Risk Management Specialist

#!/usr/bin/env python3
"""
FMEA Analyzer - Failure Mode and Effects Analysis for medical device risk management.

Supports Design FMEA (dFMEA) and Process FMEA (pFMEA) per ISO 14971 and IEC 60812.
Calculates Risk Priority Numbers (RPN), identifies critical items, and generates
risk reduction recommendations.

Usage:
    python fmea_analyzer.py --data fmea_input.json
    python fmea_analyzer.py --interactive
    python fmea_analyzer.py --data fmea_input.json --output json
"""

import argparse
import json
import sys
from dataclasses import dataclass, field, asdict
from typing import List, Dict, Optional, Tuple
from enum import Enum
from datetime import datetime


class FMEAType(Enum):
    DESIGN = "Design FMEA"
    PROCESS = "Process FMEA"


class Severity(Enum):
    INCONSEQUENTIAL = 1
    MINOR = 2
    MODERATE = 3
    SIGNIFICANT = 4
    SERIOUS = 5
    CRITICAL = 6
    SERIOUS_HAZARD = 7
    HAZARDOUS = 8
    HAZARDOUS_NO_WARNING = 9
    CATASTROPHIC = 10


class Occurrence(Enum):
    REMOTE = 1
    LOW = 2
    LOW_MODERATE = 3
    MODERATE = 4
    MODERATE_HIGH = 5
    HIGH = 6
    VERY_HIGH = 7
    EXTREMELY_HIGH = 8
    ALMOST_CERTAIN = 9
    INEVITABLE = 10


class Detection(Enum):
    ALMOST_CERTAIN = 1
    VERY_HIGH = 2
    HIGH = 3
    MODERATE_HIGH = 4
    MODERATE = 5
    LOW_MODERATE = 6
    LOW = 7
    VERY_LOW = 8
    REMOTE = 9
    ABSOLUTELY_UNCERTAIN = 10


@dataclass
class FMEAEntry:
    """Single FMEA line item."""
    item_process: str
    function: str
    failure_mode: str
    effect: str
    severity: int
    cause: str
    occurrence: int
    current_controls: str
    detection: int
    rpn: int = 0
    criticality: str = ""
    recommended_actions: List[str] = field(default_factory=list)
    responsibility: str = ""
    target_date: str = ""
    actions_taken: str = ""
    revised_severity: int = 0
    revised_occurrence: int = 0
    revised_detection: int = 0
    revised_rpn: int = 0

    def calculate_rpn(self):
        self.rpn = self.severity * self.occurrence * self.detection
        if self.severity >= 8:
            self.criticality = "CRITICAL"
        elif self.rpn >= 200:
            self.criticality = "HIGH"
        elif self.rpn >= 100:
            self.criticality = "MEDIUM"
        else:
            self.criticality = "LOW"

    def calculate_revised_rpn(self):
        if self.revised_severity and self.revised_occurrence and self.revised_detection:
            self.revised_rpn = self.revised_severity * self.revised_occurrence * self.revised_detection


@dataclass
class FMEAReport:
    """Complete FMEA analysis report."""
    fmea_type: str
    product_process: str
    team: List[str]
    date: str
    entries: List[FMEAEntry]
    summary: Dict
    risk_reduction_actions: List[Dict]


class FMEAAnalyzer:
    """Analyzes FMEA data and generates risk assessments."""

    # RPN thresholds
    RPN_CRITICAL = 200
    RPN_HIGH = 100
    RPN_MEDIUM = 50

    def __init__(self, fmea_type: FMEAType = FMEAType.DESIGN):
        self.fmea_type = fmea_type

    def analyze_entries(self, entries: List[FMEAEntry]) -> Dict:
        """Analyze all FMEA entries and generate summary."""
        for entry in entries:
            entry.calculate_rpn()
            entry.calculate_revised_rpn()

        rpns = [e.rpn for e in entries if e.rpn > 0]
        revised_rpns = [e.revised_rpn for e in entries if e.revised_rpn > 0]

        critical = [e for e in entries if e.criticality == "CRITICAL"]
        high = [e for e in entries if e.criticality == "HIGH"]
        medium = [e for e in entries if e.criticality == "MEDIUM"]

        # Severity distribution
        sev_dist = {}
        for e in entries:
            sev_range = "1-3 (Low)" if e.severity <= 3 else "4-6 (Medium)" if e.severity <= 6 else "7-10 (High)"
            sev_dist[sev_range] = sev_dist.get(sev_range, 0) + 1

        summary = {
            "total_entries": len(entries),
            "rpn_statistics": {
                "min": min(rpns) if rpns else 0,
                "max": max(rpns) if rpns else 0,
                "average": round(sum(rpns) / len(rpns), 1) if rpns else 0,
                "median": sorted(rpns)[len(rpns) // 2] if rpns else 0
            },
            "risk_distribution": {
                "critical_severity": len(critical),
                "high_rpn": len(high),
                "medium_rpn": len(medium),
                "low_rpn": len(entries) - len(critical) - len(high) - len(medium)
            },
            "severity_distribution": sev_dist,
            "top_risks": [
                {
                    "item": e.item_process,
                    "failure_mode": e.failure_mode,
                    "rpn": e.rpn,
                    "severity": e.severity
                }
                for e in sorted(entries, key=lambda x: x.rpn, reverse=True)[:5]
            ]
        }

        if revised_rpns:
            summary["revised_rpn_statistics"] = {
                "min": min(revised_rpns),
                "max": max(revised_rpns),
                "average": round(sum(revised_rpns) / len(revised_rpns), 1),
                "improvement": round((sum(rpns) - sum(revised_rpns)) / sum(rpns) * 100, 1) if rpns else 0
            }

        return summary

    def generate_risk_reduction_actions(self, entries: List[FMEAEntry]) -> List[Dict]:
        """Generate recommended risk reduction actions."""
        actions = []

        # Sort by RPN descending
        sorted_entries = sorted(entries, key=lambda e: e.rpn, reverse=True)

        for entry in sorted_entries[:10]:  # Top 10 risks
            if entry.rpn >= self.RPN_HIGH or entry.severity >= 8:
                strategies = []

                # Severity reduction strategies (highest priority for high severity)
                if entry.severity >= 7:
                    strategies.append({
                        "type": "Severity Reduction",
                        "action": f"Redesign {entry.item_process} to eliminate failure mode: {entry.failure_mode}",
                        "priority": "Highest",
                        "expected_impact": "May reduce severity by 2-4 points"
                    })

                # Occurrence reduction strategies
                if entry.occurrence >= 5:
                    strategies.append({
                        "type": "Occurrence Reduction",
                        "action": f"Implement preventive controls for cause: {entry.cause}",
                        "priority": "High",
                        "expected_impact": f"Target occurrence reduction from {entry.occurrence} to {max(1, entry.occurrence - 3)}"
                    })

                # Detection improvement strategies
                if entry.detection >= 5:
                    strategies.append({
                        "type": "Detection Improvement",
                        "action": f"Enhance detection methods: {entry.current_controls}",
                        "priority": "Medium",
                        "expected_impact": f"Target detection improvement from {entry.detection} to {max(1, entry.detection - 3)}"
                    })

                actions.append({
                    "item": entry.item_process,
                    "failure_mode": entry.failure_mode,
                    "current_rpn": entry.rpn,
                    "current_severity": entry.severity,
                    "strategies": strategies
                })

        return actions

    def create_entry_from_dict(self, data: Dict) -> FMEAEntry:
        """Create FMEA entry from dictionary."""
        entry = FMEAEntry(
            item_process=data.get("item_process", ""),
            function=data.get("function", ""),
            failure_mode=data.get("failure_mode", ""),
            effect=data.get("effect", ""),
            severity=data.get("severity", 1),
            cause=data.get("cause", ""),
            occurrence=data.get("occurrence", 1),
            current_controls=data.get("current_controls", ""),
            detection=data.get("detection", 1),
            recommended_actions=data.get("recommended_actions", []),
            responsibility=data.get("responsibility", ""),
            target_date=data.get("target_date", ""),
            actions_taken=data.get("actions_taken", ""),
            revised_severity=data.get("revised_severity", 0),
            revised_occurrence=data.get("revised_occurrence", 0),
            revised_detection=data.get("revised_detection", 0)
        )
        entry.calculate_rpn()
        entry.calculate_revised_rpn()
        return entry

    def generate_report(self, product_process: str, team: List[str], entries_data: List[Dict]) -> FMEAReport:
        """Generate complete FMEA report."""
        entries = [self.create_entry_from_dict(e) for e in entries_data]
        summary = self.analyze_entries(entries)
        actions = self.generate_risk_reduction_actions(entries)

        return FMEAReport(
            fmea_type=self.fmea_type.value,
            product_process=product_process,
            team=team,
            date=datetime.now().strftime("%Y-%m-%d"),
            entries=entries,
            summary=summary,
            risk_reduction_actions=actions
        )


def format_fmea_text(report: FMEAReport) -> str:
    """Format FMEA report as text."""
    lines = [
        "=" * 80,
        f"{report.fmea_type.upper()} REPORT",
        "=" * 80,
        f"Product/Process: {report.product_process}",
        f"Date: {report.date}",
        f"Team: {', '.join(report.team)}",
        "",
        "SUMMARY",
        "-" * 60,
        f"Total Failure Modes Analyzed: {report.summary['total_entries']}",
        f"Critical Severity (≥8): {report.summary['risk_distribution']['critical_severity']}",
        f"High RPN (≥100): {report.summary['risk_distribution']['high_rpn']}",
        f"Medium RPN (50-99): {report.summary['risk_distribution']['medium_rpn']}",
        "",
        "RPN Statistics:",
        f"  Min: {report.summary['rpn_statistics']['min']}",
        f"  Max: {report.summary['rpn_statistics']['max']}",
        f"  Average: {report.summary['rpn_statistics']['average']}",
        f"  Median: {report.summary['rpn_statistics']['median']}",
    ]

    if "revised_rpn_statistics" in report.summary:
        lines.extend([
            "",
            "Revised RPN Statistics:",
            f"  Average: {report.summary['revised_rpn_statistics']['average']}",
            f"  Improvement: {report.summary['revised_rpn_statistics']['improvement']}%",
        ])

    lines.extend([
        "",
        "TOP RISKS",
        "-" * 60,
        f"{'Item':<25} {'Failure Mode':<30} {'RPN':>5} {'Sev':>4}",
        "-" * 66,
    ])
    for risk in report.summary.get("top_risks", []):
        lines.append(f"{risk['item'][:24]:<25} {risk['failure_mode'][:29]:<30} {risk['rpn']:>5} {risk['severity']:>4}")

    lines.extend([
        "",
        "FMEA ENTRIES",
        "-" * 60,
    ])

    for i, entry in enumerate(report.entries, 1):
        marker = "⚠" if entry.criticality in ["CRITICAL", "HIGH"] else "•"
        lines.extend([
            f"",
            f"{marker} Entry {i}: {entry.item_process} - {entry.function}",
            f"  Failure Mode: {entry.failure_mode}",
            f"  Effect: {entry.effect}",
            f"  Cause: {entry.cause}",
            f"  S={entry.severity} × O={entry.occurrence} × D={entry.detection} = RPN {entry.rpn} [{entry.criticality}]",
            f"  Current Controls: {entry.current_controls}",
        ])
        if entry.recommended_actions:
            lines.append(f"  Recommended Actions:")
            for action in entry.recommended_actions:
                lines.append(f"    → {action}")
        if entry.revised_rpn > 0:
            lines.append(f"  Revised: S={entry.revised_severity} × O={entry.revised_occurrence} × D={entry.revised_detection} = RPN {entry.revised_rpn}")

    if report.risk_reduction_actions:
        lines.extend([
            "",
            "RISK REDUCTION RECOMMENDATIONS",
            "-" * 60,
        ])
        for action in report.risk_reduction_actions:
            lines.extend([
                f"",
                f"  {action['item']} - {action['failure_mode']}",
                f"  Current RPN: {action['current_rpn']} (Severity: {action['current_severity']})",
            ])
            for strategy in action["strategies"]:
                lines.append(f"    [{strategy['priority']}] {strategy['type']}: {strategy['action']}")
                lines.append(f"      Expected: {strategy['expected_impact']}")

    lines.append("=" * 80)
    return "\n".join(lines)


def main():
    parser = argparse.ArgumentParser(description="FMEA Analyzer for Medical Device Risk Management")
    parser.add_argument("--type", choices=["design", "process"], default="design", help="FMEA type")
    parser.add_argument("--data", type=str, help="JSON file with FMEA data")
    parser.add_argument("--output", choices=["text", "json"], default="text", help="Output format")
    parser.add_argument("--interactive", action="store_true", help="Interactive mode")

    args = parser.parse_args()

    fmea_type = FMEAType.DESIGN if args.type == "design" else FMEAType.PROCESS
    analyzer = FMEAAnalyzer(fmea_type)

    if args.data:
        with open(args.data) as f:
            data = json.load(f)
        report = analyzer.generate_report(
            product_process=data.get("product_process", ""),
            team=data.get("team", []),
            entries_data=data.get("entries", [])
        )
    else:
        # Demo data
        demo_entries = [
            {
                "item_process": "Battery Module",
                "function": "Provide power for 8 hours",
                "failure_mode": "Premature battery drain",
                "effect": "Device shuts down during procedure",
                "severity": 8,
                "cause": "Cell degradation due to temperature cycling",
                "occurrence": 4,
                "current_controls": "Incoming battery testing, temperature spec in IFU",
                "detection": 5,
                "recommended_actions": ["Add battery health monitoring algorithm", "Implement low-battery warning at 20%"]
            },
            {
                "item_process": "Software Controller",
                "function": "Control device operation",
                "failure_mode": "Firmware crash",
                "effect": "Device becomes unresponsive",
                "severity": 7,
                "cause": "Memory leak in logging module",
                "occurrence": 3,
                "current_controls": "Code review, unit testing, integration testing",
                "detection": 4,
                "recommended_actions": ["Add watchdog timer", "Implement memory usage monitoring"]
            },
            {
                "item_process": "Sterile Packaging",
                "function": "Maintain sterility until use",
                "failure_mode": "Seal breach",
                "effect": "Device contamination",
                "severity": 9,
                "cause": "Sealing jaw temperature variation",
                "occurrence": 2,
                "current_controls": "Seal integrity testing (dye penetration), SPC on sealing process",
                "detection": 3,
                "recommended_actions": ["Add real-time seal temperature monitoring", "Implement 100% seal integrity testing"]
            }
        ]
        report = analyzer.generate_report(
            product_process="Insulin Pump Model X200",
            team=["Quality Engineer", "R&D Lead", "Manufacturing Engineer", "Risk Manager"],
            entries_data=demo_entries
        )

    if args.output == "json":
        result = {
            "fmea_type": report.fmea_type,
            "product_process": report.product_process,
            "date": report.date,
            "team": report.team,
            "entries": [asdict(e) for e in report.entries],
            "summary": report.summary,
            "risk_reduction_actions": report.risk_reduction_actions
        }
        print(json.dumps(result, indent=2))
    else:
        print(format_fmea_text(report))


if __name__ == "__main__":
    main()

#!/usr/bin/env python3
"""
Risk Matrix Calculator

Calculate risk levels based on probability and severity ratings per ISO 14971.
Supports multiple risk matrix configurations and FMEA RPN calculations.

Usage:
    python risk_matrix_calculator.py --probability 3 --severity 4
    python risk_matrix_calculator.py --fmea --severity 8 --occurrence 5 --detection 6
    python risk_matrix_calculator.py --interactive
    python risk_matrix_calculator.py --list-criteria
"""

import argparse
import json
import sys
from typing import Tuple, Optional


# Standard 5x5 Risk Matrix per ISO 14971 common practice
PROBABILITY_LEVELS = {
    1: {"name": "Improbable", "description": "Very unlikely to occur", "frequency": "<10^-6"},
    2: {"name": "Remote", "description": "Unlikely to occur", "frequency": "10^-5 to 10^-6"},
    3: {"name": "Occasional", "description": "May occur", "frequency": "10^-4 to 10^-5"},
    4: {"name": "Probable", "description": "Likely to occur", "frequency": "10^-3 to 10^-4"},
    5: {"name": "Frequent", "description": "Expected to occur", "frequency": ">10^-3"}
}

SEVERITY_LEVELS = {
    1: {"name": "Negligible", "description": "Inconvenience or temporary discomfort", "harm": "No injury"},
    2: {"name": "Minor", "description": "Temporary injury not requiring intervention", "harm": "Temporary discomfort"},
    3: {"name": "Serious", "description": "Injury requiring professional intervention", "harm": "Reversible injury"},
    4: {"name": "Critical", "description": "Permanent impairment or life-threatening", "harm": "Permanent impairment"},
    5: {"name": "Catastrophic", "description": "Death", "harm": "Death"}
}

# Risk matrix: RISK_MATRIX[probability][severity] = risk_level
RISK_MATRIX = {
    1: {1: "Low", 2: "Low", 3: "Low", 4: "Medium", 5: "Medium"},
    2: {1: "Low", 2: "Low", 3: "Medium", 4: "Medium", 5: "High"},
    3: {1: "Low", 2: "Medium", 3: "Medium", 4: "High", 5: "High"},
    4: {1: "Medium", 2: "Medium", 3: "High", 4: "High", 5: "Unacceptable"},
    5: {1: "Medium", 2: "High", 3: "High", 4: "Unacceptable", 5: "Unacceptable"}
}

# Risk level definitions and required actions
RISK_ACTIONS = {
    "Low": {
        "acceptable": True,
        "action": "Document and accept. No further action required.",
        "color": "green"
    },
    "Medium": {
        "acceptable": "AFAP",
        "action": "Reduce as far as possible (AFAP). Document why further reduction is impossible. EU MDR: no economic considerations in acceptability (MDR Annex I GSPR 1-4; EN ISO 14971:2019/A11:2021).",
        "color": "yellow"
    },
    "High": {
        "acceptable": "AFAP",
        "action": "Risk reduction required. Must demonstrate reduction as far as possible (AFAP) if residual risk remains high. EU MDR: no economic considerations in acceptability.",
        "color": "orange"
    },
    "Unacceptable": {
        "acceptable": False,
        "action": "Risk reduction mandatory. Design change required before proceeding.",
        "color": "red"
    }
}

# FMEA scales (1-10)
FMEA_SEVERITY = {
    1: "No effect",
    2: "Very minor effect",
    3: "Minor effect",
    4: "Very low effect",
    5: "Low effect",
    6: "Moderate effect",
    7: "High effect",
    8: "Very high effect",
    9: "Hazardous with warning",
    10: "Hazardous without warning"
}

FMEA_OCCURRENCE = {
    1: "Remote (<1 in 1,500,000)",
    2: "Very low (1 in 150,000)",
    3: "Low (1 in 15,000)",
    4: "Moderately low (1 in 2,000)",
    5: "Moderate (1 in 400)",
    6: "Moderately high (1 in 80)",
    7: "High (1 in 20)",
    8: "Very high (1 in 8)",
    9: "Extremely high (1 in 3)",
    10: "Almost certain (>1 in 2)"
}

FMEA_DETECTION = {
    1: "Almost certain detection",
    2: "Very high detection",
    3: "High detection",
    4: "Moderately high detection",
    5: "Moderate detection",
    6: "Low detection",
    7: "Very low detection",
    8: "Remote detection",
    9: "Very remote detection",
    10: "Cannot detect"
}


def calculate_risk_level(probability: int, severity: int) -> dict:
    """Calculate risk level from probability and severity ratings."""
    if probability < 1 or probability > 5:
        return {"error": f"Probability must be 1-5, got {probability}"}
    if severity < 1 or severity > 5:
        return {"error": f"Severity must be 1-5, got {severity}"}

    risk_level = RISK_MATRIX[probability][severity]
    risk_info = RISK_ACTIONS[risk_level]

    return {
        "probability": {
            "rating": probability,
            **PROBABILITY_LEVELS[probability]
        },
        "severity": {
            "rating": severity,
            **SEVERITY_LEVELS[severity]
        },
        "risk_level": risk_level,
        "acceptable": risk_info["acceptable"],
        "action_required": risk_info["action"],
        "risk_index": probability * severity
    }


def calculate_rpn(severity: int, occurrence: int, detection: int) -> dict:
    """Calculate FMEA Risk Priority Number."""
    if not all(1 <= x <= 10 for x in [severity, occurrence, detection]):
        return {"error": "All FMEA ratings must be 1-10"}

    rpn = severity * occurrence * detection

    # Determine priority level
    if rpn > 200:
        priority = "Critical"
        action = "Immediate action required"
    elif rpn > 100:
        priority = "High"
        action = "Action plan required"
    elif rpn > 50:
        priority = "Medium"
        action = "Consider risk reduction"
    else:
        priority = "Low"
        action = "Monitor"

    return {
        "severity": {
            "rating": severity,
            "description": FMEA_SEVERITY[severity]
        },
        "occurrence": {
            "rating": occurrence,
            "description": FMEA_OCCURRENCE[occurrence]
        },
        "detection": {
            "rating": detection,
            "description": FMEA_DETECTION[detection]
        },
        "rpn": rpn,
        "priority": priority,
        "action_required": action,
        "max_rpn": 1000,
        "rpn_percentage": round(rpn / 10, 1)
    }


def display_risk_matrix():
    """Display the full risk matrix."""
    print("\n" + "=" * 70)
    print("ISO 14971 RISK MATRIX (5x5)")
    print("=" * 70)

    # Header
    print("\n" + " " * 15, end="")
    for s in range(1, 6):
        print(f"S{s:^10}", end="")
    print()

    print(" " * 15, end="")
    for s in range(1, 6):
        print(f"{SEVERITY_LEVELS[s]['name'][:10]:^10}", end="")
    print()

    print("-" * 70)

    # Matrix rows
    for p in range(5, 0, -1):
        print(f"P{p} {PROBABILITY_LEVELS[p]['name'][:10]:>10} |", end="")
        for s in range(1, 6):
            level = RISK_MATRIX[p][s]
            print(f"{level:^10}", end="")
        print()

    print("\n" + "-" * 70)
    print("Risk Levels: Low (Acceptable) | Medium (reduce AFAP) | High (reduce AFAP) | Unacceptable")
    print("EU MDR: reduce as far as possible (AFAP), no economic considerations in acceptability.")
    print("=" * 70)


def display_criteria():
    """Display probability and severity criteria."""
    print("\n" + "=" * 70)
    print("PROBABILITY CRITERIA")
    print("=" * 70)
    for level, info in PROBABILITY_LEVELS.items():
        print(f"\nP{level}: {info['name']}")
        print(f"   Description: {info['description']}")
        print(f"   Frequency: {info['frequency']}")

    print("\n" + "=" * 70)
    print("SEVERITY CRITERIA")
    print("=" * 70)
    for level, info in SEVERITY_LEVELS.items():
        print(f"\nS{level}: {info['name']}")
        print(f"   Description: {info['description']}")
        print(f"   Harm: {info['harm']}")

    print("\n" + "=" * 70)
    print("RISK LEVEL ACTIONS")
    print("=" * 70)
    for level, info in RISK_ACTIONS.items():
        acceptable = "Yes" if info['acceptable'] == True else ("After reduction AFAP" if info['acceptable'] == "AFAP" else "No")
        print(f"\n{level}:")
        print(f"   Acceptable: {acceptable}")
        print(f"   Action: {info['action']}")


def format_result_text(result: dict, analysis_type: str) -> str:
    """Format result for text output."""
    lines = []
    lines.append("\n" + "=" * 50)

    if analysis_type == "risk":
        lines.append("RISK ASSESSMENT RESULT")
        lines.append("=" * 50)
        lines.append(f"\nProbability: P{result['probability']['rating']} - {result['probability']['name']}")
        lines.append(f"  {result['probability']['description']}")
        lines.append(f"\nSeverity: S{result['severity']['rating']} - {result['severity']['name']}")
        lines.append(f"  {result['severity']['description']}")
        lines.append(f"\n{'-' * 50}")
        lines.append(f"RISK LEVEL: {result['risk_level']}")
        lines.append(f"Risk Index: {result['risk_index']} (P × S)")
        lines.append(f"Acceptable: {result['acceptable']}")
        lines.append(f"\nAction Required:")
        lines.append(f"  {result['action_required']}")

    elif analysis_type == "fmea":
        lines.append("FMEA RPN CALCULATION")
        lines.append("=" * 50)
        lines.append(f"\nSeverity: {result['severity']['rating']}/10")
        lines.append(f"  {result['severity']['description']}")
        lines.append(f"\nOccurrence: {result['occurrence']['rating']}/10")
        lines.append(f"  {result['occurrence']['description']}")
        lines.append(f"\nDetection: {result['detection']['rating']}/10")
        lines.append(f"  {result['detection']['description']}")
        lines.append(f"\n{'-' * 50}")
        lines.append(f"RPN: {result['rpn']} / {result['max_rpn']} ({result['rpn_percentage']}%)")
        lines.append(f"Priority: {result['priority']}")
        lines.append(f"\nAction Required:")
        lines.append(f"  {result['action_required']}")

    lines.append("=" * 50)
    return "\n".join(lines)


def interactive_mode():
    """Run interactive risk assessment."""
    print("\n" + "=" * 50)
    print("RISK MATRIX CALCULATOR - Interactive Mode")
    print("=" * 50)

    print("\nSelect analysis type:")
    print("1. Risk Matrix (ISO 14971 style)")
    print("2. FMEA RPN Calculation")
    print("3. Display Risk Matrix")
    print("4. Display Criteria")
    print("5. Exit")

    choice = input("\nEnter choice (1-5): ").strip()

    if choice == "1":
        display_criteria()
        print("\n" + "-" * 50)
        try:
            p = int(input("Enter Probability (1-5): "))
            s = int(input("Enter Severity (1-5): "))
            result = calculate_risk_level(p, s)
            if "error" in result:
                print(f"\nError: {result['error']}")
            else:
                print(format_result_text(result, "risk"))
        except ValueError:
            print("Invalid input. Please enter numbers.")

    elif choice == "2":
        print("\nFMEA Scales:")
        print("  Severity: 1 (No effect) to 10 (Hazardous without warning)")
        print("  Occurrence: 1 (Remote) to 10 (Almost certain)")
        print("  Detection: 1 (Almost certain) to 10 (Cannot detect)")
        print("-" * 50)
        try:
            s = int(input("Enter Severity (1-10): "))
            o = int(input("Enter Occurrence (1-10): "))
            d = int(input("Enter Detection (1-10): "))
            result = calculate_rpn(s, o, d)
            if "error" in result:
                print(f"\nError: {result['error']}")
            else:
                print(format_result_text(result, "fmea"))
        except ValueError:
            print("Invalid input. Please enter numbers.")

    elif choice == "3":
        display_risk_matrix()

    elif choice == "4":
        display_criteria()

    elif choice == "5":
        print("Exiting.")
        return

    else:
        print("Invalid choice.")


def main():
    parser = argparse.ArgumentParser(
        description="Calculate risk levels per ISO 14971 or FMEA RPN",
        formatter_class=argparse.RawDescriptionHelpFormatter,
        epilog="""
Examples:
  # ISO 14971 risk matrix calculation
  python risk_matrix_calculator.py --probability 3 --severity 4

  # FMEA RPN calculation
  python risk_matrix_calculator.py --fmea --severity 8 --occurrence 5 --detection 6

  # Interactive mode
  python risk_matrix_calculator.py --interactive

  # Display risk matrix
  python risk_matrix_calculator.py --show-matrix

  # Display criteria definitions
  python risk_matrix_calculator.py --list-criteria

  # JSON output
  python risk_matrix_calculator.py -p 4 -s 3 --output json
        """
    )

    parser.add_argument("-p", "--probability", type=int, help="Probability rating (1-5)")
    parser.add_argument("-s", "--severity", type=int, help="Severity rating (1-5 for risk, 1-10 for FMEA)")
    parser.add_argument("-o", "--occurrence", type=int, help="FMEA occurrence rating (1-10)")
    parser.add_argument("-d", "--detection", type=int, help="FMEA detection rating (1-10)")
    parser.add_argument("--fmea", action="store_true", help="Use FMEA RPN calculation")
    parser.add_argument("--output", choices=["text", "json"], default="text", help="Output format")
    parser.add_argument("--show-matrix", action="store_true", help="Display risk matrix")
    parser.add_argument("--list-criteria", action="store_true", help="Display probability and severity criteria")
    parser.add_argument("--interactive", action="store_true", help="Run in interactive mode")

    args = parser.parse_args()

    if args.interactive:
        interactive_mode()
        return

    if args.show_matrix:
        display_risk_matrix()
        return

    if args.list_criteria:
        display_criteria()
        return

    if args.fmea:
        if not all([args.severity, args.occurrence, args.detection]):
            parser.error("FMEA requires --severity, --occurrence, and --detection")

        result = calculate_rpn(args.severity, args.occurrence, args.detection)
        if "error" in result:
            print(f"Error: {result['error']}")
            sys.exit(1)

        if args.output == "json":
            print(json.dumps(result, indent=2))
        else:
            print(format_result_text(result, "fmea"))

    else:
        if not all([args.probability, args.severity]):
            parser.error("Risk calculation requires --probability and --severity")

        result = calculate_risk_level(args.probability, args.severity)
        if "error" in result:
            print(f"Error: {result['error']}")
            sys.exit(1)

        if args.output == "json":
            print(json.dumps(result, indent=2))
        else:
            print(format_result_text(result, "risk"))


if __name__ == "__main__":
    main()