Manufacturing Optimization
Optimizing Depots and the Industrial Base
Providing decisive advantages to the warfighter begins with optimizing throughput inside the defense industrial base. Manufacturing optimization means surfacing and applying insights faster and with more efficacy from systems, processes, and people—a level of performance made possible by AI-enabled systems.
US Navy estimate of budget required to implement Shipyard Infrastructure Optimization Plan (SIOP).
Amount of man-hours saved on testing through implementing AI-based visual inspection solution.
Average of 10 days advance warning to pending machine failures enabled by AI predictive maintenance solutions.
DoD depots, shipyards, and aerospace and defense manufacturers are complex environments with numerous variables that impact quality, efficiency, regulatory compliance, worker safety, and environmental sustainability requirements.
Minimizing asset failures and accidents is critically important to maintaining production tempo and managing costs. But most of the industry still relies on preventive maintenance to avert failures, checking and repairing assets at pre-scheduled intervals. This is preferable to allowing assets to otherwise fail, but inherently wasteful, burning valuable time and resources on assets that may not need repair, while still often failing to catch unexpected or unusual failures.
Machine learning that leverages the sensor data the defense manufacturers already have enables a better approach—predictive maintenance—detecting true-positive emerging asset failures before they occur with time to schedule cost-effective maintenance while leaving alone assets that are exhibiting normal behavior. Further, by incorporating unstructured data, maintenance solutions are able to ingest historical records and service manuals, as well as past courses of action taken by subject matter experts. Using this diverse set of data, the solution can speed up maintenance processes by listing possible next steps and suggesting corrective measures closing the loop of what typically are unfinished jobs.
How AI Optimizes
Manufacturing Efficiency
By leveraging historical records like work instructions and job guides, manufacturing staff improve time to resolution when addressing true positive alerts.
- Reduce idle time and stoppages.
- Increase OJT efforts.
- Resolve gaps in workforce skills.
Monitoring and alerting on safety issues in real time using autonomous computer vision solutions prevents injury and downtime.
- Ensure PPE compliance.
- Analyze field reports for potential hazards.
- Mitigate dangerous equipment failures.
Identifying and alerting on asset issues allows the industrial defense base to improve throughput and reduce overall cost of the value chain.
- Receive advance notice of failures.
- Extend asset lifetimes.
- Optimize process efficiency.
Solving The Problem
SGS Industrial AI Platform for Defense provides a scalable solution that harnesses the power of AI to enable real-time KPI monitoring, proactive maintenance systems, and 360° visibility into operations, enabling defense manufacturers to extract actionable insights from configurable data pipelines connected to structured and/or unstructured datasets. Perfected over ten years of real-world engagements, Industrial AI Platform has yielded outcomes in past deployments, including the ability to increase production efficiency by up to 20%, alert on pending failures days, if not weeks, in advance, and avoid potentially millions of dollars in maintenance costs.