Smart Factories: The Path to More Intelligent Manufacturing

What Is Exactly A Smart Factories?

Smart manufacturing is defined by the United States National Institute of Standards and Technology (NIST) as “completely integrated, collaborative production systems that adapt in real-time to changing needs and situations in the plant, supply chain, and customer requirements.”

A smart factory is a byproduct of Industry 4.0, the fourth industrial revolution, which is fueled by technologies such as big data, the Industrial Internet of Things (IIoT), and artificial intelligence/machine learning.

Intelligent factories are defined by a high level of complicated industrial automation, which implies the ability to conduct production processes with little or no human interaction. Industrial IoT technologies include hardware (sensors, actuators) and software to enable this automation.

The Advantages Of A Smart Factory

  • Process Of Agile Production

Due to the integration of several systems (e.g., an IIoT solution, ERP, MES, and SCM), a smart factory enables manufacturers to swiftly adjust to changing customer demands, budgets, and product quality criteria.

Manufacturers employ this contemporary technique or strategy to adapt swiftly to changing client wants and market expectations. You may become an agile manufacturer via a combination of elements, including modular and customer-focused product design, information technology, corporate partners, and knowledge culture.

  • Increased Manufacturing Efficiency

The sensor network enables the collection of data on the manufacturing process, the environment, and the equipment. The cloud software analyses this data in near-real-time, enabling manufacturers to make immediate modifications to equipment operating conditions, for example. Additional analysis of sensor-generated data enables the identification of patterns and improvement possibilities throughout the manufacturing process.

  • Increased Manufacturing Operation Dependability

Equipment availability is often assured in US manufacturing by the presence of backup equipment, i.e. purchasing two machines when one will deliver the needed throughput. As a result, preventive maintenance loses its urgency, and breakdown repair becomes the norm. More significantly, critical maintenance concerns go unnoticed.

  • Enhancement Of Product Quality

AI technologies are utilized to ensure the quality of products in smart factories. For instance, cameras equipped with computer vision algorithms can quickly spot faults, while sophisticated analytics software may assist in determining the root cause of a problem.

  • Increased Visibility Into The Activities Of The Shop Floor

By providing producers with constant real-time data on production activities and the state of industrial assets, the IIoT improves insight into shop floor operations.

  • Data Protection

Data security is secured by at-rest and in-transit encryption, access restriction, and AI-powered detection of aberrant user behavior inside a smart factory, among other measures.

  • Maintenance That Is Predictive

The IIoT enables near-real-time transmission to the cloud of data on numerous equipment metrics that indicate its health and performance. It is then supplied, along with metadata, to machine learning algorithms that assist in detecting problematic patterns. Thus, it becomes feasible to forecast probable equipment failures and take corrective action in a timely manner.

  • Enhancement Of Worker Safety

Robots may be used to do potentially hazardous tasks in place of human labor.

Technologies That Are Incorporated In Smart Factories

  • Computing In The Cloud

Popular cloud systems (e.g., AWS, Azure) enable the safe processing, storage, and analysis of massive volumes of data.

  • Identification Via Radio Frequency (RFID)

RFID technology enables smart factories to monitor industrial equipment and machinery, inventories, completed items, as well as objects and personnel.

  • Massive Data

This technology is used to gather, store, and analyze massive volumes of production-related data in real-time.

  • Machine Learning And Artificial Intelligence (AI)

AI and machine learning are used to automate the whole manufacturing process, as well as equipment monitoring. Additionally, these technologies allow the development of sophisticated analytical insights (e.g., predictive maintenance, detection of quality improvement opportunities).

Want to Know More About Smart Factories? Check Our Blogs…

Enhance The Intelligence Of Your Industrial Processes

Switching to a smart manufacturing model is a significant undertaking that will demand significant time and financial commitment. To ensure a seamless transition and to get benefits quickly, Blocknize recommends iterating the transformation. For example, it may be viable, to begin with, a cloud-based big data storage system that would ultimately serve as the basis for enterprise-wide analytics, offering insights for production planning and management, industrial asset management, and more. If you want guidance on where to begin or are ready to embark on the road of digital transformation, Blocknize’s staff is always here to assist.

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