#pAutomator: Yan Freitas Marques, IHM Stefanini, Brazil

For our #pAutomator this week, we spoke to Yan Freitas Marques, Senior Analyst: Automation Systems at IHM Stefanini, Brazil. Marques had been involved lately with the concepts and applications of Reliability Engineering and Intelligent Physical Asset Management.

In this interaction, he discusses intelligent instruments and shares how digital practices like Industry 4.0 allow you to increase productivity. This makes the industry increasingly competitive. Read on for excerpts from the interview…

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Can you describe your journey in this industry? How has your experience been?


I started my career as an intern, working as a technician in industrial automation for a system integrator company. I worked mainly at Mining, Steel Mills and Ethanol plants. As a CLP and SCADA programmer, my mission was to develop robust and simple, understandable systems.

After all, maintenance people should not waste time deciphering codes during unplanned downtime. We must develop the system to facilitate tracing the shutdown’s root causes. Working on this mission, I became interested in the diagnostics of intelligent instruments.

Studying Production Engineering, I met professors who guided me to research methods for analyzing the reliability of intelligent devices and maintenance processes.

Since then, I have focused my studies and work on expert systems of condition monitoring of physical assets, industrial field networks and connectivity. 

You are actively involved with Reliability Engineering and Intelligent Physical Asset Management. Can you brief us on the developments in this area?   

Many articles, guidelines and books focused on intelligent physical asset management have come out in the last 5 years.

Leading automation technology vendors and startups have launched expert system platforms. However, it is difficult for most industries to absorb these new technologies. This is due to the need for specific equipment knowledge and the initial impact on changing maintenance plans.

I am currently working on a cloud system that monitors and predicts failure in a control loop, which would allow the user to maximize instrument availability and monitor control loop performance. For this, I set up a multidisciplinary team with specific knowledge in instrumentation, control, automation, process, maintenance and data analysis. My goal is to create a platform where experts can access data remotely and define the workflow in a way that allows them to interact with the customer maintenance planning team.

The degree of assertiveness in the analysis of the process or equipment is directly related to the quantity and quality of the available data. Each client has a different IT / OT structure. Some are outdated, others are modern. The challenge is to guarantee a certain degree of assertiveness in the prognosis without the necessary bunch of data. But even with fewer data and low quality, it is still possible to generate some insights that will reduce unplanned downtime.

After proving the efficiency of this system to the customer, they have the baseline to create incremental investment plans for the processor equipment modernization.

#pAutomator: Yan Freitas Marques, IHM Stefanini, Brazil
#pAutomator: Yan Freitas Marques, IHM Stefanini, Brazil

In your role in your current company, what are your target areas and customer base?

My current role is to coordinate field technicians, analyze instrument failures and support the sales team. Specifically, to guarantee that the instruments meet the needs of the customers, we offer on-site installation and repair support.

The industry is our main customer, but we have also been enlisted by OEMs to implement sensors, create fault prediction models, performance monitoring and integrate the controllers of the machines to the plant controllers.

What do must you keep in mind to help a customer select the right instrument for the right application?

Deciding the measuring principle to use is a tradeoff between required accuracy and process conditions. This stage is the most complicated. This is because experience and knowledge about the process influence the decision-making.

After defining the right principle, it is important to check which manufacturer has the most intelligent instrument. According to the terminology defined by the International Society of Automation (ISA) in the technical report 108, published in 2015, an intelligent device must have digital communication and supplementary functions, such as diagnostics, in addition to its basic purpose.

Therefore, the more comprehensive the diagnoses, the more intelligent the instrument is. This intelligence can help reduce operational risk, plant downtime, increase maintainability, and predict the use of spare parts.

Meeting changing customer demands is always important. What are the major customer queries you cater to in your domain? Can you share any unique experience you’ve had solving a customer query?

All industries have an engineering team, which is always looking for new technologies to increase the plant’s operational availability. In the last few years, it’s become important not only to guarantee the availability of assets, but also to maintain the performance of these assets according to product specification. In my opinion, this is very important.

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Each client has their own needs, and I always try to understand what these are. For example, one customer came to me because he had a problem with a smart valve positioner, which was impacting the control loop stability.

The positioner was failing randomly, so he replaced it with a new one. The lab did not find any problems. We started a fault analysis. The positioner had several diagnostics capable of detecting anomalies. However, there was no database with diagnostics. Thus, we could not compare it with the operation data. However, we could access a log of diagnostics using a HandHeld. This log had no conditions recorded that helped the positioner’s operation. Then, we expanded the possible causes of failure.

We came to the conclusion that the problem was in the Spur connecting the positioner with the main trunk of the network. After this, the engineering and maintenance teams understood they must treat Fieldbus as critical. So they established procedures to monitor the condition of all field networks using the appropriate tools.

Even when the industry has intelligent devices working on the plant, diagnostics hardly ever solve problems. Thus, investing only in cutting-edge products will not solve the plant’s problems. It is necessary keep improving the process. Also, we must motivate and inform employees of the newest technologies.

#pAutomator: Yan Freitas Marques, IHM Stefanini, Brazil
#pAutomator: Yan Freitas Marques, IHM Stefanini, Brazil

How do you see the entire industry evolving? What are your views on growing digital practices like Industry 4.0 or IIoT?

Are these just selling proposition to customers, or do they contribute to the business models? Technology is evolving and becoming increasingly complex. As a result, the industry increasingly demands specialized labor to keep the systems operating.

In the example I mentioned earlier, the maintenance and engineering team knew how to operate the network. However, they had no knowledge of how to monitor and keep the network running. Field networks facilitate and reduce plant startup and commissioning time.

One must invest not only in the equipment but also in the workforce. Digitization allows you to create methods that increase efficiency, making the industry increasingly competitive.

For example, IIoT, one of the pillars of industry 4.0, enables the implementation of dedicated plant monitoring systems. So, specialists can access these systems remotely to assess the condition of the plant and to define operation and maintenance plans.

This flexibility allowed the creation of products and services with lower costs. To achieve state-of-the-art digitization, we must modify more than the business models of service providers. Also, the industry has to adapt part of its physical and organizational structure to interact with service providers.

That is why I see industry 4.0 as a milestone, not just the evolution of the production chain.

How do you foresee the industry changing? what is your advice for next-generation engineers?

The problems of the industry are the same, but how to solve them is changing. It is necessary to keep in mind that solutions are provisional, and their period of validity is getting smaller.

Therefore, it is fundamental to make the notion of certainty more flexible. It is necessary to be open and motivated to produce new knowledge. That is why it is important to keep up-to-date on new technologies and creative. Most importantly, one must promote a good relationship with all generations.

After all, everyone has a lot to learn and teach.

 

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