Abstract: A method and system for processing the data of any one of a variety of processes without doing a total custom design for each process. The system includes a computer and database that communicates with various monitors of the process to gather, store and retrieve the process data. A user interfaces to the computer via a client device. The computer includes a program that identifies events and activities of the process based on input from the user or from process data collected as the process runs. Attributes of the events and activities are also identified. These events, activities and attributes are classified according to a data structure that includes event types, activity types and attribute types. Storage volumes are allocated to each of the defined event types and/or activity types for storage and retrieval of the data by attribute type. The composite event or activity data can be retrieved in multiple views, such as row, column, graphical and the like.

Abstract: A method and apparatus that processes time series, event and/or activity data of a process according to a data structure is disclosed. The data structure defines one or more activities that frame the time series, event and/or activity data. Each activity and each event has one or more attributes. Each attribute has a value. At least one of the attributes defines an interval of the activity by start and end times. Another attribute includes a time varying parameter that represents the time series data. Another attribute defines a time stamp of an event. The time varying parameter is linked to a device that produces the time series data when the process is run. The time series, event and/or activity data is collected and processed according to the data structure for storage in and/or retrieval from a memory.

Abstract: A method and apparatus that processes time series, event and/or activity data of a process according to a data structure. The data structure defines one or more activities that frame the time series, event and/or activity data. Each activity and each event has one or more attributes. Each attribute has a value. At least one of the attributes defines an interval of the activity by start and end times. Another attribute includes a time varying parameter that represents the time series data. Another attribute defines a time stamp of an event. The time varying parameter is linked to a device that produces the time series data when the process is run. The time series, event and/or activity data is collected and processed according to the data structure for storage in and/or retrieval from a memory. A relationship between data of one or more activities and the time series, event and/or activity data is processed according to the data structure to retrieve the time series, event and/or activity data from the memory.

Abstract: A method and apparatus that processes time series, event and/or activity data of a process according to a data structure. The data structure defines one or more activities that frame the time series, event and/or activity data. Each activity and each event has one or more attributes. Each attribute has a value. At least one of the attributes defines an interval of the activity by start and end times. Another attribute includes a time varying parameter that represents the time series data. Another attribute defines a time stamp of an event. The time varying parameter is linked to a device that produces the time series data when the process is run. The time series, event and/or activity data is collected and processed according to the data structure for storage in and/or retrieval from a memory. A relationship between data of one or more activities and the time series, event and/or activity data is processed according to the data structure to retrieve the time series, event and/or activity data from the memory.

Abstract: A method and apparatus that processes time series, event and/or activity data of a process according to a data structure is disclosed. The data structure defines one or more activities that frame the time series, event and/or activity data. Each activity and each event has one or more attributes. Each attribute has a value. At least one of the attributes defines an interval of the activity by start and end times. Another attribute includes a time varying parameter that represents the time series data. Another attribute defines a time stamp of an event. The time varying parameter is linked to a device that produces the time series data when the process is run. The time series, event and/or activity data is collected and processed according to the data structure for storage in and/or retrieval from a memory.

Abstract: A method and system for processing the data of any one of a variety of processes without doing a total custom design for each process. The system includes a computer and database that communicates with various monitors of the process to gather, store and retrieve the process data. A user interfaces to the computer via a client device. The computer includes a program that identifies events and activities of the process based on input from the user or from process data collected as the process runs. Attributes of the events and activities are also identified. These events, activities and attributes are classified according to a data structure that includes event types, activity types and attribute types. Storage volumes are allocated to each of the defined event and/or types, activity types for storage and retrieval of the data by attribute type. The composite event or activity data can be retrieved in multiple views, such as row, column, graphical and the like.

Abstract: A method and apparatus that processes time series, event and/or activity data of a process according to a data structure. The data structure defines one or more activities that frame the time series, event and/or activity data. Each activity and each event has one or more attributes. Each attribute has a value. At least one of the attributes defines an interval of the activity by start and end times. Another attribute includes a time varying parameter that represents the time series data. Another attribute defines a time stamp of an event. The time varying parameter is linked to a device that produces the time series data when the process is run. The time series, event and/or activity data is collected and processed according to the data structure for storage in and/or retrieval from a memory. A relationship between data of one or more activities and the time series, event and/or activity data is processed according to the data structure to retrieve the time series, event and/or activity data from the memory.

Abstract: A system which comprises: a graphical tool which is capable of building discrete phase sequential steps and a smart device control for input/output device control; a microprocessor which is capable of running the phase sequential steps; and a I/O communication processor which is capable of communicating the phase sequential steps to the input/output device.