Smart Sensors Drive Flour Mill Equipment Transformation and Upgrade

Smart Sensors Drive Flour Mill Equipment Transformation and Upgrade

Edited by: www.immyhitech.com   www.immy.cn 

In the wave of intelligent transformation of the global food processing industry, the wheat processing industry is facing multiple 

challenges of production efficiency, quality control and sustainable development needs. In this paper, we will systematically 

analyse the application scenarios of intelligent sensor technology, discuss the technical route and implementation strategy 

of flour mill equipment transformation and upgrading, and provide the industry with a digital transformation programme 

that can be implemented. 

First, the intelligent transformation of the flour milling industry background The current flour milling industry in China still has 

three major pain points:  

Process parameters rely on artificial experience: the traditional milling machine, flour cleaning machine operating parameters 

adjustment lack of real-time data support, flour rate and energy consumption fluctuations;  

Imperfect quality traceability system: key indicators such as ash, wet gluten and other key indicators lag behind in detection, 

batch consistency is difficult to ensure;  

High equipment maintenance costs: key equipment failure warning mechanism is missing, unexpected downtime resulting 

in significant capacity losses. According to industry statistics, the average energy consumption of flour mills using intelligent 

transformation is reduced by 18%, and the comprehensive efficiency of equipment is improved by 25%, which verifies the 

urgency of technological upgrading.  

Second, the core application scenarios of intelligent sensor technology 

(a) Raw material pretreatment process Near-infrared spectral sensors: real-time detection of wheat weight, moisture, protein 

content, to build a digital archive of raw materials, to achieve the precise regulation of the wheat preparation process 

(accuracy of ± 0.5%); machine vision system: high-resolution CCD camera to identify the type of impurities (such as stones, 

heterogeneous grain particles), combined with the pneumatic sorting device to achieve impurities rejection efficiency increased by 40%.  

(ii) Monitoring of the milling process Multi-spectral imaging sensor: online monitoring of the particle size distribution of the

 mill discharge, dynamically adjusting the pitch pressure through PID algorithms to ensure optimal grinding efficiency;

 Vibration sensor array: deploying MEMS vibration sensors in the mill roll bearings and transmission gearboxes, combining 

with the machine learning model to predict the remaining life of the equipment, and the accuracy of the failure warning rate of up to 92%.  

(iii) Closed-loop control of finished product quality Laser particle size analyser: replacing the traditional sieving method, 

providing real-time feedback of flour particle gradation data (shortening the detection cycle to 30 seconds); Electronic 

nose odour sensor: constructing a fingerprint of volatile organic compounds (VOCs), providing 48 hours' warning of the 

risk of exceeding the fatty acid value. 

 Third, the implementation path of technological upgrading and transformation 

(1) phased intelligent transformation program Primary stage: deploy sensor networks in the wheat dispenser, milling machine,

 packaging line and other key nodes, to establish a basic data acquisition system (single line transformation cost of about 80-1.2 

million yuan); advanced stage: build an industrial Internet platform, integration of ERP, MES and PLC systems, to achieve automatic

 optimisation of process parameters (payback period of about 2.3 years); Ultimate goal: Build a digital factory, optimise the layout

 of production lines through virtual debugging, and shorten the development cycle of new products by 60%.  

(2) Suggestions for selection of key technologies Edge computing gateway: adopt industrial gateway with TSN (Time Sensitive 

Network) protocol to ensure that the delay of real-time transmission of key data is less than 10ms; AI algorithm framework: 

develop special algorithm libraries for flour milling, including wear prediction model for grinding rollers, optimisation model

 for flour yield, etc.; energy management system: install smart meters in energy-consuming equipments such as air compressors,

 high-pressure fans, etc. to build a digital image of energy consumption. Energy management system: install smart meters in 

high energy-consuming equipment such as air compressors and high-pressure fans to build a digital portrait of energy consumption. 

Benchmark case study

A 1,000-ton-per-day wheat processing intelligent factory The project adopts the ‘5G+Industrial Internet’ architecture, 

deploys 327 intelligent sensor nodes, and achieves significant benefits: process optimization: through the dynamic adjustment 

of milling spacing, the electricity consumption of tonnes of wheat is reduced from 58kW-h to 47kW-h; quality enhancement: 

the range of fluctuation of flour ash is narrowed from ±0.08% to ±0.03%; innovation in operation and maintenance: the proportion

 of preventive maintenance of equipment is increased to 85%, and the annual maintenance ratio is increased to 85%, and the annual

 maintenance ratio is increased to 85%, and the annual maintenance ratio is increased to 85%. Maintenance ratio increased to

 85%, annual maintenance cost decreased by 42%. 

V. Future technology development trend Digital olfactory technology

Online monitoring device based on gas chromatography-ion mobility spectrometry (GC-IMS), realizing real-time detection of 

gluten odour; Flexible manufacturing system: developing reconfigurable milling module, supporting rapid switching of 

production of multiple varieties of flour; Blockchain traceability: combining with the sensor data to build a quality trust chain,

 to meet the traceability needs of high-end bakery flour.  

The intelligent transformation of the flour milling industry has entered a critical window. Through the organic integration 

of intelligent sensor networks, industrial big data platforms and advanced control algorithms, enterprises can realise a 

fundamental shift from experience-driven to data-driven. It is recommended that the main body of the industry develop 

a 3-5 year technology roadmap, prioritising the quality of the

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