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A Method to Generate an Automatic Retrieval and Statistical Analysis of Event-Based Production Information

IP.com Disclosure Number: IPCOM000132503D
Publication Date: 2005-Dec-19
Document File: 5 page(s) / 169K

Publishing Venue

The IP.com Prior Art Database

Related People

David DesRochers: AUTHOR [+2]

Related Documents

US20030158795: PATAPP

Abstract

Improved data mining tools are described for use with integrated manufacturing control systems using event-based methodologies. Automated data extraction and analysis using Excel spreadsheets or other data processing tools can be done to quickly provide summary information about manufacturing processes and events that contribute to waste, delay, or quality issues.

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A Method to Generate an Automatic Retrieval and Statistical Analysis of Event-Based Production Information

David DesRochers and Aaron Schilpp Kimberly-Clark Corporation

Neenah, Wisconsin

Abstract

Improved data mining tools are described for use with integrated manufacturing control systems using event-based methodologies. Automated data extraction and analysis using Excel spreadsheets or other data processing tools can be done to quickly provide summary information about manufacturing processes and events that contribute to waste, delay, or quality issues.

Background

Kimberly-Clark Corporation has pioneered the development of integrated software systems for process control and productivity enhancement based on process events. Such systems are described in detail in published patent applications dealing with K-C's PIPE system ("Process Information Per Event") such as US20030158795A1, "Quality Management and Intelligent Manufacturing with Labels and Smart Tags in Event-Based Product Manufacturing" by C.E. Markham et al., published Aug. 21, 2003; US20030149373A1, "Intelligent Agent System and Method for Evaluating Data Integrity in Process Information Databases" by Walter Reade et al., published Aug. 7, 2003; US20030150908A1, "User Interface for Reporting Event-Based Production Information in Product Manufacturing" by M.R. Pokorny et al., published Aug. 14, 2003; and US20030154144A1, "Integrating Event-Based Production Information with Financial and Purchasing Systems in Product Manufacturing" by M.R. Pokorny et al., published Aug. 14, 2003 (also see US Pat. No. 6,904,330, "Manufacturing Information and Troubleshooting System and Method" by R.L. Popp et al., issued June 7, 2005, and US Pat. No. 6,829,516, "Combined Information Exchange Systems and Methods" by R.L. Popp et al., issued Dec. 7, 2004). In all these systems, information related to a wide variety of manufacturing events is acquired and stored in ways that can allow performance attributes at many levels to be related to manufacturing events throughout the system. With such data, subtle effects and complex relationships can be isolated and acted upon that may have been missed using previous manufacturing systems.

In extracting the desired information from the obtained process event data (the PIPE database) to address specific questions and hypotheses, users should follow efficient strategies to avoid unnecessary delays in sorting through the large bodies of available data. One useful method involves automatically retrieving and statistically analyzing a specific set of event-based production data (e.g. PIPE data) based on initial user inputs. The automation of this method involves a series of data acquisition, filtering, and analysis tasks that can be executed by a computer based on initial user inputs. The computations generate an output which can be used for data mining purposes as described in the examples of the above-mentioned publication, US20030154144A1. The automatio...