Configuring a Safety Instrumented Function
Configuring a Safety Instrumented Function in SLM allows users to model the complete structure of a SIF, including its inputs, logic solver, outputs and voting layers.
Within the Instrumented Systems module, Configuring a Safety Instrumented Function involves creating a new SIF, relating it to the correct unit or Safety Instrumented System, building the required architecture and defining which elements are included in the SIL calculation.
This guide explains how to create a SIF object, organise its parent-child relationships and begin building an architecture that accurately reflects the safety function installed in the field.
What Is a Safety Instrumented Function?
A Safety Instrumented Function is a protective function designed to move a process to a safe state when defined conditions are detected. It normally includes one or more inputs, a logic solver and one or more final elements.
In SLM, the complete SIF architecture can be modelled as a structured hierarchy. This may include input groups, input voting groups, individual sensors, a logic solver, output groups, output voting groups and final elements.
This structure allows users to represent both simple and complex safety functions, including architectures with multiple layers of voting. The completed model can then be used to support SIL calculations and other Instrumented Systems activities.
Configuring a Safety Instrumented Function in SLM
To create a new SIF, navigate to the Instrumented Systems module and select the parent object beneath which the function should be created. In most cases, this will be a unit or an existing Safety Instrumented System.
From the parent object, open the Edit Tools menu and select Add SIF. SLM then allows the user to enter a new SIF ID or select an existing SIF from the same site or scope.
Existing SIF objects can be linked, cloned independently or cloned together with their child objects. These options can reduce setup time where similar safety functions already exist elsewhere in the system.
After the SIF ID has been entered, select Save and Edit to create the function and open the new SIF object. The function will then appear in the object tree beneath the selected parent.
If the SIF was created at unit level, it can later be related to an SIS by selecting it in the SIS-related functions field or by dragging the SIF onto the SIS within the object tree.
For more information about how complete systems and functions are organised, see the Instrumented Systems Overview.
Building the SIF Architecture
When Configuring a Safety Instrumented Function, the next step after creating the SIF is to build the architecture that represents the complete protective function.
On the input side, the structure may include an input group, one or more input voting groups and the individual input devices. On the output side, the same pattern is used for output groups, output voting groups and final elements. A logic solver connects the two sides.
These objects can be created individually by moving through the parent-child hierarchy in the object tree. For example, an input voting group is created beneath an input group, while an individual input is created beneath the relevant input voting group.
A faster method is available from the SIF Architecture tab. This centralised view allows users to create the logic solver, input groups, voting groups, inputs, output groups and outputs without navigating repeatedly between separate objects.
Creating the logic solver first is recommended because the graphical SIF diagram will not begin to render until a logic solver object exists.
As each object is added, its parent relationship must be selected correctly. SLM uses these relationships to position every element within the SIF hierarchy and to build the architecture diagram.
For a broader explanation of SIF components, see Instrumented Functions (IPLs).
Creating Inputs, Outputs and Logic Solvers
A complete Safety Instrumented Function consists of several related objects that together represent the protective function installed in the field. These include the logic solver, input groups, input voting groups, individual inputs, output groups, output voting groups and final elements.
The SIF Architecture tab provides a central location for creating each of these components. This makes Configuring a Safety Instrumented Function more efficient because users can add and organise the required objects without repeatedly navigating through the object tree.
Users can expand the relevant section, select the appropriate Add option and specify an ID for each new object before saving it.
Each object must be assigned to its correct parent before it can be created successfully. For example, an input voting group must belong to an input group, while each input must be assigned to an existing input voting group. SLM validates these relationships before allowing the object to be saved.
As objects are added, the SIF hierarchy is automatically constructed within the object tree. Once a logic solver has been created, the graphical architecture diagram also begins to populate, allowing engineers to visualise the complete Safety Instrumented Function.
By continuing this process for additional sensors, voting groups and final elements, users can model both simple and highly complex SIF architectures while maintaining clear parent-child relationships throughout the design.
Applying Voting Configuration
Once the Safety Instrumented Function architecture has been completed, voting must be configured so that SLM knows which objects are included within the SIL calculation. Voting is applied at each layer of the architecture, including input groups, input voting groups, the logic solver and output groups.
Users select the relevant objects that should participate in the calculation before specifying the required voting arrangement, such as one-out-of-one (1oo1), one-out-of-two (1oo2) or two-out-of-two (2oo2), depending on the design of the safety function.
When Configuring a Safety Instrumented Function, voting can be applied directly to each individual object or more efficiently from the SIF Architecture tab, where every voting layer can be updated from a single location.
This centralised approach significantly reduces navigation when working with larger or more complex architectures.
As voting is applied, the architecture diagram provides immediate visual feedback. Objects included within the SIL calculation become fully coloured, while components surrounded by dotted outlines indicate that they are not currently participating in the calculation.
This visual representation makes it easy to identify incomplete voting configurations before SIL calculations are performed, helping engineers confirm that every required layer has been configured correctly.
For additional guidance on documenting complete safety functions, see the Safety Requirement Specification (SRS).
Understanding SIL Calculation Architecture
The SIL calculation architecture is derived directly from the completed Safety Instrumented Function. Every object that participates in the voting configuration contributes to the calculation model used within SLM.
As voting is assigned throughout the architecture, the graphical diagram updates to reflect which components are actively included in the SIL calculation. This allows engineers to verify the completeness of the model before continuing with reliability analysis.
Complex Safety Instrumented Functions may contain multiple input groups, several voting layers and numerous final elements. The architecture view provides a consistent method for confirming that each layer has been configured correctly and that every required object has been selected.
If any section of the diagram continues to display dotted outlines after voting has been configured elsewhere, this provides a clear indication that additional configuration is still required before the Safety Instrumented Function is fully represented within the SIL calculation.
Using the architecture view in this way helps engineering teams identify missing relationships early, reducing rework and improving confidence in the completed Instrumented System model.
Best Practices for Configuring Safety Instrumented Functions
A well-structured Safety Instrumented Function is easier to maintain, review and verify throughout its lifecycle. Establishing a consistent configuration process helps ensure that every component is modelled correctly and that SIL calculations accurately represent the installed protection system.
- Create the logic solver before building the remainder of the architecture so the SIF diagram can begin rendering immediately.
- Always assign the correct parent object before saving new groups, voting groups or individual devices.
- Use the SIF Architecture tab to build and manage larger Safety Instrumented Functions more efficiently.
- Clone existing inputs or outputs when multiple devices share the same configuration, updating only the unique information such as the object ID.
- Confirm that every required voting layer has been configured before completing SIL calculations.
- Review the architecture diagram to ensure no dotted sections remain where objects should participate in the calculation.
Following these practices when Configuring a Safety Instrumented Function improves consistency across Instrumented System projects, reduces engineering effort and makes future modifications easier to manage.
Related Instrumented Systems Guides
Configuring a Safety Instrumented Function is one stage in developing a complete Instrumented System. The following guides explain related activities, from defining system requirements through to documenting and verifying the completed design.
- Instrumented Systems Overview
- Safety Requirement Specification (SRS)
- SIL Calculation Reports
- Cause and Effect Matrices
- Instrumented Functions (IPLs)
For additional information on the functional safety lifecycle and Safety Instrumented Systems, refer to the International Electrotechnical Commission (IEC), which publishes the IEC 61511 standard used throughout the process industries.
Configuring a SIF
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Welcome to this Application Explainer video, part of our Instrumented Systems topic range.
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In this video, we’ll cover the subject of configuring a safety instrumented function in SLM.
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Within the SLM Instrumented Systems module, users can model their safety functions, detailing the complete architecture of inputs, outputs, and the layers of voting in between.
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The following information will be covered in this training.
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Chapter one will be SIF creation.
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Chapter 2 will be SIF architecture creation and SIF calculation architecture.
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Chapter 3 will be voting configuration.
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In Chapter 1, we will cover where to navigate to create new SIF objects, creation of SIF objects, and relationship to the unit or sys navigating to the Instrumented Systems module.
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Users can create a safety instrumented function.
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Similarly to creating any object in the SLM system, we’re going to want to navigate to the parent of that object that we’re looking to create.
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So in this instance, the parent of the SIF would be the unit object.
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You can create a SIF from a unit or from an SIS object as well.
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Once you’re on the parent object, you can use the Edit Tools button to hit the Add SIF button.
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This will prompt a pop up window that will allow the user to specify a new SIF ID.
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Or the user can select from a drop down list containing the existing Sifs that exist within the same scope or site that you’re working in.
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From there you could choose to link the selected object and bring it to that unit.
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You could also clone the object alone or clone the object and its associated children.
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This particular example, we’re going to specify new SIF titled SIF LAH One O 1.
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Once we’ve completed specifying the ID, we can hit Save and Edit and that will take us to the SIF object.
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You’ll see it’s now created on the object tree.
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Now you can also do this process from the SIS object as well.
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We can hit Edit Tools and add SIF here.
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If you’ve created the SIF from the unit level, you can relate the SIF to the SIS by navigating to the SIS object, hitting the Related Functions field, and selecting that SIF from the dropdown.
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Here we could select it and hit save, or we could simply take our SIF in the object tree, click and hold, and drag and drop it on Thesis.
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And now that relationship has been created.
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In Chapter 2, we’ll cover how to build out the SIF architecture and creation of input and output objects, and things to consider how to efficiently leverage existing objects for faster SIF creation, including templates and cloning.
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For building out SIF architecture, the process is identical to building the SIF itself.
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You start the parent object and use the Edit Tools button to add the children.
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The SIF can be configured to have multiple layers of voting on the sensor or input side.
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You will create the input group, the input voting group, and then from there the actual inputs themselves.
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On the output side, similarly, the output group, the output voting group, and the outputs themselves, and in the middle you’ll have the logic solver object.
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This can all be created again from the parent child relationship.
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At the parent you can create the logic solver, the input group, and the output group.
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At the Input Group object, you can create the Input Voting group.
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At the Input Voting group object, you can use the edit tools to create the input itself.
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A more efficient way to create the SIF architecture is on the SIF object itself and on the Silk Arc Architecture tab.
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This tab allows you to create all of the architecture in one place without having to navigate to so many different objects.
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On the Silk Architecture tab.
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You can expand these sliders here to add information.
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So the user can begin by expanding the logic solver, hitting the Add Logic Solver button.
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Here we can simply specify the logic solver ID, so I’ll put logic solver one O 1 and we can hit save changes.
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Once this is complete, that logic solver now exists and you can see it just here.
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For the input groups, the user can expand the input group section and you can see a selection of four tables on the input groups table.
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We can add an input group.
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We’ll put input Group One O 1 here and save changes.
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Now that input group will exist for this SIF.
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Now we can move on to the input voting group.
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We can add the input voting group by selecting the Add Input voting group button.
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We can specify the title for it.
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We will use IVG one O 1 Now for this.
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Saving changes will not work.
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The table contains missing data.
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We need to select where the input voting group is going to exist.
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So under the parent input groups box, we must click here and we must select the input group that exists for this input voting group to exist underneath.
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Now we can hit save and that input voting group now exists in that input group.
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As we do this, we can see that the SIF is being built out in the object tree.
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For the inputs themselves, we can do the same thing on the inputs table.
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Add an input, specify the input ID.
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So we’ll put LT1O1A.
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And again, if we try to save this, it won’t work because we’re containing missing data.
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We have to specify where the parent of this is.
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So on the parent input voting group, we can select the input voting group that exists.
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Now we can save changes and now that input has been created.
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This if it’s not yet rendering, but when we choose to do so, we can either hit refresh or hit the Silk Architecture tab.
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And now you see that the diagram is beginning to form at the top.
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This diagram will not begin to form until the Logic solver object has been created.
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That’s why we recommend creating that first.
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To continue with the architecture of the SIF, you would simply repeat that process.
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If you need more input groups, you can add them there.
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If you want to add more inputs, you can click Add Additional Inputs and for the outputs it’s the same concept.
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If you expand the output section, you can add output groups, you can add outputs, output voting groups.
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It’s an identical process to the inputs.
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Now a more efficient way to create the inputs and outputs is actually to create one of them, fill out the data that may be identical across multiple inputs or outputs, and then clone and copy that.
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So for example, let’s say in this SIF we want to create 2 identical level transmitters, LT101A and B.
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So instead of coming to this inputs table and simply adding a new input, typing LT101B and filling out all the information here, what we can do is fill out LT101A and fill in some of the information here.
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What’s its function?
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What’s its process measurement input type?
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Is it related to prior use certificate?
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Does it have a dangerous failure percentage, a custom failure rate?
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Let’s say it’s .0001 proof, test coverage, diagnostic coverage.
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We can save those changes for LT101A.
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Now if we want an identical LT101B, what we can do is now hit add input.
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We can type in LT101A and then when we click on this, it’s going to auto fill in all of the data that’s identical to LT101A.
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So we have all of this information now populated.
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Now what we’ll do is go to the ID and change it from LT101A to LT101B and then we’ll have to select the parent input group again if we save changes.
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And now this input will exist in the object tree.
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If we refresh the page, we’ll see LT1O1B on the diagram.
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That’s a more efficient way to create identical redundant inputs or outputs through this process.
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Now, by repeating this process, we can build out the rest of the architecture for the SIF, the outputs, the output voting groups, the outputs themselves, and we can build out the full architecture for this SIF.
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Now in the SLM system, Sifs can be built into complex architectures with multiple layers of voting.
8:56
So we can see this simple SIF has 2 transmitters, 2 final elements, but we can get into much more complex structures and layers of voting that exist.
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SLM is designed this way so the user can model their Sifs accurately and consistently as they are out in the field.
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In Chapter 3, we’ll cover how to apply voting to the SIF layers and SIF diagram indicators.
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Applicability to the SIL calculation.
9:26
Now that we’ve got the full architecture of the safety function built out, we need to apply the voting for the SIL calculation.
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This can be completed on each object representing the layers of the SIF so we can navigate to the Input group object.
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Now here we would need to use the SIL Calc Input voting groups field to specify which of the input voting groups are going to be considered as part of the voting.
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We’ll see here.
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For the voting configuration, right now we have nothing out of 0 because nothing’s selected.
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Once.
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I specify this input voting group as being part of the SIL calculation and save that 0 is going to be updated to A1.
10:03
Now I can specify that this particular layer is a one out of one voting group and save that.
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Now this can be completed on all of the layers, the input voting group.
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Similarly selecting again, we would select the inputs that want to be applied.
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We can select both of these here.
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Save and the zero will be updated to a 2 now and then we can specify this is a one out of two.
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This should be the same thing in the same process for the layers of the logic solver and the output groups.
10:32
Now as you have more complex Sifs there may be more groups, more things to apply, and more voting layers to deal with.
10:39
Now a more efficient way to complete the filling in of the voting for the safety function is again, to navigate to the SIF object and to the Silk Out architecture tab.
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Now in these expanded tables, we can see all the layers we built out previously.
10:53
And from there we can actually apply the voting.
10:56
So voting layers between input groups.
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We can take the Silk Out input groups button, click on that to select.
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It’s there.
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We know that it’s one, so we’re going to fill in a one out of one and we can save changes for the input voting groups.
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The same thing.
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We’ve got an input voting group here.
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We want to click on that, change it to A1.
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That will to update to A1.
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Now we’ve selected that and save changes.
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Now for the inputs themselves with two inputs, we want to scroll here, select both of them to be applied for the voting, and then we’ll select this to be a one out of two.
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This will also update to be a 2 here.
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Now, as we’ve applied the voting, we’re seeing these colours are filling in.
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So before when we did this, you’ll see the voting layers are not filled in with a dotted line around them.
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That is an indication that they’re not being considered for the SIL calculation itself.
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Now that we’ve filled in some of this, I’ll refresh the page and you’ll see that now the voting’s applied.
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These are filled in and coloured.
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That means that they’re applied and they’re being considered as part of the SIL calculation.
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Now, again, we can do this for the other layers.
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We can open up the logic solver here.
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Click the logic solver.
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There’s one out of one.
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On that one, we’ll save that.
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It will auto update.
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And for the output groups themselves, same process, click the output groups, there’s only 1, so it’s one out of one save.
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For the output voting groups, there’s only one, one out of one save.
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And for the outputs themselves, this is going to be a valve and actuator.
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So we’ll select both of these and we’ll save for this.
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It’s going to be a two out of two and we’ll save that.
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Now that’s been completed, we can come back up here and refresh again and we’ll see that all of this is now filled in.
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That’s indicated that the entire SIF is now being considered as part of the SIL calculation.
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If we look at a different example, this is a SIF that’s built out with voting, but where you see the not filled in dotted lines that would represent part of the SIF that is not being considered for the SIL calculation.
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This is a good way and a good indicator to know if there’s anything missing as part of your SIL calc.