We asked: When will critical decisions regarding pipeline maintenance and repair actions be made by computer systems based on machine learning and data analytics for predictive maintenance, rather than humans?

a.  It's happening today
b.  In less than 5 years
c.  In 5 to 15 years
d.  It's never going to happen

Poll Results

For the first time (in our polls), you are not all on the same page! We were surprised to see how evenly spread your answers were! Although not everyone agrees when, something we all seem to agree on is that it will happen, sooner rather than later. Perhaps one reason why we cannot agree on when it is happening is our understanding of what machine learning or automation really is. If we are talking about using machine-learning algorithms to sort and prioritize data, we are already doing that today. However, if we are talking about robots sitting at our desks analyzing data and making pipeline maintenance and rehabilitation plans, no, that will likely never happen.

Either way, there is definitely value in allocating more resources to automation. However, in all of this autonomous thinking, we cannot eliminate the human factor and the benefits our cognitive abilities bring to the table. Michael Smith said it perfectly in his article “Repair or Replacement?” posted on LinkedIn: The “purpose of machines should be to enhance our abilities and ‘repair’ our flaws, but not to replace us.”

In response to your answer, our next question gets a little more specific, so please participate in this edition’s poll question.

In which area do you believe automation will have the biggest impact for the management of industrial assets?

a. Process Optimization
b. Data Collection
c. Data Analysis 

Please vote within your newsletter.


Learn more about integrity solutions

Comprehensive asset care does not stop with operational efficiency activities and the collection of data. It integrates these results from several years to identify behavioral patterns and trends to predict, amongst others, lifetime of assets. This is what comprises the integrity component. At ROSEN we are proud to host one of the largest integrity engineering teams in the industry with several hundred years of combined project experience.