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High Business Value Technologies I

7 November 11:00 a.m. - 12:30 p.m.

Session Type: Paper

Track: Creating Business Value through Automation

Paths(s): ExecutiveExecutive   EngineerEngineer   

This session provides specific examples of how specific advanced automation technologies can be applied to drive improved business value. For decades the value of some of these technologies was understood to exist but specifics behind the level of value generation each could provide was scant. These presentations will help automation professionals to justify investments in the technologies that may provide the greatest returns for their businesses.


Model-Predictive Control for pH and Concentration Control Optimization

Flavio Briguente, Monsanto Read Bio

Flavio P. Briguente is currently Technologist Specialist at Monsanto - Sao Jose dos Campos in Brazil. He holds bachelors in chemical engineering degree from University of Sao Paulo and two masters' degrees - in automation and in environmental engineering. Recently started a phD in Process Engineering. He has been working with Monsanto since 2003. 

Greg McMillan, CDI Process & Industrial Read Bio

Greg is a retired Senior Fellow from Monsanto-Solutia and an ISA Fellow. Greg received the ISA “Kermit Fischer Environmental” Award for pH control in 1991, the Control Magazine “Engineer of the Year” Award for the Process Industry in 1994, was inducted into the Control “Process Automation Hall of Fame” in 2001, was honored by InTech Magazine in 2003 as one of the most influential innovators in automation, and received the ISA Life Achievement Award in 2010.  Greg is the author of numerous books on process control, his most recent book 101 Tips for a Successful Automation Career was inspired by the ISA mentor program he started at ISA Automation Week 2011. Greg has been the monthly “Control Talk” columnist for Control magazine since 2002.  Greg has a Control Talk blog at and provides posts on ISA Interchange website at Many of his presentations are at


This paper outlines a model predictive control (MPC) solution for a continuous reactor in order to reduce pH and concentration variability, and consequently reduce costs associated with raw materials usage. MPC is based on constraint, disturbance, controlled and manipulated variables which establish the process control strategy in order to optimize costs and improve process efficiency regarding to process variability, quality control, safety and environmental risks, and raw materials consumption.

For this case study, the plant consisted of a slurry tank in series with a reactor in a recycle loop. In order to maximize production rate using less raw materials, two MPC controllers were created.  The first consisted of a single controlled variable (pH), one manipulated variable (income base flow rate), and two disturbances variables (income water flow rate and product outlet flow rate). The second MPC application used a single controlled variable (concentration), one manipulated variable (income water flow rate), and one disturbance variable (slurry density). The modeling process was started by performing the plant runs. Both MPC applications run independently of each other.

This project accomplished the goals, improving the base reactant usage in 3.6%, reducing operating cost with low capital investment.  Additionally the MPC applications have demonstrated their importance for reducing by 70% the pH and concentration variability and for maximizing process output.

Optimizing Heat Recovery with Control Performance

Chris McAnarney, ExperTune, Inc. Read Bio

Chris McAnarney is currently Manager, Services and Support, at ExperTune.  Chris' work history brings a unique perspective to ExperTune and their customers.  He has held positions as a plant based Process Engineer, corporate based Process Engineer, Plant Manager, and as a corporate based Project Engineering Manager.  Chris holds a B.S. in Chemical and Petroleum Refining Engineering from the Colorado School of Mines.


This case study from a power plant in Florida demonstrates the ability to reduce operating costs through improved process control and the importance of quickly identifying the root cause of a process disturbance.  The power plant was able to utilize software based tools and analysis techniques to deliver up to $90,000 in annual natural gas savings and identified the root cause of a possible plant trip.  The net effect was improved reliability and increased operating cash flow.

Process variability introduces inefficiencies in the conversion of energy from the fuel source into electricity.  Reducing the variability in steam temperature control allows the operator to increase the steam temperature while remaining confident that turbine specification limits will not be exceeded.  Higher steam temperatures at the turbine directly translates to increased electrical generation for the same amount of fuel.

Finding the root cause of process disturbances is a tedious and time consuming using traditional analytical methods. This Florida-based power plant looked for root cause with software-based analysis tools including a process interaction map.  These tools correctly identified all correlated loops during a known process disturbance and pinpointed which control loop was the root cause. 

These methods highlight tools and techniques to analyze real time process variation, as well as process interaction mapping to identify the root cause of a process disturbance.  These methods have been able to deliver measurable results faster and more reliably than manual auditing approaches of the past.

Analysis of Power System Failure at IFFCO-Aonla and Subsequent Measures to Enhance Reliability---A Case Study

A.K. Bhaduri, Indian Farmers Fertiliser Co-Operative Limited, New Delhi,India Read Bio

Mr. A.K. Bhaduri is presently working in the capacity of Senior General Manager at Corporate office of Indian Farmers Fertiliser Co-operative Ltd.(IFFCO), New Delhi.

He holds a degree in Instrumentation and Electronics Engineering from Jadavpur University, Calcutta and is a Fellow of the Institute  of Engineers, India . He joined IFFCO in the year 1978 as a Graduate Engineer Trainee at Kalol Unit and started his career.  He has worked in all the Units of IFFCO at various capacities and has a wide exposure in the fields of Instrumentation & Process Control. He has experience of working in maintenance and projects starting from the shop floors. He had undergone Process Simulation training at the US & UK and senior executive training at Administrative Staff College of India, Hyderabad and  other managerial trainings at XLRI, Jamshedpur and IIM, Calcutta.

He was involved in grass-root project activities like construction, commissioning of Instrumentation & Control Systems at IFFCO's Phulpur Unit – I, Aonla Unit – I and II, where in he had significant contribution including many new/innovative equipments/systems. He was also involved in renovating of Paradeep Unit immediately after its take over.  On the similar lines, he contributed in the initial stages of IFFCO's overseas Joint Venture projects like Egypt, Jordan and has worked on deputation for two years at Oman India Fertiliser Project , Oman. He is well travelled and has experience of working  with people of various Nationality & culture.

Prior to his present assignment he was at the Aonla Unit of IFFCO at various capacities.During his tenure at IFFCO's Aonla Unit as General Manager(Technical),the Unit bagged various prestigious awards in the fields of Safety,Environment and Training.—This includes SHE Award of International Fertiliser Association and GreenTech Foundation HR Award on Training Excellence.


IFFCO-Aonla Fertilizer complex consists of two streams of Ammonia Plants and four streams of Urea Plants. Two Gas Turbine Generators (GTGs) cater to the total electrical power requirements of the complex. Additionally there is a back-up connection with the State Grid.

There have been instances of failure of one GTG and consequential tripping of the second GTG as well as the UPPCL feeder overloading, causing a major power outage at the complex and tripping of all major plants. The phenomenon was found attributable to the slow response of the Load Management System (LMS) PLC.

Analysis revealed four critical factors which impacted modifications done to handle this issue.  The modification has been done without any investment.  Since implementation of the modification, there have been three occasions of trip of one GTG, but no incident of total power failure nor were there any outages of Ammonia Plants.