Ctrl2GO's predictive software cuts maintenance costs by 20%
Ctrl2GO claims its PMM software (Predictive Maintenance and Monitoring) has helped energy and industrial clients cut their equipment maintenance costs by 20 percent in 2020.
The solutions developed by Ctrl2GO are designed to efficiently process and analyse big industrial data, assessing the technical condition of the equipment and predicting its potential behavior. Such an approach allows companies to streamline maintenance processes, extend overhaul intervals, and prevent up to 80 percent of equipment malfunctions.
Over the past year, companies using PMM software packages have reduced downtime and unplanned repairs by 20 percent, and cut direct repair costs by 5-8 percent. Diagnostics lead times have been reduced by 90 percent, while the technical productivity of staff rose by 15-22 percent.
A definitive case that illustrates the effectiveness of the PMM solution is the servicing of 'a metals mining and processing giant' that saved $510,000 due to higher reliability of the equipment. The issues faced by the client involved the insufficiency of reliability of the equipment that caused unplanned failures in the operation of boilers and turbines, leading to a loss of revenue due to downtime.
The solution developed by Ctrl2GO provided technical condition tracking, which was integrated into a single maintenance and repair process of the enterprise equipment. This resulted in a unified approach to monitoring different equipment fleets and a transfer of existing technologies to previously unfamiliar equipment. As a result, the client managed to reduce repair costs by $50,700, and increased revenues while reducing equipment downtime to $455,000.
Another example saw an energy client reduce electricity consumption of 139 injection pumps by $10 million per year. Initially, the pumps consumed more power than necessary, which resulted in increased energy costs and shortening of the pumps' lifespan.
The deficiencies in the infrastructure for data collection on energy consumption were solved and a concept of digitalization focused on the reliability of the equipment was developed, reducing electricity consumption and prolonging the useful life of $10 million worth of equipment, while energy efficiency increased by 4 percent.
The changing business environment, in which the demand for the automation of human labour and the optimisation of industrial processes is on the rise, is paving the way for the growth of the predictive analytics software market. The global market for predictive analytics is set to grow to $22 billion by 2027, up from $6 billion in 2020, according to ReportLinker.com.
New Perception of "Complete" with Connected Field Execution
Our individual perception of reality is often a direct result of our experiences. For example, if you’re in your kitchen prepping a cheeseburger with the lettuce, tomatoes, cheese and bun, you might see your “project” as about half done, just waiting for the patty. The person at the grill in charge of cooking the patty, however, may see the same project as 90% done once their step is complete, with all those other items needed to make a complete cheeseburger as just “extras.”
Translate this idea to construction execution, where instead of a burger you have a foundation with an integrated slab. One engineer might look at the excavated footing and intricately placed rebar and say we're about half done. But that slab could be 10,000 square feet, broken into multiple pours and much larger than the exterior footing. Until you make progress pouring the slab, you really can't say that you’re about half done with such an operation. So, how can we add reality to what each party perceives as “complete” without overcomplicating our progress workflows? By standardizing realistic progress tracking details and seamlessly submitting them through real-time, connected data processing.
Slicing and Dicing Complex Data — Tradition versus Technology
Think back to the most extreme level of detail you were ever asked to track during construction work planning and execution. How did you manage to do it? While crews have traditionally managed by working off a printed to-do list, more often than not, we see customers migrating to the engineer’s best friend; a spreadsheet of some sort. One might argue that this is using technology to simplify things, but in such a disconnected state, it may not be the best option.
Let’s say you’re dealing with the electrical side of a project. Cable, conduit, cable tray, boxes; all these different electrical components are very detailed, very specific and often in huge volumes. Tracking each of the cables on every project can be extremely difficult, often expanding your list by 500 to 10,000 extra line items. Plus, you’re not only tracking where they're being installed but also the inventory. Is there enough cable on site to continue? Will the team be ready on time where the cable is to be installed next?
Trying to capture where they go and when they are installed on a to-do list can be daunting. In fact, one of my colleagues once had to print 11 X 17 copies of the cable schedule, carry them out to the field and physically mark items complete on paper. Then he had to come back and enter all that data into each of the siloed systems, including the progress spreadsheet. Definitely not a fun process, and time wise, it took him an average of three extra hours a day on top of his eight-hour shift. But it’s from experiences like this that we can begin to understand the true importance of technology and why it's crucial to eliminate duplicate entry and manual tracking in the field to not only bring data together, but save so much time, money and frustration.
With today’s connected data technology, you can deal with complex, large amounts of progress data that don't naturally translate well from one business process to another — from high-level budget codes to detailed quantity step in the field. This is the challenge that technology can solve; how to slice and dice data sets, especially when they're not in the same format, and aggregate them back together again.
Standardizing Details to Remove Unconscious Data Biases
While connected data flows and the end of manual entry are great, standardization is the true key to a more accurate picture of reality. Suppose you were to ask a superintendent, what percent complete are you on this scope of work? They’d put their thumb in the air, tilt their head one way, and finally say 50%. But what if, in reality, you’re only 48% complete with that scope of work? (We know that people tend to round up, not down due to optimism bias.) That 2% may not seem like a huge difference to them on paper, but if that scope of work is worth $10 million, then 2% is throwing your forecast off by $200,000.
And as the numbers keep getting bigger, how much of your forecast will you really be able to rely on? As different people on the jobsite continue to give you their best guesses, you begin to see a sway with where things are in your forecast. The fallout out from these inaccurate guesses can lead to the misidentification of issues that could have been be resolved, as well as problems with your schedule. Because when we're talking percent complete, we're really looking at how everyone is performing against both cost and schedule.
By introducing standardization, you can also start to become a learning organization. For example, if we dissect an erect and strip formwork code into weighted steps of 60% for form and 40% for strip early on, we may eventually find that we are not spending that much up front. Maybe it's really 55% for form and 45% for strip. When you start learning as a team through standardization, you can make those decisions at an organizational level, meaning that everyone is standardized — and adjust accordingly for overall success. People start trusting those numbers, and that builds confidence in the progress you’re reporting and in its accuracy. Then, you can start making informed decisions on that data.
Aggregating Project Data in the Fewest Steps Possible
Another place where it has been traditionally tough with paper and spreadsheets is in the steps needed to aggregate progress data for different reports or dashboards. Fortunately, this is also an area where connected data can help. Say that you took what was a single weld and broke out the important steps, including quality steps that could quite literally make or break that weld. How will you take these simple counts of welds and slice that into the very important detail of what is safe?
With connected data software, now you not only know at a glance if the weld is complete on a high-level report, but you can also drill down into a more granular view of who completed each step and signed the final paperwork. It is this kind of component-level detail you need to see, when you need to see it. The power of that detail is magnified because those components sit below all your different work breakdown structures. Progress data can now roll up to schedule activities in a more precise manner, to cost structures, or even roll up to some alternative structure like turnover packages or test plans to see progress in those phases.
Why does all of this matter? Because now you know you have eliminated the optimism bias and your own personal biases in the tracking of work progress. It’s very exciting to be able to have progress tracking that is this accurate with percent complete fed to all these different higher-level structures in such detail, with no manual intervention required. Because when you have all of the data digitally tallied among thousands of items — whether you are talking about welds or the piece marks of steel or the cable schedule — if you associate the correct metadata to those items, you can easily roll that structure back up into whatever you need it to be.
A Culture of Connected Learning From the Field
Making all of this detail accessible to all of your stakeholders is not only going to help with progressing data, but it will also increase project certainty for everyone. The procurement group will know when to make a requisition based on how things are tracking. The accounting department will have all of the data they need to process billing. And the leadership team will have trust in the information because it’s coming directly from the field with standardized detail.
Perhaps most importantly, you can take information from past projects and use it on the next estimate to confidently win more work while you enhance construction work planning and operation efficiency through lessons learned. And that kind of learning starts to have a ripple effect. The improvement in efficiency makes data more reliable, makes accurately tracking progress in the field easier, and allows your team to remove the guesswork from progress tracking.
However long you may have been working in the field, there will always be an element of bias in what you perceive at a glance to be complete. But with today’s connected data technology, you can remove this bias through a standardized level of detail for tracking progress in the field and a real-time connection back to each work breakdown structure. The time is right to add certainty to your projects and remove the “thumb in the air” guesswork of what is truly complete.
InEight's connected construction analytics solutions help you make real-time decisions because you’re gaining visibility into metrics, KPIs and trends, driving continuity in operations. Request a demo.