Relevant bibliographies by topics / Inventory control management system

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

Academic literature on the topic 'Inventory control management system'

Author: Grafiati
Published: 4 June 2021
Last updated: 16 February 2022

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Journal articles on the topic "Inventory control management system"

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Freeman, Jim, and C. D. J. Waters. "Inventory Control and Management." Journal of the Operational Research Society 44, no. 3 (March 1993): 316. http://dx.doi.org/10.2307/2584204.

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Freeman, Jim. "Inventory Control and Management." Journal of the Operational Research Society 44, no. 3 (March 1993): 316–17. http://dx.doi.org/10.1057/jors.1993.59.

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Gelders, L. F. "Inventory control and management." European Journal of Operational Research 62, no. 3 (November 1992): 386–87. http://dx.doi.org/10.1016/0377-2217(92)90136-w.

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Dona Sabila, Alzena, Mustafid Mustafid, and Suryono Suryono. "Inventory Control System by Using Vendor Managed Inventory (VMI)." E3S Web of Conferences 31 (2018): 11015. http://dx.doi.org/10.1051/e3sconf/20183111015.

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The inventory control system has a strategic role for the business in managing inventory operations. Management of conventional inventory creates problems in the stock of goods that often runs into vacancies and excess goods at the retail level. This study aims to build inventory control system that can maintain the stability of goods availability at the retail level. The implementation of Vendor Managed Inventory (VMI) method on inventory control system provides transparency of sales data and inventory of goods at retailer level to supplier. Inventory control is performed by calculating safety stock and reorder point of goods based on sales data received by the system. Rule-based reasoning is provided on the system to facilitate the monitoring of inventory status information, thereby helping the process of inventory updates appropriately. Utilization of SMS technology is also considered as a medium of collecting sales data in real-time due to the ease of use. The results of this study indicate that inventory control using VMI ensures the availability of goods ± 70% and can reduce the accumulation of goods ± 30% at the retail level.
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Potamianos, J., and A. J. Orman. "An Interactive Dynamic Inventory-Production Control System." Journal of the Operational Research Society 47, no. 8 (August 1996): 1017. http://dx.doi.org/10.2307/3010409.

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Potamianos, J., and A. J. Orman. "An Interactive Dynamic Inventory-Production Control System." Journal of the Operational Research Society 47, no. 8 (August 1996): 1017–28. http://dx.doi.org/10.1057/jors.1996.128.

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Pons, Dirk. "System model of production inventory control." International Journal of Manufacturing Technology and Management 20, no. 1/2/3/4 (2010): 120. http://dx.doi.org/10.1504/ijmtm.2010.032895.

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Sinha, Diptendu, Nasir Ghiaseddin, and Khalil Matta. "Expert systems for inventory control management." Computers & Industrial Engineering 17, no. 1-4 (January 1989): 425–29. http://dx.doi.org/10.1016/0360-8352(89)90099-5.

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Gardner, Everette S. "Evaluating Forecast Performance in an Inventory Control System." Management Science 36, no. 4 (April 1990): 490–99. http://dx.doi.org/10.1287/mnsc.36.4.490.

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Krajčovič, Martin, and Dariusz Plinta. "Adaptive inventory control system for material items with continuous non-stationary demand." Management and Production Engineering Review 5, no. 1 (March 1, 2014): 11–20. http://dx.doi.org/10.2478/mper-2014-0002.

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Abstract This paper describes an algorithm of dynamic inventory control system for large numbers of material items with continuous non-stationary demand. It uses principles of pull inventory control systems, statistical inventory analysis and joint replenishment inventory systems. This algorithm was processed in software module (VBA for Excel) and applied in practice. The target of described algorithm is to keep an optimum inventory level and optimum customer service level in terms of inventory control of items with non-stationary demand.
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Dissertations / Theses on the topic "Inventory control management system"

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Maxwell, Andrew Charles. "A TEACHING JOB SHOP CONTROL SYSTEM WITH REAL-TIME INVENTORY MANAGEMENT." NCSU, 2005. http://www.lib.ncsu.edu/theses/available/etd-06302005-195145/.

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This thesis presents a teaching job shop control system for running in assembly laboratories at colleges and universities in preparing Industrial Engineering students for challenges faced in real-world factories. Current techniques fail to encompass this idea of training for students like the proposed method does. Microsoft Access was used in creating a database that is the center point in this new system. Inventory is managed using this database system and added if parts are created in the manufacturing lab and moved to the assembly area. The system will stop if parts are low until new parts are created. In this new system, a pallet with an unfinished product on it moves down a conveyor system until it reaches the next workstation. At this station, the station operator scans a barcode on the pallet. This barcode contains what product is on this pallet. Based on this information, an ordered list of tasks appears on the workstation computer screen and must be done before the pallet can be moved on. When all tasks have been completed at a station, the station operator clicks ?done? on the screen and then can either move to the next pallet or end the run. Statistics are kept on the quality of the final products and parts as well as a work-in-process and on a goal percentage of good products out at the end of a one-hour time frame. Administrators will be able to assign tasks and parts to products and stations, as well as be able assign the goal ahead of time.
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Sanyal, Chiranjib. "Development of a web based inventory management system for a small retail business." [Denver, Colo.] : Regis University, 2005. http://165.236.235.140/lib/CSanyal2005.pdf.

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Chancasanampa-Mandujano, Jesenia, Karla Espinoza-Poblete, Juan Sotelo-Raffo, Jose Maria Alvarez, and Carlos Raymundo-Ibañez. "Inventory management model based on a stock control system and a kraljic matrix to reduce raw materials inventory." Association for Computing Machinery, 2019. http://hdl.handle.net/10757/656253.

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El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.
This research project proposes a supply management model in a consumer goods company in Lima, Peru, to improve stock control and avoid raw materials stockouts and overstock. A Kraljic matrix was used to identify products based on their criticality considering material segmentation, warehouse capacity and times, and ABC segmentation to classify products on each quadrant of the matrix. This project also focuses on defining purchasing and supply strategies in each quadrant of the matrix. This model involves the development of three processes that are related to a new purchasing strategy: economic order quantity, lot-for-lot ordering, and just in time. This new system is based on a more accurate inventory because continuous improvement attracts employees’ attention and engages them in reducing the number of manual notifications made by operators every month. Moreover, after implementing the new procedure for recording inventories, the inventory record was 87% accurate, whereas, in the past, the inventory was not counted and was performed by employees of other areas.
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Veatch, Michael H. "Queueing control problems for production/inventory systems." Thesis, Massachusetts Institute of Technology, 1992. http://hdl.handle.net/1721.1/12859.

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Horwatt, Robert M. "Web-based inventory management system for the West Virginia State Police." Morgantown, W. Va. : [West Virginia University Libraries], 2007. https://eidr.wvu.edu/etd/documentdata.eTD?documentid=5204.

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Thesis (M.S.)--West Virginia University, 2007.
Title from document title page. Document formatted into pages; contains ix, 142 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 25).
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Ozpamukcu, Serkan. "An Assessment Of A Two-echelon Inventory System Againstalternative Systems." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613949/index.pdf.

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In this study, we focus on a real life problem that involves a single item which is used in military operations. The items in use fail according to a Poisson process and lead times are deterministic. Four alternative inventory control models are developed. Among these models, a two-echelon system consisting of a depot in the upper and several bases in the lower echelon is operated currently. This system is compared to a single-echelon system that consists of several bases. The comparison reveals the importance of the holding cost incurred for the items intransit between the depot and the base which is ignored in most of the studies in literature. Both the two and single-echelon models are also extended to have repair ability. A continuous-review base-stock policy is used for all models. Exact models are formulated. The results are obtained under various lead time, unit costs and demand parameters. Results of four different settings are compared and the findings are reported.
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Bai, Sherman Xiewei. "Scheduling manufacturing systems with work-in-process inventory control." Thesis, Massachusetts Institute of Technology, 1991. http://hdl.handle.net/1721.1/13477.

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Edara, Praveen Kumar. "Dynamic Travel Demand Management Strategies: Dynamic Congestion Pricing and Highway Space Inventory Control System." Diss., Virginia Tech, 2005. http://hdl.handle.net/10919/28889.

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The number of trips on highways and urban networks has significantly increased in the recent decades in many cities across the world. At the same time, the road network capacities have not kept up with this increase in travel demand. Urban road networks in many countries are severely congested, resulting in increased travel times, increased number of stops, unexpected delays, greater travel costs, inconvenience to drivers and passengers, increased air pollution and noise level, and increased number of traffic accidents. Expanding traffic network capacities by building more roads is extremely costly as well as environmentally damaging. More efficient usage of the existing supply is vital in order to sustain the growing travel demand. Travel Demand Management (TDM) techniques involving various strategies that increase the travel choices to the consumers have been proposed by the researchers, planners, and transportation professionals. TDM helps create a well balanced, less automobile dependent transportation system. In the past, several TDM strategies have been proposed and implemented in several cities around the world. All these TDM strategies, with very few exceptions, are static in nature. For example, in the case of congestion pricing, the toll schedules are previously set and are implemented on a daily basis. The amount of toll does not vary dynamically, with time of day and level of traffic on the highway (though the peak period tolls are different from the off-peak tolls, they are still static in the sense that the tolls don't vary continuously with time and level of traffic). The advent of Electronic Payment Systems (EPS), a branch of the Intelligent Transportation Systems (ITS), has made it possible for the planners and researchers to conceive of dynamic TDM strategies. Recently, few congestion pricing projects are beginning to adopt dynamic tolls that vary continuously with the time of day based on the level of traffic (e.g. I-15 value pricing in California). Dynamic TDM is a relatively new and unexplored topic and the future research attempts to provide answers to the following questions: 1) How to propose and model a Dynamic TDM strategy, 2) What are the advantages of Dynamic TDM strategies as compared to their Static counterparts, 3) What are the benefits and costs of implementing such strategies, 4) What are the travel impacts of implementing Dynamic TDM strategies, and 5) How equitable are the Dynamic TDM strategies as compared to their Static counterparts. This dissertation attempts to address question 1 in detail and deal with the remaining questions to the extent possible, as questions 2, 3, 4, and 5, can be best answered only after some real life implementation of the proposed Dynamic TDM strategies. Two novel Dynamic TDM strategies are proposed and modeled in this dissertation -- a) Dynamic Congestion Pricing and b) Dynamic Highway Space Inventory Control System. In the first part, dynamic congestion pricing, a real-time road pricing system in the case of a two-link parallel network is proposed and modeled. The system that is based on a combination of Dynamic Programming and Neural Networks makes "on-line" decisions about road toll values. In the first phase of the proposed model, the best road toll sequences during certain time period are calculated off-line for many different patterns of vehicle arrivals. These toll sequences are computed using Dynamic Programming approach. In the second phase, learning from vehicle arrival patterns and the corresponding optimal toll sequences, neural network is trained. The results obtained during on-line tests are close to the best solution obtained off-line assuming that the arrival pattern is known. Highway Space Inventory Control System (HSICS), a relatively new demand management concept, is proposed and modeled in the second half of this dissertation. The basic idea of HSICS is that all road users have to make reservations in advance to enter the highway. The system allows highway operators to make real-time decisions whether to accept or reject travellers' requests to use the highway system in order to achieve certain system-wide objectives. The proposed HSICS model consists of two modules -- Highway Allocation System (HAS) and the Highway Reservation System (HRS). The HAS is an off-line module and determines the maximum number of trips from each user class (categorized based on time of departure, vehicle type, vehicle occupancy, and trip distance) to be accepted by the system given a pre-defined demand. It develops the optimal highway allocations for different traffic scenarios. The "traffic scenarios-optimal allocations" data obtained in this way enables the development of HRS. The HRS module operates in the on-line mode to determine whether a request to make a trip between certain origin-destination pair in certain time interval is accepted or rejected.
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Kletter, David B. (David Brian). "Planning and control of an unreliable machine in a multi-item production-inventory system." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/10794.

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Allen, Mary Kay. "The development of an artificial intelligence system for inventory management using multiple experts /." The Ohio State University, 1986. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487266691094494.

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Books on the topic "Inventory control management system"

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U.S. DEPT. OF THE ARMY. Supply support activity supply system: Manual procedures : inventory management. Washington, DC: Headquarters, Dept. of the Army, 1998.

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Parts management models and applications: A supply chain system integration perspective. New York: Springer, 2005.

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Inventory management explained: A focus on forecasting, lot sizing, safety stock, and ordering systems. Pleasant Prairie, WI: Ops Pub., 2009.

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McCarter, James B. Landscape Management System: A computer tool for helping family forest owners make management decisions. [Pullman, Wash.]: Washington State University Extension, 2007.

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1937-, Peterson Rein, ed. Decision systems for inventory management and production planning. 2nd ed. New York: Wiley, 1985.

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Silver, Edward A. Decision systems for inventory management and production planning. 2nd ed. New York: Wiley, 1985.

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service), SpringerLink (Online, ed. Periodic Review Inventory Systems: Performance Analysis and Optimization of Inventory Systems within Supply Chains. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2011.

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Integrating Kanban with MRPII: Automating a pull system for enhanced JIT inventory management. Portland, Or: Productivity Press, 1997.

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Allen, Mary Kathryn. The development of an artificial intelligence system for inventory management using multiple experts. Oak Brook, Ill: Council of Logistics Management, 1987.

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Zobrist, Kevin. Inventory Wizard: A new tool that makes it easy to get started with the Landscape Management System. [Pullman]: Washington State University Extension, 2006.

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Book chapters on the topic "Inventory control management system"

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Shenoy, Dinesh, and Roberto Rosas. "Inventory Control Systems: Design Factors." In Problems & Solutions in Inventory Management, 13–32. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-65696-0_2.

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Nazarov, Anatoly, Valentina Broner, and Alexander Moiseev. "Inventory Management System with Two-Switch Synchronous Control." In Developments in Language Theory, 212–23. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99447-5_18.

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Richter, Knut, and Imre Dobos. "Production-Inventory Control in an EOQ-Type Reverse Logistics System." In Supply Chain Management and Reverse Logistics, 139–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24815-6_7.

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Nazarov, Anatoly, and Valentina Broner. "Inventory Management System with On/Off Control of Input Product Flow." In Information Technologies and Mathematical Modelling. Queueing Theory and Applications, 370–81. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-68069-9_30.

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Nazarov, Anatoly, and Valentina Broner. "Inventory Management System with On/Off Control of Output Product Flow." In Analytical and Computational Methods in Probability Theory, 132–44. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-71504-9_13.

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Panigrahi, Rashmi Ranjan, and Duryodhan Jena. "Inventory Control for Materials Management Functions—A Conceptual Study." In Advances in Intelligent Systems and Computing, 187–93. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9330-3_17.

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Mandel, Alexander, and Sergey Granin. "Multi-step Problem of Inventory Control with Returns." In Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems, 521–27. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-85874-2_55.

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Liu, Ming-wu, Feng Xi, and Hong Chen. "Control Policies for a Markov Queueing-Inventory System with Two Demand Classes." In International Asia Conference on Industrial Engineering and Management Innovation (IEMI2012) Proceedings, 1543–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38445-5_162.

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Mane, Sandip, Jay Bhuva, and Smit Patel. "Implementation of 5S to Set Up Inventory Control System with HTML Coded Spare Management System." In Proceedings of International Conference on Intelligent Manufacturing and Automation, 327–36. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4485-9_34.

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Loy, Maari L., Rodney D. Traub, Limin Zhang, Pratap Kotala, Monte Roemmich, Jesse Breidenbach, and Robert Nelson. "Beyond the Use of Robotics: Operations and Supply Chain Control for Effective Inventory Management in a Health System Pharmacy." In Advances in Healthcare Informatics and Analytics, 145–55. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-23294-2_7.

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Conference papers on the topic "Inventory control management system"

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Kumbhakarna, Govind A., and R. P. Chaudhari. "RFID basedlab inventory management system." In 2017 International Conference on Information, Communication, Instrumentation and Control (ICICIC). IEEE, 2017. http://dx.doi.org/10.1109/icomicon.2017.8279154.

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Wang, Weipeng. "Safety inventory management — A system dynamics model." In 2012 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER). IEEE, 2012. http://dx.doi.org/10.1109/cyber.2012.6320054.

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Alexander, V. A. Mandel. "Inventory control policies for random lead times." In 2017 Tenth International Conference Management of Large-Scale System Development (MLSD). IEEE, 2017. http://dx.doi.org/10.1109/mlsd.2017.8109659.

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Binti Ismail, Siti Zubaidah, S. C. Morton, J. A. Harding, and R. Michaelides. "Product-Service System in inventory control: A new paradigm?" In 2015 International Conference on Industrial Engineering and Operations Management (IEOM). IEEE, 2015. http://dx.doi.org/10.1109/ieom.2015.7093775.

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Satiti, D., A. Rusdiansyah, and R. S. Dewi. "Review of Refrigerated Inventory Control System for Perishable Products." In 2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2018. http://dx.doi.org/10.1109/ieem.2018.8607825.

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Schwartz, Jay D., Manuel R. Arahal, and Daniel E. Rivera. "Control-relevant demand forecasting for management of a production-inventory system." In 2008 American Control Conference (ACC '08). IEEE, 2008. http://dx.doi.org/10.1109/acc.2008.4587127.

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Tahir, Numera, and Muhammad Abbas Choudhary. "Development of a decision support system for Inventory Analysis and Control." In 2011 IEEE International Technology Management Conference (ITMC). IEEE, 2011. http://dx.doi.org/10.1109/itmc.2011.5996067.

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Li, Jizi, Peiling Guo, and Zhijun Zuo. "Inventory Control Model for Mobile Supply Chain Management." In 2008 International Conference on Embedded Software and Systems Symposia (ICESS Symposia). IEEE, 2008. http://dx.doi.org/10.1109/icess.symposia.2008.85.

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Tewary, Moumita, Debabrata Das, and Nirmal Baran Hui. "Inventory control model of a 4-Echelon production-distribution system." In 2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2017. http://dx.doi.org/10.1109/ieem.2017.8289929.

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Hai, Dong, Tang Xiao-hua, Tong Yan, and Li Yan-ping. "Research on Model Predictive Control for Inventory Management in Decentralized Supply Chain System." In 2009 International Conference on Information Management, Innovation Management and Industrial Engineering. IEEE, 2009. http://dx.doi.org/10.1109/iciii.2009.67.

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Reports on the topic "Inventory control management system"

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Allen, James, Matthew Werth, Marissa Campobasso, and Yazen Kashlan. Sustainment management system, water control structures : inventory and inspection template. Engineer Research and Development Center (U.S.), March 2021. http://dx.doi.org/10.21079/11681/39859.

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Author, Not Given. RIMS (Records Inventory Management System) Handbook. Office of Scientific and Technical Information (OSTI), March 1989. http://dx.doi.org/10.2172/6201982.

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CORPS OF ENGINEERS WASHINGTON DC. Management Information Control: Management Information Control System. Fort Belvoir, VA: Defense Technical Information Center, January 1990. http://dx.doi.org/10.21236/ada404680.

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Rafnson, Gary. Designing an (s,S) Inventory Control System. Fort Belvoir, VA: Defense Technical Information Center, June 1998. http://dx.doi.org/10.21236/ada348287.

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Bence, P. J. Management control system description. Office of Scientific and Technical Information (OSTI), October 1990. http://dx.doi.org/10.2172/12982133.

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Wilson, D. Inventory processes for HANDI 2000 business management system. Office of Scientific and Technical Information (OSTI), August 1998. http://dx.doi.org/10.2172/10154406.

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Bowles, David, Michael Williams, Hope Dodd, Lloyd Morrison, Janice Hinsey, Tyler Cribbs, Gareth Rowell, Michael DeBacker, Jennifer Haack-Gaynor, and Jeffrey Williams. Protocol for monitoring aquatic invertebrates of small streams in the Heartland Inventory & Monitoring Network: Version 2.1. National Park Service, April 2021. http://dx.doi.org/10.36967/nrr-2284622.

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The Heartland Inventory and Monitoring Network (HTLN) is a component of the National Park Service’s (NPS) strategy to improve park management through greater reliance on scientific information. The purposes of this program are to design and implement long-term ecological monitoring and provide information for park managers to evaluate the integrity of park ecosystems and better understand ecosystem processes. Concerns over declining surface water quality have led to the development of various monitoring approaches to assess stream water quality. Freshwater streams in network parks are threatened by numerous stressors, most of which originate outside park boundaries. Stream condition and ecosystem health are dependent on processes occurring in the entire watershed as well as riparian and floodplain areas; therefore, they cannot be manipulated independently of this interrelationship. Land use activities—such as timber management, landfills, grazing, confined animal feeding operations, urbanization, stream channelization, removal of riparian vegetation and gravel, and mineral and metals mining—threaten stream quality. Accordingly, the framework for this aquatic monitoring is directed towards maintaining the ecological integrity of the streams in those parks. Invertebrates are an important tool for understanding and detecting changes in ecosystem integrity, and they can be used to reflect cumulative impacts that cannot otherwise be detected through traditional water quality monitoring. The broad diversity of invertebrate species occurring in aquatic systems similarly demonstrates a broad range of responses to different environmental stressors. Benthic invertebrates are sensitive to the wide variety of impacts that influence Ozark streams. Benthic invertebrate community structure can be quantified to reflect stream integrity in several ways, including the absence of pollution sensitive taxa, dominance by a particular taxon combined with low overall taxa richness, or appreciable shifts in community composition relative to reference condition. Furthermore, changes in the diversity and community structure of benthic invertebrates are relatively simple to communicate to resource managers and the public. To assess the natural and anthropo-genic processes influencing invertebrate communities, this protocol has been designed to incorporate the spatial relationship of benthic invertebrates with their local habitat including substrate size and embeddedness, and water quality parameters (temperature, dissolved oxygen, pH, specific conductance, and turbidity). Rigid quality control and quality assurance are used to ensure maximum data integrity. Detailed standard operating procedures (SOPs) and supporting information are associated with this protocol.
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Aas, Christopher A., James E. Lenhart, Olin H. Bray, and Christina Jenkin Witcher. Defense Nuclear Material Stewardship Integrated Inventory Information Management System (IIIMS). Office of Scientific and Technical Information (OSTI), November 2004. http://dx.doi.org/10.2172/975256.

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Clark, Sr, and Robert B. Tomahawk Weapon Control System Release Management Study. Fort Belvoir, VA: Defense Technical Information Center, March 1990. http://dx.doi.org/10.21236/ada221057.

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Wilson, D. Funds control for HANDI 2000 business management system. Office of Scientific and Technical Information (OSTI), August 1998. http://dx.doi.org/10.2172/10154388.

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