Holcim has invested in UK technology company Cloud Cycle to extend real-time concrete quality monitoring from batching plants into mixer trucks, using in-truck sensors, edge computing, and machine learning during delivery.
The technology is already installed on more than 150 Holcim mixer trucks in the UK, Italy, and Switzerland. Holcim intends to accelerate deployment across its wider fleet while integrating the system with other digital quality tools used in its concrete and cement operations.
Cloud Cycle monitors concrete between the batch plant and the point of discharge, collecting operational data while the material is in transit. The system is intended to give producers a continuous picture of delivery conditions rather than relying solely on the original batch record and tests carried out before or after transport.
That fills a difficult gap in ready-mix production. Concrete leaves a controlled manufacturing environment but continues to change inside the mixer truck, with time, temperature, mixing, delays, and any water additions capable of influencing the condition of the load before it reaches the pour.
A producer can manufacture material correctly at the plant and still face problems at the construction site if conditions shift during delivery. Tracking the journey gives quality and dispatch teams more information when deciding whether a load remains within the required operating window.
Holcim says the technology can help reduce returned concrete while improving mix control. Returned loads carry direct costs in materials, vehicle utilisation, plant capacity, disposal, and replacement deliveries, while the cement already contained in rejected concrete carries an embedded carbon cost that cannot be recovered merely by sending another truck.
Cloud Cycle’s approach effectively treats the delivery vehicle as another part of the production system. Sensors collect information from the truck, local computing processes data close to the asset, and the company’s software platform turns those signals into information that can be used by producers during the delivery cycle.
That distinction becomes more relevant as concrete specifications evolve. Producers are increasing the use of supplementary cementitious materials, recycled components, and lower-carbon binders, all of which can alter workability, setting behaviour, and sensitivity to process conditions.
Lower-carbon formulations still have to arrive at site with predictable handling and performance characteristics. A material that reduces clinker content on paper but produces inconsistent deliveries will struggle to scale commercially, particularly on projects where placement windows and quality requirements leave little room for trial and error.
Holcim’s investment therefore links digital control with its wider materials programme. Earlier this month the company started a calcined clay production line in the Czech Republic, adding physical manufacturing capacity for lower-clinker cement products.
The Cloud Cycle deployment addresses a different stage of the value chain, but both developments depend on the same underlying discipline: new materials and lower-carbon processes still need repeatability, measurement, and quality assurance if they are to move beyond specialist applications.
Cloud Cycle also introduces a data-integration challenge. Ready-mix businesses already use batching software, dispatch platforms, laboratory systems, vehicle telematics, order-management tools, and quality records, often supplied by different technology vendors.
An additional stream of truck data is useful only if it reaches the people and systems capable of acting on it. Alerting an operator to a change in a load after discharge is considerably less valuable than identifying it early enough to alter delivery, investigate the mix, or prevent avoidable waste.
Sensor reliability and calibration are equally important. Concrete production is a demanding physical environment, and data-driven quality decisions are only as good as the measurement chain feeding the algorithm.
Machine-learning models also need validation against actual material behaviour. Concrete performance depends on raw materials, mix design, ambient conditions, process history, and site handling, so a model developed around one operating environment may require further work before it can be treated with equal confidence across a global fleet.
Holcim plans to use Cloud Cycle alongside systems including Q-Predict, its real-time cement-property prediction tool. That creates more measurement points across manufacturing and delivery, but it also increases the need for consistent data definitions, software maintenance, and clear responsibility when different systems produce conflicting information.
The investment was made through Holcim MAQER Ventures, which has completed 21 investments to date. For Cloud Cycle, the relationship provides access to a large international fleet where the technology can be tested across different truck types, plants, climates, materials, and customer requirements.
The useful performance measures are relatively conventional despite the machine-learning label: rejected loads, returned concrete, quality consistency, delivery reliability, plant utilisation, and the time required to investigate problems. If those improve across a wider fleet, the digital layer becomes part of production control rather than another dashboard attached to the concrete business.
