MechChem Africa

At an Endress+Hauser breakfast function held at the African Automation Fair 2017, Jenish Gheewala, Industry manager for mining, presented experiences from around the world about the implementation of the industrial Internet of Things (IIoT) and how advanced diagnostics is adding value to process plant operations.

Janish GheewalaFollowing a long history of R&D and solving practical problems being experienced in mining and minerals processing applications around the world, Gheewala was tasked to look at the opportunities on offer via the Industrial Internet of Things (IIoT).
Insert pic: Janish Gheewala

“The first thing I did when I was asked to look at how to implement IIoT was to do some research,” says Gheewala. “On average, two to four articles a week are being published about IoT technology, which immediately makes one ask: is this just hype or can we use the IIoT? Can it be useful in solving some real problems?”

In order to go beyond simple marketing, Gheewala decided to take his research to branch level, to talk to Endess+Hauser plant managers and their customers.

“The initial feedback I got from those responsible for service provision was scepticism. Plant operators wanted to know whether large investments were necessary and if so, when they could expect a return on this investment. In addition customers asked: Do I have to uproot the systems I have right now and install new systems to enable the IoT?

“At the root of all of these questions, plant engineers wanted to know what problems could be solved, which needs addressed and how would smart devices work at plant level?

“Where is the gap?” Gheewala asks.

Displaying a diagram of the traditional automation pyramid, he says that, like the pyramids of Egypt, traditional systems – those that rely on sensors feeding into PLCs for control purposes, with SCADA’s for transparency, and remote connections to higher level big-data software such as MES and ERP systems – are very stable.

“The new IoT paradigm, however, in addition to traditional process control, also promises process and reliability optimisation opportunities,” he advises.

“What is the IoT about? We are all consuming a huge amount of data. Weather, temperature and humidity information and GPS data from satellites, for example, is instant and immediately available on any smartphone no matter where you are in the world. Simply put, the IIoT is about using the vast amount of data we are able to collect in the industrial world, via two important new principals: instant access and data analytics.” Gheewala suggests.

“In the past instrumentation was limited, not because of a lack of physics’ knowledge but due to limited computing power. Now we can clean up raw signals to make reliable measurement available – and even the noise can be useful,” he says adding that he not pushing new systems that are more expensive and require more maintenance. “It’s more a case of using the information already available to us to better solve the problems we face,” he suggests.

Speculations versus big data

“On a visit to a customer operating a geothermal power plant in Guatemala, an interesting question arose: The customer asked: ‘Out of your existing sensors can you can get additional information?” Gheewala continues.

Showing a general schematic of the steam production process, he says that a significant amount of data is already collected from steam generation systems: Feed water temperature and flowrate; fuel volume and mass flowrate; and steam pressure, temperature and flowrate.

“Can the data being collected also be used to extract maintenance, fuel quality and steam quality information, though?” the customer asked. “If more data, such as the viscosity of oil used in the burner or the calorific value of gas used was accessible, we would be able to identify new opportunities for reducing energy loss,” he adds.

“Operators say there are leaks in their plant, so the flow readings are not good enough or the condensation traps on the steam lines might not be working well enough. This is not information, it’s speculation and customers do not like speculation. They like certainty,” Gheewala argues.

“Using existing sensors, a lot of this speculation can be confirmed. We can check the quality of the steam, the quantity of fuel being consumed and the quality of that fuel. The data needed for these analyses is already being collected: all you need to do it to add some algorithms to extract the specific information needed,” he reveals.

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