如何利用大數(shù)據(jù)優(yōu)化供應(yīng)鏈?
Optimizing Supply Chains with Big Data
In the age of digital transformation, businesses are looking to optimize their supply chains through big data management. By tapping into data from various systems, companies can gain insights and improve the efficiency of material production and delivery processes while reducing costs.
Real-life Application of Big Data in a Manufacturing Plant
A notable example is Gree Electric Appliances’ manufacturing plant in Wuhu, China. The company leverages data analytics across four key areas: logistics analysis, operational efficiency monitoring, production line monitoring, and quality control.
1. Logistics Analysis
Gree’s plant uses a large display screen to monitor real-time operations and detect any inefficiencies or issues in the supply chain. The system also tracks material inventory levels for each storage location in the warehouse.
2. Operational Efficiency Monitoring
The company monitors order completion rates, picking progress, and product assembly status, as well as the efficiency of individual production machines.
3. Production Line Monitoring
Data collected by MES and MPR systems are processed and analyzed in Yonghong Z-Suite to enable real-time multidimensional analysis of processes such as material matching inspections. This has resulted in IT staff productivity gains of over 30 percent.
4. Quality Control
Gree's previous quality control strategy relied heavily on manual data collection, Excel spreadsheet analysis, and pie charts. By leveraging big data analytics software, the company is now able to identify production issues in real-time across multiple dimensions including teams, shifts, and factories.
By analyzing data across the entire supply chain, Gree Electric Appliances is able to significantly increase the efficiency of material management, production processes, and logistics. The use of big data analytics has also reduced defect rates in production, resulting in considerable cost savings.
In summary, the key benefits of leveraging big data for supply chain optimization include:
1. Comprehensive monitoring of all data points in the supply chain through BI analysis.
2. Improved material inventory matching and better control over production processes to increase efficiency.
An optimized supply chain can reduce costs and even make traditional warehousing obsolete, with materials being transported directly from one point to another in mobile warehouses. Companies that leverage big data management for their supply chains are able to transform their operations, save on costs, and gain a competitive edge in today's market.
<本文由himall原創(chuàng),商業(yè)轉(zhuǎn)載請聯(lián)系作者獲得授權(quán),非商業(yè)轉(zhuǎn)載請標(biāo)明:himall原創(chuàng)>
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