How to Use Predictive Analytics to Build Your Own Business in Chemical Engineering The Power of Process Data in the Hands of Chemical Engineers
Predictive analytics is one of the most fruitful disciplines in chemical engineering when talking about building your own business, whether a start-up or a consulting one.
You have probably heard of that before but maybe have no idea about - how?
Let's first explore - WHY? After that, let's also explore - HOW?
The field of data analytics is evolving quickly, and an increasing number of tools are being designed. Big data, smart devices, Industrial Internet of Things (IIoT) – these days, these are all terms that seem impossible to avoid across different process industries.
As such, they are in the focus of many who are building or upgrading their start-ups or consulting businesses. Even if this was not in your focus until now, it is worth considering. It could be you building it. One thing is certain - chemical engineers have all the knowledge, resourses and capabilities to be the leaders of the field.
Why predictive analytics???
- It can be applied to any process, process section, or piece of equipment or even only to a part of the equipment,
- It can be applied for technological, mechanical, economical, process or any other parameter,
- It can be used to monitor, to predict, to control, to test, to verify any parameter, property or variable,
- It applies to research as well as to day-to-day operations and businesses,
- It is very well connected with the key concepts and terms of industrial progress today: optimization, maintenance, improvement, safety, efficiency, sustainability IIoT, etc.
A couple of "Why's" which are not related to industrial language, however, resonate powerfully with me:
- It is a very creative part of chemical engineering – your mind is the only real limitation to what is possible to achieve with predictive analytics!
- It is relatively simple if you know the basics and are ready to learn and gain experience,
- There are fantastic tools available out there – from practical and simple open-source tools to different programming options and high-profile self-learning and self-programing applications.
- It will be an integral part for the plants of tomorrow.
Let's now jump to HOW:
I'll give a few examples and guidlines that I can confirm as feasible and valuable from my experience.
1. Developing unique applications for industry clients
Although data availability and analysis technologies have made massive strides in recent years, these platforms are limited if end users cannot easily apply them and measure the benefits they provide.
There are always day-to-day questions and operation challenges occurring that process engineers cannot fully bring their focus on. Process and data experts and consultants know the right tools and are aware of opportunities that can bring significant benefits and help in solving day-to-day operation challenges. They are also able to look into a greater picture, help their industry clients gain feasible and measurable results and savings.
Problems that can successfully be addressed with predictive analytics applications is, for instance, diagnosing a fouling problem with the opportunity to minimize its impact and reduce potential future anomalies.
Predictive analytics application, once developed and tuned, can recommend certain parameters to smoother and optimized operation, can suggest root causes, and compare events, and it can even reveal early indicators for adverse asset behavior.
Predictive analytics applications with the focus on energy-savings and energy efficiency improvement are, as well, common and beneficial. For example, by looking into the unit's energy consumption historical values, often unexpected spikes in consumption can be found, This can lead to an examination of steam and fuel usage and different causes can be detected, analyzed and improved. These types of comparative analytics are also useful in other improvement areas.
Developing virtual sensors with specifically defined goals and their online and continuous operation is the application of predictive analytics that can and should be applied on every single process unit.
If you are developing your own consulting business, make it a goal for yourself to find as many of those. If you are looking to get even more inspired, take this free Masterclass and find even more opportunities to implement predictive analytics applications.
2. Designing applications for equipment monitoring and fault detection
Advanced monitoring applications today are closely connected with plant maintenance and support both predictive and preventive maintenance that in the long run can save an industry client a great deal of money.
Predictive monitoring application connected to the history database can be trained and tuned to successfully give a notification or prediction for any anomalies or faults of process equipment operation. Such as normal operation of pump, compressor, valve or heat exchanger etc, even reactor or a distillation column. It is like knowing where you're going and having a GPS at your fingertips.
Applications of that type are best developed and applied in small teams. Start-ups that involve flexible, dedicated, and technically prepared individuals with the vision for the plant of the future are those who can bring significant impact into modernization of industry.
3. Developing expert systems
Previously mentioned applications are more or less referring to specifically focused problems and their solutions.
However, one of the greatest values that predictive analytics can bring for the plant of the future is it's a systematical and consolidated approach to all the aspects of a plant: its safety, efficiency, sustainability, energy efficiency, optimization, economy, and product management.
Bringing the eyes of the plant manager and plant personnel into past, present and future operation fully and thoroughly, through analysis, prediction, fault detection and running a parallel virtual plant as a guide and map to the most profitable, sustainable and safe operation is the vision that is not so far from our industry standards anymore and it is going to need a great number of chemical engineers who understand and can recognize, evaluate and implement the power of process data and predictive analytics.
Let your vision inspire you to create...because innovation starts with you!
If you would you like to learn how to recognize, evaluate, and develop predictive analytics applications in 10 steps? Take the opportunity and challenge through this specially designed course: "Process Optimization with Predictive Analytics - 10-DAYS-CHALLENGE".
Also, take the advantage of the free Mini-course to get inspired for your future predictive analytics projects.
Ivana is Ph.D. in chemical engineering and works as a process modeling and simulation expert in her family company Model. Through her 15+ years of experience, she has been involved in the execution of projects that include: optimization studies and projects, conceptual and basic design, energy efficiency improvement projects, data-driven models and predictive analytics, advanced process control and operator training simulators as an engineer and later consultant.
Process analysis, development and optimization are her passion in all areas of life and she is very much motivated to transfer her passion for problem-solving to younger engineers. Some of her experiences she is sharing as an instructor at Model Development Courses.
She'd like to see more chemical engineering entrepreneurs who are confident and motivated enough to take responsibility and leadership in creating better and sustainable paths and processes to help environment preservation, pollution minimization and more efficient waste conversion.
Connect with Ivana through her LinkedIn profile.
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