How data logging taught Wientjens more about their machines in the field
Wientjens - The Dutch Water Company produces water and energy recycling equipment for textile laundries, for circularity benefits in the washing process. When they started looking into their machine data, they found that their impact on sustainability was bigger than expected. They got surprising insights. Both for machine performance and on how to deploy new service offerings at the right time.
It may not sound like a problem, but Wientjens runs into the issue that their machine quality is too high. On average, their recycling machines have a life span which is longer than the general life expectancy. This means customers don’t have to buy a replacement machine for a long period of time.
Few big malfunctions occur due to the quality of the machines, and maintenance is performed by the customers themselves. Wientjens had little insight into the actual operation of the machines, or how the equipment actually behaves in the field. Operator misuse or errors can result in a serious drop of output quality.
Wientjens has no intention to compromise on the quality of their machines going forward. So they came up with new service models to offer customers added value throughout the machine’s lifecycle. Their customers were not interested, at least not at the time Wientjens was offering the service. This is when Wientjens started thinking about how to offer their customers exactly what they needed, at exactly the right time.
“We realised that we could help our customers with our data,” says Gerry Wientjens, CEO at Wientjens. Data was only locally available at the PLC, without historical data. Even the HMI was only available on-site with insights for the operator. Wientjens needed a solution that enabled data visualisation in the cloud.
Wientjens came across IXON and now standardly equips every machine with an IXrouter. This enables them to remotely access their machines in the field, and more importantly, get access to data. Wientjens started logging data and created dashboards to get insights in their machines. Wientjens now analyses their data to see when their customers need what information in which form.
Data is worthless unless you are going to analyse and act on it
Based on machine data Wientjens can determine when’s the best moment to offer certain services to their customers. “We can see when maintenance is needed, and when the customer has done the required maintenance. We then offer them a spare parts maintenance kit to restock their used parts,” says Gerry. This way Wientjens adds value for their customers by unburdening them in terms of stock management.
Additionally, Wientjens is deliberately not offering extensive training packages in the initial quote since their experience is that this is often not perceived as valuable and only adds costs to the deal. Whereas, based on data on how the machine is used, they can tailor their training package to the right person with a specific demand throughout the lifetime of the machine.
However, data insights are not only used to get a better understanding of their customers needs, but also to create commercial benefits and USPs. First Wientjens didn’t know exactly how their machines were operating in the field, but data logging and analysis has yielded the following insights:
- Their machines need even less backflush water than they thought
- Their machines reduce water and energy costs with 50% on average in laundries
- The temperature of their insulated water tanks barely drops at night (only 1.5°C instead of the expected 15°C) which again positively affects the OPEX
The reliability, scalability and the ease of use of IXON Cloud convinced us. The intuitivity of the platform gives you the ‘Apple feeling’,
“Remote access and data visualisation in IXON Cloud create a win-win situation for both us and our customers,” says Gerry. Improved service for them, and a better view for us on how we can establish and strengthen the partnership with our customers. We can now provide valuable advice based on our machine knowledge combined with actual customer field data,” he concludes.
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