Let’s look at how MaxInsighter can serve some of the main applications of data analytics in the Manufacturing space:
Predictive Maintenance
Leverage data to perform preventive maintenance before machine/equipment failure that may cause production downtimes. This benefits with:
- Cost Savings: from emergency repairs and product defects from equipment failures
- Extend asset lifespan: Predictive maintenance ensures equipment and machines are well-maintained before they reach catastrophic failures. This will prolong the equipment’s life and reduce the need for costly replacements.
- Minimize Downtime – avoid unnecessary downtime, maximizing production capacity to ensure a consistent supply of high-quality products.
Supply Chain Optimization
Having data managed and analyzed can empower manufacturers with optimal flow rates from procuring raw materials to delivery of finished goods to customers. This can happen with:
- Optimized & Real-time Inventory Management – the data insights can allow manufacturers to maintain optimal inventory levels and reduce costs associated with excess inventory & opportunity costs with limited inventory. It also helps in
- Accurate Demand Forecasting: Analyzing historical sales data to identify emerging patterns, and anticipate demand fluctuations, manufacturers can adjust their strategies accordingly to predict demands with greater precision ensuring they have the right quantities of the SKUs every time
Quality Control
With data analytics, manufacturers can consistently maintain high-quality levels and ensure quality control with lower defect rates, etc.
- Detect Prediction: By having predictive analytics in place, manufacturers can improve quality control by being able to foresee potential defects by analyzing data from various sensors, production logs, etc. with Industry4.0 by identify patterns that can indicate potential defects
- Early Intervention: Even if the analytics fails to predict potential defects, it can identify real defects as early as possible, allowing the manufacturers to intervene and make adjustments proactively to ensure that non-defective products proceed along the line.
- Root cause analysis: Data analytics can pinpoint issues by examining multiple variables and differentiate between correlations and causations to identify the actual source of the problem. Addressing the root cause will allow continuous improvement of manufacturing processes with a sustainable solution rather than just resolving immediate issues.
