke
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Agustian, Indra, Eka Muktiono, Akhmat Nuryadin, and Bambang Suharjo. "WAREHOUSHING AND INVENTORY INFORMATION SYSTEM MODEL USING RADIO FREQUENCY IDENTIFICATION (RFID) IN EASTERN NAVAL WAREHOUSING." JOURNAL ASRO 10, no. 2 (July 24, 2019): 31. http://dx.doi.org/10.37875/asro.v10i2.127.
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Eastern Naval Warehousing is the technical implementation elements in charge of receiving, storing, maintaining and distributing supplies to support existing user in the Navy in particular user located in the eastern region. To support the operational activities of the Navy, Eastern Naval Warehousing as service organizations should be supported with the provision of an information system capable of supporting the activities become more optimal provisioning. Speed and accuracy of support provision to user is an indication for the success of a service. Information technology nowadays has grown very rapidly to develop into the current warehousing system. RFID (Radio Frequency Identification) is the process of identifying an object automatically by Radio Frequency. There are two important components of an RFID system is the card (tag) and the reader. Application warehousing information system can be integrated with RFID technology, so that the system can run more optimal for warehousing system. This research aims to design warehousing information system based on RFID in Eastern Naval Warehousing used in processing existing warehousing system to gain optimal in provisioning operations running in Eastern Naval Warehousing to support provisioning activities to meet the requirement of existing user in Navy. Field studies conducted in Eastern Naval Warehousing, aimed to determine the current state of warehousing system that runs to identify existing problems. Furthermore, to process the data, created the design of an information system based on RFID warehousing in software system. This paper get to report out of the goods, report the amount of inventory in real time, the location of goods and EOQ value of goods to determine the optimal inventory level of each item.
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Ratner, Helene, and Christopher Gad. "Data warehousing organization: Infrastructural experimentation with educational governance." Organization 26, no. 4 (October 29, 2018): 537–52. http://dx.doi.org/10.1177/1350508418808233.
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Organization is increasingly entwined with databased governance infrastructures. Developing the idea of ‘infrastructure as partial connection’ with inspiration from Marilyn Strathern and Science and Technology Studies, this article proposes that database infrastructures are intrinsic to processes of organizing intra- and inter-organizational relations. Seeing infrastructure as partial connection brings our attention to the ontological experimentation with knowing organizations through work of establishing and cutting relations. We illustrate this claim through a multi-sited ethnographic study of ‘The Data Warehouse’. ‘The Data Warehouse’ is an important infrastructural component in the current reorganization of Danish educational governance which makes schools’ performance public and comparable. We suggest that ‘The Data Warehouse’ materializes different, but overlapping, infrastructural experiments with governing education at different organizational sites enacting a governmental hierarchy. Each site can be seen as belonging to the same governance infrastructure but also as constituting ‘centres’ in its own right. ‘The Data Warehouse’ participates in the always-unfinished business of organizational world making and is made to (partially) relate to different organizational concerns and practices. This argument has implications for how we analyze the organizational effects of pervasive databased governance infrastructures and invites exploring their multiple organizing effects.
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Nguyen, Benjamin, Antoine Vion, François-Xavier Dudouet, Dario Colazzo, Ioana Manolescu, and Pierre Senellart. "XML Content Warehousing: Improving Sociological Studies of Mailing Lists and Web Data." Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique 112, no. 1 (October 2011): 5–31. http://dx.doi.org/10.1177/0759106311417540.
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Goh, Shao Hung. "Barriers to low-carbon warehousing and the link to carbon abatement." International Journal of Physical Distribution & Logistics Management 49, no. 6 (August 15, 2019): 679–704. http://dx.doi.org/10.1108/ijpdlm-10-2018-0354.
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Purpose Warehouses are large emitters of greenhouse gases and their impact on climate change is under increasing focus. The purpose of this paper is to investigate the barriers that inhibit the adoption of low-carbon warehousing in Asia-Pacific and their links to carbon abatement performance. Design/methodology/approach An exploratory conceptual model was first developed from a literature review of the general barriers to sustainable supply chain practices and hence potentially in low-carbon warehousing. A large contract logistics services provider in the Asia-Pacific served as the subject of a case study. The perceived barriers to low-carbon warehousing were derived from an internal survey of respondents from the case company and regressed against carbon abatement outcomes at that organization’s operations across the region. Findings Results show that the case company reduced carbon emissions by 36 percent on a revenue-normalized basis between 2008 and 2014, but with relatively lower success in emerging markets vs mature markets. An Elastic Net regression analysis confirms that technology and government-related factors are the most important barriers in the case company’s efforts to “decarbonize” its local warehousing operations. However, results suggest that the customer-related barrier, which is highly correlated with the government barrier, is in part driven by the latter. Research limitations/implications This case study is based on a single multinational company in Asia-Pacific, but nonetheless serves as an impetus for more cross-sectional studies to form an industry-wide view. Originality/value An extended stewardship framework based on the natural resource-based view has been proposed, in which logistics services providers take on a proactive boundary-spanning role to lower the external barriers to low-carbon warehousing.
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Okeudo, Geraldine, and Okoli Margaret. N. "The Impact of Marketing Mix (4Ps) on Warehousing Operations: Case Study of Unilever Nigeria PLC." American Journal of Business and Management 2, no. 2 (May 30, 2013): 155. http://dx.doi.org/10.11634/216796061706282.
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The study investigates the impact of marketing mix (4ps) on warehousing operations with a case study of Unilever Nigeria Plc. with objectives to aim at establishing a link between the resultant effects of marketing mix efforts on warehousing operations to find challenges and opportunities to improve on. Data used where secondary data collected from the warehouse activity profiles. Through-put/hour is used the estimated the activity at the warehouse; Sales in volumes is used the estimated the sales level. Data was analysed the regression model to determine what influence that marketing mix elements has on warehouse activity levels. Findings show that the higher sales go the higher the activities that constitute warehousing operations in the warehouse and price and promotional activities has a low influence on this warehouse operations. Consequently, it was concluded that the price and promotion activities have low influence on the model while sales-in-volume has the highest influence on the model. The relationship shows that the higher the volume-in-sales the activity is the warehouse operations while price and promotion activities do not have consider impact on these activities. We therefore recommend that Companies should develop better internal information system so as to effectively convey the information on real time basis within the firm especially when these warehouses are operated of decentralized policy.
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Pardillo, Jesús, Jose-Norberto Mazón, and Juan Trujillo. "An MDA Approach and QVT Transformations for the Integrated Development of Goal-Oriented Data Warehouses and Data Marts." Journal of Database Management 22, no. 1 (January 2011): 43–68. http://dx.doi.org/10.4018/jdm.2011010103.
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To customize a data warehouse, many organizations develop concrete data marts focused on a particular department or business process. However, the integrated development of these data marts is an open problem for many organizations due to the technical and organizational challenges involved during the design of these repositories as a complete solution. In this article, the authors present a design approach that employs user requirements to build both corporate data warehouses and data marts in an integrated manner. The approach links information requirements to specific data marts elicited by using goal-oriented requirement engineering, which are automatically translated into the implementation of corresponding data repositories by means of model-driven engineering techniques. The authors provide two UML profiles that integrate the design of both data warehouses and data marts and a set of QVT transformations with which to automate this process. The advantage of this approach is that user requirements are captured from the early development stages of a data-warehousing project to automatically translate them into the entire data-warehousing platform, considering the different data marts. Finally, the authors provide screenshots of the CASE tools that support the approach, and a case study to show its benefits.
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Caballero-Morales, Santiago-Omar, and Gladys Bonilla-Enriquez. "SIX-SIGMA GUIDELINES TO IMPROVE INVENTORY MANAGEMENT IN A BOTTLING COMPANY." International Journal of Entrepreneurial Knowledge 10, no. 1 (June 30, 2022): 20–33. http://dx.doi.org/10.37335/ijek.v10i1.154.
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Warehousing allows timely distribution of goods between suppliers, manufacturers, retailers, and end customers. Thus, its optimal performance is crucial for the global supply chain. While there are methodologies to accomplish its optimal performance, few practical cases are reported in the specialized literature. This work describes the implementation of Six-Sigma to improve the warehousing operations associated to inventory management in an international bottling company in Mexico. This was performed through the DMAIC methodology with the following qualitative and quantitative tools: 5WH1, Root Cause Analysis, Ishikawa Diagram, SIPOC, and the 5 Why’s. After a three-month implementation plan, the improved inventory policies reduced stockout/overstock risks, order rejection rates, warehouse saturation, loading/unloading maneuvers, unsuitable storing practices, and increased distribution fleet utilization. These improvements implicated expected annual savings of approximately $4.0M, which can be increased if other processes beyond warehousing such as route and location planning are considered. The implementation details contribute to the limited case studies literature that can support the application to solve warehousing problems in other industries.
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Rogers, W. Pratt, M. Mustafa Kahraman, and Sean Dessureault. "Exploring the value of using data: a case study of continuous improvement through data warehousing." International Journal of Mining, Reclamation and Environment 33, no. 4 (November 24, 2017): 286–96. http://dx.doi.org/10.1080/17480930.2017.1405473.
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HONG, SOONGOO, PAIRIN KATERATTANAKUL, SUK-KI HONG, and QING CAO. "USAGE AND PERCEIVED IMPACT OF DATA WAREHOUSES: A STUDY IN KOREAN FINANCIAL COMPANIES." International Journal of Information Technology & Decision Making 05, no. 02 (June 2006): 297–315. http://dx.doi.org/10.1142/s0219622006001927.
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Although several previous studies have investigated the success factors and implementations of data warehouses, only few of them have explored the end-users' perceptions of data warehouses. Moreover, none of these previous studies were conducted in a company outside North America. Thus, this study was conducted to identify the data warehousing system characteristics affecting end-users' usage and perceived impact of using data warehouses in Korean financial companies. A research model for end-users' usage and perceived impact of using data warehouses was developed based on the Technology Acceptance Model and the IS Success Model. Then, a survey questionnaire was design to collect data from the data warehousing users in four leading Korean financial companies. We analyzed these data to test the proposed hypotheses by using Structural Equation Modeling. Results of this study suggest that Data Quality and End-user Support and Training are significant system characteristics affecting end-users' usage of data warehouses and perceived impact of data warehouses.
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Abhishek P.G. and Maheshwar Pratap. "Achieving Lean Warehousing Through Value Stream Mapping." South Asian Journal of Business and Management Cases 9, no. 3 (October 26, 2020): 387–401. http://dx.doi.org/10.1177/2277977920958551.
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This article applies value stream mapping (VSM) in a distribution warehouse after identifying and categorizing different warehousing wastes. The study suggests solutions for the reduction of each type of waste and employs lead time as the metric to understand the overall effectiveness of the suggested remedies. The distribution warehouse faced severe stock-out situations and high lead time for all deliveries. Current state and future state maps were utilized for mapping the current and revamped system, respectively. While existing studies on lean warehousing have utilized VSM to study a specific type of waste, this study extends it to include all types of warehousing waste, classifies them into seven types and provides a real case study along with evidence for improvement schemes for each category. This research, employing a case study, suggests an integrated lean warehousing method for design and operation of distribution warehouses. Dilemma/research question/purpose: Can the warehouse avoid stock-outs and decrease the lead time by identifying and reducing or eliminating the seven types of wastes in the warehouse operations? Theory: Lean management principle applied to a warehouse using value stream mapping to eliminate wastes. Type of the case: A problem-solving using lean tools carried out in a warehouse. Protagonist: Not needed. Options: Allow the current state to continue causing stock-outs and high lead times, or identify and reduce the wastes in the warehouse operations and avoid stock-outs, decrease lead times, and improve the overall efficiency of the warehouse. Discussions and case questions: Is it possible for the firm to go one step further than what the future state map has shown in the study? What other lean tools do you see fit to reduce or eliminate the types of waste outlined in this article?
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O'Leary, Daniel E. "BUILDING AND EVOLVING DATA WAREHOUSING AND BUSINESS INTELLIGENCE ARTEFACTS: THE CASE OF SYSCO." Intelligent Systems in Accounting, Finance and Management 18, no. 4 (October 2011): 195–213. http://dx.doi.org/10.1002/isaf.330.
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Salman, Ban, Nada M. Alhakkak, and Mustafa Musa Jaber. "Football Player Decision Support System Baghdad-City as a Case Study." International Journal of Engineering & Technology 7, no. 3.20 (September 1, 2018): 406. http://dx.doi.org/10.14419/ijet.v7i3.20.20582.
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Decision support system (DSS) is an area of information systems (IS) discipline which focuses on supporting decision-making. DSS includes personal decision support systems, executive information systems, online analytical processing systems, data warehousing, business intelligence, and group support systems. This paper introduced the implementation of a DSS related to football players with a case study.
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Lewczuk, Konrad, Michał Kłodawski, and Paweł Gepner. "Energy Consumption in a Distributional Warehouse: A Practical Case Study for Different Warehouse Technologies." Energies 14, no. 9 (May 9, 2021): 2709. http://dx.doi.org/10.3390/en14092709.
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Energy consumption by distribution warehouses has become an essential component of green warehousing and research on reducing the carbon footprint of supply chains. Energy consumption in warehousing is a complex and multilayered problem, which is generally considered in the literature in relation to its detailed components, not as part of comparative studies. In this article, the authors consider six cross-sectional variants of warehouse technology, from manual to fully automatic, and analyze the energy consumption of a warehouse in various configurations. A methodology for estimating storage space and determining energy consumption is proposed. The energy balance of the warehouse variants includes energy for material handling equipment operation, energy consumption for building maintenance (heating, cooling, lighting, etc.), and energy generated by the photovoltaic system on the roof. Then, the operational costs of the variants are estimated and, on their basis, an automation index is determined. The index allows for a comparative analysis of energy consumption and the mechanization and automation of a warehouse. It is shown that a significant part of the energy is spent on maintaining a warehouse building, especially in the case of facilities with a low degree of automation.
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Tomas Kucera. "Application of the Activity-Based Costing to the Logistics Cost Calculation for Warehousing in the Automotive Industry." Communications - Scientific letters of the University of Zilina 21, no. 4 (October 1, 2019): 35–42. http://dx.doi.org/10.26552/com.c.2019.4.35-42.
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Activity-based costing is one of the procedures that proved to be very suitable for the financial management of warehouse activities in the automotive industry. Accurate and up-to-date data enables managers to properly plan and manage all the warehousing related activities in the automotive industry. In the activity-based costing approach, overheads costs are allocated in relation to specific logistics activities of the company. The aim of the article is the application of activity-based costing to the logistics cost calculation for warehousing in the automotive industry. The article focuses on the practical application of activity-based costing to the logistics cost calculation for warehousing in the automotive industry to a particular logistics service provider. It highlights the positive and negative use of this method in the practical case study, which is one of the major qualitative scientific methods. The resulting effect of using the activity-based costing method should be to refine the information that is used for the decision-making problems of the top management of the logistics service provider.
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Miao, Xian, and Hong Qing Liu. "Approach of Economical Efficiency of Scale for Raw Materials Inventory: A Case (MRP) in Manufacturing." Applied Mechanics and Materials 401-403 (September 2013): 2337–40. http://dx.doi.org/10.4028/www.scientific.net/amm.401-403.2337.
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nformation transformation is important for state-owned manufacturing enterprises to improve the warehousing efficiency. Our work was: that with EDI in Intranet, applying the network database technology, designed the raw materials database and its application system for a large component supplier. Practice shows that this system realizes centralizing and processing for all kinds of contracts, suppliers, wagons, planning, bills for collection and inventory data. Thereby improve validity and timeliness of raw material delivery; reduce inventory management cost.
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Tufano, Alessandro, Riccardo Accorsi, and Riccardo Manzini. "A machine learning approach for predictive warehouse design." International Journal of Advanced Manufacturing Technology 119, no. 3-4 (December 9, 2021): 2369–92. http://dx.doi.org/10.1007/s00170-021-08035-w.
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AbstractWarehouse management systems (WMS) track warehousing and picking operations, generating a huge volumes of data quantified in millions to billions of records. Logistic operators incur significant costs to maintain these IT systems, without actively mining the collected data to monitor their business processes, smooth the warehousing flows, and support the strategic decisions. This study explores the impact of tracing data beyond the simple traceability purpose. We aim at supporting the strategic design of a warehousing system by training classifiers that can predict the storage technology (ST), the material handling system (MHS), the storage allocation strategy (SAS), and the picking policy (PP) of a storage system. We introduce the definition of a learning table, whose attributes are benchmarking metrics applicable to any storage system. Then, we investigate how the availability of data in the warehouse management system (i.e. varying the number of attributes of the learning table) affects the accuracy of the predictions. To validate the approach, we illustrate a generalisable case study which collects data from sixteen different real companies belonging to different industrial sectors (automotive, manufacturing, food and beverage, cosmetics and publishing) and different players (distribution centres and third-party logistic providers). The benchmarking metrics are applied and used to generate learning tables with varying number of attributes. A bunch of classifiers is used to identify the crucial input data attributes in the prediction of ST, MHS, SAS, and PP. The managerial relevance of the data-driven methodology for warehouse design is showcased for 3PL providers experiencing a fast rotation of the SKUs stored in their storage systems.
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Waubert de Puiseau, Constantin, Dimitri Tegomo Nanfack, Hasan Tercan, Johannes Löbbert-Plattfaut, and Tobias Meisen. "Dynamic Storage Location Assignment in Warehouses Using Deep Reinforcement Learning." Technologies 10, no. 6 (December 11, 2022): 129. http://dx.doi.org/10.3390/technologies10060129.
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The warehousing industry is faced with increasing customer demands and growing global competition. A major factor in the efficient operation of warehouses is the strategic storage location assignment of arriving goods, termed the dynamic storage location assignment problem (DSLAP). This paper presents a real-world use case of the DSLAP, in which deep reinforcement learning (DRL) is used to derive a suitable storage location assignment strategy to decrease transportation costs within the warehouse. The DRL agent is trained on historic data of storage and retrieval operations gathered over one year of operation. The evaluation of the agent on new data of two months shows a 6.3% decrease in incurring costs compared to the currently utilized storage location assignment strategy which is based on manual ABC-classifications. Hence, DRL proves to be a competitive solution alternative for the DSLAP and related problems in the warehousing industry.
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Totin, Ashley, and Brett Connor. "Evaluating Business Models Enabling Organic Additive Manufacturing for Maintenance and Sustainment." Defense Procurement and Public Policy Regulation, no. 90 (October 1, 2019): 380–417. http://dx.doi.org/10.22594/dau.18-815.26.04.
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This research examines the spare parts data business models allowing the government to produce parts on demand (i.e., only when required versus long-term warehousing) and at the point-of-need using additive manufacturing. The research includes a survey of acquisition and engineering professionals within government and industry, and an analysis using an aviation case study.
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Healey, R. G., and J. Delve. "Integrating GIS and data warehousing in a Web environment: A case study of the US 1880 Census." International Journal of Geographical Information Science 21, no. 6 (July 2007): 603–24. http://dx.doi.org/10.1080/13658810601135742.
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Wasson, Christina, Melanie Medina, Miyoung Chong, Brittany LeMay, Emma Nalin, and Kenneth Saintonge. "Designing for Diverse User Groups: Case Study of a Language Archive." Journal of Business Anthropology 7, no. 2 (November 12, 2018): 235–67. http://dx.doi.org/10.22439/jba.v7i2.5605.
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This article explores the challenges of designing large-scale computing systems for multiple, diverse user groups. Such computing systems house large, complex datasets, and often provide analytic tools to interpret the data. They are increasingly central to activities in industry, science, and government agencies, and are often associated with “big data,” data warehousing, and/or scientific “cyberinfrastructure”. A key characteristic of these systems is the diversity and multiplicity of their intended user groups, which may range from various scientific disciplines, to assorted business functions, to government officials and citizen groups. These user groups occupy structurally different positions in local and global political economies, and bring different forms of expertise to the data housed in the computing system. We argue that design anthropologists can contribute to the usefulness of such systems by engaging in collaborative ethnographic research with the targeted user groups, and communicating findings to the designers and developers creating these systems.
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He, Dan. "Teaching Practices of a Warehousing Management Curriculum based on Virtual Reality Simulation Technology." International Journal of Emerging Technologies in Learning (iJET) 17, no. 09 (May 10, 2022): 96–109. http://dx.doi.org/10.3991/ijet.v17i09.30939.
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Warehousing management is a specialized core curriculum in the logistics management major. The curriculum not only teaches strong theoretical concepts, but also practical skills. Traditional teaching mode emphasizes on theoretical teaching due to the lack of sufficient practical conditions; hence, students’ practical abilities cannot be developed comprehensively. Therefore, this study proposed teaching reform measures, such as reconstructing the curriculum content, implementing modularized teaching, and creating a build-task-exercise-evaluation teaching mode by introducing virtual reality (VR) simulation technology and improving the teaching method. With these measures, students could finish their tasks and realize their learning objectives in the virtual intelligent warehouse environment by combining the knowledge and skills they have learned. Moreover, students were asked to design a warehouse layout by using the simulation software according to enterprise case data. Results show that the task-driven teaching reform for warehousing management curriculum based on VR technology improves the efficiency and quality of students’ skill training.
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Malinowska, Magdalena, Andrzej Rzeczycki, and Mariusz Sowa. "Roadmap to sustainable warehouse." SHS Web of Conferences 57 (2018): 01028. http://dx.doi.org/10.1051/shsconf/20185701028.
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Heading towards sustainable logistic is a popular tendency. However it is widely discussed in case of supply chain, there are many studies concerning warehouse and warehousing. Introducing and developing sustainable warehouse solutions is often a challenge. In the article, the authors analysed the literature sources (scientific publications and professional studies) to indicate directions and changes in technological, managerial, social, environmental and economic aspects of warehouse functioning that are required to go forward to sustainable tendency. To summarize the studies, the application model presenting assessment of the status of sustainable warehouse is proposed. The purpose of this model is to provide policy-makers insights to identify actual state of warehouse in a company and perspectives of its development.
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Gibbs, Alison L., Kevin J. Keen, and Liqun Wang. "Case studies in data analysis." Canadian Journal of Statistics 39, no. 2 (May 23, 2011): 181–217. http://dx.doi.org/10.1002/cjs.10102.
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Marrelli, Anne F. "Collecting data through case studies." Performance Improvement 46, no. 7 (2007): 39–44. http://dx.doi.org/10.1002/pfi.148.
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