These Technological Trends will make Smart Manufacturing

Smart manufacturing technologies can improve efficiency, safety, and productivity by incorporating data collection and analysis systems to create a virtual model covering all aspects of the business from supply chain to manufacturing.

Apac CIOOutlook | Monday, July 08, 2019

Smart manufacturing technologies can improve efficiency, safety, and productivity by incorporating data collection and analysis systems to create a virtual model covering all aspects of the business from supply chain to manufacturing.

FREMONT, CA: Smart manufacturing is a technology-driven approach that aims to monitor the production process with the help of internet-connected machinery. Smart manufacturing stands out as a specific application of the industrial internet of things (IIoT), which consists of manufacturing machines with embedded sensors to collect data required for analyzing operational status and performance. Conventionally, such data were exclusively stored on individual devices and were only accessed in case of a failure. Moreover, with smart manufacturing, the manufacturers are also equipped with data trends that indicate the weak link in the system.

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With organizations readily adopting some or the other form of smart manufacturing in their systems, here are some of the technologies that will impact the smart manufacturing landscape:

• Cloud Computing

Cloud computing and storage will allow the companies to outsource the overheads of managing the data and memory required for emerging technology. However, the major challenge will be to ensure a smooth migration of the system to the cloud while keeping the migration budget within an affordable range.

• Network Optimization

The goal of optimizing network is to provide a network that connects and optimizes the utilization of the complete data set collected by the emerging technology. For instance, inventory control drones depend closely on these systems while sending and receiving data to help the managers with real-time management of the product data.

• Automatic Identification and Sensors

Manual steps from the quality assurance process across the supply chain can be removed with the help of sensor solutions like RFID tags and add SKU-level visibility. However, the challenge here is the infrastructure equipped with high processing speeds and memory to store the enormous quantity of data collected by the sensors.

• Predictive Analysis

Predictive analytics utilizes the large data sets gained from the latest technology to predict problems and improve forecasting abilities. The primary goal is to work on moving from predictive analysis to prescriptive analysis. The prescriptive analysis involves software that suggests the future steps to the supply chain manager.

• Internet of Things (IoT)

Smart manufacturing can leverage Internet of Things (IoT) up to the hilt where sensors in pallets, production lines, and forklifts can be adapted to provide data to a central system. The major limitation comes up in the form of a common platform that enables a wide variety of systems to interact.

Check out: The Manufacturing Outlook

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