Iet Prestige Lecture Coping With Complexity 7th December

Editor's Notes

1. We will see how to manage some of the information being generated to deal with the specificaiton of complex systemsWe can use fairly simple measures to compare the complexity of one system with anotherApparent complexity is important as we want to distinguish true complexity from just difficult and challenging work
2. The term System of Systems has arisen for two main reasons. Firstly, the increased interconnectedness of the built world arising from the pervasiveness of distributed information systems, supported by novel sensors, GPS and computer intelligence. This provides opportunities to develop more complex entities by joining up existing ones, and building new ones, based on sharing of information. Secondly, science is improving our knowledge of how systems interact to the point where we are in a better position to explain – though not always predict – system of systems behaviour. The classic example is climate change. Although meteorological science, supported by modern supercomputers, allows us predict the weather 2 or 3 days ahead quite reliably, it has taken research on global warming to make us realise that the whole eco-system – comprising rivers, oceans, atmosphere, biosphere and human economic activity - are all coupled with each other and giving rise to largely undesirable emergent outcomes.
3. As systems have evolved they have also become nested and hierarchical sometimes the single elements of SoS are in themselves simple systems.
4. Electrical & Electronic Systems are in fact Systems of Systems being composed of a number of individual System of Systems such as engine management systems, chassis control systems, body control systems and infotainment systems which have their own particular functions but rely on shared resources such as power supplies, processing resources and networked data. This approach is necessary for their effective & efficient implementation, however this systems of systems approach also brings accompanying issues of emergent behaviour that can manifest itself as quality problems (3, 4 )Complexity50 – 100 ECUs, 10+ Networks, 100M L.O.C. now, 200M – 300M in near future according to Frost & SullivanHuge number of variants – the first instance of many of these will be when they are producedTime to market< 2 years from approval to Start of ProductionVolumes (10s – 100s thousands units per annum)Constrains testing on each unit producedExposure to tolerance spreadCosts of rectificationImpact of failuresMix criticality safety, comfort & convenience but Even failures associated with convenience features damaging for customer retention & Brand imageIncreasing levels of integration with SupersystemsDiagnostics & manufacturingConsumer Electronics - Bluetooth, USBITS – Road-tolling, traffic information, Advanced Driver Support
5. In the first two cases – Directed and Collaborative System of systems – it is possible to lay out some heuristics or ‘rules of thumb’ to guide their development. These are intended to allow system of systems to grow, or be reconfigured, for new technology to be added and for the constituent systems to be developed with relative independence. Aim for stable intermediate formsApply triage – direct effort only to those areas which are important, and in which you can make a differenceLeverage at interfacesEnsure cooperation between developersRecognise the Primacy of CommunicationsA key issue in applying these heuristics is the ability of those seeking to achieve particular results, in the form of desirable emergent properties, to predict or control the outcome of making particular changes to constituent systems. The underlying problem is that when complexity increases, it becomes difficult to characterise the systems in terms of simple, abstract models. In the extreme, for truly complex systems, there is no model of the system simpler than the system itself.
6. Excel-based, dependences are represented using simple notationLots of DSM tools support Both freeware and commercial toolsLots of analytical approachesBanding, partitioning, tearing, clusteringOptimising task sequences, team structures, system architecturesImpact analysis (feedback loops and iterations).
7. A key characteristic for successful implementation of System of Systems is robustness. Robustness concerns the resilience of a system to maintain an appropriate level of function during and after variations or disturbances. It is the ability to cope with variation rather than relying on preventing it occurring. For an automotive electrical system comprising of many interlinked sub-systems is it clearly desirable that any abnormal behaviour in one sub-system is not cascaded to other sub-systems.
8. To date there is a lack of analytical modelling techniques at SoS level to capture inter system interactions. Part of the reason for this is the inherent scale of Systems of Systems and the subsequent conflict between detail and coverage as well as differing levels of detail known by integrator across sub-systems. This paper will describe the development of novel robustness models for distributed automotive electronics systems.
9. None of these is a complete solution, almost certianly a hybrid approach will need to be used