Empowering Manufacturing Industry with Data Analytics

By using big data analytics, manufacturing companies can determine the market demand for products more accurately. With the help of Analytics technology, manufacturers can track and trace the entire supply chain, analyze the data, and streamline the entire process. Additionally, the supply chain may be more important for manufacturers than the production process, since inefficiencies can result in losses.

With Polestar Solution Analytics services, various challenges can be overcome, such as:

• Managing Automation and Human Labor- Companies can use workforce analytics to implement and measure workable staffing solutions, especially as they integrate more automation.
• Data breaches and cyberattacks- Manufacturers must take these considerations into account, especially as cyberattacks increase. It is important, however, to implement a data solution backed by enterprise-grade security to protect your data.
• Maintaining low operational costs- Users can respond quickly to ad hoc requests using search-driven analytics. Data visualization models can be embedded in shared workflows and portals for easy reading.

The manufacturing industry can benefit from Analytics in many ways, including:

• In order to improve the time to market for new materials for next-generation technology nodes.
• Achieving higher yields.
• In order to achieve zero defects in the manufacturing of devices.
• Reducing delays in the supply chain.
• It is possible for manufacturers to capture, cleanse, and analyze machine data quickly and to reveal insights that can assist them in improving efficiency.

The Key Use Cases for Analytics in Manufacturing are as follows:

• 1. Inventory optimization:

  Supply chain management involves storing raw materials, coordinating logistics, and distributing products. Data from multiple sources is required for a sound decision-making process.

• 2. Increasing workforce efficiency & safety:

  Increasingly, companies are implementing digital software and connected devices to reduce the need for manual data collection and documentation.

• 3. Analyzing customer feedback:

  Data analytics can also help businesses make better decisions. Analyzing feedback, buying patterns, and general market data can help you discover what your customers unconsciously want to tell you.

Big data transforms manufacturing in these three areas:

• Product quality: Most manufacturing companies prioritize product quality. Although manufacturers already have the quality data necessary to improve, they haven't been able to use it effectively.
• Maintenance: Real-time operational data can now be collected and analyzed from virtually any machine. In this way, maintenance and prevention can be predicted well in advance.
• Enterprise comparisons: By analyzing big data, we can quickly identify why production differs at different sites. By developing "what-if" scenarios, manufacturers can predict market futures.