Data Platform

Smart Manufacturing

A strong multi-layered data platform

Smart manufacturing uses internet-connected machines to monitor production processes. Analyzing this data can help manufacturers quickly adapt to changes throughout their manufacturing and supply chain processes.

Why is Smart Manufacturing Important?

Traditional manufacturing cannot respond to environmental changes because it was not designed with flexibility in mind. From the outset, smart manufacturing is designed to be adaptable. Analyzing data from sensors and digital feeds about factors such as demand helps manufacturers quickly respond to changing conditions.

Benefits of Smart Manufacturing

Below are some of the benefits of using smart manufacturing over traditional manufacturing technologies and processes:

  • Plants can boost productivity because reliable real-time data helps predict failures and identify safety and quality assurance issues.
  • Predictive analytics can optimize logistics and improve on-time delivery with real-time information on traffic conditions, shipping container bottlenecks, adverse weather and more. Plus, smart sensors can identify issues with vehicles and drivers to help prevent breakdowns and accidents.
  • Manufacturers can realize labor improvements by optimizing and automating processes to carry out projects more efficiently.
  • In the supply chain, predictive analytics can optimize inventory replenishment, quickly scaling production up or down as needed.
  • Analyzing data on carbon emissions, energy and water use, and waste can lead to insights on reducing your environmental footprint.

Potential Challenges for Implementing Smart Manufacturing

Smart manufacturing projects can encounter the following challenges during approval and rollout:

  • Perceived risk is a major obstacle often addressed through an incremental or phased rollout that assesses the risk at multiple milestones.
  • The need to reengineer existing processes to adopt smart technology can slow down a project.
  • Technology integration in IT and OT can be complex due to differing APIs and network requirements.
  • Automation can be challenging due to the many robotic alternatives that manufacturers must assess based on various use cases.
  • Employees often need training, including change management.

Actian Helps Smart Manufacturing

The Actian Data Platform is the ideal cross-cloud solution for connecting, integrating, structuring, and storing multiple data sources for advanced analytical processing. The Actian Data Platform provides hundreds of data connectors to load data for advanced analysis. The Actian Data Platform provides the fastest analytics, vector processing, and cluster-aware columnar database technology available on-premises and in the cloud. Get started today with a free 30-day trial at our website.


The automotive industry is evolving from a model of refinement of existing processes practiced for decades. Companies such as Tesla simplify production by removing steps wherever possible. Parts such as the heat exchanger serve more aspects of the vehicle, and components are constantly changed to allow faster automation. Ultrasonic sensors on the bumpers have been eliminated, and their function has been assigned to cameras aided by more advanced image processing for depth perception.

Mercedes places barcodes on the windshields of partially built trucks in Mexico to make them easier to find in parking lots where they are held, awaiting parts that were unavailable during initial vehicle manufacturing. Cameras and drones confirm locations after the vehicle is parked.

Power Generation

Power generation uses expensive machines such as nuclear reactors, hydro turbines, and offshore windmills. These machines use IoT sensors to allow manufacturers to monitor their use in production. The analytics driven by the sensor data streams allow 3D service monitoring applications to predict proactive maintenance intervals.


Retailers such as Sainsbury’s and Cost Plus use smart algorithms to predict consumption to drive replenishment orders, with managers simply monitoring automated orders. Insights from real-time customer behavior and streamed point-of-sales data help retailers understand demand as it’s happening.

Smart Logistics

Carriers of refrigerated goods from farm to store are excellent examples of smart logistics. They can include a cellular-connected temperature sensor with produce packed and chilled in the field to detect overheating in transit and alert the shipper of potential spoilage. The flagged goods can be assessed at arrival to prevent the spread of disease.


Farming makes broad use of smart technologies—drones survey fields to map crops that are ready to harvest. Organic farms use robots that wander the fields day and night using video recognition to identify weeds and zap them with a laser, maximizing yield without pesticides.

Quality Control

Farming makes broad use of smart technologies—drones survey fields to map crops that are ready to harvest. Organic farms use robots that wander the fields day and night using video recognition to identify weeds and zap them with a laser, maximizing yield without pesticides.

Data Analytics

Smart manufacturing relies on data analytics to improve the efficiency and effectiveness of manufacturing processes. Sensors collect data, and data streaming services share data using a publish and subscribe model. The data is stored in a data platform where artificial intelligence (AI) techniques such as machine learning (ML) can perform advanced analytics whose output is used to prescribe or directly make operational changes on the factory floor.