Industrial Analytics for an industry in change
Learn what industrial analytics are, how they contribute to revenue and why they could be your key to digital transformation in 2017.
Every business faces pressure to transform and meet the increasing demands of being a competitor in 2017. This requires the ability to leverage new technologies and identify opportunities for optimization.
One of the best ways to gain insight is to apply advanced analytics to the data generated by your revenue-generating assets and processes. Unlike generic analytics, industrial analytics solutions are designed to meet the exacting standards of the industry to which they apply. This includes the ability to process vast quantities of time series data from various sources, and turn it into actionable insights for the users. This makes industrial analytics relevant to any company that is manufacturing and/or selling physical products.
What are industrial analytics?
Industrial analytics (IA) refers to the collection, analysis and usage of data generated in industrial operations and throughout the entire product lifecycle.
As such, industrial analytics covers a very wide range of data captured from all kinds of sources and devices. Anything with a sensor creates data – and industrial analytics looks at all this data. The great variety of sources can create a lot of confusion, misconceptions and even disappointment in the market for those who are taking the first steps to bring the promise of Industry 4.0 into their organization – but the potential benefits are huge.
The benefits of industrial analytics
With an industrial analytics solution, you can gain insight into all your assets and processes. Previously hidden trends and patterns become clear and can inform your decision-making. From high-level performance monitoring to the most granular investigations, industrial analytics deliver insight where it is most needed: in safety, efficiency and performance.
That’s the high level benefit to a business owner – but there is another level of benefit that is often missed: the level of the user. If you use an industrial analytics solution that focuses on self-service, you can gain benefits in the day-to-day running of your plant(s) too. This includes improved root cause analysis, objective performance prediction, automated monitoring and knowledge retention (a critical issue in an aging workforce). By sharing analytics insights with users, they are able to take action immediately when a trend appears. This allows users to directly contribute to improving overall plant performance.
A note on time
Many people wonder if this type of analytics is worth the time needed to get started.
The answer is: Yes! And not just in the long term…
With a self-service industrial analytics tool like TrendMiner, the benefits may be big – but the time investment is very small. You don’t need to wait while a data model is being selected and built – you can start immediately after deployment by analyzing the historical and live performance data from your own assets and processes. You don’t need a long implementation project either – the software is plug and play, and can be implemented by your own IT team within an hour. Likewise, long trainings are not required, because the interface is designed for users: a simple interface that is easy to operate and quick to learn.
So you do not need to invest time to start saving time.
Is your organization ready to leverage industrial analytics on the work floor?
Why not contact us to discuss your specific needs – you may be more ready for transformation than you think.
More information?
See 5 ways to improve production with self-service process analytics. Discover how a self-service approach allows your process engineers and subject matter experts to analyze, monitor and predict process performance without depending on data scientists.
