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IndustrialSQL Server. Factory to Office. Plant Database - Why?. Store all of the data produced by your plant - make it accessible to everyone in your organization. Production History. Material History. Process History. Requirements. Say you Wanted to . . .
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Plant Database - Why? Store all of the data produced by your plant - make it accessible to everyone in your organization. Production History Material History Process History
Requirements Say you Wanted to . . . View Trend of 1 Sensor over 1 Year (Pretty Simple, huh?) • Then you would Have to . . . • Acquire Data From Sensor (Changes 1/sec) • Store Data in SQL Database • Query Data from Client • Process and Display Queried Data at Client
Acquiring Data Done Done 3) Hire a DB Guru Done Done Write your own or Buy one from a 3rd Party 1) Free up your Calendar 2) Get your Masters in Database Administration (or) See Above See Above
Storing Data 10s - 100s/sec Activity Industrial Traditional RDMBS Database 31 536 000 (1 rec/sec * 60 sec/min * 60 min/hr * 24 hr/day * 365 day/yr) 31 536 000 Records Stored for 1 Year (For 1 Point!) 10 000s/sec Storage Rate On Standard PC 100% of Conventional RDBMS 2% of Conventional RDBMS Hard Disk Storage Required 50x Conventional RDBMS Online Storage 1x Conventional RDBMS Available Plants don’t stop - 24x7x365
Engineering The Critical Link Production Focus Select a Bar Drilldown to Real Time Data Database Server “Backbone” Timebased Analysis Realtime Relational Database
Maintenance • Control/Process This Operators Production Plant Managers QA Control Network Access to Data • Why? • SQL Common Language • Proven IT Technology • Ad -Hoc Queries • Accepted by Business • Why NOT? • Speed • Volume of data • SQL does not support time series data
Moore Siemens Honeywell Allen Bradley Yokogawa Modicon Data Acquisition & Compression Need to acquire data approximately 300 times faster than standard databases (10,000 updates/sec). Over 600 IO Servers • PLCs, DCS, RTU, etc.. • OPC, SuiteLink, DDE
1,000 instruments - sensors Data Compression 1,000 records/second 60,000 records/minute 3,600,000 records/hour 86,000,000 records/day 2,678,400,000 records/month
Moore Siemens Honeywell Allen Bradley Yokogawa Modicon Real-time SQL Extensions • Extensions to the standard SQL language to support time series data • data resolution • time and frequency functions
Legacy Applications Internet Moore Siemens Honeywell Allen Bradley Yokogawa Modicon Real Time Relational Database Leverage Standards