6th International Doctoral Student Workshop on Logistics

Transcription

1 Róbert Skapinyecz (PhD student), Béla Illés (Prof. Dr., Head of department) University of Miskolc, Department of Materials Handling and Logistics

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5 Standard risk management tools: Qualitative methods: - Scenario analysis - Methods based on fuzzy-logic - Methods based on questionnaries, etc. Quantitative (statistical) methods: - Event and Fault-tree analysis - Sensitivity analysis - Monte Carlo type simulations - FMEA, etc.

6 - Initially, risk-management was only applied for IT security (with a few exceptions) - Since the early 90s, business-and operational risk in IT-based systems have also gained more importance - Different approaches started to appear: - distinction of user-levels and risk-categories (e.g. Kazanchi & Sutton), - trust-variables and trust-models (e.g. W. Manchala),

7 - models focusing on partner-selection, - models based on knowledge sharing, - complete extended-enterprise analysis tools, (eg. IBM, EEML, etc.). - decision support systems and web-based applications (e.g. Ngai-Wat, Wulan-Petrovic, etc.). Common aspects: complex modeling of interorganizational relationships; use of multiple risk-categries; use of fuzzy logic and different heuristics.

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9 c p T 6 OG UG 6 where: T is tolerance, σ is the standard deviation, OG is the upper bound, UG is the lower bound. c pk min{c po ;c pu } c po OG 3 c pu UG 3

10 Table 1: Statistical meaning of six sigma Table 1: Statistical meaning of six sigma c p c pk Sigma level Yield Percentage Yield DPMO 0,33-0, , , ,1 0,67 0, , , ,2 1,00 0, , , ,6 1,33 0, , , ,7 1,67 1, , ,3 232,7 2,00 1, , ,6 3,4

11 Table 2: The value of a given risk parameter in accordance with the associated σ levels c p c pk sigma level DPMO value of p 1,00 0, ,6 1,0668 1,33 0, ,7 1,0062 1,67 1, ,7 1,0002 2,00 1,50 6 3,4 1 p f ( c ) ; p 6 10 DPMO p 6 10

12 Table 3: Weighted Defects Per Million Opportunities Critical Weight Sigma DPMO Weighted-DPMO Process (x) (w) Level (k) (w) x (DPMO) x 1 w 1 k 1 d 1 (w 1 ) d 1 x 2 w 2 k 2 d 2 (w 2 ) d 2 x n w n k n d n (w n ) d n n D wid i1 i

13 Table 4: Main risk parameters for a logistics service provider (freight-forwarder or transportation co.) Risk-parameter Weight (w) Description f w r Failures failure-rates among the goods during transportation q w q Quantities deviation in the quantities of the transported goods d w d Dates deviation from the pre-defined delivery dates p w f w c w d f c d i i i i i i i

14 n m F k k i ij j i i1 j1 C p c q b min m m k j i j j1 j1 q b q i Problems: -The cost-relationship could differ form linear -Lack of a unified evaluation for the whole system

15 l k k1 k1 P f p...p...p l P C C Rk 1 i n Where: -Ck is the estimated cost of the k-th mandate in the examined period, - CRk is the realized cost of the k-th mandate in the examined period.

16 P l l l l k k k C Rk CRkb 1 CRkb i CRkbn k1 k1 k1 k1 l l l l C C C C k k k k k1 k 1 k 1 k 1 P f p...p...p w p w p w p 1 i n 1 1 i i n n

17 Based on linear combination, we can state that: l l l k k CRkbi Ckbi CRkbi 6 k1 k 1 k 1 10 DPMOi i i l i l i l 6 w p ; w p C C C b k k k i k1 k 1 k 1 10

18 Assumption and implications: l l l k k k 6 CRkb1 CRkbi CRkbn o k1 k 1 k l i l n l 10 k k k Ckb1 Ckbi Ckbn k1 k 1 k 1 10 DPMO w w w DPMO1 10 DPMOi 10 DPMO P w1 w 6 i w 6 n n

19 Table 5: Values of the systemic risk parameter relative to the sigma level of the system Overall DPMO for the system Sigma level of the system Value of P ,6 3 1, ,7 4 1, ,7 5 1,0002 3,4 6 1

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