Geometric Process Control

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Francine Walters
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1 Geometric Process Control Process and Product Improvement through Visual Data Mining Affordable Real-Time Optimisation from Bakeries to Oil Refineries Dr Robin Brooks Curvaceous Software Limited Curvaceous Software Founded in 1998 to research and develop applications of n- dimensional geometry for the process industries. A 25-year goal to find a practical way to analyse process history data hundreds of variables in ONE graph. Unification of Process Control, Quality Control AND Alarm Management. First method of calculating values for Alarm Limits Several new discoveries including one patent granted and several more in progress 60+ Customers, mostly in UK Claims proven in two Field Trials at large UK chemicals sites Winners of the EPSC 2003 Award for the Biggest Single Contribution to Increasing Plant Safety 1

A 25-year goal to find a practical way to analyse process history data hundreds of variables in ONE graph. Unification of Process Control, Quality Control AND Alarm Management.

2 Some Curvaceous Clients ICI Conoco Nestle BNFL Genzyme Nova Chemicals Mallinckrodt INCO Heinz Carnaud Metal Box Dow Corning Ineos Chlor Texaco GlaxoSmithKline BAE Eurofighter Infineon Philips Petroleum Marathon Oil LaFarge Cement Ethyl Petroleum DSM Advanced Elastomers PCS Potash Cabot Carbon BAE Rockets James Robinson Ltd. Pilkington Glass Aughinish Alumina Curvaceous 6 Sigma Mapping Characterize Optimize Six Sigma Measurement Analysis Improvement Control Curvaceous CVE CRSV CPM Key Six Sigma Activities: Select key product Define performance variables Create process map Select performance variables Benchmark Identify success factors Improving the 6 Sigma Process Define goal Propose causal variables Confirm causal variables Establish operating limits Verify performance Define control system Validate control system Implement control system Monitor performance metrics 2

Pilkington Glass Aughinish Alumina Curvaceous 6 Sigma Mapping Characterize Optimize Six Sigma Measurement Analysis Improvement Control Curvaceous CVE CRSV CPM Key Six Sigma Activities: Select key

3 How does it work? Process Data Mining The Root Problem Human brains are visually oriented Data Visualisation and Data Mining are intertwined A picture is worth 1000 words But we can only draw a graph of 2 or 3 variables.. How many graphs would you need to show all the interactions between 30 Copyright Curvaceous variables? Software Ltd

Visualisation and Data Mining are intertwined A picture is worth 1000 words But we

4 OvhF Naptha Crude Distillation Unit (CDU) RfxinT RfxoT Reflux KStm KinT KouT KinF Kero Pumparound KT Kero LStm LGO LinT LouT LinF LGO Pumparound Steam HouT HGO Feed FdT FdTr StmBF BotT BotF One Operating Point 4

Kero LStm LGO LinT LouT LinF LGO Pumparound Steam

5 3 Months of Hourly Data Temperature Profile 5

6 High Feed Without Inversion Variables most affecting Inversion 6

7 How does it work? Modelling Quality Management Alarm Management The Problems Operations need values of process variables that will deliver the desired quality values Qualities are variables that can only be measured after the product has been made, for instance product qualities, yields, efficiencies, KPI s 7

values of process variables that will deliver the desired quality values

8 The Used Operating Region Used Operating Region Range P1 2-D Range P2 The Best Operating Zone The Best Operating Zone Concept Used Operating Region Range P1 2-D Range P2 The Best Operating Zone What would a 20-variable BOZ look like? 8

Zone Concept Used Operating Region Range P1 2-D Range P2

9 A BOZ from 20 Variables The yellow region is a 20-dimensional BOZ chosen by the specifications on feed and upper temperature inversion. The Chosen BOZ 9

10 Alarms and Operating Points Throughput increased One incident, two alarms Alarm Limits decreased as throughput increased Large-Scale Process Behaviour 10

11 Building a CPM Model 2. Focus on the yellow points, remove unwanted variables and save as 1. Decide where to operate by applying KPI criteria as a query. The yellow area is the KPI for Buns within ±2mm of revised target size. 3. Open the file in CPM, create the red envelopes and start to use. Here it is being used in CRSV mode to understand variable interactions and opportunity giveaway Alarms Today 11

The yellow area is the KPI for Buns within ±2mm of revised target size. 3.

12 8 Modes of Operation found by Clustering on 5 main control variables Region boundaries over 3 months of operation. Also 5 th and 95 th percentiles and median line 12

13 But the median is not an operating point. Conclusions Visual Analysis is much faster and much less mathematical and Communication of results to others greatly simplified so more analysis will be done resulting in more discovery and improvements. GPC improves Six Sigma by offering multi-variate data analysis methods that anyone can use as an alternative to statistics. GPC Models are multi-variable, non-linear, cheap to implement and reduce dependence on laboratory results and online analysers Eliminate experiments in a DOE exercise. Unifying mathematics of GPC simultaneously improves product quality, process operations and process alarms and safety. 13

resulting in more discovery and improvements.

NEW ALARMS AND ALERTS FROM OPERATING ENVELOPES DRIVE ECONOMIC BENEFITS AS WELL AS SAFER PROCESSES

NEW ALARMS AND ALERTS FROM OPERATING ENVELOPES DRIVE ECONOMIC BENEFITS AS WELL AS SAFER PROCESSES Robin W. Brooks, Alan Mahoney, John Wilson, and Na Zhao Process Plant Computing Limited (PPCL), Gerrards