Having built up a huge library of data on different mixers, HF has also developed software to calculate throughputs required for specific tire production runs – to keep the mixer working efficiently. There are also packages to estimate manufacturing cost per mixing line and optimise workflow in the mixing room.
HF has recently set up a ‘3D database’ to analyse and present library data: by location, by mixing line, by production order, recipes, time and label data. This can provide data on individual or multiple mixing lines, and even multiple locations.
The next step, said Monyer, is to generate a 3D layout of the complete plant to help customers make decisions and reduce risk around selection of and investment in mixing equipment.
Furthermore, HF is working to establish two-way sharing of machine-status data with customers using localised cloud applications.
“Today we cannot compare the data from one machine to the other, from one customer to the other,” Monyer explained. “What we would like to do in the future is to collect this type of equipment information.”
To that end, HF has developed a ‘process data firewall’ that takes out all process-related and production-related data, and collects only equipment-status information from different mixing lines into a single database.
With such data, Monyer said “we can put it into a predictive analytics model and try to predict if there is a failure on a specific device, if there is a failure coming up in production. Therefore, we really need more data [and] would like to gather all the equipment information from different plants.”
As well as enabling customers to better predict downtime and spare parts requirements, these capabilities would help HF to optimise its manufacture of spare parts and reduce delivery times for items such as rotors and mixing chambers.
“So if we know that 50 mixing chambers will be worn out within the next six or seven months we could start to manufacture them,” said Monyer, pointing out that HF plans to start up a pilot project in this area by the end of this year.
“We hope that we can convince customers to participate in this in order to have a community, he concluded. “Getting this industrial mixing community together to collect data will benefit all of us.”
Jan Grashuis, vice president of global R&D at VMI, said that while many parts of the tire manufacturing and supply-chain process provide data that helps optimise use of materials and machine-time, “what is really new” is that you now get data from the tire.
At the Dutch tire-building machine maker, “we know our products, our sales channels, our customers but we now get a lot more information from the use of the end products,” said Grashuis – noting that this was particularly the case for truck tires.