Klasificiranje vrednosti značilnice s pomočjo ABC analize

Murn, Blaž (author), Berlec, Tomaž (mentor)

V zaključni nalogi smo primerjali različne metode ABC analize, ki klasificira določene pojave glede na njihovo pomembnost oziroma vrednost značilnice. Želeli smo določiti najučinkovitejši pristop za klasificiranje pojavov in s tem zagotoviti optimalno poslovanje. Sprva smo naredili dve klasični analizi v interaktivni računalniški aplikaciji Microsoft Excel. Razlikovali sta se po kriterijih razčlenjevanja pojavov. Nato smo v programskem jeziku Python po že znanem algoritmu naredili program ABC analize s tremi premicami. Le tega smo primerjali s svojim algoritmom, prav tako narejenega v programskem jeziku Python, katerega pa smo poenostavili s pomočjo permutacije. Med seboj smo primerjali dobljene grafe in ugotovili, da z obema programoma sicer pridemo do enakih rezultatov,vendar pa je naš algoritem (program) enostavnejši in hitrejši. Rezultati se od klasične analize razlikujejo, saj so le ti pridobljeni z različnimi kriteriji. Ugotovili smo, da je za klasificiranje pojavov pomembna tudi notranja presoja osebe, saj si ta sama postavlja kriterije razvrščanja in tudi vrednosti značilnosti posameznega pojava.

• Language: Slovenian
• Keywords: ABC analize, algoritmi, permutacije, matematične formulacije, regresijske premice, funkcionali
• Work type: Final paper
• Typology: 2.11 - Undergraduate Thesis
• Organization: FS - Faculty of Mechanical Engineering
• Place of publishing: Ljubljana
• Publisher: [B. Murn]
• Year: 2019
• Number of pages: XIV, 28 f., [15] f. pril.
• PID: 20.500.12556/RUL-109612
• UDC: 658.511:004.421(043.2)
• COBISS.SI-ID: 16939803
• Publication date in RUL: 06.09.2019

Secondary language

• Language: English
• Title: Classification of the characteristic values using the ABC analysis

Abstract

In the final task, we compared different methods of ABC analysis which classifies certain phenomena according to their significance or value of the characteristic. We wanted to determine the most effective approach for classifying phenomena and thus ensuring optimum business performance. Initially we made two classic analyzes in an interactive Microsoft Excel computer application. They were distinguished by the criteria of parsing phenomena. Then we made an ABC analysis program with three lines according to the already known algorithm in the Python programming language. We compared this with our algorithm also made in the Python programming language which we simplified using permutation. We compared each of the obtained graphs and found that with both programs we get the same results. However our algorithm (program) is simpler and faster. The results vary from classical analysis, as they are obtained by different criteria. We have found that internal classification of a person is also important for classification of phenomena since he himself sets the classification criteria and the values of the characteristics of an individual phenomenon.

• Keywords: ABC analysis, algorithms, permutations, mathemtaical formulations, regression lines, functionals