Extending the capabilities of the FMV
There is an increasing interest in utilising the FRAM approach for the analysis of what exactly is going on in complex sociotechnical systems in practical high hazard environments. There are, for example, a number of ongoing projects at the moment in aviation, self-driving vehicles and, of course, on the challenges of the COVID 19 pandemic for healthcare responses. But as well as these practical applications there is an increasing interest from the academic community, in extending and developing further, the underpinning concepts, as shown in the recent review (below)
These groups are thus interested in taking the modelling power of the FRAM approach to the next level. Their interests include exploring in more detail how interactions occur and how the effects of variability can be addressed and predicted more formally, as well as enabling dynamic visualisation of processes and the quantification of expected outcomes.
What makes this now more attractive, has been the development of a rigorous model checking methodology, the FRAM Model Interpreter, FMI (Hollnagel, E,) (www.safetysynthesis.com )
To support these developments the FRAM Model Visualiser has also been given extra facilities, which now include an option to use, what is essentially a laboratory sand box to provide research laboratory experimental facilities for different groups to utilise.
From time to time, it is planned to add additional features that are still under development and not officially released as part of the FMV Pro version, but may be made available to groups for the purposes of experimentation and feedback from the users.
Building on the FMI functionality, the metadata feature in the FMV, now provides the ability to calculate metadata values as Functions are activated during the FMI cycles.
The manual details these here
The calculations are expressed as user defined equations that can reference other metadata keys, standard variables, standard mathematical functions, logic conditions, and mathematical operators. One or two resulting metadata values can then be expressed as a coloured visualisation within each function. The colours and value ranges can be customised by the user.
When you Ctrl-Click a Function, or select and press Ctrl-M, the metadata section will appear above the model in the visualiser window and display the extended features.
The first two text boxes are for entering metadata as a list of key/value pairs, as is already available in the standard FMV Pro versions. A Key is entered in the first box shaded grey, but it will not be saved for the selected Function until a Value or an Equation is also entered for that Key. The corresponding Value is entered in the second text box.
When a Key is saved for a Function, It will be shown along with all saved Key names when any other Function is selected. As such, the Key names become common across all Functions. However, the corresponding Values are unique to each individual Function.
Key names can be used as Variable names and referenced in Equations if they start with a capital letter (this is to differentiate between Variables and mathematical functions).
To calculate the Value of a Key for a Function (when it is activated by the FMI) click the ‘=’ button and another text input box will appear for entering an equation.
Equations can contain Key names to reference other Values that appear above them in the same Function, or Standard Variables can be used to reference Values from upstream Functions, connected by couplings that are activated during the FMI cycles. This is explained in further sections.
To turn the equation off, click the ‘=’ button again (this is a toggle button) and the equation will disappear, it is still saved but will not be used to calculate the Value.
The next section is a list of available mathematical functions and variables available for use in Equations. You can switch between these two types by using the Functions/Variables toggle buttons above the list. The Variables list is initially empty but will be populated as you create Keys and make selections within the model.
The top colour range is used to display results in the inside top of each function, the bottom range in the inside bottom of each function. Click on any of the three main colour circles to change the colour. The intermediate colours are blended from the three main colours.
The number boxes below the colour ranges are used to convert the Values to the colour range for dsiplay.
The last two text boxes on the right labeled ‘Key 1’ and ‘Key 2’ are for selecting which of the Keys provide values for displaying the results, Key 1 for the top range and Key 2 for the bottom range.
When faced with the prospect of finding at what goes right, the task is daunting, You may, of course, simply begin by looking at what others do every day – or even better, pay attention to what you do yourself. Although unfamiliar for most, it is actually not so difficult to do so once you stop looking for ‘errors’ and instead look for the basic types of performance adjustments: adjustments to create and/or maintain required working conditions, adjustments to compensate for something that may be missing (time, information, tools, materials, etc.), and finally adjustments to avoid changes and/or conditions that may be harmful or make it impossible to carry out the work.
Most people have little or no practice in looking at just what happens, and it may therefore be useful to make a deliberate effort, at least initially. Work descriptions often start from ideas about how an activity ought to be carried out – such as they are found in design documents, instructions, procedures, training materials, etc. Looking at what happens is, however, about work-as-done rather than about work-as-imagined and must therefore refer to work as it is usually is done in an everyday setting.
The best source of information for this is not surprisingly the people who actually do the work, either at the workplace that is directly associated with the analysis, or at a workplace that is highly similar. The primary source for getting this information is interviews; a secondary source may be field observations, or even an exchange of people between departments or units, since this will provide a set of fresh eyes. The discussion here will nevertheless limit itself to systematic data collection by interviews.
Before an interview it is important carefully to think through the situation and to consider how the information is going to be used. It is, as always, important to prepare well before going into ‘the field’, for instance by consulting available sources of information, such as rules and regulations, statistics for various types of events, known ‘worst cases’ or ‘worst scenarios’, stability of the workplace (rate of change of staff, equipment, procedures, organisation), and the commonly known history of major events or changes (preferably not limited to accidents) that have happened in the near past. This background information is the basis for defining the set of questions that should be asked during the interviews.
It is equally important to know as much as possible about the workplace itself, i.e., the actual physical and environmental conditions (or context) where work takes place. This information can be found by looking at architectural drawings (lay-out of the workplace), photos and videos, and other available types of information. The data collection / interview should also – if at all possible – take place at the actual place where the activity is carried out. A ‘guided tour’ of the premises is an additional source of valuable information that cannot easily be conveyed in any other form. Walking around to get a sense of what it is like to work in a particular setting is very useful both for asking questions and for interpreting answers. An interviewer will bring a pair of ‘fresh’ eyes to the setting and may notice things that the people who work there no longer see.
The goal of an interview is to find out how people do their work. This can be prompted by some simple questions such as:
It is also essential to prepare the people who are interviewed. First of all, they must of course agree to be interviewed. Once this agreement has been obtained, it is important that they are informed about what the purpose and nature of the data collection is. The general experience is that people are more than willing to tell about how they do their work, and how they manage tricky situations. It may be a good idea to interview two people at the same time, since they then often realise that one person may do things quite differently form another.
In addition to interviews – and field observations – some general techniques from organisational development may also be used. They all share the position that the questions we ask tend to focus the attention in a particular direction, a version of ‘what you look for is what you find’. Looking for how work is done, rather than for how something went wrong, will produce different types of information and potentially even change people’s mindset – to say nothing about the organisational culture. The search should be for how problems are solved rather than for which problems there are.
We are looking forward to seeing the results of using this new facility and seeing the range and scope of applications and studies significantly extended. Perhaps we will see some examples at the next FRAMily Workshop in Kyoto next year, COVID willing.
© Copyright Erik Hollnagel 2016. All Rights Reserved.