Predictive Maintenance for Smart Manufacturing

Harness AI and IoT to revolutionize manufacturing. Predict equipment failures, optimize maintenance schedules, and boost efficiency, ensuring seamless operations and reduced costs for industry-leading performance.

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What You Can Do
Overcoming Unplanned Downtime and Costly Repairs
Unscheduled equipment failures disrupt production, delay operations, and increase repair costs. Predictive maintenance leverages AI-powered insights to monitor equipment health in real-time, ensuring uninterrupted production, minimizing costly repairs, and boosting operational efficiency.

50%

less downtime and 25% lower costs are achieved with AI predictive maintenance, preventing failures.

Enhancing Resource Allocation with IoT Automation
Manually tracking maintenance schedules is time-consuming and inefficient, leading to wasted resources. IoT-enabled automation streamlines data collection, optimizes workforce allocation, and ensures equipment operates at peak performance, driving productivity and cost-effectiveness in manufacturing.

40%

of maintenance labor is wasted, but IoT automation optimizes scheduling and boosts efficiency.

Reducing Escalating Inspection Expenses Through Real-Time Monitoring
Regular manual inspections inflate operational costs and increase downtime. Real-time monitoring with AI and IoT eliminates unnecessary inspections, reduces expenses, and ensures precise, timely intervention without disrupting production workflows or compromising quality.

25%

lower inspection costs are realized with real-time AI monitoring, eliminating redundant checks and downtime.

Forecasting Capital Needs with AI Analytics
Unplanned expenses from unpredictable equipment failures disrupt financial planning. AI-powered predictive maintenance analyzes data to forecast capital requirements accurately, enabling better resource allocation, streamlined budgets, and reduced risks of unexpected expenditure.

25%

cost savings and 20% longer asset life is achieved with AI analytics improving financial planning.

Why Predictive Maintenance Matters for Manufacturing Enterprises?

Predictive maintenance minimizes downtime, reduces costs, enhances equipment efficiency, boosts productivity, extends asset lifespan, and ensures seamless operations, enabling manufacturers to achieve higher profitability and remain competitive in an ever-evolving market.

Real-time Manufacturing Analytics
Gain actionable insights by monitoring multiple plants with IoT-enabled sensors. Optimize overall equipment effectiveness (OEE) through advanced analytics, enabling manufacturers to improve efficiency, reduce waste, and maintain seamless operational performance across all facilities.
Lifecycle Data Analysis
Analyze historical and real-time data to forecast maintenance needs accurately. This capability enhances equipment performance, reduces downtime, and streamlines operational planning, ensuring optimized production schedules and resource utilization for manufacturing enterprises.
Integrated Process Management
Streamline manufacturing workflows using adaptive, collaborative environments. Align maintenance strategies with production goals, enabling manufacturers to improve efficiency, reduce bottlenecks, and ensure cohesive operations across diverse teams and equipment.
Condition-Based Monitoring
Leverage IoT sensors to continuously assess equipment health in real time. Trigger maintenance only when necessary, eliminating over-servicing, reducing costs, and ensuring uninterrupted production with optimal equipment performance.
Failure Pattern Detection
Harness AI to identify recurring failure patterns and predict potential issues. Implement preventive actions proactively, avoiding critical breakdowns, maintaining production continuity, and reducing unexpected repair costs.
Our Partnerships

Maximize Equipment Uptime with Predictive Maintenance

Prevent unexpected failures and optimize production with AI-powered predictive insights. Reduce costs and improve efficiency with proactive maintenance solutions.

Talk to Experts
See How Organizations Are Innovating

Situation

United Tractors (UT) struggled with costly equipment downtime and inefficient manual maintenance. Managing heavy machinery across 100+ locations required a predictive approach. Their on-premise SAP HANA system lacked real-time analytics. Cloud adoption was critical for improving efficiency and decision-making.

Solution

UT migrated SAP HANA to Microsoft Azure, enabling AI-powered predictive maintenance. Real-time analytics optimized resource allocation and reduced unexpected failures. Microsoft 365 improved collaboration for maintenance teams across locations. With AGIT’s support, UT completed the cloud migration in just six months.

Impact​

Predictive maintenance reduced unplanned downtime by 30% and increased uptime by 25%. Azure enabled 30x faster application deployment with no additional capital expenses. Operational flexibility improved, cutting maintenance costs and boosting productivity. UT’s cloud-first approach strengthened its leadership in Indonesia’s heavy equipment sector.

Situation

Manufacturers struggle with unexpected machine failures, leading to costly downtime and inefficiencies. Fixed maintenance schedules result in premature part replacements, wasting resources and increasing operational expenses. Bosch needed a predictive maintenance solution to enhance machine reliability, reduce downtime, and optimize overall production efficiency.

Solution

Bosch developed IAPM, a Digital Twin powered by Microsoft Azure, analyzing real-time and historical machine data for predictive maintenance. Integrated with Azure IoT Hub and Dynamics 365, it automates maintenance alerts and scheduling. HoloLens 2 enables remote inspections, improving response times, efficiency, and reducing operational disruptions caused by unexpected failures.

Impact​

Predictive maintenance has significantly reduced downtime, optimized resource allocation, and extended machine lifespan. With 53% of rotating machines in the DACH region, Bosch gained industry confidence. Enhanced energy efficiency lowers costs, reduces waste, and improves sustainability. This innovation won the Microsoft Intelligent Manufacturing Award 2021.

Situation

Manufacturers struggle with unplanned downtimes and costly repairs due to undetected structural stress. Traditional maintenance relies on periodic inspections, often missing early warning signs. A predictive, real-time monitoring system is needed to prevent failures, enhance safety, and optimize maintenance schedules efficiently.

Solution

fischerwerke integrated IoT and cloud analytics using Microsoft Azure, enabling continuous structural monitoring. SensorAnchor and SensorDisc collect real-time data, detecting anomalies and predicting maintenance needs. Azure Event Hub processes alerts, ensuring timely interventions. This seamless, data-driven approach enhances operational efficiency and structural reliability.

Impact​

Predictive maintenance reduced unexpected failures by 40% and maintenance costs by 30%. Automated monitoring eliminated unnecessary inspections, reducing labor and environmental impact. Industries like construction and energy improved asset lifespan, regulatory compliance, and operational agility through real-time data-driven decision-making.

Situation

FRÄNKISCHE Industrial Pipes faced challenges in maintaining high production quality and real-time supply chain transparency. Manual processes and siloed systems made error detection difficult. With 70,000 metric tons of raw materials processed annually, the company needed a predictive maintenance solution to enhance efficiency and traceability.

Solution

Implementing Azure IoT, FRÄNKISCHE digitized its entire production lifecycle with real-time monitoring, predictive maintenance, and AI-driven quality assurance. Data flows from edge devices to Azure IoT Hub, enabling automated alerts, QR code tracking, and early failure detection, ensuring faster issue resolution and enhanced operational efficiency across multiple global manufacturing sites.

Impact​

Azure IoT reduced unplanned downtime by 30%, improved product quality, and enabled 300+ machines to operate with near-full automation. Real-time insights minimized defects, optimized maintenance, and enhanced customer transparency, providing a scalable digital infrastructure for future predictive maintenance, quality improvements, and operational innovation across FRÄNKISCHE’s global operations.
Generating Business Value Across Industries
Minimized Production Downtime

By predicting failures early and proactively, manufacturers can prevent production halts, ensure continuous operations, and meet delivery deadlines without incurring costly disruptions or delays.

Optimized Maintenance Scheduling

Align maintenance schedules with production demands for maximum efficiency. This balance minimizes disruptions, ensuring machinery operates at peak performance without unnecessary downtime, yielding ideal business impact.

Asset Lifecycle Management

Extend equipment lifespan by scheduling timely maintenance. Reduce the need for frequent replacements, optimizing capital investment, and ensuring long-term operational stability.

Cost-Effective Inspections

Automate equipment monitoring with sensor-driven systems. Reduce dependency on frequent manual inspections, cutting inspection costs and enhancing operational efficiency for manufacturers.

Energy Consumption Optimization

Analyze energy use to identify inefficiencies in manufacturing operations. Reduce energy costs, improve sustainability, and ensure equipment operates at optimal efficiency across the production line.

Supply Chain Synchronization

Coordinate maintenance with inventory management to reduce delays. Ensure the availability of replacement parts on time, improving supply chain efficiency and production continuity.

Enhanced Worker Safety

Monitor equipment conditions in real-time to detect potential hazards early using vision technology. Address risks proactively to maintain a safer working environment and minimize workplace accidents.

Improved Compliance Reporting

Maintain automated, detailed maintenance records for regulatory audits. Ensure compliance with industry standards, reducing risks associated with non-compliance and enhancing organizational accountability.