Energy efficiency improvements are a critical way for dairy processing plants to reduce energy costs, lower emissions of energy-related pollutants, and reduce susceptibility to volatile energy prices.
As is well known, spray drying is by far the most common process in dairy and whey processing. The downside is the energy required. By linking energy flows and using waste heat through heat recovery, many dairy processing plants have been able to increase energy efficiency. However, there still remains a gap between additional efficiency opportunities and the energy savings initiatives implemented.
Drying is one of the oldest methods of preserving food. The removal of moisture reduces water activity in food, which delays the growth of vegetative microbial cells and prevents the formation of germs, moulds and bacteria. When liquid is transformed into dry powder, almost all moisture is removed from the food. Thanks to their low water content, products in concentrate or powder form not only have a longer shelf life, but are also easier to transport and store.
However, dairy and other produce are sensitive to heat. Their functional properties and digestibility can be seriously affected by the influence of heat treatment after water separation. It is therefore evident that a single water removal process cannot provide optimum results throughout the dehydration process. Depending on the product, several successive process steps are therefore required. Two main water removal processes are used in dairy and feed processing:
Vacuum evaporation: In this process, the liquid is separated from the produce and a low-viscosity liquid such as milk is converted into a relatively high-viscosity concentrate.
Spray drying (SD): To convert this concentrate into powder, small droplets are sprayed into a hot air stream.
Roller drying, in which the milk concentrate is applied in a thin layer to rotating drying rollers, is another process used, for example, in chocolate production.
Vacuum evaporation and spray drying plants are among the biggest energy guzzlers in the dairy industry, requiring pasteurisation systems, homogenisers, pumps and compressors. For example, around 1.1 kilograms of steam is necessary to evaporate 1 kilogram of moisture from a product. According to experts, the energy costs for this are around 2,700 kJ*kg-1.
In order to fully exploit the energy-saving potential in milk processing, it is necessary to obtain information on the energy consumption of each product, depending on its physico-chemical properties, the technology used and the external conditions, in real-time.
Energy utilisation and peak consumption
Suppliers prefer customers with constant, high capacity utilisation (load factor). If these have a sudden peak, the suppliers have to keep energy on standby to meet the unexpected demand. Supply customers are usually "punished" with higher tariffs for such peaks.
Energy efficiency requires a structured and persistent approach
The first step in optimising energy efficiency is to lay the foundations. Obvious problems should be eliminated immediately and untapped savings potential should be uncovered. Initial results can be targeted with reactive power condensation, insulation materials, new and more energy-efficient devices and regulated electronic drive systems.
Monitoring and ongoing efficiency analyses help to maintain these savings
To create the necessary transparency, SolutionSync offers an IoT-based energy monitoring and visualisation solution that displays the consumption of electricity, gas and steam (kW) in relation to the output (to.), the operating state of the spray-drying equipment (e.g. standby, production, water, CIP), the outside conditions, the product and the work shift, in the form of a time stream in an attractive dashboard - in real time.
Complex installations, as is common in the dairy industry, require the best data connectivity specialists who not only bring a wealth of experience from the dairy industry, but also deliver robust, safe and reliable solutions.
The system is provided ready to use in a loaded stainless steel cabinet. The plant's electrician only needs to install the data acquisition devices.
Ideally, the raw data is collected from the PLC via Open Platform Communication (OPC), otherwise industry-proven, safe, intelligent, wired or wireless sensors are used. Near the plant, the collected data is first stored and pre-processed in a time series database and then further processed and evaluated in the cloud-enabled analysis software by sophisticated AI or machine learning, either locally or in the cloud.
What makes a good batch?
In addition to monitoring energy consumption, the collected data is analysed for a variety of additional tasks. For example, to investigate the parameters influencing product quality of a batch, to avoid waste, to report process malfunctions at an early stage and to analyse the causes of unplanned machine failures. Thanks to the open interface, context data from ERP and other systems can be integrated into the AI-based analysis and visualisation.
5-10 percent energy cost reduction despite energy recovery
With this complete transparency, a well-known baby food producer was able to reduce its energy costs by 5 to 10% annually despite energy recovery. This was achieved by the consistently optimal, demand-oriented provision of energy in coordination with the process steps of the spray drying plant and the reduction of energy losses. The findings from the measurement data obtained and visualised have ensured that management was able to implement target-oriented savings measures. The real-time dashboards in the production rooms have also strengthened the sense of responsibility of the employees.
Savings can be lost easily
Unplanned, uncontrolled failures of plant and equipment or lack of condition monitoring of motors and equipment can eventually completely ruin the purported cost savings or even turn them into the opposite.
Without energy and condition monitoring of equipment, Topmotor.ch calculates, up to 12% of savings can be lost.
Fotos: Brian Robinson ✝︎; Smart Factory, Limerick; SolutionSync