feat: implement simulation analyzer module with web worker for performance.
This commit is contained in:
70
app/src/modules/simulation/analyzer/analyzer.state.ts
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70
app/src/modules/simulation/analyzer/analyzer.state.ts
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export const historicalData: Record<string, any[]> = {};
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export let materialHistory: any[] = [];
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export const queueLengths: Record<string, { timestamp: number; length: number }[]> = {};
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export const errorCounts: Record<string, number> = {};
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export const completedActions: Record<string, number> = {};
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export const stateTransitions: Record<string, any[]> = {};
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export const materialAdditions: Record<string, { materialId: string; materialType: string; timestamp: number; fromAsset?: string }[]> = {};
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export const materialRemovals: Record<string, { materialId: string; materialType: string; timestamp: number; toAsset?: string; processingTime?: number }[]> = {};
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export const assetStateChanges: Record<string, { fromState: string; toState: string; timestamp: number; duration?: number }[]> = {};
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export const assetCycles: Record<string, { cycleId: string; startTime: number; endTime?: number; cycleType: string; materialsInvolved: string[]; success: boolean }[]> = {};
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export const actionCompletionTimes: Record<string, { actionId: string; actionType: string; startTime: number; endTime: number; duration: number; success: boolean }[]> = {};
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export const materialProcessingTimes: Record<string, { materialId: string; entryTime: number; exitTime?: number; processingDuration?: number; waitTime?: number }[]> = {};
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export const wipSnapshots: Record<string, { timestamp: number; wipCount: number; materialIds: string[] }[]> = {};
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export const throughputSnapshots: Record<string, { timestamp: number; itemsProcessed: number; timeWindow: number; rate: number }[]> = {};
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export const performanceSnapshots: Record<string, { timestamp: number; utilization: number; efficiency: number; quality: number; oee: number }[]> = {};
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export const bottleneckEvents: Record<string, { timestamp: number; queueLength: number; utilizationRate: number; waitingMaterials: string[] }[]> = {};
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export const previousAssetStates: Record<string, { state: string; isActive: boolean; materialCount: number; timestamp: number }> = {};
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export const previousArmBotActions: Record<string, string | undefined> = {};
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export const previousMachineActions: Record<string, string | undefined> = {};
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export const previousStorageLoads: Record<string, number> = {};
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export const previousHumanCounts: Record<string, Record<string, number>> = {};
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export const previousVehiclePhases: Record<string, string> = {};
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export const previousCranePhases: Record<string, string> = {};
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export const materialLifecycle: Record<
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string,
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{
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materialId: string;
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createdAt: number;
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completedAt?: number;
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path: { assetId: string; assetType: string; entryTime: number; exitTime?: number }[];
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totalProcessingTime?: number;
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totalWaitTime?: number;
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}
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> = {};
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export const resetState = () => {
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const clear = (obj: any) => {
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for (const k in obj) delete obj[k];
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};
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clear(historicalData);
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materialHistory.length = 0;
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clear(queueLengths);
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clear(errorCounts);
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clear(completedActions);
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clear(stateTransitions);
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clear(materialAdditions);
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clear(materialRemovals);
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clear(assetStateChanges);
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clear(assetCycles);
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clear(actionCompletionTimes);
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clear(materialProcessingTimes);
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clear(wipSnapshots);
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clear(throughputSnapshots);
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clear(performanceSnapshots);
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clear(bottleneckEvents);
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clear(previousAssetStates);
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clear(previousArmBotActions);
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clear(previousMachineActions);
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clear(previousStorageLoads);
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clear(previousHumanCounts);
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clear(previousVehiclePhases);
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clear(previousCranePhases);
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clear(materialLifecycle);
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};
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File diff suppressed because it is too large
Load Diff
122
app/src/modules/simulation/analyzer/analyzer.types.ts
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122
app/src/modules/simulation/analyzer/analyzer.types.ts
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@@ -0,0 +1,122 @@
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export const HOURLY_RATES: Record<string, number> = {
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CONVEYOR: 50,
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VEHICLE: 75,
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MACHINE: 100,
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ROBOTIC_ARM: 120,
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HUMAN: 35,
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CRANE: 150,
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STORAGE: 25,
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};
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export const MAINTENANCE_COSTS: Record<string, number> = {
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CONVEYOR: 0.5,
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VEHICLE: 2,
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MACHINE: 5,
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ROBOTIC_ARM: 8,
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HUMAN: 0.1,
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CRANE: 10,
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STORAGE: 1,
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};
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export const ENERGY_COSTS: Record<string, number> = {
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CONVEYOR: 5,
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VEHICLE: 10,
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MACHINE: 15,
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ROBOTIC_ARM: 20,
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HUMAN: 0,
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CRANE: 25,
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STORAGE: 2,
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};
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export const ENERGY_CONSUMPTION_RATES: Record<string, number> = {
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CONVEYOR: 7.5,
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VEHICLE: 15,
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VEHICLE_DISTANCE_FACTOR: 0.1,
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MACHINE: 20,
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ROBOTIC_ARM: 10,
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HUMAN: 0,
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CRANE: 25,
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STORAGE: 2,
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DEFAULT: 5,
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};
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export const ENERGY_CONSTANTS = {
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COST_PER_KWH: 0.12,
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CO2_PER_KWH: 0.5,
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};
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export const EFFICIENCY_ADJUSTMENTS: Record<string, number> = {
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CONVEYOR: 1.0,
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VEHICLE: 0.95,
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MACHINE: 0.9,
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ROBOTIC_ARM: 0.92,
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HUMAN: 0.85,
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CRANE: 0.88,
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STORAGE: 0.98,
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DEFAULT: 1.0,
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};
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export const PERFORMANCE_BENCHMARKS = {
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CONVEYOR_LENGTH: 10,
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VEHICLE_IDEAL_TRIP_TIME: 60,
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VEHICLE_OPTIMAL_DISTANCE: 100,
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ARM_IDEAL_CYCLE_TIME: 5,
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MACHINE_DEFAULT_PROCESS_TIME: 30,
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CRANE_IDEAL_CYCLE_TIME: 20,
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HUMAN_IDEAL_ACTIONS_PER_HOUR: 60,
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CRANE_DEFAULT_LIFT_HEIGHT: 5,
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};
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export const QUALITY_CONSTANTS = {
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DEFAULT_SCRAP_RATE: 0.1,
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DEFAULT_REWORK_RATE: 0.9,
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MACHINE_SCRAP_RATIO: 0.7,
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MACHINE_REWORK_RATIO: 0.3,
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};
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export const ANALYSIS_SETTINGS = {
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HISTORY_LIMIT: 100,
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THROUGHPUT_WINDOW: 60,
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BOTTLENECK_QUEUE_THRESHOLD: 2,
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BOTTLENECK_UTILIZATION_THRESHOLD: 0.85,
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CRITICAL_UTILIZATION: 0.95,
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HIGH_UTILIZATION: 0.9,
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};
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export const FINANCIAL_PARAMS = {
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REVENUE_PER_UNIT: 150,
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VALUE_PER_UNIT: 10,
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MATERIAL_VALUE: 25,
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HOLDING_COST_RATE: 0.25,
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SCRAP_RECOVERY_RATE: 0.1,
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FIXED_COST_RATIO: 0.4,
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VARIABLE_COST_RATIO: 0.6,
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};
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export const SUSTAINABILITY_CONSTANTS = {
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WASTE_PER_SCRAP_KG: 5,
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RECYCLABLE_RATIO: 0.3,
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WATER_USAGE_PER_UNIT: 10,
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};
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export interface WorkerMessage {
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type: "UPDATE" | "RESET";
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payload?: AnalyzerStatePayload;
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}
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export interface AnalyzerStatePayload {
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conveyors: any[];
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vehicles: any[];
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machines: any[];
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armBots: any[];
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humans: any[];
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cranes: any[];
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storageUnits: any[];
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materials: any[];
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materialHistory: any[];
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humanEventManagerData: any[];
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simulationTime: number;
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speed: number;
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isPlaying: boolean;
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isPaused: boolean;
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}
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631
app/src/modules/simulation/analyzer/analyzer.worker.assets.ts
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631
app/src/modules/simulation/analyzer/analyzer.worker.assets.ts
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@@ -0,0 +1,631 @@
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import { ANALYSIS_SETTINGS, PERFORMANCE_BENCHMARKS, QUALITY_CONSTANTS } from "./analyzer.types";
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import { completedActions, historicalData, errorCounts, queueLengths } from "./analyzer.state";
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import {
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calculateAdvancedTimeMetrics,
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calculateCostMetrics,
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calculateEnergyMetrics,
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calculateMaterialFlowMetricsForAsset,
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calculateOEE,
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calculatePerformanceMetrics,
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calculateQualityMetrics,
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getSimulationTime,
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} from "./analyzer.worker.utils";
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export const analyzeConveyor = (conveyor: any, materials: any[]) => {
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const assetId = conveyor.modelUuid;
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const errorCount = errorCounts[assetId] || 0;
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const timeMetrics = calculateAdvancedTimeMetrics(conveyor.idleTime || 0, conveyor.activeTime || 0, assetId, errorCount);
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const materialFlow = calculateMaterialFlowMetricsForAsset(
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assetId,
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materials.filter((m) => m.current?.modelUuid === assetId)
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);
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const materialsProcessed = materialFlow.totalMaterialsProcessed;
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const defects = errorCounts[`${assetId}_defects`] || 0;
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const qualityMetrics = calculateQualityMetrics(assetId, materialsProcessed, defects);
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const conveyorLength = PERFORMANCE_BENCHMARKS.CONVEYOR_LENGTH;
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const idealSpeed = conveyor.speed;
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const idealThroughput = idealSpeed > 0 ? (idealSpeed * 3600) / (conveyorLength / 2) : 0;
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const actualThroughput = materialFlow.throughput * 3600;
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const performance = calculatePerformanceMetrics(materialsProcessed, idealThroughput * (timeMetrics.totalTime / 3600), timeMetrics.totalTime, materialsProcessed * 2, "conveyor");
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const costMetrics = calculateCostMetrics(assetId, "conveyor", conveyor.activeTime || 0, materialsProcessed);
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const energyMetrics = calculateEnergyMetrics("conveyor", conveyor.activeTime || 0);
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const timestamp = getSimulationTime();
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const newEntry = {
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timestamp,
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isActive: !conveyor.isPaused,
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speed: conveyor.speed,
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state: conveyor.state,
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materialsCount: materialFlow.currentMaterials,
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throughput: actualThroughput,
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performance: performance.performanceRate,
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};
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const currentData = historicalData[assetId] || [];
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historicalData[assetId] = [...currentData, newEntry].slice(-ANALYSIS_SETTINGS.HISTORY_LIMIT);
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const queueLength = materialFlow.wip;
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const currentQueueData = queueLengths[assetId] || [];
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queueLengths[assetId] = [...currentQueueData, { timestamp, length: queueLength }].slice(-ANALYSIS_SETTINGS.HISTORY_LIMIT);
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return {
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assetId,
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assetName: conveyor.modelName,
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assetType: "conveyor",
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currentStatus: {
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isActive: !conveyor.isPaused,
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isPaused: conveyor.isPaused,
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state: conveyor.state,
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speed: conveyor.speed,
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currentProduct: conveyor.productUuid,
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currentMaterials: materialFlow.currentMaterials,
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queueLength,
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},
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timeMetrics: {
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...timeMetrics,
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idleTime: conveyor.idleTime || 0,
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activeTime: conveyor.activeTime || 0,
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availability: timeMetrics.uptime,
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},
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throughput: {
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itemsPerHour: actualThroughput,
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itemsPerDay: actualThroughput * 24,
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materialFlowRate: conveyor.speed * 60,
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capacityUtilization: timeMetrics.utilizationRate * 100,
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materialsProcessed,
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averageProcessingTime: materialFlow.avgCycleTime,
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wip: materialFlow.wip,
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throughputEfficiency: (actualThroughput / Math.max(1, idealThroughput)) * 100,
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bottleneckIndex: timeMetrics.utilizationRate > ANALYSIS_SETTINGS.HIGH_UTILIZATION ? 1 : 0,
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},
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efficiency: {
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overallEffectiveness: calculateOEE(timeMetrics.uptime, performance.performanceRate, qualityMetrics.firstPassYield),
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availability: timeMetrics.uptime,
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performance: performance.performanceRate,
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quality: qualityMetrics.firstPassYield,
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timeEfficiency: performance.timeEfficiency,
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energyEfficiency: energyMetrics.energyEfficiency,
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costEfficiency: 100 - costMetrics.costPerUnit * 10,
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scheduleEfficiency: timeMetrics.scheduleAdherence,
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},
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quality: qualityMetrics,
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costMetrics,
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energyMetrics: {
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...energyMetrics,
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energyPerUnit: materialsProcessed > 0 ? energyMetrics.energyConsumed / materialsProcessed : 0,
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},
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materialFlow: {
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wip: materialFlow.wip,
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throughput: materialFlow.throughput,
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avgCycleTime: materialFlow.avgCycleTime,
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materialVelocity: materialFlow.materialVelocity,
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inventoryTurns: materialFlow.inventoryTurns,
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leadTimeVariance: 0,
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},
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historicalData: historicalData[assetId] || [],
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};
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};
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export const analyzeVehicle = (vehicle: any, materials: any[]) => {
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const assetId = vehicle.modelUuid;
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const errorCount = errorCounts[assetId] || 0;
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const timeMetrics = calculateAdvancedTimeMetrics(vehicle.idleTime || 0, vehicle.activeTime || 0, assetId, errorCount);
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const materialFlow = calculateMaterialFlowMetricsForAsset(
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assetId,
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materials.filter((m) => m.current?.modelUuid === assetId)
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);
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const tripsCompleted = completedActions[assetId] || 0;
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const totalLoadsDelivered = completedActions[`${assetId}_loads`] || 0;
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const defects = errorCount;
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const qualityMetrics = calculateQualityMetrics(assetId, totalLoadsDelivered, defects);
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const loadCapacity = vehicle.point?.action?.loadCapacity || 1;
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const avgLoad = tripsCompleted > 0 ? totalLoadsDelivered / tripsCompleted : 0;
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const loadUtilization = (avgLoad / loadCapacity) * 100;
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const idealTripTime = PERFORMANCE_BENCHMARKS.VEHICLE_IDEAL_TRIP_TIME;
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const actualTripTime = tripsCompleted > 0 ? timeMetrics.totalTime / tripsCompleted : 0;
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const idealThroughput = loadCapacity * (3600 / idealTripTime);
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const actualThroughput = materialFlow.throughput * 3600;
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const performance = calculatePerformanceMetrics(totalLoadsDelivered, idealThroughput * (timeMetrics.totalTime / 3600), timeMetrics.totalTime, idealTripTime * tripsCompleted, "vehicle");
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const optimalDistance = PERFORMANCE_BENCHMARKS.VEHICLE_OPTIMAL_DISTANCE;
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const actualDistance = vehicle.distanceTraveled || 0;
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const routeEfficiency = actualDistance > 0 ? Math.min((optimalDistance / actualDistance) * 100, 100) : 100;
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const costMetrics = calculateCostMetrics(assetId, "vehicle", vehicle.activeTime || 0, totalLoadsDelivered);
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const energyMetrics = calculateEnergyMetrics("vehicle", vehicle.activeTime || 0, actualDistance);
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const timestamp = getSimulationTime();
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const currentData = historicalData[assetId] || [];
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historicalData[assetId] = [
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...currentData,
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{
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timestamp,
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phase: vehicle.currentPhase,
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load: vehicle.currentLoad,
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distanceTraveled: actualDistance,
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state: vehicle.state,
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performance: performance.performanceRate,
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speed: vehicle.speed,
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tripsCompleted,
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},
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].slice(-ANALYSIS_SETTINGS.HISTORY_LIMIT);
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return {
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assetId,
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assetName: vehicle.modelName,
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assetType: "vehicle",
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currentStatus: {
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isActive: vehicle.isActive,
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isPicking: vehicle.isPicking,
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currentPhase: vehicle.currentPhase,
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state: vehicle.state,
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speed: vehicle.speed,
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currentLoad: vehicle.currentLoad,
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currentMaterials: vehicle.currentMaterials, // Assuming serializable
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distanceTraveled: actualDistance,
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currentRouteEfficiency: routeEfficiency,
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},
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timeMetrics: { ...timeMetrics, idleTime: vehicle.idleTime, activeTime: vehicle.activeTime, averageTripTime: actualTripTime },
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throughput: {
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itemsPerHour: actualThroughput,
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itemsPerDay: actualThroughput * 24,
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materialFlowRate: vehicle.speed,
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capacityUtilization: timeMetrics.utilizationRate * 100,
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tripsCompleted,
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averageLoadsPerTrip: avgLoad,
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totalLoadsDelivered,
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throughputEfficiency: (actualThroughput / Math.max(1, idealThroughput)) * 100,
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wip: materialFlow.wip,
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bottleneckIndex: timeMetrics.utilizationRate > ANALYSIS_SETTINGS.BOTTLENECK_UTILIZATION_THRESHOLD ? 1 : 0,
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},
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movementMetrics: {
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distanceTraveled: actualDistance,
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averageSpeedActual: timeMetrics.totalTime > 0 ? actualDistance / timeMetrics.totalTime : 0,
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fuelEfficiency: actualDistance > 0 ? totalLoadsDelivered / actualDistance : 0,
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routeEfficiency,
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idleDistance: vehicle.idleTime || 0,
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totalTrips: tripsCompleted,
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averageTripDistance: tripsCompleted > 0 ? actualDistance / tripsCompleted : 0,
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distanceEfficiency: routeEfficiency,
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},
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efficiency: {
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overallEffectiveness: calculateOEE(timeMetrics.uptime, performance.performanceRate, qualityMetrics.firstPassYield),
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availability: timeMetrics.uptime,
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performance: performance.performanceRate,
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quality: qualityMetrics.firstPassYield,
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loadUtilization,
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timeEfficiency: performance.timeEfficiency,
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energyEfficiency: energyMetrics.energyEfficiency,
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routeEfficiency,
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costEfficiency: 100 - costMetrics.costPerUnit * 5,
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},
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quality: {
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...qualityMetrics,
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onTimeDelivery: tripsCompleted > 0 ? ((tripsCompleted - defects) / tripsCompleted) * 100 : 100,
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damageRate: defects > 0 ? (defects / totalLoadsDelivered) * 100 : 0,
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accuracyRate: 100 - qualityMetrics.defectRate,
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},
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costMetrics: {
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...costMetrics,
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costPerMile: actualDistance > 0 ? costMetrics.totalCost / (actualDistance / 1609.34) : 0,
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costPerTrip: tripsCompleted > 0 ? costMetrics.totalCost / tripsCompleted : 0,
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costPerLoad: totalLoadsDelivered > 0 ? costMetrics.totalCost / totalLoadsDelivered : 0,
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},
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energyMetrics: {
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...energyMetrics,
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energyPerMile: actualDistance > 0 ? energyMetrics.energyConsumed / actualDistance : 0,
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energyPerTrip: tripsCompleted > 0 ? energyMetrics.energyConsumed / tripsCompleted : 0,
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},
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historicalData: historicalData[assetId] || [],
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};
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||||
};
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export const analyzeRoboticArm = (armBot: any, materials: any[]) => {
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const assetId = armBot.modelUuid;
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const errorCount = errorCounts[assetId] || 0;
|
||||
const timeMetrics = calculateAdvancedTimeMetrics(armBot.idleTime || 0, armBot.activeTime || 0, assetId, errorCount);
|
||||
const materialFlow = calculateMaterialFlowMetricsForAsset(
|
||||
assetId,
|
||||
materials.filter((m) => m.current?.modelUuid === assetId)
|
||||
);
|
||||
|
||||
const cyclesCompleted = completedActions[assetId] || 0;
|
||||
const pickAndPlaceCount = completedActions[`${assetId}_pickplace`] || cyclesCompleted;
|
||||
const defects = errorCount;
|
||||
const qualityMetrics = calculateQualityMetrics(assetId, pickAndPlaceCount, defects);
|
||||
|
||||
const idealCycleTime = PERFORMANCE_BENCHMARKS.ARM_IDEAL_CYCLE_TIME;
|
||||
const actualCycleTime = cyclesCompleted > 0 ? timeMetrics.totalTime / cyclesCompleted : 0;
|
||||
const idealThroughput = 3600 / idealCycleTime;
|
||||
const actualThroughput = materialFlow.throughput * 3600;
|
||||
|
||||
const performance = calculatePerformanceMetrics(pickAndPlaceCount, idealThroughput * (timeMetrics.totalTime / 3600), timeMetrics.totalTime, idealCycleTime * cyclesCompleted, "roboticArm");
|
||||
const costMetrics = calculateCostMetrics(assetId, "roboticArm", armBot.activeTime || 0, pickAndPlaceCount);
|
||||
const energyMetrics = calculateEnergyMetrics("roboticArm", armBot.activeTime || 0);
|
||||
|
||||
const pickSuccessCount = completedActions[`${assetId}_pick`] || pickAndPlaceCount / 2;
|
||||
const placeSuccessCount = completedActions[`${assetId}_place`] || pickAndPlaceCount / 2;
|
||||
const pickErrors = errorCounts[`${assetId}_pick`] || 0;
|
||||
const placeErrors = errorCounts[`${assetId}_place`] || 0;
|
||||
|
||||
const remainingErrors = Math.max(0, errorCount - pickErrors - placeErrors);
|
||||
const effectivePickErrors = pickErrors + (remainingErrors > 0 ? Math.ceil(remainingErrors / 2) : 0);
|
||||
const effectivePlaceErrors = placeErrors + (remainingErrors > 0 ? Math.floor(remainingErrors / 2) : 0);
|
||||
|
||||
const pickAttempts = pickSuccessCount + effectivePickErrors;
|
||||
const placeAttempts = placeSuccessCount + effectivePlaceErrors;
|
||||
const pickSuccessRate = pickAttempts > 0 ? (pickSuccessCount / pickAttempts) * 100 : 100;
|
||||
const placeAccuracy = placeAttempts > 0 ? (placeSuccessCount / placeAttempts) * 100 : 100;
|
||||
|
||||
const timestamp = getSimulationTime();
|
||||
const currentData = historicalData[assetId] || [];
|
||||
historicalData[assetId] = [
|
||||
...currentData,
|
||||
{
|
||||
timestamp,
|
||||
cycleTime: actualCycleTime,
|
||||
actionType: armBot.currentAction?.actionName || "unknown",
|
||||
isActive: armBot.isActive,
|
||||
state: armBot.state,
|
||||
speed: armBot.speed,
|
||||
cyclesCompleted,
|
||||
successRate: pickSuccessRate,
|
||||
performance: performance.performanceRate,
|
||||
},
|
||||
].slice(-ANALYSIS_SETTINGS.HISTORY_LIMIT);
|
||||
|
||||
return {
|
||||
assetId,
|
||||
assetName: armBot.modelName,
|
||||
assetType: "roboticArm",
|
||||
currentStatus: {
|
||||
isActive: armBot.isActive,
|
||||
state: armBot.state,
|
||||
speed: armBot.speed,
|
||||
currentAction: armBot.currentAction || null,
|
||||
},
|
||||
timeMetrics: { ...timeMetrics, idleTime: armBot.idleTime, activeTime: armBot.activeTime, averageCycleTime: actualCycleTime },
|
||||
throughput: {
|
||||
itemsPerHour: actualThroughput,
|
||||
itemsPerDay: actualThroughput * 24,
|
||||
materialFlowRate: armBot.speed,
|
||||
capacityUtilization: timeMetrics.utilizationRate * 100,
|
||||
cyclesCompleted,
|
||||
pickAndPlaceCount,
|
||||
throughputEfficiency: (actualThroughput / Math.max(1, idealThroughput)) * 100,
|
||||
wip: materialFlow.wip,
|
||||
bottleneckIndex: timeMetrics.utilizationRate > ANALYSIS_SETTINGS.BOTTLENECK_UTILIZATION_THRESHOLD ? 1 : 0,
|
||||
},
|
||||
efficiency: {
|
||||
overallEffectiveness: calculateOEE(timeMetrics.uptime, performance.performanceRate, qualityMetrics.firstPassYield),
|
||||
availability: timeMetrics.uptime,
|
||||
performance: performance.performanceRate,
|
||||
quality: qualityMetrics.firstPassYield,
|
||||
cycleTimeEfficiency: performance.timeEfficiency,
|
||||
},
|
||||
quality: { ...qualityMetrics, pickSuccessRate, placeAccuracy },
|
||||
costMetrics: { ...costMetrics, roi: costMetrics.roi, valueAdded: costMetrics.valueAdded },
|
||||
energyMetrics: { ...energyMetrics, energyPerUnit: pickAndPlaceCount > 0 ? energyMetrics.energyConsumed / pickAndPlaceCount : 0 },
|
||||
historicalData: historicalData[assetId] || [],
|
||||
};
|
||||
};
|
||||
|
||||
export const analyzeMachine = (machine: any, materials: any[]) => {
|
||||
const assetId = machine.modelUuid;
|
||||
const errorCount = errorCounts[assetId] || 0;
|
||||
const timeMetrics = calculateAdvancedTimeMetrics(machine.idleTime || 0, machine.activeTime || 0, assetId, errorCount);
|
||||
const materialFlow = calculateMaterialFlowMetricsForAsset(
|
||||
assetId,
|
||||
materials.filter((m) => m.current?.modelUuid === assetId)
|
||||
);
|
||||
|
||||
const cyclesCompleted = completedActions[assetId] || 0;
|
||||
const partsProcessed = completedActions[`${assetId}_parts`] || cyclesCompleted;
|
||||
const defects = errorCounts[`${assetId}_defects`] || 0;
|
||||
|
||||
const qualityMetrics = calculateQualityMetrics(assetId, partsProcessed, defects);
|
||||
|
||||
const targetProcessTime = machine.point?.action?.processTime || PERFORMANCE_BENCHMARKS.MACHINE_DEFAULT_PROCESS_TIME;
|
||||
const actualProcessTime = cyclesCompleted > 0 ? timeMetrics.totalTime / cyclesCompleted : 0;
|
||||
const idealThroughput = 3600 / targetProcessTime;
|
||||
const actualThroughput = materialFlow.throughput * 3600;
|
||||
|
||||
const performance = calculatePerformanceMetrics(partsProcessed, idealThroughput * (timeMetrics.totalTime / 3600), timeMetrics.totalTime, targetProcessTime * cyclesCompleted, "machine");
|
||||
const costMetrics = calculateCostMetrics(assetId, "machine", machine.activeTime || 0, partsProcessed);
|
||||
const energyMetrics = calculateEnergyMetrics("machine", machine.activeTime || 0);
|
||||
|
||||
const totalParts = partsProcessed + defects;
|
||||
const defectRate = totalParts > 0 ? (defects / totalParts) * 100 : 0;
|
||||
const reworkRate = defectRate * QUALITY_CONSTANTS.MACHINE_REWORK_RATIO;
|
||||
const scrapRate = defectRate * QUALITY_CONSTANTS.MACHINE_SCRAP_RATIO;
|
||||
|
||||
const timestamp = getSimulationTime();
|
||||
const currentData = historicalData[assetId] || [];
|
||||
historicalData[assetId] = [
|
||||
...currentData,
|
||||
{
|
||||
timestamp,
|
||||
processTime: actualProcessTime,
|
||||
partsProcessed,
|
||||
isActive: machine.isActive,
|
||||
state: machine.state,
|
||||
defectRate,
|
||||
performance: performance.performanceRate,
|
||||
},
|
||||
].slice(-ANALYSIS_SETTINGS.HISTORY_LIMIT);
|
||||
|
||||
return {
|
||||
assetId,
|
||||
assetName: machine.modelName,
|
||||
assetType: "machine",
|
||||
currentStatus: { isActive: machine.isActive, state: machine.state, currentAction: machine.currentAction || null },
|
||||
timeMetrics: { ...timeMetrics, idleTime: machine.idleTime, activeTime: machine.activeTime, averageProcessTime: actualProcessTime },
|
||||
throughput: {
|
||||
itemsPerHour: actualThroughput,
|
||||
itemsPerDay: actualThroughput * 24,
|
||||
materialFlowRate: partsProcessed > 0 ? partsProcessed / (timeMetrics.totalTime / 60) : 0,
|
||||
capacityUtilization: timeMetrics.utilizationRate * 100,
|
||||
cyclesCompleted,
|
||||
partsProcessed,
|
||||
throughputEfficiency: (actualThroughput / Math.max(1, idealThroughput)) * 100,
|
||||
wip: materialFlow.wip,
|
||||
bottleneckIndex: timeMetrics.utilizationRate > ANALYSIS_SETTINGS.BOTTLENECK_UTILIZATION_THRESHOLD ? 1 : 0,
|
||||
},
|
||||
efficiency: {
|
||||
overallEffectiveness: calculateOEE(timeMetrics.uptime, performance.performanceRate, qualityMetrics.firstPassYield),
|
||||
availability: timeMetrics.uptime,
|
||||
performance: performance.performanceRate,
|
||||
quality: qualityMetrics.firstPassYield,
|
||||
targetVsActual: performance.timeEfficiency,
|
||||
},
|
||||
quality: { ...qualityMetrics, defectRate, reworkRate, scrapRate },
|
||||
costMetrics: { ...costMetrics, costPerUnit: partsProcessed > 0 ? costMetrics.totalCost / partsProcessed : 0 },
|
||||
energyMetrics: { ...energyMetrics, energyPerUnit: partsProcessed > 0 ? energyMetrics.energyConsumed / partsProcessed : 0 },
|
||||
historicalData: historicalData[assetId] || [],
|
||||
};
|
||||
};
|
||||
|
||||
export const analyzeStorage = (storage: any, materials: any[]) => {
|
||||
// Placeholder to save space, logic is very similar to others.
|
||||
// I'll implement it strictly
|
||||
const assetId = storage.modelUuid;
|
||||
const errorCount = errorCounts[assetId] || 0;
|
||||
const timeMetrics = calculateAdvancedTimeMetrics(storage.idleTime || 0, storage.activeTime || 0, assetId, errorCount);
|
||||
|
||||
const currentLoad = storage.currentLoad || 0;
|
||||
const capacity = storage.storageCapacity || 1;
|
||||
const utilizationRate = (currentLoad / capacity) * 100;
|
||||
|
||||
const storeOps = completedActions[`${assetId}_store`] || 0;
|
||||
const retrieveOps = completedActions[`${assetId}_retrieve`] || 0;
|
||||
const totalOps = storeOps + retrieveOps;
|
||||
|
||||
const qualityMetrics = calculateQualityMetrics(assetId, totalOps, errorCount);
|
||||
const turnoverRate = timeMetrics.totalTime > 0 ? (totalOps / timeMetrics.totalTime) * 3600 : 0;
|
||||
|
||||
const timestamp = getSimulationTime();
|
||||
const currentData = historicalData[assetId] || [];
|
||||
historicalData[assetId] = [
|
||||
...currentData,
|
||||
{
|
||||
timestamp,
|
||||
currentLoad,
|
||||
utilizationRate,
|
||||
operation: storeOps > retrieveOps ? "store" : "retrieve",
|
||||
totalOps,
|
||||
state: storage.state,
|
||||
},
|
||||
].slice(-ANALYSIS_SETTINGS.HISTORY_LIMIT);
|
||||
|
||||
const occupancyData = historicalData[assetId] || [];
|
||||
const peakOccupancy = occupancyData.length > 0 ? Math.max(...occupancyData.map((d: any) => d.utilizationRate)) : utilizationRate;
|
||||
const averageOccupancy = occupancyData.length > 0 ? occupancyData.reduce((sum: number, d: any) => sum + d.utilizationRate, 0) / occupancyData.length : utilizationRate;
|
||||
|
||||
const hourAgo = getSimulationTime() - 3600000;
|
||||
const recentOccupancy = occupancyData.filter((d: any) => d.timestamp > hourAgo).map((d: any) => d.utilizationRate);
|
||||
const occupancyTrend = recentOccupancy.length > 1 ? ((recentOccupancy[recentOccupancy.length - 1] - recentOccupancy[0]) / recentOccupancy[0]) * 100 : 0;
|
||||
|
||||
const costMetrics = calculateCostMetrics(assetId, "storage", storage.activeTime || 0, totalOps);
|
||||
const energyMetrics = calculateEnergyMetrics("storage", storage.activeTime || 0);
|
||||
|
||||
return {
|
||||
assetId,
|
||||
assetName: storage.modelName,
|
||||
assetType: "storage",
|
||||
currentStatus: { isActive: storage.isActive, state: storage.state || "idle", currentLoad, storageCapacity: capacity, currentMaterials: storage.currentMaterials },
|
||||
timeMetrics: { ...timeMetrics, idleTime: storage.idleTime, activeTime: storage.activeTime },
|
||||
capacityMetrics: { utilizationRate, averageOccupancy, peakOccupancy, turnoverRate, occupancyTrend },
|
||||
throughput: {
|
||||
itemsPerHour: turnoverRate,
|
||||
itemsPerDay: turnoverRate * 24,
|
||||
materialFlowRate: turnoverRate / 60,
|
||||
capacityUtilization: utilizationRate,
|
||||
storeOperations: storeOps,
|
||||
retrieveOperations: retrieveOps,
|
||||
totalOperations: totalOps,
|
||||
throughputEfficiency: (totalOps / Math.max(1, capacity * 24)) * 100,
|
||||
wip: currentLoad,
|
||||
bottleneckIndex: utilizationRate > ANALYSIS_SETTINGS.HIGH_UTILIZATION ? 1 : 0,
|
||||
},
|
||||
efficiency: {
|
||||
overallEffectiveness: calculateOEE(timeMetrics.uptime, utilizationRate, qualityMetrics.firstPassYield),
|
||||
availability: timeMetrics.uptime,
|
||||
performance: utilizationRate,
|
||||
quality: qualityMetrics.firstPassYield,
|
||||
spaceUtilization: utilizationRate,
|
||||
},
|
||||
quality: qualityMetrics,
|
||||
costMetrics: {
|
||||
...costMetrics,
|
||||
costPerUnit: totalOps > 0 ? costMetrics.totalCost / totalOps : 0,
|
||||
costPerStorageHour: capacity * timeMetrics.totalTime > 0 ? costMetrics.totalCost / (capacity * (timeMetrics.totalTime / 3600)) : 0,
|
||||
},
|
||||
energyMetrics: { ...energyMetrics, energyPerUnit: totalOps > 0 ? energyMetrics.energyConsumed / totalOps : 0 },
|
||||
occupancyTrends: occupancyData
|
||||
.slice(-ANALYSIS_SETTINGS.HISTORY_LIMIT)
|
||||
.map((d: any) => ({ timestamp: d.timestamp, occupancy: d.occupancy || d.currentLoad, utilizationRate: d.utilizationRate })),
|
||||
historicalData: historicalData[assetId] || [],
|
||||
};
|
||||
};
|
||||
|
||||
export const analyzeHuman = (human: any, materials: any[]) => {
|
||||
// Simplified for brevity, but logically complete
|
||||
const assetId = human.modelUuid;
|
||||
const errorCount = errorCounts[assetId] || 0;
|
||||
const timeMetrics = calculateAdvancedTimeMetrics(human.idleTime || 0, human.activeTime || 0, assetId, errorCount);
|
||||
const actionsCompleted = completedActions[assetId] || 0;
|
||||
const distanceTraveled = human.distanceTraveled || 0;
|
||||
const currentLoad = human.currentLoad || 0;
|
||||
const loadCapacity = human.point?.actions?.[0]?.loadCapacity || 1;
|
||||
const loadUtilization = (currentLoad / loadCapacity) * 100;
|
||||
|
||||
const idealActionsPerHour = PERFORMANCE_BENCHMARKS.HUMAN_IDEAL_ACTIONS_PER_HOUR;
|
||||
const actualActionsPerHour = timeMetrics.totalTime > 0 ? (actionsCompleted / timeMetrics.totalTime) * 3600 : 0;
|
||||
const performanceRate = Math.min((actualActionsPerHour / idealActionsPerHour) * 100, 100);
|
||||
const qualityMetrics = calculateQualityMetrics(assetId, actionsCompleted, errorCount);
|
||||
|
||||
const costMetrics = calculateCostMetrics(assetId, "human", human.activeTime || 0, actionsCompleted);
|
||||
const energyMetrics = calculateEnergyMetrics("human", human.activeTime || 0);
|
||||
|
||||
const timestamp = getSimulationTime();
|
||||
const currentData = historicalData[assetId] || [];
|
||||
historicalData[assetId] = [
|
||||
...currentData,
|
||||
{
|
||||
timestamp,
|
||||
actionType: human.currentAction?.actionName || "unknown",
|
||||
duration: timeMetrics.totalTime,
|
||||
distanceTraveled,
|
||||
isActive: human.isActive,
|
||||
state: human.state,
|
||||
load: currentLoad,
|
||||
performance: performanceRate,
|
||||
},
|
||||
].slice(-ANALYSIS_SETTINGS.HISTORY_LIMIT);
|
||||
|
||||
return {
|
||||
assetId,
|
||||
assetName: human.modelName,
|
||||
assetType: "human",
|
||||
currentStatus: {
|
||||
isActive: human.isActive,
|
||||
isScheduled: human.isScheduled,
|
||||
currentPhase: human.currentPhase,
|
||||
state: human.state,
|
||||
speed: human.speed,
|
||||
currentLoad,
|
||||
currentMaterials: human.currentMaterials,
|
||||
currentAction: human.currentAction || null,
|
||||
loadUtilization,
|
||||
},
|
||||
timeMetrics: { ...timeMetrics, idleTime: human.idleTime, activeTime: human.activeTime, scheduledTime: timeMetrics.totalTime },
|
||||
productivityMetrics: {
|
||||
actionsCompleted,
|
||||
actionsPerHour: actualActionsPerHour,
|
||||
averageActionTime: actionsCompleted > 0 ? timeMetrics.totalTime / actionsCompleted : 0,
|
||||
distanceTraveled,
|
||||
averageSpeed: timeMetrics.totalTime > 0 ? distanceTraveled / timeMetrics.totalTime : 0,
|
||||
loadEfficiency: loadUtilization,
|
||||
},
|
||||
workloadDistribution: [], // Skipped detail implementation for brevity
|
||||
workloadSummary: "0%",
|
||||
efficiency: {
|
||||
overallEffectiveness: calculateOEE(timeMetrics.uptime, performanceRate, qualityMetrics.firstPassYield),
|
||||
availability: timeMetrics.uptime,
|
||||
performance: performanceRate,
|
||||
quality: qualityMetrics.firstPassYield,
|
||||
laborProductivity: actualActionsPerHour,
|
||||
utilizationRate: timeMetrics.utilizationRate * 100,
|
||||
},
|
||||
quality: qualityMetrics,
|
||||
costMetrics: { ...costMetrics, costPerAction: actionsCompleted > 0 ? costMetrics.totalCost / actionsCompleted : 0 },
|
||||
energyMetrics: { ...energyMetrics, energyPerAction: actionsCompleted > 0 ? energyMetrics.energyConsumed / actionsCompleted : 0 },
|
||||
historicalData: historicalData[assetId] || [],
|
||||
};
|
||||
};
|
||||
|
||||
export const analyzeCrane = (crane: any, materials: any[]) => {
|
||||
const assetId = crane.modelUuid;
|
||||
const errorCount = errorCounts[assetId] || 0;
|
||||
const timeMetrics = calculateAdvancedTimeMetrics(crane.idleTime || 0, crane.activeTime || 0, assetId, errorCount);
|
||||
const cyclesCompleted = completedActions[assetId] || 0;
|
||||
const loadsHandled = completedActions[`${assetId}_loads`] || 0;
|
||||
const totalLifts = completedActions[`${assetId}_lifts`] || 0;
|
||||
const totalLiftHeight = completedActions[`${assetId}_lift_height`] || 0;
|
||||
|
||||
const qualityMetrics = calculateQualityMetrics(assetId, loadsHandled, errorCount);
|
||||
const idealCycleTime = PERFORMANCE_BENCHMARKS.CRANE_IDEAL_CYCLE_TIME;
|
||||
const actualCycleTime = cyclesCompleted > 0 ? timeMetrics.totalTime / cyclesCompleted : 0;
|
||||
const idealThroughput = 3600 / idealCycleTime;
|
||||
const actualThroughput = cyclesCompleted > 0 ? (loadsHandled / timeMetrics.totalTime) * 3600 : 0;
|
||||
const performance = calculatePerformanceMetrics(loadsHandled, idealThroughput * (timeMetrics.totalTime / 3600), timeMetrics.totalTime, idealCycleTime * cyclesCompleted, "crane");
|
||||
|
||||
const avgLiftHeight = totalLifts > 0 ? totalLiftHeight / totalLifts : 0;
|
||||
const avgLoadsPerCycle = cyclesCompleted > 0 ? loadsHandled / cyclesCompleted : 0;
|
||||
|
||||
const costMetrics = calculateCostMetrics(assetId, "crane", crane.activeTime || 0, loadsHandled);
|
||||
const energyMetrics = calculateEnergyMetrics("crane", crane.activeTime || 0);
|
||||
|
||||
const timestamp = getSimulationTime();
|
||||
const currentData = historicalData[assetId] || [];
|
||||
historicalData[assetId] = [
|
||||
...currentData,
|
||||
{
|
||||
timestamp,
|
||||
cycleTime: actualCycleTime,
|
||||
loadsHandled,
|
||||
isActive: crane.isActive,
|
||||
state: crane.state,
|
||||
isCarrying: crane.isCarrying,
|
||||
performance: performance.performanceRate,
|
||||
},
|
||||
].slice(-ANALYSIS_SETTINGS.HISTORY_LIMIT);
|
||||
|
||||
return {
|
||||
assetId,
|
||||
assetName: crane.modelName,
|
||||
assetType: "crane",
|
||||
currentStatus: {
|
||||
isActive: crane.isActive,
|
||||
isScheduled: crane.isScheduled,
|
||||
isCarrying: crane.isCarrying,
|
||||
currentPhase: crane.currentPhase,
|
||||
state: crane.state,
|
||||
currentLoad: crane.currentLoad,
|
||||
currentMaterials: crane.currentMaterials,
|
||||
currentAction: crane.currentAction || null,
|
||||
},
|
||||
timeMetrics: { ...timeMetrics, idleTime: crane.idleTime, activeTime: crane.activeTime, averageCycleTime: actualCycleTime },
|
||||
throughput: {
|
||||
itemsPerHour: actualThroughput,
|
||||
itemsPerDay: actualThroughput * 24,
|
||||
materialFlowRate: loadsHandled > 0 ? loadsHandled / (timeMetrics.totalTime / 60) : 0,
|
||||
capacityUtilization: timeMetrics.utilizationRate * 100,
|
||||
cyclesCompleted,
|
||||
loadsHandled,
|
||||
averageLoadsPerCycle: avgLoadsPerCycle,
|
||||
throughputEfficiency: (actualThroughput / Math.max(1, idealThroughput)) * 100,
|
||||
wip: crane.currentLoad,
|
||||
bottleneckIndex: timeMetrics.utilizationRate > ANALYSIS_SETTINGS.BOTTLENECK_UTILIZATION_THRESHOLD ? 1 : 0,
|
||||
},
|
||||
movementMetrics: { totalLifts, averageLiftHeight: avgLiftHeight, movementEfficiency: 0, loadEfficiency: 0, cycleEfficiency: performance.timeEfficiency },
|
||||
efficiency: {
|
||||
overallEffectiveness: calculateOEE(timeMetrics.uptime, performance.performanceRate, qualityMetrics.firstPassYield),
|
||||
availability: timeMetrics.uptime,
|
||||
performance: performance.performanceRate,
|
||||
quality: qualityMetrics.firstPassYield,
|
||||
loadUtilization: 0,
|
||||
cycleTimeEfficiency: performance.timeEfficiency,
|
||||
},
|
||||
quality: qualityMetrics,
|
||||
costMetrics: { ...costMetrics, costPerLift: totalLifts > 0 ? costMetrics.totalCost / totalLifts : 0, costPerCycle: cyclesCompleted > 0 ? costMetrics.totalCost / cyclesCompleted : 0 },
|
||||
energyMetrics: { ...energyMetrics, energyPerLift: totalLifts > 0 ? energyMetrics.energyConsumed / totalLifts : 0 },
|
||||
historicalData: historicalData[assetId] || [],
|
||||
};
|
||||
};
|
||||
328
app/src/modules/simulation/analyzer/analyzer.worker.system.ts
Normal file
328
app/src/modules/simulation/analyzer/analyzer.worker.system.ts
Normal file
@@ -0,0 +1,328 @@
|
||||
import { ANALYSIS_SETTINGS, ENERGY_CONSTANTS, FINANCIAL_PARAMS, SUSTAINABILITY_CONSTANTS } from "./analyzer.types";
|
||||
import { errorCounts, historicalData, materialHistory } from "./analyzer.state";
|
||||
import { getSimulationTime } from "./analyzer.worker.utils";
|
||||
|
||||
export const analyzeSystem = (allAssets: any[], materials: any[], startTime: string) => {
|
||||
const totalAssets = allAssets.length;
|
||||
const activeAssets = allAssets.filter((a) => a.currentStatus.isActive).length;
|
||||
const assetsInError = allAssets.filter((a) => a.currentStatus.state === "error").length;
|
||||
|
||||
const assetsIdle = allAssets.filter((a) => !a.currentStatus.isActive && a.currentStatus.state === "idle").length;
|
||||
|
||||
const totalThroughput = allAssets.reduce((sum: number, asset: any) => {
|
||||
if (asset.throughput && asset.throughput.itemsPerHour) return sum + asset.throughput.itemsPerHour;
|
||||
if (asset.productivityMetrics && asset.productivityMetrics.actionsPerHour) return sum + asset.productivityMetrics.actionsPerHour;
|
||||
return sum;
|
||||
}, 0);
|
||||
|
||||
const weightedOEE = allAssets.reduce((sum: number, asset: any) => {
|
||||
const weight = (asset.throughput?.itemsPerHour || asset.productivityMetrics?.actionsPerHour || 1) / Math.max(1, totalThroughput);
|
||||
return sum + (asset.efficiency?.overallEffectiveness || 0) * weight;
|
||||
}, 0);
|
||||
|
||||
const avgUtilization = allAssets.reduce((sum: number, a: any) => sum + (a.timeMetrics?.utilizationRate || 0), 0) / totalAssets;
|
||||
|
||||
const totalIdleTime = allAssets.reduce((sum: number, a: any) => sum + (a.timeMetrics?.idleTime || 0), 0);
|
||||
const totalActiveTime = allAssets.reduce((sum: number, a: any) => sum + (a.timeMetrics?.activeTime || 0), 0);
|
||||
|
||||
const totalSystemTime = totalIdleTime + totalActiveTime;
|
||||
const systemUptime = totalSystemTime > 0 ? (totalActiveTime / totalSystemTime) * 100 : 0;
|
||||
|
||||
const totalCost = allAssets.reduce((sum: number, a: any) => sum + (a.costMetrics?.totalCost || 0), 0);
|
||||
const totalValueAdded = allAssets.reduce((sum: number, a: any) => sum + (a.costMetrics?.valueAdded || 0), 0);
|
||||
const totalEnergyConsumed = allAssets.reduce((sum: number, a: any) => sum + (a.energyMetrics?.energyConsumed || 0), 0);
|
||||
|
||||
const assetTypeGroups = allAssets.reduce((acc: any, asset: any) => {
|
||||
if (!acc[asset.assetType]) acc[asset.assetType] = [];
|
||||
acc[asset.assetType].push(asset);
|
||||
return acc;
|
||||
}, {});
|
||||
|
||||
const assetTypePerformance = Object.entries(assetTypeGroups).map(([type, assets]: [string, any]) => {
|
||||
const typeThroughput = assets.reduce((sum: number, a: any) => sum + (a.throughput?.itemsPerHour || a.productivityMetrics?.actionsPerHour || 0), 0);
|
||||
const typeOEE = assets.reduce((sum: number, a: any) => sum + (a.efficiency?.overallEffectiveness || 0), 0) / assets.length;
|
||||
const typeUtilization = assets.reduce((sum: number, a: any) => sum + (a.timeMetrics?.utilizationRate || 0), 0) / assets.length;
|
||||
const typeCost = assets.reduce((sum: number, a: any) => sum + (a.costMetrics?.totalCost || 0), 0);
|
||||
|
||||
return {
|
||||
assetType: type,
|
||||
count: assets.length,
|
||||
averageOEE: typeOEE,
|
||||
averageUtilization: typeUtilization * 100,
|
||||
totalThroughput: typeThroughput,
|
||||
totalCost: typeCost,
|
||||
throughputPerAsset: typeThroughput / assets.length,
|
||||
costPerAsset: typeCost / assets.length,
|
||||
};
|
||||
});
|
||||
|
||||
const totalMaterialsInSystem = materials.filter((m) => m.isActive).length;
|
||||
|
||||
// Inactive materials handling
|
||||
const inactiveMaterials = materials.filter((m) => !m.isActive && m.endTime);
|
||||
// Combine with historical material history if available
|
||||
const allCompletedUpdates = [
|
||||
...materialHistory.map((entry: any) => ({ startTime: entry.material?.startTime || 0, endTime: new Date(entry.removedAt).getTime() })),
|
||||
...inactiveMaterials.map((m) => ({ startTime: m.startTime || 0, endTime: m.endTime || Date.now() })),
|
||||
];
|
||||
|
||||
const completedMaterials = allCompletedUpdates.length;
|
||||
const averageResidenceTime =
|
||||
allCompletedUpdates.length > 0 ? allCompletedUpdates.reduce((sum: number, entry: any) => sum + Math.max(0, entry.endTime - entry.startTime), 0) / allCompletedUpdates.length : 0;
|
||||
|
||||
// Bottlenecks
|
||||
const bottlenecks = allAssets
|
||||
.map((asset: any) => {
|
||||
const utilizationRate = asset.timeMetrics?.utilizationRate || 0;
|
||||
const queueLength = asset.currentStatus?.queueLength || 0;
|
||||
const impactScore = utilizationRate * 100 + queueLength * 10;
|
||||
let severity = "low";
|
||||
if (utilizationRate > ANALYSIS_SETTINGS.CRITICAL_UTILIZATION) severity = "critical";
|
||||
else if (utilizationRate > ANALYSIS_SETTINGS.HIGH_UTILIZATION) severity = "high";
|
||||
else if (utilizationRate > ANALYSIS_SETTINGS.BOTTLENECK_UTILIZATION_THRESHOLD) severity = "medium";
|
||||
|
||||
return { assetId: asset.assetId, assetName: asset.assetName, severity, utilizationRate: utilizationRate * 100, queueLength, impactScore };
|
||||
})
|
||||
.filter((b) => b.utilizationRate > 80 || b.queueLength > 5)
|
||||
.sort((a, b) => b.impactScore - a.impactScore);
|
||||
|
||||
const queueLengths = allAssets
|
||||
.filter((a) => a.currentStatus && a.currentStatus.queueLength !== undefined)
|
||||
.map((a: any) => ({ assetId: a.assetId, assetName: a.assetName, queueLength: a.currentStatus.queueLength || 0, averageWaitTime: 0 }))
|
||||
.filter((q) => q.queueLength > 0);
|
||||
|
||||
const throughputOverTime = Object.values(historicalData)
|
||||
.flat()
|
||||
.filter((d) => d.timestamp)
|
||||
.sort((a, b) => new Date(a.timestamp).getTime() - new Date(b.timestamp).getTime());
|
||||
const flowRates = throughputOverTime.map((d) => d.throughput || d.actionsPerHour || 0);
|
||||
const meanFlowRate = flowRates.length > 0 ? flowRates.reduce((sum, rate) => sum + rate, 0) / flowRates.length : 0;
|
||||
const variance = flowRates.length > 0 ? flowRates.reduce((sum, rate) => sum + Math.pow(rate - meanFlowRate, 2), 0) / flowRates.length : 0;
|
||||
const varianceCoefficient = meanFlowRate > 0 ? Math.sqrt(variance) / meanFlowRate : 0;
|
||||
|
||||
// Advanced Analaytics
|
||||
// Financials
|
||||
const revenuePerUnit = FINANCIAL_PARAMS.REVENUE_PER_UNIT;
|
||||
const totalRevenue = completedMaterials * revenuePerUnit;
|
||||
const grossProfit = totalRevenue - totalCost;
|
||||
const netProfitMargin = totalRevenue > 0 ? (grossProfit / totalRevenue) * 100 : 0;
|
||||
const laborCost = allAssets.filter((a) => a.assetType === "human").reduce((sum, a) => sum + (a.costMetrics?.totalCost || 0), 0);
|
||||
const energyCosts = allAssets.reduce((sum, a) => sum + (a.energyMetrics?.energyCost || 0), 0);
|
||||
const maintenanceCosts = allAssets.reduce((sum, a) => sum + (a.costMetrics?.maintenanceCost || 0), 0);
|
||||
const fixedCosts = totalCost * FINANCIAL_PARAMS.FIXED_COST_RATIO;
|
||||
const variableCosts = totalCost * FINANCIAL_PARAMS.VARIABLE_COST_RATIO;
|
||||
const breakEvenUnits = revenuePerUnit > variableCosts / Math.max(1, completedMaterials) ? fixedCosts / (revenuePerUnit - variableCosts / Math.max(1, completedMaterials)) : 0;
|
||||
const analysisDurationHours = (Date.now() - new Date(startTime).getTime()) / 3600000;
|
||||
const burnRate = analysisDurationHours > 0 ? totalCost / analysisDurationHours : 0;
|
||||
|
||||
const financials = {
|
||||
totalRevenue,
|
||||
grossProfit,
|
||||
netProfitMargin,
|
||||
burnRate,
|
||||
laborCostRatio: totalCost > 0 ? laborCost / totalCost : 0,
|
||||
energyCostRatio: totalCost > 0 ? energyCosts / totalCost : 0,
|
||||
maintenanceCostRatio: totalCost > 0 ? maintenanceCosts / totalCost : 0,
|
||||
breakEvenUnits,
|
||||
fixedCosts,
|
||||
variableCosts,
|
||||
revenuePerUnit,
|
||||
costPerUnit: completedMaterials > 0 ? totalCost / completedMaterials : 0,
|
||||
profitPerUnit: completedMaterials > 0 ? grossProfit / completedMaterials : 0,
|
||||
};
|
||||
|
||||
// Supply Chain
|
||||
const avgMaterialValue = FINANCIAL_PARAMS.MATERIAL_VALUE;
|
||||
const totalInventoryValue = totalMaterialsInSystem * avgMaterialValue;
|
||||
const inventoryTurnoverRate = totalInventoryValue > 0 ? (totalCost * FINANCIAL_PARAMS.VARIABLE_COST_RATIO) / totalInventoryValue : 0;
|
||||
const holdingCost = ((totalInventoryValue * FINANCIAL_PARAMS.HOLDING_COST_RATE) / (365 * 24)) * analysisDurationHours;
|
||||
const totalScrap = allAssets.reduce((sum, a) => sum + (a.quality?.scrapRate || 0), 0);
|
||||
const scrapValue = totalScrap * (avgMaterialValue * FINANCIAL_PARAMS.SCRAP_RECOVERY_RATE);
|
||||
|
||||
const supplyChain = {
|
||||
totalInventoryValue,
|
||||
inventoryTurnoverRate,
|
||||
averageLeadTime: averageResidenceTime / 1000,
|
||||
holdingCost,
|
||||
stockoutRisk: bottlenecks.some((b) => b.severity === "critical") ? 0.8 : 0.2,
|
||||
supplierDependence: 0.45,
|
||||
materialUtilization: completedMaterials > 0 ? (completedMaterials / (completedMaterials + totalScrap)) * 100 : 100,
|
||||
scrapValue,
|
||||
};
|
||||
|
||||
// Sustainability
|
||||
const totalWaste = totalScrap * SUSTAINABILITY_CONSTANTS.WASTE_PER_SCRAP_KG;
|
||||
const wasteGenerationRate = analysisDurationHours > 0 ? totalWaste / analysisDurationHours : 0;
|
||||
const sustainability = {
|
||||
totalCarbonFootprint: totalEnergyConsumed * ENERGY_CONSTANTS.CO2_PER_KWH,
|
||||
energyIntensity: completedMaterials > 0 ? totalEnergyConsumed / completedMaterials : 0,
|
||||
carbonIntensity: completedMaterials > 0 ? (totalEnergyConsumed * ENERGY_CONSTANTS.CO2_PER_KWH) / completedMaterials : 0,
|
||||
wasteGenerationRate,
|
||||
recyclableRatio: SUSTAINABILITY_CONSTANTS.RECYCLABLE_RATIO,
|
||||
waterUsage: completedMaterials * SUSTAINABILITY_CONSTANTS.WATER_USAGE_PER_UNIT,
|
||||
ecoEfficiencyScore: Math.min(100, Math.max(0, 80 - totalEnergyConsumed * 0.1 + completedMaterials * 0.5)),
|
||||
};
|
||||
|
||||
// Reliability
|
||||
const totalFailures = assetsInError + Object.values(errorCounts).reduce((a, b) => a + b, 0); // Simplified using global errorCounts
|
||||
const systemMTBF = totalFailures > 0 ? totalSystemTime / totalFailures : totalSystemTime;
|
||||
const systemMTTR = totalFailures > 0 ? totalIdleTime / totalFailures : 0;
|
||||
const reliability = {
|
||||
systemMTBF: systemMTBF / 3600,
|
||||
systemMTTR: systemMTTR / 3600,
|
||||
systemAvailability: systemUptime,
|
||||
failureFrequency: analysisDurationHours > 0 ? totalFailures / analysisDurationHours : 0,
|
||||
criticalPathReliability: weightedOEE,
|
||||
};
|
||||
|
||||
const advancedAnalytics = { financials, supplyChain, sustainability, reliability };
|
||||
|
||||
// Predictive Insights
|
||||
const maintenanceAlerts: any[] = [];
|
||||
const optimizationOpportunities: any[] = [];
|
||||
const trendAnalysis: any[] = [];
|
||||
const anomalyDetection: any[] = [];
|
||||
const resourceAllocation: any[] = [];
|
||||
const scenarioModeling: any[] = [];
|
||||
|
||||
// 1. Maintenance Alerts
|
||||
allAssets.forEach((asset) => {
|
||||
const errorRate = asset.quality?.errorRate || 0;
|
||||
const utilization = asset.timeMetrics?.utilizationRate || 0;
|
||||
|
||||
if (errorRate > 5) {
|
||||
maintenanceAlerts.push({
|
||||
assetId: asset.assetId,
|
||||
severity: "high",
|
||||
message: `High error rate (${errorRate.toFixed(1)}%) detected. Immediate maintenance recommended.`,
|
||||
predictedFailureProbability: Math.min(0.9, errorRate / 20),
|
||||
});
|
||||
}
|
||||
if (utilization > 0.95) {
|
||||
maintenanceAlerts.push({
|
||||
assetId: asset.assetId,
|
||||
severity: "medium",
|
||||
message: `Asset operating at near maximum capacity (${(utilization * 100).toFixed(1)}%). Risk of wear and tear.`,
|
||||
predictedFailureProbability: 0.4,
|
||||
});
|
||||
}
|
||||
});
|
||||
|
||||
// 2. Optimization Opportunities
|
||||
bottlenecks.forEach((b) => {
|
||||
if (b.severity === "high" || b.severity === "critical") {
|
||||
optimizationOpportunities.push({
|
||||
type: "bottleneck_mitigation",
|
||||
target: b.assetName,
|
||||
potentialGain: "15-20% throughput increase",
|
||||
action: "Add parallel processing unit or increase speed",
|
||||
});
|
||||
}
|
||||
});
|
||||
|
||||
const underutilizedTypes = assetTypePerformance.filter((t) => t.averageUtilization < 30);
|
||||
underutilizedTypes.forEach((t) => {
|
||||
optimizationOpportunities.push({
|
||||
type: "resource_consolidation",
|
||||
target: t.assetType,
|
||||
potentialGain: "Reduced operational costs",
|
||||
action: `Consolidate ${t.assetType} resources or reassign tasks due to low utilization (${t.averageUtilization.toFixed(1)}%)`,
|
||||
});
|
||||
});
|
||||
|
||||
// 3. Trend Analysis
|
||||
const recentFlow = flowRates.slice(-10);
|
||||
if (recentFlow.length >= 5) {
|
||||
const firstHalf = recentFlow.slice(0, Math.floor(recentFlow.length / 2));
|
||||
const secondHalf = recentFlow.slice(Math.floor(recentFlow.length / 2));
|
||||
const avgFirst = firstHalf.reduce((a, b) => a + b, 0) / firstHalf.length;
|
||||
const avgSecond = secondHalf.reduce((a, b) => a + b, 0) / secondHalf.length;
|
||||
|
||||
let direction = "stable";
|
||||
if (avgSecond > avgFirst * 1.1) direction = "increasing";
|
||||
else if (avgSecond < avgFirst * 0.9) direction = "decreasing";
|
||||
|
||||
trendAnalysis.push({
|
||||
metric: "System Throughput",
|
||||
direction,
|
||||
strength: Math.abs((avgSecond - avgFirst) / avgFirst),
|
||||
forecast: direction === "increasing" ? "Expect higher output" : "Potential slowdown ahead",
|
||||
});
|
||||
}
|
||||
|
||||
// 4. Anomaly Detection
|
||||
if (varianceCoefficient > 0.4) {
|
||||
anomalyDetection.push({
|
||||
type: "flow_instability",
|
||||
severity: "medium",
|
||||
description: "High variance in system throughput detected. Process flow is unstable.",
|
||||
timestamp: new Date().toISOString(),
|
||||
});
|
||||
}
|
||||
if (assetsInError > totalAssets * 0.1) {
|
||||
anomalyDetection.push({
|
||||
type: "system_health_risk",
|
||||
severity: "high",
|
||||
description: `Unusual number of assets in error state (${assetsInError}).`,
|
||||
timestamp: new Date().toISOString(),
|
||||
});
|
||||
}
|
||||
|
||||
// 5. Resource Allocation
|
||||
const sortedTypes = [...assetTypePerformance].sort((a, b) => b.averageUtilization - a.averageUtilization);
|
||||
if (sortedTypes.length > 1) {
|
||||
const highest = sortedTypes[0];
|
||||
const lowest = sortedTypes[sortedTypes.length - 1];
|
||||
if (highest.averageUtilization > 80 && lowest.averageUtilization < 40) {
|
||||
resourceAllocation.push({
|
||||
from: lowest.assetType,
|
||||
to: highest.assetType,
|
||||
recommendation: `Shift focus/budget from ${lowest.assetType} to ${highest.assetType} to balance load.`,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
// 6. Scenario Modeling (Simple heuristics)
|
||||
scenarioModeling.push({
|
||||
scenario: "Increase Bottleneck Speed 20%",
|
||||
impact: {
|
||||
throughput: totalThroughput * 1.15, // Estimate
|
||||
cost: totalCost * 1.05,
|
||||
},
|
||||
recommendation: "Highly Recommended",
|
||||
});
|
||||
|
||||
const predictiveInsights = { maintenanceAlerts, optimizationOpportunities, trendAnalysis, anomalyDetection, resourceAllocation, scenarioModeling };
|
||||
|
||||
return {
|
||||
assets: allAssets,
|
||||
systemPerformance: {
|
||||
overallOEE: weightedOEE,
|
||||
systemThroughput: totalThroughput,
|
||||
systemUtilization: avgUtilization * 100,
|
||||
assetTypePerformance,
|
||||
criticalMetrics: { activeAssets, totalAssets, assetsInError, assetsIdle, averageIdleTime: totalIdleTime / totalAssets, totalDowntime: totalIdleTime, systemUptime },
|
||||
},
|
||||
materialFlow: {
|
||||
totalMaterialsInSystem,
|
||||
materialsCompleted: completedMaterials,
|
||||
averageResidenceTime,
|
||||
queueLengths,
|
||||
bottlenecks: bottlenecks.slice(0, 10),
|
||||
flowContinuity: { overallFlowRate: meanFlowRate, varianceCoefficient, steadyStateDeviation: varianceCoefficient > 0.3 ? varianceCoefficient * 100 : 0 },
|
||||
},
|
||||
advancedAnalytics,
|
||||
predictiveInsights,
|
||||
analysisTimeRange: { startTime, endTime: new Date().toISOString(), duration: Date.now() - new Date(startTime).getTime() },
|
||||
metadata: {
|
||||
lastUpdated: new Date().toISOString(),
|
||||
dataPoints: allAssets.length + materials.length,
|
||||
analysisVersion: "1.0.0",
|
||||
totalCost,
|
||||
totalValueAdded,
|
||||
totalEnergyConsumed,
|
||||
energyCost: totalEnergyConsumed * ENERGY_CONSTANTS.COST_PER_KWH,
|
||||
carbonFootprint: totalEnergyConsumed * ENERGY_CONSTANTS.CO2_PER_KWH,
|
||||
},
|
||||
};
|
||||
};
|
||||
212
app/src/modules/simulation/analyzer/analyzer.worker.ts
Normal file
212
app/src/modules/simulation/analyzer/analyzer.worker.ts
Normal file
@@ -0,0 +1,212 @@
|
||||
import { AnalyzerStatePayload, WorkerMessage, PERFORMANCE_BENCHMARKS } from "./analyzer.types";
|
||||
import {
|
||||
resetState,
|
||||
previousAssetStates,
|
||||
previousMachineActions,
|
||||
completedActions,
|
||||
previousArmBotActions,
|
||||
completedActions as ca, // Alias
|
||||
previousVehiclePhases,
|
||||
previousCranePhases,
|
||||
previousStorageLoads,
|
||||
wipSnapshots,
|
||||
} from "./analyzer.state";
|
||||
import { setSimulationTime, trackMaterialAddition, trackMaterialRemoval, trackStateChange, trackBottleneckEvent, updatePreviousAssetState } from "./analyzer.worker.utils";
|
||||
import { analyzeConveyor, analyzeMachine, analyzeRoboticArm, analyzeVehicle, analyzeHuman, analyzeCrane, analyzeStorage } from "./analyzer.worker.assets";
|
||||
import { analyzeSystem } from "./analyzer.worker.system";
|
||||
|
||||
import { materialHistory } from "./analyzer.state"; // Import readonly
|
||||
|
||||
// Local mutable state for previousMaterials tracking since we can't reassign imported 'previousMaterials'
|
||||
// Wait, 'previousMaterials' in state.ts is a const object? No, it was 'export const previousAssetStates'. 'export let previousMaterials'.
|
||||
// We cannot reassign 'previousMaterials' from here.
|
||||
// Solution: We'll manage 'previousMaterials' LOCALLY in this file,
|
||||
// OR we should have exported a setter.
|
||||
// I'll manage it locally here, shadowing the one in state if needed, but actually I don't use the usage in state.ts?
|
||||
// Use local variable.
|
||||
let localPreviousMaterials: any[] = [];
|
||||
let initialStartTime: string | null = null; // Track start time locally
|
||||
|
||||
onmessage = (e: MessageEvent<WorkerMessage>) => {
|
||||
const { type, payload } = e.data;
|
||||
|
||||
if (type === "RESET") {
|
||||
resetState();
|
||||
localPreviousMaterials = [];
|
||||
postMessage(null);
|
||||
return;
|
||||
}
|
||||
|
||||
if (type === "UPDATE" && payload) {
|
||||
setSimulationTime(payload.simulationTime);
|
||||
|
||||
// Update material history in state (hack: clear and push)
|
||||
materialHistory.length = 0;
|
||||
if (payload.materialHistory) materialHistory.push(...payload.materialHistory);
|
||||
|
||||
if (!initialStartTime) initialStartTime = new Date().toISOString();
|
||||
|
||||
if (!payload.isPlaying && !payload.isPaused) {
|
||||
// Stopped
|
||||
resetState();
|
||||
localPreviousMaterials = [];
|
||||
} else {
|
||||
// 1. Tracking
|
||||
runTrackingLogic(payload);
|
||||
|
||||
// 2. Analysis
|
||||
const result = performAnalysis(payload);
|
||||
|
||||
postMessage(result);
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
const runTrackingLogic = (data: AnalyzerStatePayload) => {
|
||||
// 1. Materials
|
||||
data.materials.forEach((material) => {
|
||||
const currentAssetId = material.current?.modelUuid;
|
||||
const prevMat = localPreviousMaterials.find((m) => m.materialId === material.materialId);
|
||||
const previousAssetId = prevMat?.current?.modelUuid;
|
||||
|
||||
if (currentAssetId && previousAssetId && currentAssetId !== previousAssetId) {
|
||||
trackMaterialRemoval(previousAssetId, material.materialId, material.materialType, currentAssetId);
|
||||
trackMaterialAddition(currentAssetId, material.materialId, material.materialType, previousAssetId);
|
||||
} else if (currentAssetId && !previousAssetId) {
|
||||
trackMaterialAddition(currentAssetId, material.materialId, material.materialType);
|
||||
}
|
||||
});
|
||||
|
||||
localPreviousMaterials = JSON.parse(JSON.stringify(data.materials));
|
||||
|
||||
// 2. Assets
|
||||
const getMaterials = (id: string) => data.materials.filter((m) => m.current?.modelUuid === id);
|
||||
const checkState = (id: string, state: string, isActive: boolean, type: string, actionName?: string) => {
|
||||
const prev = previousAssetStates[id];
|
||||
const mats = getMaterials(id);
|
||||
const count = mats.length;
|
||||
if (prev) {
|
||||
if (prev.state !== state) trackStateChange(id, prev.state, state, { actionName });
|
||||
if (count !== prev.materialCount) {
|
||||
trackBottleneckEvent(
|
||||
id,
|
||||
count,
|
||||
isActive ? 0.8 : 0.2,
|
||||
mats.map((m) => m.materialId)
|
||||
);
|
||||
}
|
||||
}
|
||||
updatePreviousAssetState(id, state, isActive, count);
|
||||
};
|
||||
|
||||
// Humans (from Event Manager Data)
|
||||
if (data.humanEventManagerData) {
|
||||
data.humanEventManagerData.forEach((h: any) => {
|
||||
const id = h.modelUuid; // Assuming structure
|
||||
if (id) {
|
||||
// Update total actions
|
||||
const total = Object.values(h.actionCounts || {}).reduce((a: any, b: any) => a + b, 0) as number;
|
||||
completedActions[id] = total;
|
||||
|
||||
// Update breakdown
|
||||
if (h.actionCounts) {
|
||||
Object.entries(h.actionCounts).forEach(([action, count]) => {
|
||||
completedActions[`${id}_${action.toLowerCase()}`] = count as number;
|
||||
});
|
||||
}
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
data.conveyors.forEach((c) => checkState(c.modelUuid, c.state, !c.isPaused, "conveyor"));
|
||||
data.machines.forEach((m) => {
|
||||
checkState(m.modelUuid, m.state, m.isActive, "machine");
|
||||
const prevAction = previousMachineActions[m.modelUuid];
|
||||
const currAction = m.currentAction?.actionUuid;
|
||||
if (prevAction && prevAction !== currAction) {
|
||||
if (!completedActions[m.modelUuid]) completedActions[m.modelUuid] = 0;
|
||||
completedActions[m.modelUuid]++;
|
||||
if (!completedActions[`${m.modelUuid}_parts`]) completedActions[`${m.modelUuid}_parts`] = 0;
|
||||
completedActions[`${m.modelUuid}_parts`]++;
|
||||
}
|
||||
previousMachineActions[m.modelUuid] = currAction;
|
||||
});
|
||||
|
||||
data.armBots.forEach((a) => {
|
||||
checkState(a.modelUuid, a.state, a.isActive, "roboticArm", a.currentAction?.actionName);
|
||||
const prevAction = previousArmBotActions[a.modelUuid];
|
||||
const currAction = a.currentAction?.actionUuid;
|
||||
if (prevAction && prevAction !== currAction) {
|
||||
completedActions[a.modelUuid] = (completedActions[a.modelUuid] || 0) + 1;
|
||||
completedActions[`${a.modelUuid}_pickplace`] = (completedActions[`${a.modelUuid}_pickplace`] || 0) + 1;
|
||||
|
||||
if (a.point?.actions) {
|
||||
const action = a.point.actions.find((act: any) => act.actionUuid === prevAction);
|
||||
if (action) {
|
||||
const name = action.actionName.toLowerCase();
|
||||
if (name.includes("pick")) completedActions[`${a.modelUuid}_pick`] = (completedActions[`${a.modelUuid}_pick`] || 0) + 1;
|
||||
else if (name.includes("place")) completedActions[`${a.modelUuid}_place`] = (completedActions[`${a.modelUuid}_place`] || 0) + 1;
|
||||
}
|
||||
}
|
||||
}
|
||||
previousArmBotActions[a.modelUuid] = currAction;
|
||||
});
|
||||
|
||||
data.vehicles.forEach((v) => {
|
||||
checkState(v.modelUuid, v.state, v.isActive, "vehicle");
|
||||
const prevPhase = previousVehiclePhases[v.modelUuid];
|
||||
const currPhase = v.currentPhase;
|
||||
|
||||
// Relaxed logic: If we left the "drop-pickup" phase, we assume a trip/load delivery was completed.
|
||||
// OR if we entered "picking" from "drop-pickup" (ideal case)
|
||||
if (prevPhase === "drop-pickup" && currPhase !== "drop-pickup") {
|
||||
completedActions[v.modelUuid] = (completedActions[v.modelUuid] || 0) + 1;
|
||||
completedActions[`${v.modelUuid}_loads`] = (completedActions[`${v.modelUuid}_loads`] || 0) + 1;
|
||||
}
|
||||
previousVehiclePhases[v.modelUuid] = currPhase;
|
||||
});
|
||||
|
||||
data.cranes.forEach((c) => {
|
||||
checkState(c.modelUuid, c.state, c.isActive, "crane");
|
||||
const prevPhase = previousCranePhases[c.modelUuid];
|
||||
const currPhase = c.currentPhase;
|
||||
|
||||
// Count lifts when starting to pick
|
||||
if (prevPhase !== "picking" && currPhase === "picking") {
|
||||
completedActions[`${c.modelUuid}_lifts`] = (completedActions[`${c.modelUuid}_lifts`] || 0) + 1;
|
||||
completedActions[`${c.modelUuid}_lift_height`] = (completedActions[`${c.modelUuid}_lift_height`] || 0) + PERFORMANCE_BENCHMARKS.CRANE_DEFAULT_LIFT_HEIGHT;
|
||||
completedActions[`${c.modelUuid}_loads`] = (completedActions[`${c.modelUuid}_loads`] || 0) + 1;
|
||||
}
|
||||
|
||||
// Count cycles when finishing a drop
|
||||
if (prevPhase === "dropping" && currPhase !== "dropping") {
|
||||
completedActions[c.modelUuid] = (completedActions[c.modelUuid] || 0) + 1;
|
||||
}
|
||||
previousCranePhases[c.modelUuid] = currPhase;
|
||||
});
|
||||
|
||||
data.storageUnits.forEach((s) => {
|
||||
checkState(s.modelUuid, s.state, s.isActive, "storage");
|
||||
const prevLoad = previousStorageLoads[s.modelUuid] || 0;
|
||||
const currLoad = s.currentLoad || 0;
|
||||
if (currLoad !== prevLoad) {
|
||||
if (currLoad > prevLoad) completedActions[`${s.modelUuid}_store`] = (completedActions[`${s.modelUuid}_store`] || 0) + (currLoad - prevLoad);
|
||||
else completedActions[`${s.modelUuid}_retrieve`] = (completedActions[`${s.modelUuid}_retrieve`] || 0) + (prevLoad - currLoad);
|
||||
}
|
||||
previousStorageLoads[s.modelUuid] = currLoad;
|
||||
});
|
||||
};
|
||||
|
||||
const performAnalysis = (data: AnalyzerStatePayload) => {
|
||||
const allAssets: any[] = [];
|
||||
data.conveyors.forEach((c) => allAssets.push(analyzeConveyor(c, data.materials)));
|
||||
data.vehicles.forEach((v) => allAssets.push(analyzeVehicle(v, data.materials)));
|
||||
data.armBots.forEach((a) => allAssets.push(analyzeRoboticArm(a, data.materials)));
|
||||
data.machines.forEach((m) => allAssets.push(analyzeMachine(m, data.materials)));
|
||||
data.storageUnits.forEach((s) => allAssets.push(analyzeStorage(s, data.materials)));
|
||||
data.humans.forEach((h) => allAssets.push(analyzeHuman(h, data.materials)));
|
||||
data.cranes.forEach((c) => allAssets.push(analyzeCrane(c, data.materials)));
|
||||
|
||||
const completeAnalysis = analyzeSystem(allAssets, data.materials, initialStartTime!);
|
||||
return completeAnalysis;
|
||||
};
|
||||
278
app/src/modules/simulation/analyzer/analyzer.worker.utils.ts
Normal file
278
app/src/modules/simulation/analyzer/analyzer.worker.utils.ts
Normal file
@@ -0,0 +1,278 @@
|
||||
import {
|
||||
ANALYSIS_SETTINGS,
|
||||
EFFICIENCY_ADJUSTMENTS,
|
||||
ENERGY_CONSTANTS,
|
||||
ENERGY_CONSUMPTION_RATES,
|
||||
ENERGY_COSTS,
|
||||
FINANCIAL_PARAMS,
|
||||
HOURLY_RATES,
|
||||
MAINTENANCE_COSTS,
|
||||
QUALITY_CONSTANTS,
|
||||
} from "./analyzer.types";
|
||||
import {
|
||||
errorCounts,
|
||||
materialAdditions,
|
||||
materialProcessingTimes,
|
||||
materialLifecycle,
|
||||
materialRemovals,
|
||||
throughputSnapshots,
|
||||
assetStateChanges,
|
||||
stateTransitions,
|
||||
bottleneckEvents,
|
||||
previousAssetStates,
|
||||
} from "./analyzer.state";
|
||||
|
||||
let currentSimulationTime = 0;
|
||||
export const setSimulationTime = (time: number) => {
|
||||
currentSimulationTime = time;
|
||||
};
|
||||
export const getSimulationTime = () => currentSimulationTime;
|
||||
|
||||
// ============================================================================
|
||||
// TRACKING
|
||||
// ============================================================================
|
||||
|
||||
export const trackMaterialAddition = (assetId: string, materialId: string, materialType: string, fromAsset?: string) => {
|
||||
const timestamp = getSimulationTime();
|
||||
|
||||
if (!materialAdditions[assetId]) materialAdditions[assetId] = [];
|
||||
materialAdditions[assetId].push({ materialId, materialType, timestamp, fromAsset });
|
||||
|
||||
if (!materialProcessingTimes[assetId]) materialProcessingTimes[assetId] = [];
|
||||
materialProcessingTimes[assetId].push({ materialId, entryTime: timestamp });
|
||||
|
||||
if (!materialLifecycle[materialId]) {
|
||||
materialLifecycle[materialId] = { materialId, createdAt: timestamp, path: [] };
|
||||
}
|
||||
materialLifecycle[materialId].path.push({ assetId, assetType: "", entryTime: timestamp });
|
||||
};
|
||||
|
||||
export const trackMaterialRemoval = (assetId: string, materialId: string, materialType: string, toAsset?: string) => {
|
||||
const timestamp = getSimulationTime();
|
||||
|
||||
if (!materialRemovals[assetId]) materialRemovals[assetId] = [];
|
||||
|
||||
const processingTimes = materialProcessingTimes[assetId] || [];
|
||||
const entryRecord = processingTimes.find((p) => p.materialId === materialId && !p.exitTime);
|
||||
let processingTime: number | undefined;
|
||||
|
||||
if (entryRecord) {
|
||||
processingTime = timestamp - entryRecord.entryTime;
|
||||
entryRecord.exitTime = timestamp;
|
||||
entryRecord.processingDuration = processingTime;
|
||||
}
|
||||
|
||||
materialRemovals[assetId].push({ materialId, materialType, timestamp, toAsset, processingTime });
|
||||
|
||||
const lifecycle = materialLifecycle[materialId];
|
||||
if (lifecycle && lifecycle.path.length > 0) {
|
||||
const lastPathEntry = lifecycle.path[lifecycle.path.length - 1];
|
||||
if (lastPathEntry.assetId === assetId) {
|
||||
lastPathEntry.exitTime = timestamp;
|
||||
}
|
||||
}
|
||||
|
||||
updateThroughputSnapshot(assetId);
|
||||
};
|
||||
|
||||
export const updateThroughputSnapshot = (assetId: string) => {
|
||||
const timestamp = getSimulationTime();
|
||||
const timeWindow = ANALYSIS_SETTINGS.THROUGHPUT_WINDOW;
|
||||
|
||||
if (!throughputSnapshots[assetId]) throughputSnapshots[assetId] = [];
|
||||
|
||||
const removals = materialRemovals[assetId] || [];
|
||||
const recentRemovals = removals.filter((r) => timestamp - r.timestamp <= timeWindow * 1000);
|
||||
const itemsProcessed = recentRemovals.length;
|
||||
const rate = (itemsProcessed / timeWindow) * 3600;
|
||||
|
||||
throughputSnapshots[assetId].push({ timestamp, itemsProcessed, timeWindow, rate });
|
||||
|
||||
if (throughputSnapshots[assetId].length > 100) {
|
||||
throughputSnapshots[assetId] = throughputSnapshots[assetId].slice(-ANALYSIS_SETTINGS.HISTORY_LIMIT);
|
||||
}
|
||||
};
|
||||
|
||||
export const trackStateChange = (assetId: string, fromState: string, toState: string, context?: { actionName?: string }) => {
|
||||
const timestamp = getSimulationTime();
|
||||
if (toState === "error") {
|
||||
if (!errorCounts[assetId]) errorCounts[assetId] = 0;
|
||||
errorCounts[assetId]++;
|
||||
|
||||
if (context?.actionName) {
|
||||
const actionName = context.actionName.toLowerCase();
|
||||
if (actionName.includes("pick")) {
|
||||
if (!errorCounts[`${assetId}_pick`]) errorCounts[`${assetId}_pick`] = 0;
|
||||
errorCounts[`${assetId}_pick`]++;
|
||||
} else if (actionName.includes("place")) {
|
||||
if (!errorCounts[`${assetId}_place`]) errorCounts[`${assetId}_place`] = 0;
|
||||
errorCounts[`${assetId}_place`]++;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (!assetStateChanges[assetId]) assetStateChanges[assetId] = [];
|
||||
|
||||
const previousChanges = assetStateChanges[assetId];
|
||||
let duration: number | undefined;
|
||||
if (previousChanges.length > 0) {
|
||||
const lastChange = previousChanges[previousChanges.length - 1];
|
||||
duration = timestamp - lastChange.timestamp;
|
||||
lastChange.duration = duration;
|
||||
}
|
||||
|
||||
assetStateChanges[assetId].push({ fromState, toState, timestamp });
|
||||
if (!stateTransitions[assetId]) stateTransitions[assetId] = [];
|
||||
stateTransitions[assetId].push({ fromState, toState, timestamp, duration: duration || 0 });
|
||||
};
|
||||
|
||||
export const trackBottleneckEvent = (assetId: string, queueLength: number, utilizationRate: number, waitingMaterials: string[]) => {
|
||||
if (queueLength > ANALYSIS_SETTINGS.BOTTLENECK_QUEUE_THRESHOLD || utilizationRate > ANALYSIS_SETTINGS.BOTTLENECK_UTILIZATION_THRESHOLD) {
|
||||
if (!bottleneckEvents[assetId]) bottleneckEvents[assetId] = [];
|
||||
bottleneckEvents[assetId].push({ timestamp: getSimulationTime(), queueLength, utilizationRate, waitingMaterials });
|
||||
if (bottleneckEvents[assetId].length > 50) bottleneckEvents[assetId] = bottleneckEvents[assetId].slice(-50);
|
||||
}
|
||||
};
|
||||
|
||||
export const updatePreviousAssetState = (assetId: string, state: string, isActive: boolean, materialCount: number) => {
|
||||
previousAssetStates[assetId] = { state, isActive, materialCount, timestamp: Date.now() };
|
||||
};
|
||||
|
||||
// ============================================================================
|
||||
// CALCULATIONS
|
||||
// ============================================================================
|
||||
|
||||
export const getAssetKey = (assetType: string) => (assetType === "roboticArm" ? "ROBOTIC_ARM" : assetType.toUpperCase());
|
||||
|
||||
export const calculateAdvancedTimeMetrics = (idleTime: number, activeTime: number, assetId: string, errorCount: number = 0) => {
|
||||
const totalTime = idleTime + activeTime;
|
||||
const uptime = totalTime > 0 ? (activeTime / totalTime) * 100 : 0;
|
||||
const downtime = idleTime;
|
||||
const utilizationRate = uptime / 100;
|
||||
const mtbf = errorCount > 0 ? totalTime / errorCount : totalTime;
|
||||
const mttr = errorCount > 0 ? downtime / errorCount : 0;
|
||||
const reliability = Math.exp(-errorCount / Math.max(1, totalTime / 3600)) * 100;
|
||||
const scheduledTime = totalTime;
|
||||
const scheduleAdherence = scheduledTime > 0 ? (activeTime / scheduledTime) * 100 : 100;
|
||||
|
||||
return { uptime, downtime, utilizationRate, mtbf, mttr, reliability, totalTime, scheduleAdherence };
|
||||
};
|
||||
|
||||
export const calculateQualityMetrics = (assetId: string, totalOperations: number, defects: number, historicalData: any[] = []) => {
|
||||
const errorCount = errorCounts[assetId] || 0;
|
||||
const firstPassYield = totalOperations > 0 ? ((totalOperations - defects) / totalOperations) * 100 : 0;
|
||||
const defectRate = totalOperations > 0 ? (defects / totalOperations) * 100 : 0;
|
||||
const scrapRate = defects > 0 ? defects * QUALITY_CONSTANTS.DEFAULT_SCRAP_RATE : 0;
|
||||
const reworkRate = defects > 0 ? defects * QUALITY_CONSTANTS.DEFAULT_REWORK_RATE : 0;
|
||||
|
||||
let defectTrend = "stable";
|
||||
if (historicalData.length > 5) {
|
||||
const recentDefects = historicalData.slice(-5).filter((d) => d.defects > 0).length;
|
||||
const olderDefects = historicalData.slice(-10, -5).filter((d) => d.defects > 0).length;
|
||||
if (recentDefects > olderDefects * 1.5) defectTrend = "increasing";
|
||||
else if (recentDefects < olderDefects * 0.5) defectTrend = "decreasing";
|
||||
}
|
||||
|
||||
const getStateTransitions = (assetId: string) => {
|
||||
const transitions = stateTransitions[assetId] || [];
|
||||
const grouped = transitions.reduce((acc, t) => {
|
||||
const key = `${t.fromState}-${t.toState}`;
|
||||
if (!acc[key]) acc[key] = { fromState: t.fromState, toState: t.toState, count: 0, totalTime: 0 };
|
||||
acc[key].count++;
|
||||
acc[key].totalTime += t.duration;
|
||||
return acc;
|
||||
}, {} as Record<string, any>);
|
||||
|
||||
return Object.values(grouped).map((g: any) => ({
|
||||
fromState: g.fromState,
|
||||
toState: g.toState,
|
||||
count: g.count,
|
||||
averageTime: g.totalTime / g.count,
|
||||
}));
|
||||
};
|
||||
|
||||
return {
|
||||
errorRate: totalOperations > 0 ? (errorCount / totalOperations) * 100 : 0,
|
||||
errorFrequency: (errorCount / Math.max(1, totalOperations)) * 1000,
|
||||
successRate: firstPassYield,
|
||||
firstPassYield,
|
||||
defectRate,
|
||||
scrapRate,
|
||||
reworkRate,
|
||||
defectTrend,
|
||||
defectsPerMillion: totalOperations > 0 ? (defects / totalOperations) * 1000000 : 0,
|
||||
stateTransitions: getStateTransitions(assetId),
|
||||
};
|
||||
};
|
||||
|
||||
export const calculateMaterialFlowMetricsForAsset = (assetId: string, currentMaterialsOnAsset: any[]) => {
|
||||
const wip = currentMaterialsOnAsset.length;
|
||||
const removals = materialRemovals[assetId] || [];
|
||||
const durationMs = getSimulationTime();
|
||||
const throughput = durationMs > 1000 ? (removals.length / durationMs) * 1000 : 0;
|
||||
const leadTimes = removals.map((m) => m.processingTime || 0).filter((t) => t > 0);
|
||||
const avgLeadTime = leadTimes.length > 0 ? leadTimes.reduce((sum, t) => sum + t, 0) / leadTimes.length : 0;
|
||||
const velocity = removals.length / Math.max(1, wip);
|
||||
|
||||
return {
|
||||
wip,
|
||||
throughput,
|
||||
avgLeadTime,
|
||||
totalMaterialsProcessed: removals.length,
|
||||
currentMaterials: wip,
|
||||
avgCycleTime: avgLeadTime / 1000,
|
||||
materialVelocity: velocity,
|
||||
inventoryTurns: throughput > 0 ? throughput / Math.max(1, wip) : 0,
|
||||
};
|
||||
};
|
||||
|
||||
export const calculatePerformanceMetrics = (actualOutput: number, idealOutput: number, actualTime: number, idealTime: number, assetType: string) => {
|
||||
if (idealTime === 0 || actualTime === 0) return { performanceRate: 100, timeEfficiency: 100, productivity: 0, outputPerHour: 0, efficiencyAdjustment: 1 };
|
||||
|
||||
const performanceRate = idealOutput > 0 ? Math.min((actualOutput / idealOutput) * 100, 100) : 100;
|
||||
const timeEfficiency = idealTime > 0 ? Math.min((idealTime / actualTime) * 100, 100) : 100;
|
||||
const productivity = actualTime > 0 ? actualOutput / actualTime : 0;
|
||||
const outputPerHour = actualTime > 0 ? (actualOutput / actualTime) * 3600 : 0;
|
||||
const assetKey = getAssetKey(assetType);
|
||||
const efficiencyAdjustment = EFFICIENCY_ADJUSTMENTS[assetKey] || EFFICIENCY_ADJUSTMENTS.DEFAULT;
|
||||
|
||||
return {
|
||||
performanceRate: performanceRate * efficiencyAdjustment,
|
||||
timeEfficiency: timeEfficiency * efficiencyAdjustment,
|
||||
productivity,
|
||||
outputPerHour,
|
||||
efficiencyAdjustment,
|
||||
};
|
||||
};
|
||||
|
||||
export const calculateCostMetrics = (assetId: string, assetType: string, activeTime: number, totalOutput: number) => {
|
||||
const assetKey = getAssetKey(assetType);
|
||||
const hourlyRate = HOURLY_RATES[assetKey] || HOURLY_RATES.CONVEYOR;
|
||||
const maintenanceCostParam = MAINTENANCE_COSTS[assetKey] || MAINTENANCE_COSTS.CONVEYOR;
|
||||
const energyCostParam = ENERGY_COSTS[assetKey] || ENERGY_COSTS.CONVEYOR;
|
||||
const hoursOperated = activeTime / 3600;
|
||||
const errorCount = errorCounts[assetId] || 0;
|
||||
const operatingCost = hoursOperated * hourlyRate;
|
||||
const maintenanceCost = errorCount * maintenanceCostParam;
|
||||
const energyCost = hoursOperated * energyCostParam;
|
||||
const totalCost = operatingCost + maintenanceCost + energyCost;
|
||||
const costPerUnit = totalOutput > 0 ? totalCost / totalOutput : 0;
|
||||
const costPerHour = totalCost / Math.max(1, hoursOperated);
|
||||
const roi = totalOutput > 0 ? (totalOutput * FINANCIAL_PARAMS.VALUE_PER_UNIT) / totalCost : 0;
|
||||
|
||||
return { operatingCost, maintenanceCost, energyCost, totalCost, costPerUnit, costPerHour, roi, valueAdded: totalOutput * FINANCIAL_PARAMS.VALUE_PER_UNIT - totalCost };
|
||||
};
|
||||
|
||||
export const calculateEnergyMetrics = (assetType: string, activeTime: number, distanceTraveled: number = 0) => {
|
||||
const assetKey = getAssetKey(assetType);
|
||||
let rate = ENERGY_CONSUMPTION_RATES[assetKey] || ENERGY_CONSUMPTION_RATES.DEFAULT;
|
||||
if (assetType === "vehicle") rate = ENERGY_CONSUMPTION_RATES.VEHICLE + distanceTraveled * ENERGY_CONSUMPTION_RATES.VEHICLE_DISTANCE_FACTOR;
|
||||
const hoursActive = activeTime / 3600;
|
||||
const energyConsumed = hoursActive * rate;
|
||||
const energyEfficiency = 85 - Math.random() * 10;
|
||||
const carbonFootprint = energyConsumed * ENERGY_CONSTANTS.CO2_PER_KWH;
|
||||
const energyCost = energyConsumed * ENERGY_CONSTANTS.COST_PER_KWH;
|
||||
return { energyConsumed, energyEfficiency, carbonFootprint, powerUsage: rate, energyCost, energyPerUnit: 0 };
|
||||
};
|
||||
|
||||
export const calculateOEE = (availability: number, performance: number, quality: number) => (availability * performance * quality) / 10000;
|
||||
2889
app/src/modules/simulation/analyzer/oldAnalyzer.tsx
Normal file
2889
app/src/modules/simulation/analyzer/oldAnalyzer.tsx
Normal file
File diff suppressed because it is too large
Load Diff
@@ -69,7 +69,7 @@ function Simulation() {
|
||||
|
||||
<Analyzer />
|
||||
|
||||
<SimulationAnalysis />
|
||||
{/* <SimulationAnalysis /> */}
|
||||
|
||||
<HeatMap />
|
||||
</>
|
||||
|
||||
Reference in New Issue
Block a user