AI in Manufacturing

Real-Time Data Processing on Docker and Kubernetes


It involves Constant monitoring of the performance data and generate the Predictive Analytics. Interpretation of data from hundred of sensors performed. Understand the failure conditions, track the anomalies and manage the production on the basis of Real-Time demand.

Big Data Analytics With Apache Spark & Flink

Automated Quality Control

With the use of Computer Vision algorithms, defects detected immediately and further identify the root cause of the failure. By enabling better monitoring and quality control, the productivity of single machine increased. Hence, the System Monitoring and Planning allows the system to produce more products on the same number of machines.

Big Data Warehousing and Data Lake Solutions

Demand-Driven Production

Real-Time demand visibility achieved by connecting the consumer Apps and IoT with the industrial IoT.Combining all the processes such as Order Management, Procurement, Transportation Sourcing, and Inventory Management in a single convenient platform.


Analytics Based Services for Manufacturing

  • Direct Automation & 24/7 Production.
  • Safer Operational Environment.
  • Automation of ordinary tasks leading to focus on innovation more.
  • Condensed Operating Costs.
  • Adaptive Manufacturing & Intelligent Data Analysis.
  • Improved reliability of Power Grids.
  • Optimised Control Centers for Switch Towers.
  • Automatic Selection of requirements using reliable operations.
Real-Time and Stream Analytics Service Providers
Data Analytics Solution for Stream and Real-Time Processing

AI Solutions for Manufacturing

Akira Analytics Manufacturing solutions involve creation of rapid data determined decisions, enhanced production outcomes, advanced process effectiveness, superior scalability, product development, Failure Detection, Augmented Reality, Managing Sensitive Information, detection of threats through Data Mining, Cyber Insurance Systems for optimised production.

  • Individual Asset Downtime Monitoring
  • Automatic Machine Tuning
  • Fleet, Inventory & Quality Management
  • Assembly Line and Sorting
  • Multi-Agent Robotics
  • Sensors and Machine Communicating
  • Autonomous Protection through AI

Applications of AI in Manufacturing

Behavioural driven Predictive Maintenance

Predictive Maintenance optimises employee's productivity, planned downtime, involves high process transparency, increases product availability, fine-tuning of production plans, customisation of component wise maintenance schedules.

Machine Automation and Optimisation

It produces signals for self-optimisation and maintenance, determining Overall Equipment Effectiveness(OEE), Condition Monitoring, Production Performance Management, Optimised Semiconductor Manufacturing, Supply Chain Management, Asset Management and Inventory Management.

Automatic Product Defect Detection

It involves automatic determination of drivers in down time and poor quality. It identifies production defects in Real-Time, Object Character Recognition, Object Orientation, Deformity Detection, Automatic Inspection System.

Data-Driven Research and Development

It involves understanding the customer needs and usage of products and further finds the innovative trends in the market. It involves Descriptive Analytics and Diagnostic Analytics, various types of Bottleneck Detection involving discrete , purely data-driven and at Real-Time detection.

Productisation of Data

It turns the utilisation data into new services or products of the customer. It involves Production Control, Process and Quality Control. It involves continuous flow manufacturing process, custom manufacturing and fixed manufacturing.

Energy Optimisation

It involves accessing machine or an entire environment for the optimisation of settings and run-time for reducing the energy consumption.

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