Small sample properties of an adaptive filter with application to low volume statistical process control

Conference · Sat Aug 01 04:00:00 EDT 1998

OSTI ID:665979

Crowder, S V ^[1]; Eshleman, L ^[2]

---

1. Sandia National Labs., Albuquerque, NM (United States)
2. Cornell Univ., Ithaca, NY (United States)

In many manufacturing environments such as the nuclear weapons complex, emphasis has shifted from the regular production and delivery of large orders to infrequent small orders. However, the challenge to maintain the same high quality and reliability standards white building much smaller lot sizes remains. To meet this challenge, specific areas need more attention, including fast and on-target process start-up, low volume statistical process control, process characterization with small experiments, and estimating reliability given few actual performance tests of the product. In this paper the authors address the issue of low volume statistical process control. They investigate an adaptive filtering approach to process monitoring with a relatively short time series of autocorrelated data. The emphasis is on estimation and minimization of mean squared error rather than the traditional hypothesis testing and run length analyses associated with process control charting. The authors develop an adaptive filtering technique that assumes initial process parameters are unknown, and updates the parameters as more data become available. Using simulation techniques, they study the data requirements (the length of a time series of autocorrelated data) necessary to adequately estimate process parameters. They show that far fewer data values are needed than is typically recommended for process control applications. And they demonstrate the techniques with a case study from the nuclear weapons manufacturing complex.

• Research Organization: Sandia National Labs., Albuquerque, NM (United States)
• Sponsoring Organization: USDOE Office of Financial Management and Controller, Washington, DC (United States)
• DOE Contract Number: AC04-94AL85000
• OSTI ID: 665979
• Report Number(s): SAND--98-1109C; CONF-981017--; ON: DE98007178; BR: YN0100000
• Country of Publication: United States
• Language: English

Related Subjects

25 ENERGY STORAGE
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION
CALCULATION METHODS
CATHODES
LITHIUM
MANUFACTURING
METAL-NONMETAL BATTERIES
PARAMETRIC ANALYSIS
PROCESS CONTROL