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.
OPSOMMINGDie rangskikking van inventarisse maak gebruik van verskeie kriteria om verskillende aspekte van inventarisbestuur te beheer. In hierdie artikel word ʼn nuwe rangskikking algoritme ontwikkel wat die klassieke ABC-klassifikasie met ʼn nuwe groeperingstrategie kombineer. Die hanteringsfrekwensie, leityd, kontrakvervaardigingproses en spesialiteit word as insetkriteria gebruik. Die uitsette is die nuwe klassoorte vir die inventarisse. Die algoritme is in ʼn 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 wasigheidsleermetodes. 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.