Helping Miners Validate Water Balance Plans


Emerson's Juan Carlos Bravo

Author: Juan Carlos Bravo

In previous blog posts we have talk extensively about water problems in mining and how water is one of top issues miners are dealing with today. The reason I come back to this topic is because I recently read an interview with professor Dirk Van Zyl, an expert in tailings and mined earth structures and a professor at University of British Columbia. He gave the interview as part of the Mine Water Solutions conference that took place in Vancouver during the week of April 12th, 2015.

In this interview professor Van Zyl says that mine water is really one of the most important pieces because either a mine has too much or has too little. It’s very seldom that a mine has just enough. If they have too much water, then miners may have storage issues, and may have issues with water treatment. If they have too little water, then they have to find water supplies and some mines go as far as desalinating ocean water and pumping it hundreds of kilometers at very high elevation heads to the mines.

So overall, mining companies are paying more and more attention to the mine water issues that they are dealing with. It is also an issue that affects the communities very much because in many cases it is a choice of using water for a mine or having it available for agriculture. That is the case in especially some of the drier regions of Chile and Peru.

One of the most interesting questions of the interview is when he was asked the number one thing that miners get wrong regarding water; he answered that all mines have water balance plans in place right now. One of the toughest pieces is having a way to validate that model. That takes time, effort, and commitment to make it happen. Continue Reading

Big Data at AIChE Spring Meeting


AIChE-logoAustin, Texas, already a hotbed for technology as recently recognized by Forbes magazine, will host a gathering of chemical engineering professionals later this month. The AIChE is hosting the 2015 Spring Meeting and 11th Global Congress on Process Safety here on April 26-30.

If you’re planning to attend, make sure to catch some of the “Big Data” sessions to see how this data is being applied in our world of process instrumentation and automation. I’ll highlight two sessions featuring members of our Emerson team here in Austin.

On Monday, April 27 at 3:30pm, Emerson’s Mark Nixon, Terry Blevins, Willy Wojsznis and John Caldwell will present, Industrial Big Data Vision and Solutions. Here’s an excerpt from the session abstract:

Emerson's Mark Nixon

Emerson's Terry Blevins

Emerson's Willy Wojsznis

Emerson's John Caldwell

The process industries adopt many Big Data approaches that are applied in other industries however the Big Data implementation for Process Industries is distinctive in that it sets specific requirements for Big Data infrastructure, learning algorithms including data analytics, and presenting the results.

The presentation will address the basic components of Big Data pipeline for the process industry: hardware and software infrastructure, data streaming, data preprocessing and data learning techniques.

The core of data learning is Data Analytics (DA) which has proven its effectiveness in process fault detection and quality prediction both for batch and continuous processes. The real prospects are that Big Data based on DA will be among the leading directions for improving process effectiveness. DA requires a significant departure from the traditional thinking about how process control is implemented. Instead of the deterministic and tangible world of signals and devices, there is an abstract realm of statistical indexes, correlation factors and matrix operations. This puts a significant strain on the control systems’ developers, engineering companies, process operation and maintenance personnel. The presentation will address these major challenges for professionals working on Big Data for the process industry.

Mark, Terry, Willy and John will also present Tuesday, April 28 at 2pm on Embedded Analytics in Industry Big Data Applications. Here is the abstract: Continue Reading

Identifying Components then Optimizing Industrial Energy Consumption


When optimizing operating costs at a production facility, the bias is toward that which can be measured. For example, the cost of chemicals additives for a process is something easily measured based upon the amount consumed. For components such as the energy to produce steam, the costs may not be so clear.

Emerson's Barbara Hamilton

Emerson’s Barbara Hamilton shared a couple of stories with me about how cost optimizations changed once unknown costs could be determined.

The first example from a pulp mill, was where consistent bleaching of the pulp stock was accomplished by keeping the inlet temperature to the oxygen delignification tower constant. Oxygen was the bleaching chemical in this case.

Barbara noted that the temperature operating target is determined by the process designer, but small fluctuations in setpoint are up to the operators’ discretion. Setting the temperature up a few degrees can save bleaching chemical and setting it down a few degrees can save steam.

The Pulp Mill Operation Manager knows exactly how much the bleaching chemicals cost, but the impact of steam is not as “real”. Even if there are internal charges from the Powerhouse, they are typically done monthly and do not address incremental costs. The impact of operating temporarily away from the design inlet temperature is not readily apparent. Continue Reading

Internet of Things in Process Instrumentation and Automation


If you subscribe or follow many of the process instrumentation and automation publications, web sites, and/or social channels, you know that the Internet of Things (IoT), also known as the Industrial Internet of Things (IIoT) is a frequent topic of conversation. Microprocessor-embedded sensors and final control elements have a long history in our industry and the Internet opens up even greater possibilities to take advantage of the data they collect and process. Emerson’s Pervasive Sensing strategies imbue IoT by combining innovative sensors with analytical software built on human centered design principles (HCD), together coupled with expertise.

Emerson's Bob Karschnia

I came across a great description of IoT and its application in Pervasive Sensing strategies by Emerson’s Bob Karschnia in terms of what these advancing technologies mean for process manufacturers and producers.

Bob noted that the additional information provided by these pervasive sensing devices provide ways to automatically improve performance, safety, reliability and energy efficiency in production facilities.

These improvements occur as a result of:

  • Collecting data from sensors (things), much more cost effectively than ever before because they are battery powered and wireless
  • Interpreting this data strategically, using subject matter expertise to effectively analyze the data, either locally or remotely
  • Presenting actionable information, built on task-oriented HCD principles, to the right person—either plant personnel or supplier-provided experts, and at the right time
  • Leading to results in performance improvements, when personnel take corrective action

IoT starts at the sensor level where pressure, level, flow, temperature, vibration, acoustic, position, analytical and other sensors collect data and send this collected information to control and monitoring systems via wired and wireless networks. Continue Reading

Measurements to Improve Process Operations


Process measurement devices are installed where required to monitor, control, and safely shutdown the process. But often, additional measurements combined with the existing ones can help to improve several areas of process operations performance.

Emerson's Jonas Berge

I saw a chart from Emerson’s Jonas Berge which highlighted four areas for potential improvement—reliability and maintenance, energy efficiency and loss control, health, safety & environmental (HS&E), and process operations productivity.

Some applications to consider for improvement in reliability and maintenance include pumps, blowers, air-cooled exchangers (fin-fans), non-process compressors, cooling towers, corrosion monitoring on pipes and vessels, valves, instrumentation, vibration, temperature, and acoustic testing rounds.

Energy losses can happen in many areas including water, compressed air, gas & other fuels, electricity, and steam. Additional measurements can help detect steam trap failures, heat exchanger fouling, cooling tower fan issues, relief valve seat leakage, and unit-wide energy consumption abnormalities.

Although health, safety and environmental extends to people and work processes, additional measurements can assist in operating safely and in regulatory compliance. These measurement applications include emergency safety shower and eyewash station monitoring, manual and bypass valve position monitoring, relief valve and rupture disk release monitoring, shutdown valve position confirmation, hydrocarbon leak detection and effluent discharge. Continue Reading