Industrial Manufacturing Data Analytics

Thrive with Iot-based predictive solutions and digitized manufacturing data analytics for accelerated growth.

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Transform your manufacturing operations with data engineering and advanced analytics

Complex supply chains are prompting industrial companies to push for complete visibility into the performance of their assets and logistics. Sigmoid helps manufacturers digitize operations by integrating data from siloed sources and IoT-enabled sensors to deliver near real-time insights. We enable advanced analytics on highly customizable dashboards, providing faster access to quality data and insights for manufacturing leaders. Maximize efficiency, improve quality and reduce downtime with our comprehensive industrial analytics service. From IoT-based predictive maintenance to process optimization, we leverage cutting-edge technology to drive business outcomes.

10X

faster insights on machine health for a leading manufacturer

800+

sensors streaming data improved fault detection for a leading industrial automation firm

6 MN+

data records analyzed in real-time for sales uplift

Industrial manufacturing analytics for better decision-making

  • Create SSOT for data across plants, equipment, and geographies
  • Ingest real-time device data from multiple plants
  • Integrate manufacturing data from SCADA systems and IoT sensors
  • Centralize machine monitoring and diagnosis
Case Study

Find out how we automated data ingestion from 30+ sources and built a robust data hub for a Fortune 500 manufacturer.

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Production quality with data analytics
  • Enable real-time, integrated, and omniscient supply chain
  • Centralized hub monitoring real-time data on dashboards
  • Streamline processes for end-to-end visibility into supply chain
  • Detect anomalies and recommend solutions
Case Study

See how Sigmoid's ML-based demand forecasting improved a customer's forecasting accuracy and reduced costs by 5x.

Read case study
Supply chain and production quality
  • Ensure performance and minimize downtime with predictive insights
  • Improve productivity and overall equipment effectiveness
  • Enhance quality with anomaly detection and reliability analysis
  • Identify new emerging risk behaviors and reduce bad alerts
Case Study

Sigmoid built and automated an AI system to improve the customer's OEE by 2.5%, providing real-time alerting and recommendations.

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Enhance quality with reliability analysis
  • Enable live tracking and analytics implementation
  • Accelerate journey to autonomous operations with digital twin
  • Gain end-to-end visibility across inventory silos
  • Real-time intelligence and actionable recommendations
Case Study

Sigmoid’s IIoT analytics re-architected data pipelines for a top manufacturer, delivering 10x improvement in dashboard performance.

Read case study
Operational Intelligence

Production

  • Create SSOT for data across plants, equipment, and geographies
  • Ingest real-time device data from multiple plants
  • Integrate manufacturing data from SCADA systems and IoT sensors
  • Centralize machine monitoring and diagnosis
Case Study

Find out how we automated data ingestion from 30+ sources and built a robust data hub for a Fortune 500 manufacturer.

Read case study

Supply Chain

  • Enable real-time, integrated, and omniscient supply chain
  • Centralized hub monitoring real-time data on dashboards
  • Streamline processes for end-to-end visibility into supply chain
  • Detect anomalies and recommend solutions
Case Study

See how Sigmoid's ML-based demand forecasting improved a customer's forecasting accuracy and reduced costs by 5x.

Read case study

Quality

  • Ensure performance and minimize downtime with predictive insights
  • Improve productivity and overall equipment effectiveness
  • Enhance quality with anomaly detection and reliability analysis
  • Identify new emerging risk behaviors and reduce bad alerts
Case Study

Sigmoid built and automated an AI system to improve the customer's OEE by 2.5%, providing real-time alerting and recommendations.

Read case study

Operational Intelligence

  • Enable live tracking and analytics implementation
  • Accelerate journey to autonomous operations with digital twin
  • Gain end-to-end visibility across inventory silos
  • Real-time intelligence and actionable recommendations
Case Study

Sigmoid’s IIoT analytics re-architected data pipelines for a top manufacturer, delivering 10x improvement in dashboard performance.

Read case study
Scale the power of data with our end-to-end industrial analytics services to deliver real time insights.
Talk to our data team

Why Choose Sigmoid?

Build IoT based predictive analytics solutions

to deliver real time insights and enhance productivity across the production cycle.

Enable faster access to quality data and insights

with a single source of truth to optimize manufacturing operations.

Maximize efficiency, improve quality

with our experience-led data analytics manufacturing solutions

Customer success stories

Insights and perspectives

Blog Boost factory floor productivity

3 ways data engineering and real-time analytics can boost factory floor productivity

Infographic IIoT and predictive maintenance

IIoT and predictive maintenance in manufacturing

Guidebook Manufacturing Production Scheduling

Optimizing manufacturing production scheduling using constraint programming

Customer testimonials

Get up to 40% reduction in factory maintenance cost!

Reduce manual effort and accelerate time to insights with IIoT and predictive maintenance.

Let’s talk

FAQs

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Manufacturing data analytics empowers businesses to gain real-time visibility into their supply chain by monitoring inventory levels, demand forecasting, and supplier performance. It identifies potential bottlenecks and inefficiencies to optimize the supply chain, reduce lead times, and ensure a seamless flow of materials. It also aids in compliance monitoring, anomaly detection, and predictive maintenance for multiple facilities, ensuring cost-effective and sustainable manufacturing practices.

Predictive analytics in manufacturing harnesses advanced data analysis and machine learning algorithms to continuously monitor process conditions. It analyzes real-time sensor data and historical performance to accurately predict when machinery and manufacturing processes are likely to fail, allowing businesses to schedule maintenance proactively. This data-driven approach minimizes downtime, reduces maintenance costs, and extends the lifespan of critical equipment, ensuring optimal efficiency and productivity in manufacturing operations.

Manufacturing analytics can analyze production data to identify patterns, anomalies, and trends that impact production efficiency. It helps pinpoint the root causes of issues such as machine breakdowns, quality defects, or production delays, allowing companies to implement targeted improvements. By optimizing processes and reducing downtime, businesses can increase throughput, minimize waste, and achieve better efficiency.

Yes, manufacturing data analytics assists in demand and supply planning by analyzing historical sales data, market trends, and customer behavior. This enables companies to optimize inventory levels, minimize stockouts, and ensure timely replenishment. It also helps in identifying demand patterns and seasonality, allowing businesses to plan production schedules efficiently and align them with customer requirements.