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Here’s the latest example of a new occasional feature in eWEEK called IT Science, in which we look at what really happens at the intersection of new-gen IT and legacy systems.
These articles describe industry solutions. The idea is to look at real-world examples of how new-gen IT products and services are making a difference in production each day. Most of them are success stories, but there will also be others about projects that blew up. We’ll have IT integrators, system consultants, analysts and other experts helping us with these as needed.
We’ve published similar articles to these in the past, but the format has evolved. We’ll keep them short and clean, and we’ll add relevant links to other eWEEK articles, whitepapers, video interviews and occasionally some outside expertise as we need it in order to tell the story.
An important feature, however, is this: We will report ROI of some kind in each article, whether it is income on the bottom line, labor hours saved or some other valued business asset.
Today’s IT Science Case Study: Certuss
Germany-based Certuss makes steam generators that are used in a large number of industries, including automotive and construction, food and beverages, health and pharmaceuticals and service and hospitality. These generators are used in heating and sanitation, hospital sterilization, laundries, breweries, wineries—a wide number of products and services.
Name the problem to be solved: Establish real-time analytics and predictive maintenance of Certuss steam generators in various use cases.
Describe the strategy that went into finding the solution: Certuss, an expert in steam generator product engineering but not IT, sought expert assistance from numerous M2M/IoT connectivity and data analytics experts prior to finding a partner in Deutsche Telekom (powered by Cumulocity IoT), which could deliver what it required.
List the key components in the solution: Cumulocity IoT platform tenant fully rebranded for Certuss; plug-and-play integration with IoT gateways, supporting Cumulocity’s Cloud Fieldbus; online storage and on-demand distribution to Certuss’ business analysis systems.
Describe how the deployment went, perhaps how long it took, and if it came off as planned: The initial pilot connected a small number of steam generators and exported the real-time status of more than 60 operational parameters to the machine-learning model for a period of six months; the resultant machine-learning model quantified some initial assumptions and also created some new insights for the operation usage.
Describe the result, new efficiencies gained, and what was learned from the project: There have been measurable improvements in four areas: service-level improvements (through fix before fail); supply chain efficiency (through accurate demand information); customer cost savings (through demand-based performance): and improved product innovation (through high quality in-life usage information).
Describe ROI, carbon footprint savings and staff time savings: Steam generator uses energy related only to the demand it needs to satisfy; servicing only needs to happen when required (saving field service time and vehicle fuels; spare parts manufacture and shippage); customers have their service assured. Certuss has reported substantial bottom-line savings in operation costs and in employee supervision time.
Certuss, founded in 1957, counts among its customers Procter & Gamble, NXP Semiconductors, TS Clean, Yards Brewing Co. and Johns Manville Textiles, among others.
For more information on Certuss case studies, go here.