A welding system comprising: - a welding machine; and - a welding monitoring system comprising: a current measuring unit configured to measure a local current at a welded part in resistance welding; a temperature measuring unit configured to measure a local temperature at the welded part; an individual piece identifying device; a welding data storage unit; a data acquisition processing unit configured to acquire welding data from the current measuring unit, the temperature measuring unit and from the individual piece identifying device and to store the acquired data in the welding data storage unit a data classification storage unit; a data classification unit configured to classify welding data by machine learning and to store the results of machine learning in the data classification storage unit; and a determination unit configured to generate a normal group and an abnormal group, which are results of machine learning, as past current information and past temperature information; and determine whether or not at least one of current information acquired from the current measuring unit and temperature information acquired from the temperature measuring unit is abnormal by comparing the current information acquired from the current measuring unit with the past current information and comparing the temperature information acquired from the temperature measuring unit with the past temperature information; - a programmable logic controller; - an inspection device configured to be instructed by the programmable logic controller to perform inspection and to inspect the component to be welded in detail if welding conditions are determined to be abnormal by the determination unit; and - an inspection information input device configured to feed back results of the detailed inspection to the data classification unit such that the groups are associated with information of types of abnormality by manual input. - a welding machine; and - a welding monitoring system comprising: a current measuring unit configured to measure a local current at a welded part in resistance welding; a temperature measuring unit configured to measure a local temperature at the welded part; an individual piece identifying device; a welding data storage unit; a data acquisition processing unit configured to acquire welding data from the current measuring unit, the temperature measuring unit and from the individual piece identifying device and to store the acquired data in the welding data storage unit a data classification storage unit; a data classification unit configured to classify welding data by machine learning and to store the results of machine learning in the data classification storage unit; and a determination unit configured to generate a normal group and an abnormal group, which are results of machine learning, as past current information and past temperature information; and determine whether or not at least one of current information acquired from the current measuring unit and temperature information acquired from the temperature measuring unit is abnormal by comparing the current information acquired from the current measuring unit with the past current information and comparing the temperature information acquired from the temperature measuring unit with the past temperature information; a current measuring unit configured to measure a local current at a welded part in resistance welding; a temperature measuring unit configured to measure a local temperature at the welded part; an individual piece identifying device; a welding data storage unit; a data acquisition processing unit configured to acquire welding data from the current measuring unit, the temperature measuring unit and from the individual piece identifying device and to store the acquired data in the welding data storage unit a data classification storage unit; a data classification unit configured to classify welding data by machine learning and to store the results of machine learning in the data classification storage unit; and a determination unit configured to generate a normal group and an abnormal group, which are results of machine learning, as past current information and past temperature information; and determine whether or not at least one of current information acquired from the current measuring unit and temperature information acquired from the temperature measuring unit is abnormal by comparing the current information acquired from the current measuring unit with the past current information and comparing the temperature information acquired from the temperature measuring unit with the past temperature information; - a programmable logic controller; - an inspection device configured to be instructed by the programmable logic controller to perform inspection and to inspect the component to be welded in detail if welding conditions are determined to be abnormal by the determination unit; and - an inspection information input device configured to feed back results of the detailed inspection to the data classification unit such that the groups are associated with information of types of abnormality by manual input.