Dynamic prediction of risk levels for manufacturing operations through leading risk indicators: dynamic risk pattern match method and system

A method for dynamic prediction of risk levels in a manufacturing operation comprising:

• collecting:
• (1) measured process data, comprising:
• data automatically collected by a data collection component, located within the manufacturing operation, in either (a) real-time or (b) from an archive server or both;
• and (2) long-term process data for a period preceding the collecting measured data;
• identifying risk and/or near-miss risk of the manufacturing operation that would otherwise be unknown or concealed in parameters P and/or groups G (of the parameters P of process data, using a pattern recognition module wherein a final dynamic pattern match probability is determined by using the measured process data, the long-term process data, and a polynomial pattern, previously uploaded to the server by a user, or an agent or employee of the user, wherein a final dynamic pattern match probability is automatically updated over time to identify operational risk and/or near-miss risk that would otherwise be unknown or concealed in parameters P;
• and
• displaying the risk or near-miss risk in a graphic that visually depicts the final dynamic pattern match probability value for a variable over a previous time horizon designated by the user or the agent or employee of the user;
• wherein the method is performed continuously and autonomously.

A display system for risk indicators for a manufacturing operation comprising:

• identifying risk and/or near-miss risk of the manufacturing operation that would otherwise be unknown or concealed in parameters P and/or groups G of the parameters P of measured process data, in real-time periodically, and/or historically wherein the measured process data is obtained by using a data collection component located within the manufacturing operation;
• using a pattern recognition module model wherein a final dynamic pattern match probability is determined by using the measured process data, long-term process data, and a pattern, previously uploaded to a server by a user, or an agent or employee of the user, wherein a final dynamic pattern match probability is automatically updated over time to identify operational risk and/or near-miss risk that would otherwise be unknown or concealed in parameters P;
• and
• displaying the risk or near-miss risk in a graphic that visually depicts the final dynamic pattern match probability value for a variable over a previous time horizon designated by the user or the agent or employee of the user.