Big Data for Manufacturing
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Lean production and cost cutting no longer provide the basis of sustainable competitive advantage. Allied Consultants’ Big Data solution for manufacturing includes industry relevant features such as preventive & preemptive maintenance (predicts cause & time of future failures), real-time precision forecasting, product quality monitoring , yield management, etc. Manufacturers can now predict design flaws in advance and improve overall equipment effectiveness (OEE). Following modules are part of the solution:
- Predictive & preemptive maintenance
- Monitor performance and up-time of systems and applications as the devices, sensors and equipment sends continuous data
- Fix things before they break and monitor assets (machines, plants) remotely and in real-time
- Quality management interface
- Predict, preempt and identify out-of-bounds manufacturing
- Aggregation & modelling of large volumes, high speed and variety of data
- Big Data analytics integration with Six Sigma DMAIC
- Correlation development between quality factors
- Yield management
- Big Data analytics to isolate factors that impact production quality
- Batch-to-batch comparisons (by comparing millions of data points) to identify factors that impact plant yield
- Aligns data sets around batch IDs, equipment, time stamps, and other factors that impact production
- Production optimization module
- The module optimizes production schedules based on near-real time data acquired from suppliers, customers, machine availability and cost constraints
- Integrated analytics predict the risk of late delivery by suppliers
- Closed-loop product management
- Creates closed-loop environment for select products, applies ETL to analyze large volume of product use data for continuous improvement in design & manufacturing process
- Integrates engineering and manufacturing design
- Install embedded sensors into products/equipment to review & optimize production
- Tracks materials logistics in real-time
- Forecasting/Demand Forecasting
- Precision forecasting of order lead times
- Forecast sales orders across the geographic regions
- Forecasts part & plant failure by factoring in maintenance records, operating environment data and production schedules
- Graphs, charts and KPI dashboards provide visibility into near-real time inventory to efficiently schedule purchasing
- Order management
- A centrally accessible dashboard that contains order cycle information (time in calendar days from order release to manufacturing to customer shipment)
- Historical log of order delivery errors (the dashboard displays delivery/order errors during a defined manufacturing run)
- Displays TAKT (average unit production time) for each product category up-to the batch level; a key metric in lean manufacturing
- Warranty claims management
- The module presents aggregated information in form of a GUI. Information includes warranty claims by location, customer segment, frequency of claims and density of claims with respect to geographical areas
Technologies
- Power BI & HDInsight
- Microsoft Dynamics
- Azure Stream Analytics
- Cortana Analytics Suite
- SQL Server 2014
- Azure DocumentDB
- Hortonworks Hadoop Cluster
- SI (Hortonworks, BigSQL, KAFKA, Splunk, ZooKeeper)
- IBM BigInsight
- SAP HANA
- SQL Azure
- ERP
- SCM
- MES
- CRM
- Web Data
- PLC’s
- Sensors
- Cameras
- Text
- Barcode
- Audio files
- Lab equipment
Tags
KEY BENEFITS

- Predict design flaws
- Decrease lost manufacturing capacity
- Improve Overall Equipment Effectiveness (OEE)
- Predict machine/plant maintenance requirements
- Predict production requirements through sales forecasting
- Offer services related to high-grossing products
- Improve value ratio by mitigating material transformation delays
- Improve inventory replenishment time
- Predict output quality based on product engineering changes
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