Enterprise Architecture for decision making in MODAF

Transcription

1 Enterprise Architecture for decision making in MODAF Ulrik Franke, Ph.D. student Industrial Information and Control Systems Royal Institute of Technology, Stockholm SESAM, Stockholm, April 27,

2 To It defines assist decision-makers, a way of representing MODAF an provides Enterprise the Architecture means of Ministry which abstracting enables of essential Defence stakeholders information to from focus the in on underlying Architecture specific areas complexity of Framework interests and presenting the it enterprise, in a way that whilst maintains retaining coherence sight of the and big consistency. picture. 2

3 Would you tell me, please, which way I ought to go from here? That depends a good deal on where you want to get to, said the Cat. I don t much care where said Alice. Then it doesn t matter which way you go, said the Cat. 3

4 LESSON #1 An Enterprise Architecture effort is not an end in itself; it is a means to something else. Never ever start an EA effort before you know what you want to achieve. 4

5 Information System Decision Domain s Availability IT Department Decision Domain DECISION MAKING Delivery Quality Business Goal Domain 5

6 ? DECISION MAKING 6

7 Information Systems SCADA System Availability Maturity IT Department Availability Management DECISION MAKING Delivery Quality Business Electricity Distribution 7

8 Information Systems SCADA System Availability IT Department Availability Management DECISION MAKING Delivery Quality Business Electricity Distribution 8

9 ? DECISION MAKING 9

10 Information Systems SCADA System Availability Maturity IT Department Availability Management DECISION MAKING Delivery Quality Business Electricity Distribution 10

11 Information Systems SCADA System Availability IT Department Availability Management DECISION MAKING Delivery Quality Business Electricity Distribution 11

12 ? Delivery Quality Delivery Quality Delivery Quality Delivery Quality DECISION MAKING Delivery Quality Delivery Quality 12

13 LESSON #2 Different decisions require different information. Good models structure what you know before making decisions, and enable scenario analysis. 13

14 Dependency analysis How do high-level operational concepts (airlift capability, search and rescue, etc.) depend upon particular technical systems (vehicles, radars, IT systems, etc.)? There is a gap between the enterprise-level decision making and the low-level implementation If this gap is not bridged, decisions will not be rational 14

15 Dependencies in MODAF Dependencies of interest to MOD include: capability dependencies, programmatic dependencies, technology dependencies etc. Analysis of dependencies of this type is considered a key use of an Enterprise Architecture. 15

16 Sample MODAF products 16

17 How should MODAF models look? The challenge is to give just enough contents to MODAF models to enable the relevant kind of decision making no more, no less! 17

18 LESSON #3 MODAF models are good for visualizing dependencies, but not so good for analyzing them. Therefore, they are difficult to use for scenario analysis. 18

19 Can MODAF become a more powerful decision making tool? Information on causal relations enables decision making using scenarios. As part of KTH research, we have developed a method for extending MODAF models with attributes and attribute relations for dependency analysis using Fault Tree Analysis and Bayesian networks 19

20 Simple FT-BN analysis example 20

21 From a MODAF model Operational <<Op. Activity>> Target acquisition <<needline>> <<Op. Activity>> Kill target <<needline>> <<Op. Activity>> C2 <<needline>> <<Op. Activity>> Strike Systems/Services <<System>> UGV TA <<needline>> <<needline>> <<System>> UAV TA <<needline>> <<System>> Comms satellite to TA system <<needline>> << System>> Comms satellite to striking system <<needline>> << System>> Armed UAV <<needline>> << System>> Artillery 21

22 to a fault tree Operational <<Op. Activity>> Target acquisition <<Op. Activity>> Kill target AND <<Op. Activity>> C2 <<Op. Activity>> Strike Systems/Services <<System>> UGV TA OR <<System>> UAV TA << System>> Comms satellite to TA system AND <<System>> Comms satellite to striking system OR << System>> Armed UAV << System>> Artillery 22

23 to a Bayesian network System Status satellite Non-failed Failed Signal delay Yes No Yes No Moving target Yes No Yes No Yes No Yes No High Quality Medium of C2 None Inspired by Dougherty [7] Systems/Services Operational <<System>> UGV TA - System status <<Node>> Target - Moving <<Op. Activity>> Target acquisition OR <<System>> UAV TA <<Op. Activity>> Kill target - Successful kill AND <<Op. Activity>> C2 AND <<System>> Comms satellite <<Node>> UAV operator platform <<Op. Activity>> Strike - Quality - Quality - Precision - Video UI enhancement status - System status - Signal latency - System status - Moving OR <<System>> Armed UAV - Autopilot status - System status <<System>> Artillery - System status Antonov et. al and Dixon et. al System status of UGV System status Non-failed Failed of UAV Non-failed Failed Non-failed Failed Video UI enhancement Nonfailed Non- Non- Non- status Failed failed Failed failed Failed failed Failed High Quality Medium of TA None Inspired by Fincannon et. al [10] Inspired by Antonov et. al [1] and Dixon et al. [6] System Status of Armed UAV Non-failed Failed System Status of Artillery Non-failed Failed Non-failed Failed Moving UAV op. Plattform Yes No Yes No Yes No Yes No Nonfailed Non- Non- Non- Non- Non- Non- Non- Autopilot status Failed failed Failed failed Failed failed Failed failed Failed failed Failed failed Failed failed Failed High Precision Medium None

24 Scenarios for decision making 24

25 LESSON #4 Fault Tree Analysis and Bayesian networks enable causality based analysis in close support of decision making needs 25

26 Summary of the lessons 1. Set the goals before you choose the means 2. Scenario analysis is a powerful way to visualize the impact of decisions 3. Traditional MODAF analysis is weak on causality and not very good for scenario driven decision making 4. Fault Tree Analysis and Bayesian networks enable causality based analysis in close support of decision making needs 26

27 Thank you! Questions and feedback? 27

28 References Ulrik Franke, Waldo Rocha Flores, Pontus Johnson: Enterprise Architecture Dependency Analysis using Fault Trees and Bayesian Networks, Proc. 42nd Annual Simulation Symposium (ANSS), pp , March 2009 Ulrik Franke, Pontus Johnson, Evelina Ericsson, Waldo Rocha Flores, Kun Zhu: Enterprise Architecture analysis using Fault Trees and MODAF, Proc. CAiSE Forum 2009, June 2009, to appear Read more on 28