| 词条 | ABC analysis | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 释义 |
In materials management, the ABC analysis (or Selective Inventory Control) is an inventory categorization technique. ABC analysis divides an inventory into three categories—"A items" with very tight control and accurate records, "B items" with less tightly controlled and good records, and "C items" with the simplest controls possible and minimal records. The ABC analysis provides a mechanism for identifying items that will have a significant impact on overall inventory cost,[1] while also providing a mechanism for identifying different categories of stock that will require different management and controls. The ABC analysis suggests that inventories of an organization are not of equal value.[2] Thus, the inventory is grouped into three categories (A, B, and C) in order of their estimated importance. 'A' items are very important for an organization. Because of the high value of these 'A' items, frequent value analysis is required. In addition to that, an organization needs to choose an appropriate order pattern (e.g. 'just-in-time') to avoid excess capacity. 'B' items are important, but of course less important than 'A' items and more important than 'C' items. Therefore, 'B' items are intergroup items. 'C' items are marginally important. ABC analysis categoriesThere are no fixed threshold for each class, different proportion can be applied based on objective and criteria. ABC Analysis is similar to the Pareto principle in that the 'A' items will typically account for a large proportion of the overall value but a small percentage of the number of items.[3] Examples of ABC class are
Another recommended breakdown of ABC classes:[4]
ABC analysis in ERP packagesMajor ERP packages have built-in function of ABC analysis. User can execute ABC analysis based on user defined criteria and system apply ABC code to items (parts). Mathematical calculation of ABC analysisComputed (calculated) ABC analysis delivers a precise mathematical calculation of the limits for the ABC classes.[5] It uses an optimization of cost (i.e. number of items) versus yield (i.e. sum of their estimated importance). Computed ABC was, for example, applied to feature selection for biomedical data,[6] business process management[7] and bankruptcy prediction.[8] Example of the application of weighed operation based on ABC classActual distribution of ABC class in the electronics manufacturing company with 4,051 active parts.
Using this distribution of ABC class and change total number of the parts to 14,213.
When equal purchasing policy is applied to all 14,213 components, for example weekly delivery and re-order point (safety stock) of two weeks' supply, the factory will have 16,000 deliveries in four weeks and average inventory will be 2½ weeks' supply.
In comparison, when weighed purchasing policy is applied based on ABC class, for example C class monthly (every four weeks) delivery with re-order point of three weeks' supply, B class bi-weekly delivery with re-order point of 2 weeks' supply, A class weekly delivery with re-order point of 1 week's supply, total number of delivery in 4 weeks will be (A 200×4=800)+(B 400×2=800)+(C 3,400×1=3,400)=5,000 and average inventory will be (A 75%×1.5weeks)+(B 15%x3 weeks)+(C 10%×3.5 weeks)=1.925 weeks' supply.
a) A class item can be applied much tighter control like JIT daily delivery. If daily delivery with one day stock is applied, delivery frequency will be 4,000 and average inventory level of A class item will be 1.5 days' supply and total inventory level will be 1.025 weeks' supply, a reduction of inventory by 59%. Total delivery frequency is also reduced to half from 16,000 to 8,200.
By applying weighed control based on ABC classification, required man-hours and inventory level are drastically reduced.
The ABC concept is based on Pareto's law.[9] If too much inventory is kept, the ABC analysis can be performed on a sample. After obtaining the random sample, the following steps are carried out for the ABC analysis.
See also
References1. ^Manufacturing planning and control systems for supply chain management By Thomas E. Vollmann 2. ^Lun, Lai, Cheng (2010) Shipping and Logistics Management, p. 158 3. ^Purchasing and Supply Chain Management By Kenneth Lysons, Brian Farrington 4. ^Best Practice in Inventory Management, by Tony Wild (2nd Ed., p. 40) 5. ^Ultsch, Alfred, Jörn Lötsch. "Computed ABC analysis for rational selection of most informative variables in multivariate data." PLOS One 10.6 (2015): e0129767. 6. ^Kringel, D., Ultsch, A., Zimmermann, M., Jansen, J. P., Ilias, W., Freynhagen, R., ... & Resch, E. (2016). Emergent biomarker derived from next-generation sequencing to identify pain patients requiring uncommonly high opioid doses. The pharmacogenomics journal. 7. ^Iovanella, A.: Vital few e trivial many, Il Punto, pp 10-13,July, 2017. 8. ^Barbara Pawelek, Jozef Pociecha, Mateusz Baryla,ABC Anal-ysis in Corporate Bankruptcy Prediction, Abstracts of the IFCS Conference,p 17, Tokyo,Japan,2017 9. ^Pareto's law in this example is that a few high usage value items constitute a major part of the capital invested in inventories whereas a large number of items having low usage value constitute an insignificant part of the capital. External links
3 : Business terms|Supply chain management|Business intelligence |
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