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Unlock the Potential of Modern Manufacturing Through IIoT

Henry Ford and Nikola Tesla are proof that whenever something new is thought of- the cliché response is, ‘Why do we need it?’ Slowly but surely, the answer changes to ‘Tell me how.’ From horses to cars, from lamps to electricity, and from dumb machines to intelligent and IIoT-run equipment, the journey always follows the same path. This is why you shouldn’t be surprised to see smart factories housing connected manufacturing equipment with retrofitted industrial IoT sensors, digitally-powered Supervisory Control and Data Acquisition (SCADA) systems, and human-machine interfaces (HMI), providing new-age industrial control and monitoring. 

 

Modern manufacturing is quickly moving towards a new breed of Programmable Logic Controllers (PLCs) with massive computing done at the ‘edge.’ This ‘edge’ becomes possible due to sensors fitted on equipment sitting far away- out of sight of the factory manager’s central cubicle. With the Industrial Internet of Things (IIoT), manufacturers are finally doing the unthinkable- but something they wish they could have had long before- the ability to process their data close to the source where it is captured.

 

There is no room for ‘why do we need it’ in the current era of manufacturing innovation and IIoT-led industrial automation. Especially when we know that world-class manufacturing sites work at 85% of their theoretical capacity. The average factory is only at about 60%- hinting strongly at a vast room for improvement in how activities are streamlined, as pointed out in a CB Insights report for 2022. Let’s move to the ‘tell me how’ then. Let’s understand what this new genie is called, the Industrial Internet of Things (IIOT), and how to use it wisely for the miracles a manufacturing enterprise wishes for.

 

IIoT – The 6th sense for machines

IIoT is IoT on a factory floor. And IoT, or the Internet of Things, is simply that- the Internet that connects things. In the case of IIoT, the ‘things’ are nothing but sensors pinned on various machines and equipment in a manufacturing set-up. IIoT means a network of internet-connected objects that collect and exchange data using sensors. With the help of this highly real-time and precise data, some beneficial decisions can be made about machines, like fixing them in advance due to alerts for repair. Or avoiding a major accident due to red flags received on time. Or they are equipped with all the information for plant scheduling, shift management, and MRO (maintenance and repair).

 

IIoT, explained in broad strokes, is the intelligent use of data spun out of sensors on machines and equipment. With the sophistication of big data and machine learning, it becomes easy to harness the data generated from connected devices and then collect, transmit, and analyze it with the right tools in the right places. This can improve machine-to-machine (M2M) communication and streamline workflow, but it can also arm decision-makers across the plant with helpful information about machines, production, uptime, breakdowns, and quality control. Powered by cloud computing, this data can be relayed anywhere without physical infrastructure limitations. With edge computing jumping in, these sensors and data-collection can be placed in complete proximity to the machines instead of confined near central servers.

 

Through well-architected and well-placed sensors working in absolute rhythm with powerful devices and fast connectivity, IIoT helps factories work on their toes- with agility and intelligence working in the perfect formula.

 

Unlike traditional manufacturing methods, where assembly lines depend heavily on manual productivity, human attention, quality, and proper planning, modern manufacturing is all about technology and automation for precise and error-free production. With the addition of IIoT in manufacturing innovation, this precision and performance can potentially remove almost all mistakes, delays, and blind spots.

 

When IIoT enters the manufacturing set-up, all its sensors and information-edge points capture and transmit immediate and complete data about machines. This real-time advantage easily translates into many beneficial manufacturing outcomes, like:

  • Improvements in efficiency due to minimal machine downtime
  • A jump in productivity achieved through well-reconciled machines with production targets
  • Immense cost reduction on MRO and planning
  • Optimized operations and labor planning
  • Granular supply chain optimization
  • Accurate and real-time asset tracking extends machine life
  • Condition-based equipment maintenance
  • Better visibility and data-driven decision-making for foremen, supervisors, and plant managers
  • High-quality assurance- thanks to immediate alerts and corrective action
  • Rise in profitability as demand can be fulfilled without any latency while inventory is managed smartly

Challenges, considerations, and future trends in IIoT

Interestingly, the manufacturing industry commands the lion’s share of investment and market share amongst all sectors due to discrete and process manufacturing intensely investing in IoT adoption. As per some estimates, as we look ahead, in the next few years, discrete manufacturing, process manufacturing, and life sciences sectors will spend the most on IoT solutions. If we look at some numbers from ResearchandMarkets, we will see that the total global IIoT market will reach $997 billion by 2028- and this growth will be driven by manufacturing and healthcare. IIoT in manufacturing alone can reach $191.3 billion globally by 2028. With this proliferation, we will see simultaneous growth in manufacturing innovation with a surge in private wireless implementations, AI combined with digital twins, cloud robotics, and teleoperation.  

 

The spotlight here falls on particular early adopters and fast-track users who embraced IIoT with the reality checks they got during the pandemic. We have seen how industries such as manufacturing, oil & gas, and transportation faced a slump in demand- thus waking up to manufacturing innovation with future and current ongoing IIoT projects for quick adjustments to productivity and capacity.

 

From now on, we will see IIoT expanding both in breadth and depth of adoption, with new use cases being developed, virtual manufacturing, high-level simulation, advanced CAD/CAM, and the use of digital twins—all these will propel IIoT to new frontiers, more so as we see a deeper integration of AI, machine learning, and blockchain in manufacturing with IIoT.

 

A McKinsey report, ‘Leveraging Industrial IoT and Advanced Technologies for Digital Transformation in Manufacturing,’ shows that – Many manufacturing organizations are already piloting digital initiatives in IIoT. A drop in compute power costs and improvements in IIoT integration, connectivity, and platform usability and management have helped to add more pace to the traction that IIoT is getting. But this report also highlights how challenges can deter this fast-growing trajectory, such as heterogeneous systems and application landscapes or issues on governance between IT and operational technology (OT), plants, the need for leadership commitment to make it an organization-wide effort- and other such pragmatic challenges.

 

The best way to make IIoT successful is to have a clear roadmap and team. Also, use tools that fit the stage and vision you aim for with your IIoT investment.

 

Carvewing can help you be fully equipped to tap all these possibilities in IIoT. This technology powerhouse offers a complete bundle of solutions to enterprises looking to arm themselves with the advantages of IIoT:

  • Business Intelligence with enterprise-context
  • Data Analytics
  • Robotic Process Automation (RPA)
  • Artificial Intelligence (AI)
  • Data as a Service
  • Data-driven decisions
  • Connected Architecture
  • Connected Products and IoT Solutions
  • MEAN stack
  • Tools for MongoDB-Express.js-Angular.js-Node.js
  • PostgreSQL as Database, Node.js
  • Python in the back end and Angular.js in the front end

A CB Insights report tells a brutal truth- despite representing nearly one-quarter of US GDP as of 2020, manufacturing remains a relatively low digitization area. When most countries around the world average fewer than 200 robots per 10,000 employees, a lot of white space lies untapped for automation and robotics investment on the factory floor. According to a PwC report, many manufacturers and industrial product companies are progressing in connecting their products and appliances to the IoT. But it is a massive business disruption that calls for new capabilities. Also, to ensure IIoT does not lead to data leakage, data vulnerabilities, and dead-ends in the process- there should be a strong emphasis on security, interoperability, and standardization.

 

IIoT is another written moment, a breakthrough, a Déjà vu of what Henry Ford and Nikola Tesla went through. We are way past the ‘why do we need it’ question. Let’s get going and ask the precious question: ‘Tell me how to do it’.

 

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