智能制造管理系统质量管控：数据驱动产品质量追溯与预警的方法指南

// 质量数据模型示例
public class QualityData
{
    public int Id { get; set; }
    public string ProductId { get; set; }
    public DateTime ProductionTime { get; set; }
    public string EquipmentId { get; set; }
    public decimal ParameterValue { get; set; }
    public bool IsWithinTolerance { get; set; }
}

// 追溯记录模型
public class TraceRecord
{
    public int Id { get; set; }
    public string BatchNumber { get; set; }
    public string MaterialSource { get; set; }
    public string ProductionProcess { get; set; }
    public string QualityInspector { get; set; }
    public DateTime InspectionTime { get; set; }
}

// 简单的质量趋势预警算法示例
class QualityAlertSystem {
  constructor(threshold) {
    this.threshold = threshold;
    this.dataHistory = [];
  }
  
  // 添加新数据点并检查预警
  addDataPoint(value) {
    this.dataHistory.push(value);
    if (this.dataHistory.length < 5) return false;
    
    const recentAvg = this.calculateAverage(this.dataHistory.slice(-5));
    const overallAvg = this.calculateAverage(this.dataHistory);
    
    // 当近期平均值偏离整体平均值超过阈值时触发预警
    if (Math.abs(recentAvg - overallAvg) > this.threshold) {
      this.triggerAlert('趋势异常', recentAvg, overallAvg);
      return true;
    }
    return false;
  }
  
  calculateAverage(data) {
    return data.reduce((sum, val) => sum + val, 0) / data.length;
  }
  
  triggerAlert(type, currentValue, expectedValue) {
    console.log(`质量预警: ${type}, 当前值: ${currentValue}, 期望值: ${expectedValue}`);
  }
}