Challenges with Multi-Dimensional Inventory Classifications and Optimization
- Dinesh Dhoka
- Lokeswara Y. Choudary
Abstract
The level of automation in Inventory Management is increasing day by day. In ERPs various parameters have to be defined to achieve even simple levels of automation like Reorder-Point, Minimum Order Quantity, Lot-Size, Lead-Time etc. Inventory Management with today’s ERP systems can become simpler if the parameter settings of Materials Requirement Planning (MRP) and Master Production Schedule (MPS) are clearly understood and mapped. Various Inventory Classification methods are used like the ABC, XYZ, VED, FSN, HML, SDE etc. to group the products and maintain similar parameter settings for different group of products. Each parameter setting and product classifications have underlying assumptions. In our daily business the underlying assumptions may often be overlooked. The primary objective in this study is to highlight one of the assumptions taken for granted and to find an optimized solution for Inventory Classification for this assumption. This in turn can help enterprises be more flexible with better managed inventory.- Full Text: PDF
- DOI:10.5539/ass.v11n4p365
This work is licensed under a Creative Commons Attribution 4.0 License.
Journal Metrics
Index
- Academic Journals Database
- BASE (Bielefeld Academic Search Engine)
- Berkeley Library
- CNKI Scholar
- COPAC
- EBSCOhost
- EconBiz
- Elektronische Zeitschriftenbibliothek (EZB)
- Excellence in Research for Australia (ERA)
- Genamics JournalSeek
- GETIT@YALE (Yale University Library)
- Harvard Library
- IBZ Online
- IDEAS
- Infotrieve
- JournalTOCs
- LOCKSS
- MIAR
- Mir@bel
- NewJour
- OAJI
- Open J-Gate
- PKP Open Archives Harvester
- Publons
- Questia Online Library
- RePEc
- SafetyLit
- SHERPA/RoMEO
- Standard Periodical Directory
- Stanford Libraries
- Technische Informationsbibliothek (TIB)
- The Keepers Registry
- Universe Digital Library
- VOCEDplus
- WorldCat
Contact
- Jenny ZhangEditorial Assistant
- ass@ccsenet.org