Bake to the Future
Smart technologies, such as the industrial internet of things (IIoT), cloud computing, smart sensors, and neural networks, have been revolutionizing various industries in recent years, and the baking industry is no exception. These technologies have been implemented in various stages of the baking process, from ingredient sourcing to finished product distribution, to improve efficiency, quality, and safety.
The industrial internet of things (IIoT) refers to the interconnectedness of industrial devices and machines through the internet. In the baking industry, IIoT technology can be used to monitor and control the various stages of the baking process, from mixing and fermentation to baking and packaging. For example, sensors can be placed on mixing machines to monitor the temperature, humidity, and consistency of the dough, and adjust the mixing speed and time accordingly. This can help to ensure a consistent product quality and reduce waste.
For technology specialist VMI, for example, the latest innovations upgrading their mixers relate to automation and the feedback of data allowing better control of the process. Their continuous mixers provide graphs and visual metering of motor intensity, dough temperature, glycol valve openings and mixing energy data, which ensures stability to the production procedures and the proper tools to control the consistency of mixing. VMI’s continuous mixers make it possible to automate the flow management towards resting phases or for a transfer to the line, while also reintegrating the dough scraps.
Reading Bakery Systems‘ expertise also allows their Exact Mixing technology to collect virtually all ingredient measurements, including instantaneous rate, temperature, and, in the case of liquids, viscosity. Gravimetric metering measures ingredient rates to a 0.5% margin. PID controls to handle the rate precisely and all data is saved and available to the operation at the HMI. With recipes stored in the mixer in advance, the operator only needs to know which recipe to select, what throughput is required, and the total amount of dough to be produced; everything else is controlled by the interface. The mixing energy is measured to be sure the produced dough is well developed. “Data is collected during operation to ensure the process is correct. Also, statistical data is collected to help understand the process and develop new processes in the future,” the company’s specialists explained, adding that they see manufacturers increasingly asking for smart features such as real-time data that allows the system to adjust to changing conditions without an operator’s intervention, an area in which this type of technology excels.
Cloud computing is another important technology that has been used in the baking industry. With the help of cloud computing, baking companies can store and process large amounts of data, such as production and inventory data, in a centralized location. This data can then be analyzed in real-time to identify patterns and trends, which can be used to improve the overall efficiency and productivity of the baking process. For example, a baking company can use cloud-based analytics to identify the most popular products and adjust production accordingly, reducing the risk of waste due to overproduction.
In order for data to be analyzed, it needs to be collected first. Smart sensors are devices that do just that – collect and transmit data, typically in real-time. In the baking industry, smart sensors can be used to monitor various aspects of the baking process, such as temperature, humidity, and pressure. This data can then be analyzed and used to optimize the process and improve product quality. For example, smart sensors can be placed in ovens to monitor the temperature and humidity inside, and adjust the oven settings accordingly to ensure a consistent product.
Neural networks, a subset of artificial intelligence (AI), are computer systems modeled after the human brain that can be trained to learn and make predictions. These technologies are increasingly being used in the baking industry to improve efficiency, productivity, and quality. Neural networks can be trained to predict the ideal fermentation time for dough, based on factors such as temperature, humidity, and yeast type. This can help bakers to produce a more consistent and high-quality product, while also reducing waste.
Machine Learning & Blockchain
In addition to these technologies, other smart technologies such as machine learning, advanced data analytics, robots and blockchain have been used in the baking industry. Machine learning algorithms are used to predict trends in customer demand, enabling bakers to better plan and schedule production, while advanced data analytics can be used to optimize the supply chain, reducing waste and costs. Robots have also been implemented in production lines to automate certain tasks such as sorting and packaging, which reduces labor cost and improves efficiency. Blockchain is the perfect tool for those wishing to create tamper-proof records of production and distribution, allowing companies to track products from the farm to the store and ensuring product safety.
You can read the rest of this article in the January-February issue of European Baker & Biscuit, which you can access by clicking here.