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Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
Effective data driven production decision making systems
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Effective data driven production decision making systems

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Executing the fundamentals is critical to success. For process management, those fundamentals include well designed and implemented plant floor data collection, management and analytics to support …

Executing the fundamentals is critical to success. For process management, those fundamentals include well designed and implemented plant floor data collection, management and analytics to support decision making. With these systems in place, the company can establish operational excellence. Without them long term success is impossible.

In this presentation, Bill Palmer reviews how the core practices of process management and analytics begin in operations and mature to become key elements of enterprise management. He draws upon his consulting experience to provide case studies illustrating what works effectively in practice.

To view webcast - http://www.nwasoft.com/resources/webinars/creating-effective-data-driven-decision-making-systems-production-quality-and-cos

The presenter:
Bill Palmer is Assistant Professor of Electromechanical Engineering Technology at Murray State University and the principal of Palmer Consulting. For 22 years he has designed and deployed quality information systems for manufacturing clients and taught manufacturers how to apply the principles of SPC and continuous improvement to plant floor operations and corporate management.

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Transcript

  • 1. It’s all about leverage
  • 2. How does management get leverage on the system.
  • 3. Work Harder?Push
  • 4. Work Smarter?Push Harder?
  • 5. Change the System! Push Harder?
  • 6. How Does This Play Out in the Plant?
  • 7. Better Operator Tools
  • 8. Islands of Information
  • 9. And, at the end of the day?
  • 10. Computerized Information is better, BUT…..
  • 11. Data Automation Shows the Process, But… Floor Manager View
  • 12. Operator Stuck in the Same Spot
  • 13. Skills and Tools forEffective ManagementFloor Manager View
  • 14. Boxplots for Mulitple Processes
  • 15. Management Needs to Understand the System 1. Convince employees that data is important. Show them you are really using it!! This may be the only best way to minimizing gaming of data. 2. Visualize the system with graphical representations of process data. 3. Understand the system with statistical knowledge. 4. Have the ability to instantly compare and study the necessary data.
  • 16. Case – ManagingCo-Producer Conformance 1 H 2 G F E D 3 C 4 B A 5 ACME William Palmer
  • 17. Track ODs With SPC Database C B ADB ACME ACME QA William Palmer
  • 18. Co-Producer Period Flavor Report William Palmer
  • 19. Period Moisture Report William Palmer
  • 20. Capability Trending William Palmer
  • 21. One Period Process Stability William Palmer
  • 22. The Leverage Point William Palmer
  • 23. Set Up Production Information System.
  • 24. Analytics and Rationalized Data SourcesStatistical Visualization Relational Statistical Visualizationand Analysis Software Database and Analysis Software Floor Manager View
  • 25. Common SPC Analytics MistakeAssumption: What’s important is theoperator seeing the real time process.Mistake: Choosing software based onwhether or not the operator will be able tosee the real time process.NEWS FLASH: ALL SPC software doesthat!
  • 26. A Common Start-Up MistakeMistake: Setting up data sources thatfocus primarily on the needs of the flooruser.Problem: The Manager SummaryReporting tools may be “too inconvenient”to use, and therefore will be underutilized.Quite often it is convenient to set up systems to look at aspecific process. The big ROI down the road might befrom comparing processes.
  • 27. Barriers to Managerial UnderstandingStatistical Visualization Excel Statistical Visualizationand Analysis Software and Analysis Software CSV Access ERP Manager View
  • 28. Rationalize What You HaveStatistical Visualization Excel Statistical Visualizationand Analysis Software and Analysis Software CSV Access ERP Manager View
  • 29. Centralized DatabaseStatistical Visualization Statistical Visualizationand Analysis Software and Analysis Software Manager View
  • 30. Centralized DatabaseAdvantage: Data is relatively easy to query. Datathat is easy to query, gets queried.Disadvantage: All data must go through the CentralDatabase, so, either all data must be written there, orspecial utilities must be developed to route data tothe Central Database.Disadvantage: You may be limited to the reportingtechnology that was developed for the CentralDatabase, thereby reducing reporting options.
  • 31. Decentralized Data SourceAdvantage: Data is also relatively easy to query. Datathat is easy to query, gets queried.Advantage: Data or reference information remains inalready convenient locations.Disadvantage: Some work needs to be done to relatethe data sources to minimize barriers to reporting.*Advantage: Easier to take advantage of reportingadvances created by 3rd party vendors.
  • 32. 3rd Party Reporting Can Help Supplier ERPOther Dbs SQL Server Quality Other DB Controls DB DB
  • 33. Combine Databases for Leverage Supplier ERPOther Dbs SQL Server Quality Other DB Controls DB DB
  • 34. Bill Palmer Palmer Consultingbpalmer999@yahoo.com

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