AI and Machine Learning

How the AIoT makes factories “smart”

The Artificial Intelligence of Things (AIoT) can integrate different types of data and information to give manufacturers a better picture of how everything works in facilities. See four AIoT factors responsible for smart factory growth.

By Sacheen Patil December 9, 2021
Courtesy: Yash Technologies

 

Learning Objectives

  • Artificial Intelligence of Things (AIoT) can help manufacturers anticipate and respond to changes in an industry that is quickly changing.
  • It can be challenging synchronizing everything because many manufacturing sectors are siloed off.
  • Successful AIoT deployments help manufacturers innovate and reduce overall costs.

Artificial intelligence (AI) is helping with the marked shift from traditional approaches, especially in manufacturing, to meet ever-evolving customer needs and fluctuating market demands as the world is undergoing a social and technological transformation. This is where the artificial intelligence of things (AIoT) comes into the picture.

It is helping organizations transition into intelligent manufacturing entities with AI and IoT functionalities playing a pivotal role. A recent study on ResearchAndMarkets.com indicates that AI in industrial machines is expected to touch $415 million worldwide by 2024 with collaborative robot growth at 42.5% compound annual growth rate (CAGR).

Using connected devices across the shop floor assisted by sensors and industrial applications, manufacturers are experiencing a sense of being in control. It should come as no surprise that for major manufacturing plants, Industrial IoT is shaping up as the nervous system being directed by AI, which is acting as the brain behind the operations. Enabling automated manufacturing, however, requires a commitment, understanding of the equipment and knowing the scale of the integration efforts to justify the return on investment (ROI).

Decoding the smart factory: Higher quality, asset management, analytics access

With a predictive approach, manufacturers can anticipate and act on anomalies across several use cases of AI & IoT, leading to better output quality enabling remodeling of business processes. An AIoT-enabled setup can dispense data-driven and actionable insights to generate higher yields, optimize performance, and augment decision-making capabilities. AIoT also can help factories self-correct and heal by spotting risks and defects, running automatic quality checks, and ensuring physical assets’ longevity. This reduces downtime while helping save maintenance costs.

The convergence of AIoT allows manufacturers to build atop existing deployments while creating new IoT products and better business models. Interlinked assets deliver intelligence on one AIoT platform in real-time, helping companies take accurate measures faster. AIoT-powered enterprises are also more secure with deep learning models based on neural networks as any faulty device can be shut down in time to avoid fatal accidents.

With AIoT capabilities, an intelligent factory achieves hardware independence by combining mobile device and IIoT applications and transparent data storage and on-the-fly analytics with a long-term data strategy. One of the most significant capabilities of the smart factory is that it gives access to information simultaneously on remote dashboards and integrates cloud computing for all data tasks on one foundation. It also minimizes energy consumption while helping manage inventory on the factory floor effectively.

Manufacturing is an industry where digitalization can have a significant impact. Courtesy: Yash Technologies

Manufacturing is an industry where digitalization can have a significant impact. Courtesy: Yash Technologies

End-to-end deployment challenges

While building a comprehensive IoT case, manufacturers continue to face several deployment hurdles.

Slow testing pilots and massive cost estimations bring down the pace of transformation while business priorities are often changing. The technology must not lose relevance for the factory so it can perform efficiently. Manufacturing units are often laden with siloed departments with little homogeneity. Stratifying IoT deployments can have a negative effect as a result.

However, this can be overcome with Big Data analytics, which transforms data from disparate sources into consumable knowledge on one platform. Some manufacturers are eager to chase trends and ignore the effect of the digitalizing effort on bottom lines, embarking on an integration journey without goals in mind. Focusing on ROI at the outset is crucial.

Improving manufacturing industries with AIoT, digitalization, digital twins

Even though current systems are built to react quickly, manufacturers are shifting gears and becoming more proactive. Manufacturing is an industry where digitalization can have a significant impact. The concept of a manufacturing digital twin of complex products for faster and cheaper production is swiftly taking root. AIoT also can help the manufacturing industry shun its critical limitations and deliver on its promise of fostering the new industrial revolution.

Four AIoT factors responsible for the growth of smart factory

1. Increases security and privacy

If critical or personal data isn’t transmitted to a central processor, it is automatically more secure. AI on the machine also allows improved access security – such as facial recognition.

2. Increases resilience

Removing the requirement for real-time data transfer improves the resilience of a machine as it can continue to operate in a standalone mode and send data to the central system when the link is re-established.

3. Increases functionality and responsiveness

By building AI into equipment, designers can provide new functionality. This may allow the device to self-diagnose faults or improve control, such as with voice or gesture control.

4. Reduces data transfer

Currently, data collected by a sensor or machine is sent to a central computer for analysis. Results are then sent back to the device for action. If a device can process the data locally and only send the results to the cloud, it dramatically reduces two-way data transfers

If strategized well, AIoT can enable manufacturers to equip the value chain with new ways to innovate, develop and manufacture while ensuring cost-effectiveness, speed, better quality and safety.

Sacheen Patil, vice president and global head – IoT and embedded practice center of excellence (Coe), Yash Technologies. Edited by Chris Vavra, web content manager, Control Engineering, CFE Media and Technologies, cvavra@cfemedia.com.

MORE ANSWERS

Keywords: Artificial Intelligence of Things, AIoT

CONSIDER THIS

Where could AIoT offer immediate benefits in your facility?


Sacheen Patil
Author Bio: Sacheen Patil is Vice President & Global Head - IoT & Embedded Practice & CoE at YASH Technologies. He has over 26+ years of experience in the Engineering/Industrial services & IT services company and predominantly worked for Manufacturing, Transportation/Automotive, Healthcare/Medical Devices and Energy & Utilities Industry Verticals sectors. He directs YASH Technologies ‘IoT & Embedded Systems Practice’ vision. He is responsible for aligning the company’s digital vision with the emerging and futuristic technologies relevant to customers and the specified industry verticals. LinkedIn Profile: https://www.linkedin.com/in/sacheenpatil/