The Myths. George Buckbee, P.E.

Similar documents
Making APC Perform 2006 ExperTune, Inc. George Buckbee, P.E. ExperTune, Inc.

How to Read Sine Language : Reduce Process Cycling to Save Money

Shift Your Focus from Analysis to Optimization Using Active Model Capture Technology

Shift Your Focus from Analysis to Optimization Using Active Model Capture Technology

Prioritizing and Optimizing Problem Loops Using a Loop Monitoring System

Real-Time Asset Performance in Process Plants ExperTune, Inc. George Buckbee, P.E. ExperTune, Inc.

Seven Methods to Improve Control Performance in Pulp and Paper

Best Practices for Controller Tuning

Interaction Detection Using Oscillation Analysis

Collaborative Production Management in the Process Industries: A Stepwise Approach from KPIs to Workflow Processes

Establishing a Basis for Performance

Don t Tune These Four Loops!

Before we discuss optimization let s quickly review why process control systems are employed:

DeltaV InSight. Introduction. Benefits. Gain new process insight from embedded process learning. Easily identify underperforming control loops

Good Engineering Practices: What Can We Learn from the Pharmaceutical Industry

DeltaV InSight. DeltaV InSight. Introduction. DeltaV Product Data Sheet. Gain new process insight from embedded process learning

DeltaV InSight. DeltaV InSight. Introduction. DeltaV Product Data Sheet. Gain new process insight from embedded process learning

Our Experience with Mill Wide Process Control Performance Monitoring

This under-utilized approach can enhance operations and the bottom line.

Automation System Optimization

Metso control performance services. Optimized process controls for optimum performance

WHITE PAPER Achieving Operational Excellence in the Chemicals Industry Using APC

ADVANCED CONTROL STRATEGIES FOR POLYOLEFIN GAS PHASE PROCESSES

Improving the Business Performance of Defs s South Texas Assets Using Web-Based Optimization Technology

Control Systems Investment and Return Part 2 of 3

Jack van der horst September 22/23, Asset optimization and management

Gregory Rogers, PE June HCP-0101 Fundamental of Advanced Controls

CT425 Optimize Your Process to Make Profits

Reducing operations & maintenance costs

3 Steps to Better Steam Temperature Control Proven Strategies to Minimize Thermal Stress and Tube Leaks

PlantTriage Project Execution at Ammonia Plant

PlantTriage Project Execution at Ammonia Plant

Papermaker s experience with

A BPM Methodology What Is It and Why It Is Important

IT 470a Six Sigma Chapter X

Do you ever get the feeling that your control system

One ABB Seminar Surabaya Ganesh Kamath, Surabaya, 30 rd October Advanced Services Powered by ServicePort TM

Key performance indicators for production - Examples from chemical industry. Krister Forsman

Fuel Savings for Gas Power Plants. Using Digital Efficiency and Flexibility Optimization

2012 Honeywell Users Group EMEA. Sustain.Ability. Stefan Willenbrecht, Honeywell Control Performance Management in Large Scale Environments

ADVANCED PROCESS CONTROL

IIoT for Process Control

CHAPTER 1 INTRODUCTION

FLOTATION CONTROL & OPTIMISATION

You Can Achieve 100% Return in 6 Months

Vendor Support Agreements: A Competitive Weapon for Optimizing Organizational Assets

Novartis E2E CM case study

Oil & Gas Industry. Smart Remote Automation. An Extension of PlantWeb Digital Architecture. PlantWeb

smar Softwares AssetView Web-based Online Plant Asset Management Software

Job Description. Job Title

SMART HVAC & LIGHTING SYSTEMS. Savings From Two Major C&I End Uses

Enterprise MRO Services PRESENTED BY:

Emerson Climate Technologies TM Supermarket Solutions

Optimizing Batch Process Control

HC900 Hybrid Controller When you need more than just discrete control

Maximize throughput, decrease costs and achieve greater manufacturing flexibility

Mott All-Metal Catalyst Recovery Systems High-strength, high-efficiency filtration of particulate

PlantTriage Project Execution at Ammonia Plant. David B. Leach Industrial Process Optimization

Process Characterization

An Evolution of Step Testing and its Impact on Model Predictive Control Project Times

Dynamic Simulation for APC projects A case study on a Reformate Splitter with side draw. Dr Sebastien OSTA TOTAL Jose Maria FERRER Inprocess

PlantCruise by Experion FOUNDATION Fieldbus Integration

Application for process automation

Connoisseur. Software Datasheet MODEL PREDICTIVE CONTROL TO IMPROVE YOUR PROCESS ECONOMICS MAXIMIZE YOUR PROFITS. Summary.

Batch Reactor Temperature Control Improvement

Using Data Analytics to Drive Process Optimisation in Whiskey Manufacturing

ARC BRIEF. Using Simulation to Optimize Results of Automation Projects. Keywords. Summary. Applications of Simulation Systems.

Safety, Health, & Environment

Ingersoll Rand Automation. Advanced Air System Control

The Arrival of Automated Continuous Commissioning: How to Optimize Operational and Energy Efficiency for Commercial Facilities

Alternatives to Optimize Gas Processing Operations

GE Digital Executive Brief. Enhance your ability to produce the right goods in time to satisfy customer demand

Modeling and Simulation of Air Compressor Energy Use

Well Pad Automation Improves Capital Efficiency and Reduces Fiscal Risk Michael Machuca* Emerson Process Management

STRATEGIC ARCHITECTURAL DESIGN: HOW TO MEET BUSINESS GOALS AND MAXIMIZE ROI

Metso ExperTune PlantTriage. Optimized performance throughout the plant s lifetime

Metso ExperTune PlantTriage. Optimized performance throughout the plant s lifetime

CONTROL SOLUTIONS DESIGNED TO FIT RIGHT IN. Energy Control Technologies

BRING CRUSHING INTO THE LIGHT. SanRemo for Crushers automation and control system

SimSci APC. Model Predictive Control to Improve Your Process Economics

SAP PM Assessment and Improvement Processes for Reliability

MDC Technology Real Time Optimization - RTO+ John McNally Project Engineer MDC Technology (Houston)

The new BioPAT MFCS 4

A Holistic Approach to Control and Optimisation of an Industrial Crushing Circuit

GE Intelligent Platforms. Solutions for Sugar Processing and Refining

Diode Array In-line NIR sensor. Reliable, Accurate, Real-time Agri and Food Measurement

Efficient Plant Operation in Process Industries Using a User-Centric Design

Adaptable power control for electrical heating applications

Hill-Climbing for Economic Plantwide Control

Process Plant Design: The High Cost of Slow Decisions Using Risk Analysis Software to Confidently Speed the Design Process

Smart Net Total Care. Realizing the Promise of Automation for Network Support Operations

Dollarizing Maintenance

Key performance indicators improve industrial performance

AUDIT PROCESS. Preplanning. Audit Process

Intelligent Process & Equipment Surveillance. Anand Vishnubhotla

Richard Salliss 25 Oct 2016 EXPLORE PROFIT SUITE APC RUNNING IN ACE AND C300

PAT for the On-line Characterization of Continuous Manufacturing Systems

UNIFORMANCE ASSET SENTINEL A Real-time Sentinel for Continuous Process Performance Monitoring and Equipment Health Surveillance

Optimizing Buildings Using Analytics and Engineering Expertise

Continuous Manufacturing: An Industry View

Transcription:

George Buckbee, P.E. The Myths Myth 1: Tuning is Everything Myth 2: Averages are More Important Than Dynamics Myth 3: There Isn t Time to Look at Everything Myth 4: Each Unit Operation is an Island Myth 5: Analog Instruments Can t Deliver Diagnostics Myth 6: You Can t Show the Value in Dollars and Cents 1

Myth1 : Tuning is Everything The Equipment Exceeding Design Capacity At Limits of Performance Degrading Over Time Poor State of Repair 2

Operations Choosing the Right Targets Managing the Process Fire-Fighting Interactions The Control Loop Noise Measure Decide Action Variability Non-Linearity Controller Design Loop not In Normal Tuning Hysteresis Stiction Valve at Limit Interactions Operator Changes Disturbances 3

Myth 1 Debunked Tuning is One Piece of the Puzzle Equipment Operations Loop Software Tools Identify the Problems Focus Your Efforts Myth 2 Averages are More Important than Dynamics 4

Which is More Efficient? Average=44 Average=44 Dynamic Inefficiencies Scrap/Waste Product Recycle Loss of Operator Attention! Downtime Excess Energy Excess Raw Material Spec Limit 5

Causes of Inefficiency Process Upsets Controls Tuning Loop Interaction Equipment Valve Stiction Operator Response Overload, Confusion Right Information not Available Setpoint Not at Optimum Stiction Cycle Myth 3 There Isn t Time to Look at Everything 6

Time is Money Your Time is Valuable! Direct Cost Opportunity Cost Automate the Grunt Work Graphical Tools Focus Your Efforts TreeMap See the Entire Plant Public-Domain Technology 7

Process Interaction Mapping See Everything t Immediately Focus Interaction Interaction Interaction Triage Your Plant Data What Matters Most? Economic & Technical Factors + = 8

You Can Look at Everything Performance Supervision Looks at Everything! Automate the Grunt Work Data Collection Calculations Analysis You Focus On the Most Important Things Prioritization Apply Graphical Tools Focus Your Efforts Myth 4 Each Unit Operation is an Island 9

Unit Operations Boiler Distillation Column Dryer Reactor Blending Filtration Raw Materials Unit Op Product Not an Island: A Network Water System Prep Area Finish Supply Boiler 1 Reactor 1 Filter 1 Boiler 2 Reactor 2 Filter 2 Finish Filter 3 Condensate Return Waste Treatment 10

Interactions Come From Units Upstream Units Downstream Recycle Loops Sharing Common Resources Control Strategy Issues Start-Up, Shut Down Batch Operations Oscillation Typical: 40% Loops Oscillating Oscillation Summary 11

Myth 4: Each Unit Op is an Island The Truth: Unit Operations are an Interacting Network Interactions Create Most of the Variation Common Cause Can be Found, Quickly Look at the Big Picture Use Modern Tools Eliminate Upsets at the Source Myth 5 Analog Instruments Can t Deliver Diagnostics 12

The Value of Diagnostics Improved Service Factor of Control Equipment Availability is improved Predictive Maintenance Plan maintenance resources and costs Improved Plant Performance Solve problems which affect Plant Performance and profitability Fieldbus Diagnostics Diagnostic Comm. Failure Valve Travel Noise Band Valve Stiction Valve Hysteresis Cause of Oscillation Impact to Process Fieldbus No No No 13

Analog Instruments + Performance Supervision Diagnostic Comm. Failure Valve Travel Noise Band Operations Performance Analog + PSS Valve Stiction Equipment Valve Hysteresis Performance Cause of Oscillation Impact to Process Control System Performance PSS = Performance Supervision System Even More Diagnostics Diagnostic Analog + PSS Diagnostic Analog + PSS Process Shift Harris Index Process Constraints Dynamic Models Robustness Response Time Opportunity Gap Settling Time 6-Sigma Mode Changes 14

Myth 5: Analog Instruments Can t Deliver Diagnostics The Truth: You Can Get Diagnostics from Your Existing Instruments, For A Lot Less Money Diagnostics Deliver Results Maximize the Value from Installed Base Data is Available via OPC Diagnostics Delivered to Your Desktop A Fraction of the cost of New Instruments Myth 6 You Can t Show the Value in Dollars and Cents 15

Myth 6 You Can t Show the Value in Dollars and Cents Performance Improvement is abstract Performance Improvement is nice to do Manufacturing Reality Many Things are Important Cost Current Performance? Quality Safety Reliability Throughput Which are the most Important? Maintenance Costs Energy Costs Focus Improvement Efforts 16

Dollars and Cents An Example Calculating Energy Reduction Reduction in Natural Gas Demand Reduced from 196 SCFM to 183 SCFM Gas Pricing: $10.89/MCF From http://tonto.eia.doe.gov/dnav/ng/ng_pri_sum_dcu_nus_m.htm 24 x 7 operation, 330 days/yr Energy Savings 13 SCFM Gas @ $10.89/MCF Gas Saved 13 SCFM X 60min X 24 hr X 330 day/yr =6178 MCF/yr Total Savings 6178 MCF/yr X $10.89/MCF =$67,274/year 17

Myth 6: You Can t Show the Value in Dollars and Cents The Truth: There are many savings opportunities, each able to show value in dollars. Reduce Variation Stabilize Shift toward the Optimum Compare to baseline results Involve others to gain alignment The Myths Questions? Myth 1: Tuning is Everything Myth 2: Averages are More Important Than Dynamics Myth 3: There Isn t Time to Look at Everything Myth 4: Each Unit Operation is an Island Myth 5: Analog Instruments Can t Deliver Diagnostics Myth 6: You Can t Show the Value in Dollars and Cents 18