System, method and computer readable medium for using performance indicators and predictive analysis for setting manufacturing equipment parameters

1. A method comprising:

receiving first data from a data warehouse by an in-memory computing module, the first data including performance indicators associated with other equipment in a manufacturing process utilizing an equipment, the in-memory computing module being configured to store the first data in random access memory (RAM) and to process operational and transactional data in real-time;

receiving second data, by the in-memory computing module, from an enterprise resource planning database, the second data including information including at least one of bill of material information, machine set-up information, tool information, and maintenance information associated with the other equipment in the manufacturing process utilizing the equipment;

predicting, by the in-memory computing module, a target time per piece based on the first data and the second data, wherein predicting the target time per piece includes determining the equipment speed over which a time per piece is minimized in order to minimize a time associated with the manufacturing process based on the performance indicators and the information; and

setting an equipment speed based on the target time per piece.

2. The method of claim 1 , wherein the in-memory computing module is associated with a data warehouse appliance configured to process the operational and transactional data using in-memory analytics and to query data stored in the RAM.

3. The method of claim 1 , wherein the first data includes performance indicator associated with other equipment in a manufacturing process utilizing the equipment.

4. The method of claim 1 , the second data includes at least one of bill of material information, machine set-up information, tool information, and maintenance information.

5. The method of claim 1 , wherein the second data includes at least one of bill of material information, machine set-up information, tool information, and maintenance information associated with other equipment in a manufacturing process utilizing the equipment.

6. The method of claim 1 , wherein predicting the target time per piece includes determining the equipment speed over which a time per piece is minimized.

7. A method comprising:

receiving first data from a data warehouse by an in-memory computing module, the first data including performance indicators associated with other equipment in a manufacturing process utilizing an equipment, the in-memory computing module being configured to store the first data in random access memory (RAM) and to process operational and transactional data in real-time;

receiving , by the in-memory computing module, second data from an enterprise resource planning database, the second data including information including at least one of bill of material information, machine set-up information, tool information, and maintenance information associated with the other equipment in the manufacturing process utilizing the equipment;

predicting , by the in-memory computing module, a target cost per piece based on the first data and the second data, wherein predicting the target cost per piece includes predicting a cost such that a cost associated with the manufacturing process in order to minimize the cost associated with the manufacturing process based on the performance indicators and the information; and

setting an equipment speed based on the target cost per piece.

8. The method of claim 7 , wherein the predicted target cost per piece is a minimum acceptable cost derived from the setting of the equipment speed.

9. The method of claim 7 , wherein the in-memory computing module is associated with a data warehouse appliance configured to process the operational and transactional data using in-memory analytics and to query data stored in the RAM.

10. The method of claim 7 , wherein the first data includes performance indicators associated with other equipment in a manufacturing process utilizing the equipment.

11. The method of claim 7 , the second data includes at least one of bill of material information, machine set-up information, tool information, and maintenance information.

12. The method of claim 7 , wherein the second data includes at least one of bill of material information, machine set-up information, tool information, and maintenance information associated with other equipment in a manufacturing process utilizing the equipment.

13. The method of claim 7 , wherein predicting the target cost per piece includes determining the equipment speed over which a cost per piece is minimized.

14. A method comprising:

receiving first data from a data warehouse by an in-memory computing module, the first data including performance indicators associated with other equipment in a manufacturing process utilizing an equipment, the in-memory computing module being configured to store the first data in random access memory (RAM) and to process operational and transactional data in real-time;

receiving , by the in-memory computing module, second data from an enterprise resource planning database, the second data including information including at least one of bill of material information, machine set-up information, tool information, and maintenance information associated with the other equipment in the manufacturing process utilizing the equipment;

predicting, by the in-memory computing module, a target time per piece based on the first data and the second data, wherein predicting the target time per piece includes determining the equipment speed over which a time per piece is minimized in order to minimize a time associated with the manufacturing process based on the real-time performance indicators and the real-time information;

predicting , by the in-memory computing module, a target cost per piece based on the first data and the second data, wherein predicting the target cost per piece includes predicting a cost such that a cost associated with the manufacturing process such that the cost associated with the manufacturing process is minimized based on the real-time performance indicators and the real-time information; and

setting an equipment speed based on the target time per piece and the target cost per piece.

15. The method of claim 14 , wherein the predicted target cost per piece is a minimum acceptable cost derived from the setting of the equipment speed.

16. The method of claim 14 , wherein the in-memory computing module is associated with a data warehouse appliance configured to process the operational and transactional data using in-memory analytics and to query data stored in the RAM.

17. The method of claim 14 , wherein

performance indicators include at least one of equipment performance indicators, product quality indicators and equipment availability indicators; and

the second data includes at least one of bill of material information, machine set-up information, tool information, and maintenance information.