By Cobus van Heerden
Today, staying competitive means being part of your customers’ digital transformation journey, including machine learning and analytics. Not only can integrators capitalize on the IoT opportunity, generate new revenue streams and deliver a higher level of value to customers, but engaging in the latest technologies also helps attract and retain the best talent.
Fortunately, the journey to success with machine learning and analytics doesn’t mean that integrators need to be data scientists. Proven processes and software technologies make analytics doable for every integrator.
Leverage domain expertise to create a process twin
Integrators are in a unique position of having exceptional domain expertise to put together process models – or process twins – and be able to interpret the models. This is the foundation for improving competitive advantage and success with analytics.
To drive analytics offerings and improve processes, align your domain expertise to five capabilities:
- Analysis: automatic root cause identification accelerates continuous improvement
- Monitoring: early warnings reduce downtime and waste
- Prediction: proactive actions improve quality, stability and reliability
- Simulation: what-if simulations accelerate accurate decisions at a lower cost
- Optimization: optimal process setpoints improve throughput at acceptable quality by up to 10%
Advanced analytics techniques are available to industrial process engineers to fulfill on these capabilities as an integrator offering. Some vendors, such as GE Digital, also provide analytics technology training in the form of a self-serve product university, detailed demo videos, integrator-licensed software and application support.
Additionally, while today’s software features enhanced ease of use and no-code implementation extensible with Python, integrators can still lean on product experts in combination with their domain expertise for competitive advantage.
Success with analytics
As an example, an integrator worked with a leading food manufacturer to drive down customer complaints by more than 33% through analytics. The manufacturer had struggled with weight control on a cube-shaped product. Make the cubes too heavy, and the manufacturer was giving away product or producing watery product if the excess weight was due to too much water.
When the cubes were too light, the company was in regulatory jeopardy as well as having trouble compacting the product into a stable cube shape.
The team used Proficy CSense to get a complete, correlated-by-lot and period picture of ingredient specs, process variables as run and lab data – using the software to look for controllable factors that correlated to excess giveaway and then comparing periods with better weight control to the factors that were true then.
Now, when the team sees how a raw material variance was successfully corrected for or a process disturbance was overcome, that understanding is embedded into a new material spec, recipe or SOP. The smart analysis with Proficy CSense yielded other benefits as well.
Another example involves an integrator applying a smart predict project at a pulp and paper manufacturer to predict critical to quality (CTQ) KPIs to improve productivity and eliminate wastewater regulatory issues.
As a final example, a partner in mining delivered an advanced process control solution that increases throughput by 10% using smart optimization technology.
Integrators can use industrial analytics software such as Proficy CSense from GE Digital to mine insight from historical data and rapidly develop, test and deploy simple calculations, predictive analytics, and optimization and control solutions to reduce variability and improve operations.
From small projects to productized analytics solutions
All integrators can and need to develop capabilities in analytics and machine learning to remain competitive in the world of digital transformation.
Over time, integrators can go from small projects to pilots to packaging their success with analytics as a productized offering – for a greatly enhanced revenue stream. Integrators’ deep domain expertise provides a foundation for modelling processes and developing the analytics that are game changers in very specific applications.
The combination of applied analytics technology with those process twin models are repeatable solutions that can be implemented over and over again, with greater margin achieved on each implementation for higher value optimization for customers and higher value for the integrator.
For your customers ready to optimize with analytics, GE Digital’s Proficy CSense turns raw data into real-time value with a Process Twin. The software uses AI and machine learning to enable process engineers to combine data across industrial data sources and rapidly identify problems; discover root causes; and automate actions to continuously improve quality, utilization, productivity and delivery of production operations.
Cobus van Heerden is senior product manager for analytics and machine learning software for GE Digital, headquartered in San Ramon, California.