# FMEA RPN Reduction What-If Calculator

> Source: https://netray.co/tools/fmea-rpn-reduction-what-if-calculator
> Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems.
> Section: Free Tools

## Short answer

Compare the current RPN with the RPN after a proposed action, and sweep the new detection rating to see how much each step of improvement is worth.

## Category

quality

## Industry

Discrete Manufacturing

## Audience

- Quality engineer
- Reliability engineer
- Process engineer

## Tool

**Kind:** calculator

**Inputs:**

#### Severity (S)

**Key:** sev

**Type:** slider

**Default:** 8

**Min:** 1

**Max:** 10

**Step:** 1

**Help:** Effect on the customer or next process. Severity normally does not change unless the design changes.

#### Current occurrence (O)

**Key:** occ

**Type:** slider

**Default:** 6

**Min:** 1

**Max:** 10

**Step:** 1

**Help:** How often the cause is expected to occur today.

#### Current detection (D)

**Key:** det

**Type:** slider

**Default:** 7

**Min:** 1

**Max:** 10

**Step:** 1

**Help:** How well current controls detect the cause or failure before it reaches the customer.

#### Planned occurrence after action

**Key:** new_occ

**Type:** slider

**Default:** 4

**Min:** 1

**Max:** 10

**Step:** 1

**Help:** Rating you expect once the prevention action is verified.

#### Planned detection after action

**Key:** new_det

**Type:** slider

**Default:** 3

**Min:** 1

**Max:** 10

**Step:** 1

**Help:** Rating you expect once the detection action is verified.

#### RPN target

**Key:** target

**Type:** number

**Default:** 100

**Min:** 1

**Max:** 1000

**Step:** 5

**Help:** Your internal threshold. Many sites use 100 or 120 as a trigger, but there is no universal limit.

**Outputs:**

#### Current RPN

**Key:** rpn_now

**Expr:** sev * occ * det

**Format:** integer

#### RPN after action

**Key:** rpn_new

**Expr:** sev * new_occ * new_det

**Format:** integer

**Primary:** true

**Description:** Severity times planned occurrence times planned detection.

#### Reduction

**Key:** drop

**Expr:** if(gt(rpn_now,0), (rpn_now - rpn_new) / rpn_now * 100, 0)

**Format:** percent

**Primary:** true

#### Margin to target (negative means above target)

**Key:** gap

**Expr:** target - rpn_new

**Format:** integer

#### Severity 9 or 10 review needed (1 = yes)

**Key:** sev_flag

**Expr:** if(gte(sev,9),1,0)

**Format:** integer

**Description:** High severity items need action regardless of the RPN value.

**Chart:**

#### RPN after action vs planned detection rating

**Type:** line

**X:** new_det

**From:** 1

**To:** 10

**Steps:** 10

**Series:**

- rpn_new

**Disclaimer:** RPN is S x O x D on 1 to 10 scales. AIAG and VDA FMEA (2019) moved to Action Priority; use this for legacy RPN-based procedures and quick comparisons.

## Content

**Intro:** The risk priority number is still the number most teams are asked to show on a recommended action line. This calculator takes the current ratings and the ratings you expect after the action, and shows what the action buys you.

**Sections:**

#### How to use the calculator

**Body:** Enter the severity, current occurrence and current detection from your PFMEA or DFMEA row. Then enter the occurrence and detection you expect after the recommended action is implemented and verified. The calculator multiplies the three ratings, shows the percentage reduction and compares the result with your target. The chart sweeps the planned detection rating from 1 to 10 so you can see which level of control is worth pursuing.

**Bullets:**

- Keep severity fixed unless the design or effect changes.
- Prevention actions lower occurrence; inspection and test actions lower detection.
- Only enter post-action ratings you can justify with evidence.

#### The formula and its limits

**Body:** RPN equals severity times occurrence times detection, giving a value from 1 to 1000. Because the ratings are ordinal, the product has well-known weaknesses: very different risk profiles can share the same RPN, and a severity 10 with low occurrence can score lower than a severity 4 with poor detection. This is why the 2019 AIAG and VDA handbook replaced RPN thresholds with Action Priority. Use RPN as a ranking aid, never as the only decision rule.

#### Reading the result

**Body:** A large percentage drop from a detection-only action can look impressive but leaves the cause untouched; defects still occur and you rely on the inspection catching them. Compare a prevention action against a detection action using the same row. If the RPN is below target but severity is 9 or 10, the flag output reminds you that the item still needs a documented review.

#### Common mistakes

**Body:** The most common error is entering hoped-for ratings before the action is proven. Another is lowering detection on a control that only works sometimes, such as visual inspection. Finally, teams often chase RPN thresholds by rating inflation. Update the post-action ratings only after the control plan reflects the change and data confirms it.

**Cta:** If your FMEA lives in spreadsheets, Netray can help link failure modes to ERP nonconformance and inspection data so ratings are based on real history.

**Faq:**

#### What is a good RPN?

**Answer:** There is no universal good value. Sites set their own trigger, often 100 or 120, and also review any severity of 9 or 10. Compare to your own procedure rather than an outside number.

#### Does a lower RPN mean lower risk?

**Answer:** Not always. The product of three ordinal ratings hides differences between combinations. Review severity separately and use Action Priority if your customer requires AIAG and VDA 2019.

#### Can I change severity after an action?

**Answer:** Only if the design or process change alters the effect, for example by removing the hazard. Detection and prevention controls do not change severity.

#### Why does the chart fall in a straight line?

**Answer:** With severity and occurrence fixed, RPN rises linearly with detection. The slope equals severity times planned occurrence.

## Search terms

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