Reasoning and diagnostics Part II

In this issue, Barney Donohew explores critical thinking

Published:  13 March, 2017

In diagnostics, deductive arguments are best used when we need to totally justify a conclusion after evaluating a specific system or component test result (e.g. "A volt drop above 250mV between these two points on this wire indicates a high resistance fault. The Volt drop is 3 Volts. Therefore, the wire has a high resistance fault between these points.")

Very likely we would decide to test the glow-plug's supply voltage and current draw, as our experience tells us that when there is only one glow plug DTC then it is likely that the glow plug itself has gone open circuit. This is an inductive argument; written formally it becomes:

Almost every time I have read just one glow-plug DTC from an engine ECU (specifically either P0671, P0672, P0673 or P0674), the glow plug within the indicated cylinder has been open circuit. This engine ECU is reporting a P0671 DTC. Therefore, the glow plug in cylinder no. 1 is open circuit.

From our prior knowledge, we have extrapolated a conclusion predicting the probable cause of an observed DTC; i.e. we have hypothesised a likely fault within a candidate component. From a perspective of critical-thinking we must bear in mind that the conclusion isn't guaranteed to be true. This is a feature of all inductive arguments and we can only assess them relative to the strength of their arguments. Diagnostically, we might use our critical-thinking to weigh-up whether the strength of an inductive argument (amongst other factors) justifies us carrying out a system or component test, but it is unwise to rely on it to entirely accept or reject any hypothesis about what is the fault. The glow-plug example could be classed as a mildly strong argument. A stronger inductive argument might be:

Every time I disconnect a CKP sensor on a running vehicle the engine stops. Therefore, if I disconnect the CKP on this vehicle the engine will stop. [I have yet to come across a vehicle where this hasn't been the case but there remains the (admittedly very slim) possibility that an engine on some vehicle somewhere in the world at some point in time might continue running with its crank position sensor disconnected].

Well, we might use parts darts... or a brute-force attack (sequentially testing each component one by one) ... or perhaps something better?! How about if we use theories (hypotheses) that relate component faults to possible symptoms and find the best match of these to the set of observed symptoms to try to predict the likely cause of the problem? If this happens to be what you do, then you are doing the right thing; it is a creative hypothesis forming process known as abductive reasoning and is the most skilful and challenging part of diagnostics. Although it is often summarised as 'forming your best guess', it is the only diagnostic strategy that, with practice and knowledge, will allow you to complete the diagnostic process efficiently and effectively.

The hypotheses we form must fit within all existing knowledge regarding system and component behaviour and explain the causes of any possible sparse and/or diverse set of observed symptoms, as well as any new observation added to that set (otherwise a new hypothesis will be required).

We use abductive reasoning when we need to predict a set of symptoms, from their hypothesised relationships to possible component faults, that best match (or cover) an observed set of symptoms. Neither reasoning method guarantees the truth of their conclusions and must be validated.

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