AI Case Studies
Food
Through data simulation and predictive analysis, Profet AI aids the food industry in moving towards a direction of safety, health, high quality, and high added value.
Application Scenarios
Process Optimization, Product Quality, Market Forecasting
Status Quo
In Taiwan, the food industry serves as a crucial pillar of the economy, facing new opportunities and challenges brought by globalization and rising consumer demands. According to the Ministry of Economic Affairs of Taiwan, the output value of Taiwan’s food manufacturing industry reached NT$951.6 billion in 2022, accounting for 4.8% of the total manufacturing output.
Challenges
As consumers’ demands for food safety and flavor continue to rise, the food industry faces numerous challenges, including quality management, traceability of raw materials, and bottlenecks in new product development. These factors bring diverse needs and changes to the global food industry. Looking ahead, we believe that the food industry will develop towards safety, health, high quality, and high-added value.
Milk Demand Forecast
The rising prices of raw materials have led to an increase in both inventory and procurement costs. Additionally, the food market’s demand is highly volatile, making predictions based on past sales experiences potentially inaccurate.
Pain Points Analysis:
- Traditional Forecasting Limitations: Relying solely on personnel’s past experiences for predictions, without proper analytical tools, severely limits forecasting accuracy.
- Perishable Raw Materials: In the food industry, most raw materials have a limited shelf life, leading to wastage if overpurchased.
- High Demand Volatility: Market fluctuations are more pronounced than ever, with over-purchasing resulting in waste, and under-purchasing causing production line stoppages due to material shortages.
Outcome Benefits:
- Optimize manufacturing processes through data-driven simulations, improving the accuracy of production and sales planning by 5%.
- Leverage advanced analytical tools to accurately forecast demand, reducing raw material waste and lowering costs by 9%.
設備糊管異常預測
優酪乳生產過程中，管道是將牛奶和優酪乳菌培養物運送至發酵罐以及成品運送的關鍵；
然而，管道異常可能導致生產中斷和品質問題。
Pain Points Analysis:
- 緊急維修成本高：管道異常導致生產停擺，需要進行緊急維修，增加維護成本
- 影響因素多：管道受溫度、原料特性等多種因素影響，難以透過傳統統計方法找出問題點
- 產線停擺：若設備異常導致產線停擺，將影響產量和交貨
Outcome Benefits:
- 透過要因分析，找出影響設備異常的關鍵要因，提升產品品質 7.6%
- 運用模擬功能，提早檢測機台是否異常，避免設備停機，減少製造成本 8.8%
Predicting Equipment Clogging Anomalies
In the yogurt production process, pipelines are crucial for transporting milk and yogurt cultures to fermentation tanks and for delivering the finished product. However, pipeline anomalies can lead to production interruptions and quality issues.
Pain Points Analysis:
- High Emergency Repair Costs: Pipeline anomalies cause production halts, necessitating emergency repairs, which increase maintenance costs.
- Multiple Influencing Factors: Pipelines are affected by various factors such as temperature and raw material characteristics, making it difficult to identify issues using traditional statistical methods.
- Production Line Stoppages: Equipment anomalies causing production line stoppages impact output and delivery schedules.
Outcome Benefits:
- Root Cause Analysis: Identifying key factors affecting equipment anomalies, improving product quality by 7.6%.
- Simulation Functions: Early detection of potential equipment issues, preventing downtime and reducing manufacturing costs by 8.8%.