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    Predictive Maintenance and Production Optimization with AWS

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    Sold by: Capgemini 
    Delivered through expert-led Professional Services engagements, PMaaS helps manufacturers and energy providers transition from reactive to predictive maintenance. Built on AWS Cloud services (Amazon SageMaker, AWS IoT Core, Amazon Bedrock, DynamoDB, and more), this solution enables earlier failure detection, smarter repair planning, and reduced downtime.

    Overview

    Delivered Through Expert-Led Professional Services and Scalable Cloud Infrastructure. Our Predictive Maintenance as a Service (PMaaS) combines deep domain expertise with the power of AWS to help manufacturers and energy providers transition from reactive to predictive maintenance. Delivered as a professional services engagement, this offering includes strategic consulting, solution design, implementation, and ongoing optimization—ensuring measurable outcomes and operational resilience. Service Framework

    1. Asset Prioritization & Criticality Assessment Our consultants work with your teams to identify and rank machinery based on operational impact and risk. This is powered by machine learning models built on Amazon SageMake, and enhanced by Retrieval-Augmented Generation (RAG) using Amazon Bedrock, enabling intelligent asset targeting.
    2. Real-Time Failure Prediction We architect and deploy real-time monitoring pipelines using AWS IoT Core and Amazon Kinesis, enabling early detection of anomalies from sensor data. Our professional services team ensures seamless integration with your existing systems and operational workflows.
    3. Automated Maintenance Planning Leveraging large language models hosted on SageMaker JumpStart or Amazon Bedrock, we generate dynamic repair procedures that incorporate technical documentation, inventory data from Amazon DynamoDB, and workforce availability. Our experts tailor these plans to your specific operational context. 4Technician Enablement & Mobile Guidance We develop mobile-first applications using AWS Amplify and Amazon API Gateway, delivering real-time service notes and step-by-step instructions to technicians. This improves field productivity and reduces human error, with content delivery optimized via Amazon CloudFront. Professional Services Value
    • End-to-End Delivery: From discovery to deployment, our team manages the full lifecycle of your predictive maintenance transformation.
    • Custom Architecture: Solutions are tailored to your environment, leveraging AWS best practices and scalable infrastructure
    • Change Management & Training: We provide onboarding, enablement, and support to ensure adoption across technical and field teams.
    • Outcome-Based Engagements Our services are aligned to KPIs such as reduced downtime, improved asset utilization, and cost savings.

    What We Deliver • Asset Assessment & Prioritization – Identify high-impact equipment using ML on SageMaker with enhanced targeting via Bedrock RAG. • Failure Prediction – Real-time anomaly detection through AWS IoT Core and Kinesis pipelines. • Automated Maintenance Planning – AI-generated repair workflows powered by Bedrock and integrated with inventory/workforce data in DynamoDB. • Technician Enablement – Mobile-ready guidance with AWS Amplify, API Gateway, and CloudFront for optimized field productivity.

    Professional Services Value • End-to-End Consulting – Discovery, design, implementation, and optimization. • AWS-Aligned Architectures – Scalable and secure by design. • Training & Change Management – Ensuring adoption across teams. • Outcome-Based Engagements – Focused on measurable KPIs: reduced downtime, improved utilization, and cost savings.

    Highlights

    • Key features include criticality analysis of machines, failure prediction and alerting, maintenance plan and guidance generation for enhancing energy and manufacturing assets efficiency. Business Value: 1. 5-8% increase in hydrocarbon production, with accelerated timeline 2. Reduction from 7 to 1.5 hours for engineering asset team to analyze underperforming and candidate wells 3. Improved well vertical lift and equipment health/ lifespan
    • Predictive Maintenance, Production Optimization, Energy & Environmental, Oil & Gas, Manufacturing & Mobility, Aerospace & Defense, Industrial IoT, GenAI, RAG, Time Series Data, Maintenance Analytics.
    • Industrial, Industrial IoT, Databases; MongoDB Atlas – a leading unified developer data platform for managing multi-format sensors, logs, time‑series, vector, and full‑text data, stream processing, charts, and vector / hybrid search—ideal for real‑time and historical analysis. AWS services – delivering scalable infrastructure and access to Generative AI models and services-- Amazon S3, Amazon EventBridge, Amazon SageMaker, Amazon Bedrock.

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    Delivery method

    Deployed on AWS

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