Modernising Manufacturing with the Industrial Internet of Things (IIoT)

by Sandeep Bhargava, Managing Director, APJ

Factory worker standing in front of a machine using a laptop

 

The pandemic has tested the resilience of most enterprises across industries, and manufacturing businesses are no exception. Businesses had to make drastic changes to keep up or adapt to the fast-changing needs of the market and the pandemic constraints to survive post-pandemic.

Digital technologies, by providing essential tools of connectivity, have empowered businesses to boost operational performance in a changing environment by enabling real-time adjustments to production and remote functioning.

Data is driving the next industrial revolution, and data-driven manufacturing is clearly the next buzzword in manufacturing operations. Using data and analytics to optimise operations and plan sales has significantly enhanced production, supply chain, and distribution efficiency.

Manufacturers can now more quickly and seamlessly incorporate data-driven decision-making in their everyday activities with the Industrial Internet of Things and smart application of big data and advanced analytics.

 

What does IIoT Mean for Manufacturing?

Industrial Internet of Things (IIoT), also known as Industry 4.0, to facilitate data-driven manufacturing is not a new concept in the industry. It is the application of IoT principles and technology in the industrial sector, more specifically, manufacturing.

IIoT efficiently uses smart sensors and actuators to strengthen and boost manufacturing and industrial processes. It uses machine learning and real-time analytics to leverage the treasure trove of data created over decades.

In manufacturing settings, IIoT has immense potential to fast-track innovation, create new revenue streams with smart products, boost operational efficiency, enhance quality control, and improve supply chain traceability and efficiency. It enables manufacturers to automate and monitor activities remotely with decisions driven by data, which improves operational efficiency.

IIoT, with its network of connecting intelligent devices, creates a platform that digitises almost all parts of their businesses and can remotely monitor, collect, manage, and analyse data in real time.

Enabling manufacturers to:

  • Understand product usage with insights on how users engage with the product features
  • Recognise and rectify product shortcomings based on user data
  • Rapidly roll out new features with superior technology and insights into user behaviour 
  • Optimise manufacturing processes and reduce operational costs with real-time performance monitoring
  • Decrease the risk of human error by minimising hand processes and entries. 
     

Watch this video to find out how an IIoT Smart Factory Accelerator works.

 

The Challenges When Adopting IIoT

With so many benefits that can be game-changing in the manufacturing business, why isn’t adopting IIoT more widespread, and why isn’t data-driven manufacturing the norm? Despite its transformational abilities, it does bring with it some challenges for manufacturers who are considering implementing IoT. Here are some top challenges faced by manufacturing businesses:

 

Data liberation

A Manufacturing floor is full of equipment from different vendors. Each cell in a production line performs some specialised activity that generates a lot of data. Most of this data is tied up in data silos, thus making it very hard for manufacturers to make data-driven decisions. To experience Data Freedom, manufacturers are now racing to unlock this huge amount of data and gain real-time actionable insights into their factory floor operations.

There are hundreds of millions of data points generated on the factory floor which will be impossible to store on-premise due to the limited storage capacities, and compute on the factory floor, and hence manufacturers are looking at storing all this data in cloud storage, where there is not only infinite storage capacity but also the economies of cost and the agility to process the data the way the manufacturers want.

 

Security

Adding more devices and networks creates not only more complexities but also more challenges in terms of security. There will be higher security gaps and opportunities for cyber-attacks as more nodes and IIoT devices are added to networks. As manufacturers, the more the number of connected instruments and cloud networks, the bigger the attack surface for data breaches or ransomware. Lack of maintenance of legacy software is a significant problem augmented by slackened testing throughout the life span.

Moreover, the volume of information being shared every day across the network continues to increase, and strict encryption standards are a must to main the integrity of the data. Using a trusted security service provider like Rackspace Technology® that offers reliable endpoint protection and detailed monitoring infrastructure can go a long way in mitigating the security risks on the cloud.

 

Connectivity

Most IIoT ecosystems rely on a centralised server-client paradigm to authenticate, authorise and connect different nodes in a network which automatically mandates having reliable data networks with sufficient capacity for smooth functioning. Many IIoT projects still fail due to pitfalls related to connectivity and integration. As the number of devices increases, networks can soon become bottlenecks without proper connectivity in addition to monitoring and tracking issues.

Even if a few machines are not connected, they will be unable to provide and receive data, which will be counterproductive. Moving to Edge can assuage some of these challenges - Edge devices can give authenticated access to a faster, more efficient backbone and core networks. Organisations can also explore peer-to-peer communications, where connected devices automatically identify and authenticate each other and communicate directly without the need for a central server.

 

Integrated Technology and Analysis

Manufacturing produces extensive volumes of heterogeneous data that need to be processed, stored, and insights extracted from it derive business value. For the data to be reliable, it needs to be comprehensive, and all devices must be connected at all times.

Many businesses are stuck with legacy systems not built for the IIoT ecosystem. While most legacy systems are equipped to deal with structured data, modern interactions mostly create unstructured data. Batch processing used by traditional analytics software is another challenge.

IIoT relies on real-time processing of data and insight generation, but batch processing does not support that. For IIoT projects to be successful, creating an integrated ecosystem driven by data and analytics is a must.

 

High Initial investment

Purchasing and deploying IIoT is not cheap, especially if you need custom IIoT development. While over a period of time, the returns are much higher with savings due to better operational efficiencies and productivity with access to business intelligence, the initial implementation costs are high.

 

Lack of Standards

The lack of standards in IIoT is a major challenge for its widespread adoption. Different providers are operating on various technologies that are competing to become the standard, causing compatibility difficulties.

Lack of standardisation in communication protocols and myriad operating systems in IIoT devices cause fragmentation issues highlighting the importance of standardisation. Now, who will be responsible for this standardisation? While governments can regulate some parts of these, the onus mainly falls on the industry, especially demand from the buyers. 

Despite the challenges, this is the fourth industrial revolution, and it is here to stay. As a manufacturer, you can work with our experts, who will work with you from prototype to production, applying their collection of hardware, cloud platforms, application, and analytics accelerators to fast-track the development of your IoT solutions.

 

Solving Together™

The Rackspace IIoT Smart Factory Accelerator is built on top of AWS IoT SiteWise, a managed service that simplifies collecting, organising, and analysing industrial equipment data at scale.

Rackspace Technology combines the power of the cloud with the hardware engineering expertise required to successfully complete your IoT or Edge solution. Our reference designs accelerate prototypes while providing a clear path to the production of a custom, certified connected smart device. 

The Rackspace IIoT Smart Factory Accelerator helps forward-looking manufacturing firms by bringing all factory floor or operational technology data across equipment and devices on a single platform.

Listen to Industrial IoT and Smart Manufacturing Webinar replay to find out how you can build smarter factories, faster.

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