AN INVENTORY CLASSIFICATION APPROACH COMBINING EXPERT SYSTEMS, CLUSTERING, AND FUZZY LOGIC WITH THE ABC METHOD, AND AN APPLICATION
| Autor: | Necaattin Barişçi, Ahmet Kürşad Türker, A Dalgic, Süleyman Ersöz, Adnan Aktepe |
|---|---|
| Přispěvatelé: | Kırıkkale Üniversitesi |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
021103 operations research
lcsh:T55.4-60.8 Computer science Process (engineering) Control (management) Inventory Grouping 0211 other engineering and technologies ComputerApplications_COMPUTERSINOTHERSYSTEMS 02 engineering and technology computer.software_genre Fuzzy logic Industrial and Manufacturing Engineering Expert system Clustering Inventory management Fuzzy Logic 0202 electrical engineering electronic engineering information engineering lcsh:Industrial engineering. Management engineering 020201 artificial intelligence & image processing Data mining Cluster analysis Pareto analysis computer Lead time |
| Zdroj: | South African Journal of Industrial Engineering, Volume: 29, Issue: 1, Pages: 49-62, Published: 2018 South African Journal of Industrial Engineering, Vol 29, Iss 1, Pp 49-62 (2018) |
| Popis: | The classification of inventories requires using several criteria to control different functions of inventory management. In this study, a new classification algorithm, called the FNS (functional, normal, and small) algorithm, is developed that combines classical ABC classification with a new grouping strategy. In the algorithm, handling frequency, lead time, contract manufacturing process, and specialty are used as input criteria, and the outputs are new classes for the inventories. The algorithm is applied in a large company operating in the defence industry. The main problem in the company is not being able to manage and track inventories effectively. The company has previously used the Pareto analysis approach, but this no longer met the company's inventory management needs. In our study, the ABC classification method is enriched and combined with the proposed FNS algorithm to create nine different classes for inventories. To achieve this, the classical ABC classification method is integrated with expert systems, clustering, and fuzzy logic methods. Now, inventories can be classified in more detail, and useful counting strategies can be created. The classification system developed is currently being used by the company, and is integrated into its enterprise resources planning (ERP) system. Die rangskikking van inventarisse maak gebruik van verskeie kriteria om verskillende aspekte van inventarisbestuur te beheer. In hierdie artikel word 'n nuwe rangskikking algoritme ontwikkel wat die klassieke ABC-klassifikasie met 'n nuwe groeperingstrategie kombineer. Die hanteringsfrekwensie, leityd, kontrakvervaardiging-proses en spesialiteit word as insetkriteria gebruik. Die uitsette is die nuwe klassoorte vir die inventarisse. Die algoritme is in 'n groot maatskappy, wat in die verdedigingsektor handel, toegepas. Die maatskappy se bestaande inventarisbestuurstelsel voldoen nie meer aan hul behoefte nie. Die bestaande stelsel het voorheen van die Pareto-analise benadering gebruik gemaak. Die voorgestelde algoritme skep nege verskillende klasse vir inventarisse. Om dit te bewerkstellig word die klassieke ABC-klassifikasie metode geïntegreer met ekspertstelsels, bondelvorming, en wasigheidsleer-metodes. Nou kan inventarisse in meer detail geklassifiseer word en nuttige voorraadopname-strategieë kan geskep word. Die voorgestelde algoritme word deur die maatskappy gebruik en is in hul hulpbron-bestuurstelsel geïntegreer. |
| Databáze: | OpenAIRE |
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