IoT, Industry 4.0, Industrial IoT (IIoT), odds are that you have heard these terms used around you recently. IoT in the consumer space is a pretty straightforward concept to understand. IoT is an interconnected world of computing, mechanical and digital devices such as in a smart home consisting of thermostats, webcams, smoke detectors, smart doorbells who can talk to each other and managed from the internet or a smartphone.
On the other hand, when we look at things at a larger scale or we can say, an “industrial scale” then it is a whole new IoT world. Industrial internet of things (IIoT) is an extension of IoT and is the use of IoT largely in manufacturing applications, and supply chain management. IIoT is driving the next wave of the industrial revolution or we can say it’s opening a gateway to ‘Industry 4.0’. The key idea driving Industry 4.0 is a connected world comprising humans, machines, sensors and data working together in real-time to transform business and manufacturing processes.
A traditional manufacturing environment application works by connecting machines to a centralised data centre. The pain points here are there isn’t any interconnection between machines, the latency rate is high and processes are manual and thus prone to errors. Contrary to this, IIoT puts a modern approach and makes processes decentralised. IIoT makes machine interconnection possible converting them into automated and smart processing units. With IIoT machines have the ability to talk to each other in their own Machine to Machine(M2M) language.
The basic components that drive an IIoT system are:
- Secure intelligent assets such as sensors and smart controllers – that can sense, communicate, store and transmit information
- Communication and data storage infrastructure – often cloud-enabled
- Data analytics and smart business apps that generate information from the data
- Skilled workforce
How IIoT Can Revolutionise an Industry
IIoT is transforming the manufacturing industry and other supply chain intensive industries by maximising efficiency, reducing downtime and increasing the overall production. While IIoT adoption is still in a nascent stage, there are some industries that have taken the first mover advantage and have started demonstrating readiness use cases.
The Smart Factory
The adoption of IIoT has reshaped traditional factories to create smart factories. The systems work with interconnected machines and real-time data exchange that merge the departmental communications along with unified operations and information systems.
How is IIoT making factories ‘smart’?
IIoT has revamped how the traditional units worked. The slow and manual processes are now automated processes with M2M communication. This can be easily demonstrated through an example of how Smart Factories deal with preventive maintenance.
A smart factory has machines, sensors, databases, and humans all working in sync with each other. Sensors within machines can automatically notice a fault and the software logic sends an automatic alert to the right human to analyse the cause behind the fault. With Artificial Intelligence incorporated, machines determine the cause of the faults and go beyond predictive to prescriptive approach pre-empting problems before they exist. This in return reduces the maintenance cost and increases uptime of the factory by introducing parameters to fix machines with accuracy. In-return this leads to increased shelf-life of components and less-time involved in problem detection and rectification.
Energy & Utilities
The Oil & Gas industry is embracing IIoT with a multitude of benefits. Now the energy and utilities have an ability to easily sync data and simultaneously operate across multiple locations. This is made possible with the adoption of cloud, and installation of sensors that capture real-time data on the operating conditions of assets, monitor physical conditions such as temperature, pressure and humidity, and even environmental conditions. The practical scenario here is that Oil & Gas companies are remotely controlling their drills and monitoring the earth’s crust by remote control sensors and maintaining the flow of resources.
Logistics
With so many moving parts in a logistics system, from factories, collection points, and the transport network, it was difficult to maintain and manage a single view of the entire process. Through an ecosystem of sensors on the machines and vehicles covering the entire supply chain, it is now possible to access real-time data. It allows advanced functionalities such as virtually positioning hundreds of vehicles and optimising their route. In the process saving energy and reducing the time for delivery. The consequence is reduced costs for fuel, vehicle maintenance, and staff, plus increased customer experience through shorter and more accurate delivery times.
Other Industries – Promising the change
The adoption of IIoT will go beyond the early adopters and revolutionise several other industries. The Transportation industry is ripe for transformation given that infrastructure is being strained and margins reduced. The challenges of demand and aging infrastructure can be best handled by IIoT.
“The success of smart cars will eventually depend on how ‘smart’ the infrastructure is,” opines Vernon Turner, Executive Analyst, Ecosystm. “Several smart cities are already thinking along these lines, and adoption of IoT in Transportation is set to rise exponentially.”
Another industry that will benefit immensely from IIoT adoption is Healthcare. At the moment, asset management IoT systems have been adopted by several organisations, as in-patient remote monitoring systems that allow clinicians to monitor and analyse patient data remotely.
“The real value of IoT will be realised when clinicians have a clear workflow that allows them to monitor patients outside the hospitals,” says Sash Mukherjee, Principal Analyst, Ecosystm. “In the past, healthcare organisations have been influenced by the Manufacturing industry – by Lean and Six Sigma. They will benefit from implementing Industry 4.0 technologies, that will transform not just the provider organisations, but healthcare in general.”
Turning IIoT into a Profit Engine
Given all of this information about IIoT you may be thinking about the ROI, associated costs, benefits and the industry-wide exposure of the Industrial IoT. It is imperative that companies large & small are embracing Industry 4.0 change. IIoT is benefitting businesses through differentiated offerings, a creation of newer revenue streams and increased monetisation of existing offerings.
The Ecosystm IoT Study, 2019 looks at the drivers of IoT adoption across industries.
The data shows that the key drivers of IoT adoption can all affect the profit margin of an organisation.
- Innovation. In today’s competitive world, innovation in product designing and service delivery is directly related to a positive impact on profit margins. Organisations are looking beyond cost savings through their investments in IoT and are using IIoT to bring new, innovative products and services to the market. They are looking at creating innovative businesses that can leverage technology and offer cost savings.
- Workforce Optimisation. It is impossible to bring change without workforce optimisation. Organisations are working on the valuable insights offered by IIoT systems which further provide ways to optimise the workforce and accelerate productivity. Implementation of automated production units and the reduction of manual labour is bringing both productivity gains and increased profits. It is also boosting employee morale – happier employees impact the profitability of organisations, reduces turnover, improves customer interactions, and promotes more job ownership.
- Customer Experience. Customer expectations have gone up and so have methods to improve customer experience. Organisations are taking IIoT seriously, as it’s unleashing capabilities to improve processes throughout the product life cycle while also improving product quality through better QCs. Feedback to product improvement time has reduced – customer features and product improvement requests can now be handled more efficiently, based on customer data.
Businesses that fully capitalise on IIoT systems are successfully building a competitive edge through their innovative products, optimised workforce, and differentiated products and service offerings to enhance customer experience.
What Lies Ahead?
As IIoT percolates into other industries, we will potentially see a new industrial revolution. This has obviously been attracting investment and technology companies quickly to offer related technology offerings that tech buyers would do well to consider along with IoT.
Cloud
Data management will become an obvious challenge with IIoT-driven data proliferation. Already the industry has been talking about going beyond cloud to “fog” computing. The real value of IIoT will be realised when the solutions become able to operate on the Edge. This will see an increased uptake of SaaS offerings that will be required for quick and accurate data-driven decisions.
AI
AI will eventually go further than basic machine learning and incorporate deep learning for better predictive and prescriptive analysis. IoT devices with embedded AI will truly revolutionise industries. This is another technology area that tech buyers should keep an eye on, irrespective of the industry.
Security and Risk Management
An explosion of IIoT devices and data will bring new risks. Cybersecurity experts and teams will be required to constantly monitor vulnerabilities, follow security best practices and eventually predict breaches.
The Future
Industry 4.0 is very much a buzzword in certain industries, with several advanced organisations already following the business and technology practices. Naturally, there are still many companies that do not see the need for new technology or would rather invest in other areas.
For organisations that are looking to modernise, innovate and remain competitive, Industry 4.0 is a good benchmark of how technology can be leveraged. IIoT is a key enabler of Industry 4.0 and has the potential to deliver benefits to majority industries through increased intelligence and curated data – the question is how soon we can witness it on a scale.
Which are the other industries that you think will benefit from IIoT? Leave your comments below
Is IIoT Edge Computing solution a real Internet of Things (IoT) trend for 2019?
As large hardware manufacturers like Cisco, HPE, Dell and more are building specific, robust and secure infrastructure for the edge, it is believed that there will be a lot of money flowing in the IIoT Edge computing world.
The Development and implementation of Edge-Machine Learning solutions is a complex process and requires a combination of rich industry experience, knowledge of automation (PLCs, SCADAS, HMIs), electrical & mechanical engineering along with unique Edge Computing distributed system. This is used by Data Scientists to develop Machine Learning algorithms which can be utilised by IIoT applications in the manufacturing industry.
For organisations looking to implement these solutions, it is always a good idea to know more on adoption and ask for the continuation of a pilot project for more than a year.
Below are the top 5 things that one should follow to accelerate implementation of IIoT edge computing solutions in the Manufacturing industry –
1) Get help to find the needle in the haystack
With the fragmented ecosystem of IIoT vendors and companies talking about the Industrial Internet or Industry 4.0, the challenge that always appears in front of the customers is to ask for free pilots from the manufacturers.
It is not just finding the needle (IIoT best or cheaper solution) in the haystack (ecosystem), it is how this needle matches with your business and technology strategies.
I know, I am selling myself, but my recommendation to you is to get advice from independent IIoT experts.
2) Avoid OT Vendor Lock-In: We need machine data availability
Powerful Edge Analytics-Machine Learning applications require data exchange with the Programmable Logic Controllers (PLCs) of the manufacturers. By looking at the specifications we may think that it will be an easy task to extract the data from PLCs going through different ways or manufacturer’s help-guides. However, the problem is vendor lock-ins, most of the top PLC manufacturer’s do not allow “easy” data access and extraction methods neither to the customers nor to any third parties.
It is not a question of protocols, it is a question of vendor lock-in and data availability.
Customers must seek and claim for open-source solutions to avoid vendor lock-in during the long run. The open source can better lead to the path of innovation in their manufacturing plants.
3) Edge Computing and Machine Learning: The last frontier to break between IT/OT
In my article “IT and OT, Friends or Foes in the Industrial Internet of Things?” I was optimistic about the quick convergence of Information Technology (IT) and Operations Technology (OT), I was wrong. If you visit and inspect a manufacturing plant floor, you will see how much progress is still to be made.
Edge Analytics is a key component in the integration of IT & OT and requires a knowledge of both to make it work. The lack of skills & knowledge in the IT and OT fields impact the business & operations and creates a dilemma on which department should lead the Edge Analytics projects.
Manufacturing companies need a role with authority (Chief IIoT Officer or CIIoT) and resources to lead the IT/OT convergence strategy.
4) Do not stop by the dilemma of Edge: To Cloud or NOT to Cloud
When I wrote in 2016 “Do not let the fog hide the clouds in the Internet of Things”, the hype around Edge Computing and Machine Learning started. There was a confusion about fog computing and edge computing and how this layer will impact the IoT architecture, especially cloud workloads.
Today, many cloud vendors offer IoT platforms and tools that combine the Cloud and the Edge application development, machine learning and analytics at the edge, governance, and end to end security. On the OT side, companies like Siemens have launched MindSphere, an open cloud-based IoT operating system based on the SAP HANA cloud platform.
Manufacturers should continue to deploy and develop Edge Computing – Machine Learning applications to monitor the health of their machines or to improve their asset maintenance or to monitor the quality control of their plant floor processes and shouldn’t stop because of the fear of the integration of their platform with the Public or Hybrid Cloud environment.
Edge Computing solutions help manufacturers to improve their competitiveness without the Clouds but make sure your Edge IIoT solution is ready for easy integration with the Clouds.
5) Connected Machines is the only way for new Business Models
Security is another major obstacle for the adoption of IIoT in the manufacturing industry. Manufacturers have been reluctant to open their manufacturing facilities to the Internet because of the risks of cyber-attacks.
In a fast-moving era where platforms and services require products and machines connected, every manufacturing factory should be able to tap into machine data remotely and make it available for Machine vendors. This requires every Edge Computing / Machine Learning system to be built with the capability to share data remotely via open and secure protocols/standards like MTConnect and OPC-UA.
Having machines connected is the first step to make machines smarter, to build smarter factories and to flourish new business models as Remote Equipment Monitoring.
Key Takeaway
The benefits of using Edge Computing / Machine Learning solutions are very attractive to the manufacturers because it offers minimal latency, conserve network bandwidth, improve operations reliability, offers quick decision-making ability, gather data, and process the collected data to gain insights. The ROI in such IIoT solutions is very attractive.
To get these benefits and to grace IIoT journey, manufacturers have to step-up and accept to receive tangible and innovative business value.