Best Practices in Data Collection for Successful Manufacturing Intelligence
by Northwest Analytics on Jan 27, 2012
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Robust Manufacturing Intelligence (MI) capabilities are fundamental to successful manufacturing enterprise management. And robust MI capabilities start with sound data collection practices. ...
Robust Manufacturing Intelligence (MI) capabilities are fundamental to successful manufacturing enterprise management. And robust MI capabilities start with sound data collection practices.
The analytics feeding management dashboards will work with any properly formed data that can be drawn from manufacturing databases. However, if that data is compromised, the decisions made by management based on the compromised data may be faulty and put the organization at risk.
The key to world-class, sound decision making is a solid data collection foundation. This webinar examines data collection best practices:
• The requirements standards such as ISA 95, FDA Q10, and ISO 9001 and good manufacturing practices place upon the data collection process.
• The business implications of poor data collection.
• What data collection best practices should be implemented:
o Operator workflow support
o SOP enforcement
o Input error reduction
o Data integrity
• How data collection integrates with manufacturing management systems
The end result is compliant process and testing data collection that dependably provides high-quality data to feed the analytics that informs MI. Data collection with integrity is a core requirement to make MI work while keeping auditors and customers satisfied.
Recording at https://www1.gotomeeting.com/register/768216009
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