A typical manufacturing plant floor is a highly hybrid and complex environment, with interconnected machines from different vendors, people with varying skill sets and complex supply chains. Manufacturers often face challenges such as defective products, on-time delivery slippage, excessive scrap and rework, unacceptable equipment downtime, and supply chain disruption. Information silos and manual data collection add complexity to making near- real-time operational decisions.

As the number of assets and production facilities increase, it becomes more difficult to diagnose and react to these challenges in a timely and scalable manner. Manufacturers can prevent such operational challenges and ensure effective and efficient resolution by unlocking insights derived from operational data. Otherwise, these difficulties can negatively affect production schedules, lead to higher production costs, lost profits, missed order fulfilment and reputational damage.

Lumada Manufacturing Insights provides a progressively intelligent manufacturing maturity model with foundational digital tools essential to Manufacturing 4.0. It leverages AI and ML techniques, as well as 4M industrial analytics to provide machine, production and quality insights. Customizable, composable software modules within Lumada Manufacturing Insights helps improve on-time delivery (planning and scheduling optimization), minimizing defective product, scrap, and rework (maximizing first-pass yield) and reducing unplanned equipment downtime (predictive and prescriptive maintenance), as well as quickly and effectively reacting to external factors such as supply chain disruptions upstream and downstream of the factory floor.

In summary, Lumada MFI helps maximize performance on the plant floor by applying industrial analytics using composable software that offers features such as:

1. Machine Productivity Optimization

Granular visualization of overall equipment effectiveness (OEE) in near real time allows production managers to quickly identify machine- related issues and take corrective action.

i. Promptly respond to issues that impact plant productivity: Stoppages (unplanned), idling and slow cycles, and rejects (startup and production).

ii. Track asset availability, performance, and quality for various pieces of equipment, regardless of type, vendor, model or year.

2. Operational Threshold Monitoring and Alerting

i. Timely detection of actionable events allows rapid reaction to take corrective action.

ii. Rapidly respond to performance, quality and availability-impacting events.

3. Maximize First-Pass Yield

i. Forecast impending quality issues.

ii. Enable quality kaizen to minimize scrap, rework, and returns, and maximize first-pass yield.

4. Anomaly Detection

i. Proactively detect unseen equipment degradation even if individual operating parameters are within threshold.

ii. Proactively react to changing conditions on the shop floor, before issues occur or spread.

5. Edge Data Collection and Processing

Connect and filter with common industrial protocols such as OPC-UA, MQTT and MTConnect, as well as proprietary controller protocols and APIs.

i. Collect and analyze data on the edge, even in environments with intermittent connectivity.

ii. Enables basic data extraction from machines and other industrial equipment for analytics, visualization, and notification.

6. Production Scheduling Optimization, Powered by AI

Apply machine learning models to data from enterprise resource planning (ERP), manufacturing execution system (MES), and machine or operator data.

i. Optimize production scheduling to fulfill customer orders, despite changing conditions at the factory floor.

ii. Quickly adapt to changing operating conditions at the plant floor, minimize changeover time, and avoid impacting customer order fulfillment.

7. Enhance and Ensure Worker Health and Safety

Reduce risk and optimize safety strategies with a holistic data analytics solution using video, 3D Lidar and sensors. See all your data on a single pane of glass, with unlimited layers of assets, objects, equipment, vehicles, cameras, IoT sensors and statistical information.

i. Gain granular, continuous intelligence using 3D Lidar.

ii. Gain the ability to see alerts, and slice and dice your data in graphical form.

Benefits

1. Up to 13% improvement in operations efficiency through better material flow and supply chain logistics.

2. Up to 15% reduction in equipment-caused quality anomaly due to a shift from reactive to predictive maintenance.

3. Up to $18M a year reduction in maintenance costs arising from predictive diagnostics and guided repair.