📐 Risk analysis for digital inputs

How Selmo systematically reduces the risk of undefined states to 0%

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🧠 Basic principle: How does risk arise?

In classical automation, risks arise from undefined states on digital inputs. The more inputs (bits), the larger the state space: 2^n.

Many of these states are:

• not allowed, or

• not defined as errors → They are indeterminate = potentially risky.

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🧮 Risk formula

Risk (%) = (2^n - (FM + Steps )) / 2^n × 100

Parameters:

• n: Number of digital inputs

• 2^n: Total number of possible states

• FM: Number of clearly defined error states

• Steps: Number of allowed operating states (e.g. process steps)

Example:

• 4 inputs → 2^4 = 16 states

• 5 allowed steps

• 3 error states

Risk = (16 - (3 + 5)) / 16 × 100 = 50 %

➡️ 50% of the possible states are indeterminate and pose a risk.

What happens now with 32 inputs?

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🎯 Goal: Minimize risk

The smaller the risk value, the more states are defined (either as allowed or as errors).

Optimization approach:

• 🔹 Expand allowed states, where safe

• 🔹 Clearly define error states

• 🔹 Avoid unknowns

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✅ The Selmo approach: Risk = 0%

Selmo solves the problem completely:

All states are explicitly handled in the model. → All other states = automatically errors.

Advantages:

• No room for unexpected states

• No gray areas

• No manual error programming

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🔎 Why does this work?

1. Complete modeling

• All allowed states are logically modeled

• Every other state = error detection

2. Deviation-based diagnosis

• As soon as a state does not match the model corresponds: → Automatic stop + precise error message

3. Clarity for the operator

• Instead of cryptic errors: → concrete cause visible in the HMI → faster resolution

4. No programming effort for errors

• No IF logic needed for error conditions

• The model handles the checking

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📊 Risk management with Selmo

• Every deviation is detected

• Documented & analyzable

• Productivity increase through elimination of root causes → Errors are not maskedNon-conforming requirements or technologies are eliminated

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🔄 Technological paradigm shift

Selmo follows the principle:

Process determines technology – not the other way around.

🧱 Software-centered engineering:

• Process logic → before hardware selection

• Machine behavior → model-driven

• Control code → automatically from the model

🧭 Behavior-oriented control:

• Every state = modeled

• Every input = deterministic reaction

• Simulable, verifiable, transparent

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📌 In summary:

Classical	Selmo
Risk from indeterminate states	Risk = 0% through modeling
Errors must be programmed	Errors = automatically detected
High testing & diagnostic effort	Immediate deviation detection
Hardware-driven	Process-driven