Predictive Maintenance for MFG Jumpstart (4wk POC)

For decades industrial organizations have witnessed proliferating volumes of data and the constant pressure to maintain scalability and cost efficiency into their operations. Predictive Analytics helps organizations gain the highest return on critical assets by supporting their predictive maintenance.

Hanu’s Predictive Maintenance solution provides early warning notification and diagnosis of equipment issues days, weeks or months before failure. This helps asset-intensive organizations reduce equipment downtime, increase reliability, and improve performance while reducing operations and maintenance expenditures.

It also integrates with a wide variety of data gathering IOT technologies and control and monitoring systems in the cloud. The system is highly scalable and can be used to monitor a single asset, plant or hundreds of remote assets across multiple sites.

Our Predictive Maintenance solutions combines the power of Azure Synapse and our deep industry experience for predictive equipment maintenance.

Our team of certified specialists will guide you through a 4-week engagement to accelerate your predictive analytics journey with Azure Synapse Analytics by helping you answer four core questions:

• What are the predictive analytics implementation challenges and how can I mitigate them with proven best practices?
• How can I showcase success and vision of these initiatives to the leadership?
• What should be the implementation roadmap and estimated costs?
• What will the post migration architecture look like?

Workshop delivery process

Week 1

• Assess data environment
• Create high-level roadmap and system architecture

Week 2 and 3

• Setup Azure Infrastructure for POC
• Enable data ingestion
• Train Machine Learning Models and test results
• Validate results and build visualizations

Week 4

• Conduct Workshop to educate team on implementation process, pain points and mitigation plan
• Socialize POC results
• Knowledge Transfer: Codes and all artifacts for next level references

Final deliverables

• High level post migration architecture
• Migration estimates and budget
• POC code and all artifacts for reference