The manufacturing sector is more productive and efficient than ever thanks to the industrial internet of things (IIoT). And it couldn’t come at a better time — global manufacturing output growth has been decelerating since 2018, according to quarterly reports published by the United Nations
By a&s International
Industrial Development Organization (UNIDO). The UNIDO attributes deceleration to increased risks and uncertainties including tariffs and trade tensions that have affected the world’s industrialized economies.
Despite a slowdown in manufacturing growth, the rise of smart factories and adoption of IIoT and cloud technologies have grown. By using the vast amount of data generated
from the Internet of Things, IIoT and cloud, manufacturers are able to predict equipment breakdowns, prevent unplanned downtime and reduce costs. However, due to this, understanding what to deploy, how to implement it and what the benefits of IIoT and cloud technologies are is critical.
Industrial Internet of Things Improves
Smart Factory Productivity
The industrial internet of things is driving the growth of smart factories and helping manufacturing be more productive and efficient.
Today’s smart factories are growing thanks to the growth of the Internet of Things (IoT), which has brought about the industrial internet of things (IIoT). As global manufacturing output slows, productivity and efficiency have become increasingly important. By using IIoT technologies, manufacturers and smart factory operators are able to collect and analyze data that enable them to optimize operations.
More Data, More Benefits Keeping up with technological innovation comes down to the aggregation, integration, processing and analyzing of data on IIoT platforms, said to Richard Howells, VP of Solution Marketing at SAP. “This is why factories are investing in IIoT in order to realize business benefits across the entire company. Many factors, applications and technological developments drive these business benefits and therefore demand for IIoT,” he said.
Nowadays factories are adopting digitization strategies that use IIoT technologies to capture additional sensor-based data (e.g., vibration, environmental, etc.) to augment their existing manufacturing data sources and provide additional insights. “This additional insight identifies opportunities to improve the operational efficiency of the asset or process as well as the health of the asset… We also see IIoT technologies being used to obtain data from older manufacturing equipment, that may be 20 to 30 years old,” said Enrique Herrera, Industry Principal for Manufacturing at OSIsoft.
However, manufacturers don’t always know exactly what type of data to collect when they want to start collecting it.
Patrick Smits, Marketeer at Ixon explained, “Objectives are not always clear from the start but evolve during the process. Using
an established IIoT provider with roots in manufacturing obviously helps lowering entry in Industry 4.0.”
IIoT in Practice The entire lifecycle of production can benefit from the many features and functions of IIoT solutions. This ranges from product design to monitoring of inventory levels in the supply chain.
Howells explained that predictive maintenance data gathered from IIoT can help minimize production downtime, which can cost a manufacturer tens of thousands of US dollars a minute, depending on the industry.
Utilizing predictive maintenance not only reduces downtime, it increases productivity by alerting operators to maintenance needs
before problems occur. Remote access that allows factory operators to connect to machines for remote support and remote assistance is another way IIoT can help optimize production processes. Smits pointed out that the ability to troubleshoot and monitor machines, as well as deploy new programmable logic controller (PLC) software over VPN, becomes much easier and saves a lot of unnecessary expenses when able to do it remotely.
More advanced use cases of remote access involves monitoring machine production or factory production, or using metrics and KPI’s to improve overall equipment effectiveness (OEE), Smits added. To do this, factories must start by logging machine data and then combine and analyze this data in order to optimize the production process.
Using IIoT solutions can also help manufacturers identify the root causes of quality issues in their production, which can also cut into productivity and lower customer satisfaction. Howells pointed to edge-to-cloud closed-loop machine learning and advanced manufacturing execution systems (MES) to reduce quality issues.
“An enterprise can leverage IoT usage and performance data to continuously improve its products. Right now, this requires engineers to analyze the data, but as more products get connected and companies leverage more AI techniques, generative design software could automatically create improved designs based on IoT data,” Howells explained.
Future of IIoT in Manufacturing While adoption of IIoT projects is growing, IHS Markit reported that currently half of all deployments fail; failure of a project is defined as not meeting the customer’s expected payback. High failure rates are often
attributed to inflated expectations and a failure to gather support and cooperation from critical personnel within the company. Half the companies deploying IIoT projects expect to see payback within one year and are not getting the payback they expected, as many of these projects can take much longer to generate returns, according to IHS Markit.
Still the annual IIoT node shipments are expected to hit 224 million units in 2023, a 100 million unit increase from 2018, as reported by IHS Markit. However, to ensure more successful deployments of IIoT projects, providers must work together with manufacturers and smart factory operators to manage expectations and develop projects that can be executed successfully.
Choosing the Right Cloud for the Industrial Internet of Things
More manufacturers are looking to use cloud computing, but choosing between a public or private solution depends on need.
More manufacturers are deploying solutions that build upon the industrial internet of things (IIoT), making operators also look to cloud computing technologies.
Benefits of Cloud Computing for IIoT
There are many benefits of using cloud computing for IIoT. One being that a cloud service provider handles all IT-related issues such as security, scalability, user management, storage, hardware and connectivity aspects, leaving factories to focus on what they do best: manufacturing, according to Patrick Smits, Marketeer at Ixon. Manufacturers are also leveraging cloud computing to take advantage of resourceintensive, advanced analytics and machine learning technologies. “Using cloud technologies, manufacturers can gain additional insights, which are identified in the cloud using advanced analytics and then fed back to the operational environment. This expertise may also come from industrial equipment manufacturers that offer third-party digital services to manufacturers,” said Enrique Herrera, Industry Principal for Manufacturing at OSIsoft.
Already many manufacturers have started to adopt machine learning models and are applying them to smart manufacturing data, according to Richard Howells, VP of Solution Marketing at SAP. Doing so allows manufacturers to minimize repeatable tasks capable of being performed by software, improve the accuracy and predictability of maintenance schedules, and drive first-time-right results across the organization. Furthermore, since cloud environments offer almost unlimited compute and processing power, it can also provide a similar interface for work from the different points of view of different employees, engineers and senior management.
Cloud-based networks of connected assets are also enabling manufacturers to shift their business models to be more prescriptive
than reactive. By creating a central repository for collecting and tracking critical information, cloud computing further allows
manufacturers to develop smarter products to capture more information about how they are operating and performing around the globe, Howells added. Additionally, there are economical and environmental benefits to using cloud computing for IIoT. Using an IIoT cloud platform with shared infrastructure can save costs and lower overall power consumption.
Private or Public Cloud?
There are several main considerations when choosing between public or private cloud for IIoT. These include economies of scale, speed to provision and integration to manufacturing enterprise solutions. It is also important to understand what the user’s end goal is for utilizing cloud.
A private cloud could be ideal for customers who want their own dedicated platform with isolated data, storage and network environments. Since a private cloud would require the manufacturer to take care of essentials such as security, scalability, flexibility, data integrity, back-ups themselves, it is a good solution for those looking to attend to their own data security, privacy and protection needs.
On the other hand, a public cloud solution means the above-mentioned essentials (e.g., security, flexibility, etc.), are all taken
care of by the cloud provider. This may be preferable to some manufacturers.
Overall, worldwide spending on public cloud services is expected to more than double between 2019 and 2023, according to a report from the International Data Corporation (IDC). Discrete manufacturing — manufacturing of distinct items — accounts for a big portion of this growth.
Howells pointed to another opportunity, one that brings the benefits of private and public clouds together: a multicloud. “Multi-cloud is a strategy in which companies can store and manage their software in the cloud environments that best fit with their chosen environment and software, such as AWS, OpenStack, Microsoft Azure, Google Cloud Platform or others, helping companies realize both cost savings and efficiencies,” he explained.
Regardless, no matter which cloud model a smart factory chooses, the top priority should be understanding the individual business needs and matching that with the top benefits of each type of cloud environment.
User Education will Promote Growth
For now, one of the main challenges is convincing manufacturers that cloud solutions are more secure than most private cloud or on-premise solutions, where local IT departments are responsible for the security and management of data. Cloud providers actually have a much better track record in securing data and connectivity options than most local IT departments, according to Smits. Ultimately, more in-depth training and education of cloud benefits could help ease the concerns of manufacturers and further propel adoption.
IIoT Infrastructure and Hardware Requirements in Smart Factories
Ensuring the success of a cloud-based IIoT system in a smart factory requires the right network infrastructure and proper security
measures. It is estimated that there are currently over 1 billion connected IIoT devices being used in factories around the world. And although the IIoT market is growing exponentially, there are several barriers to even greater success. Deploying the right network infrastructure for cloud-based connected industrial internet of things (IIoT) solutions and securing that network are key to the market’s future growth.
From Fieldbus to Ethernet to Wireless
Today’s factories overwhelmingly use the industrial ethernet and fieldbus protocols for connectivity to manufacturing equipment.
Traditionally, the industrial sector used fieldbus — a group of industrial computer network protocols specifically designed for communication between industrial controllers and sensors — to connect to the industrial network; however, industrial ethernet
is set to overtake fieldbus as the primary network medium in 2020, according to IHS Markit.
Fieldbus technologies offer various advantages such as determinism and more physically robust connectors and components, but are not optimized to be linked up to a wider network setup or the internet, IHS Markit said. Their report added that the transition from fieldbus to industrial ethernet is key to future-proofing and benefiting from IIoT solutions. Industrial ethernet is not
only faster than fieldbus, but also supports the IP addressability required for IIoT.
The growing adoption of industrial ethernet is also expected to further enable the transmission of larger volumes of data due to the greater bandwidth compared to fieldbus. IHS Markit believes this will ultimately bring in more technologies like the cloud, which will “supercharge” the IIoT business.
Wireless technologies could also help advance connectivity in factories, although uptake has been slow. Enrique Herrera, Industry Principal for Manufacturing at OSIsoft explained, “There is significant investment by the telecommunications companies to push 5G and private LTE technologies into factories, but adoption is still in its early days.” These telecommunication technologies, though, may be more readily accepted with remote or geographically dispersed assets.
Securing Cloud and Network Infrastructure
Faster connectivity is allowing manufacturers to utilize cloud-based solutions, but security still remains a concern. Ideally, IoT connectivity hardware should not be directly accessible via the internet. Software on these devices is often not updated regularly, which makes exposing them directly to the internet not a good idea. This is especially true nowadays with vulnerability scanners like Shodan.io available to everyone and anyone.
Making sure every factory router is completely secure is more important than ever. To do this, Ixon’s strategy is to block all incoming traffic on the router. “On boot Ixon’s IXrouter sets up a secure VPN connection to our cloud platform to make sure all communication to and from the platform is well secured. All other access options are disabled by default, so there are no ports from the company network or internet that can be abused by hackers to gain access,” said Patrick Smits, Marketeer at Ixon.
From a cloud perspective, cloud providers are able to secure both the cloud infrastructure and on-premise hardware with highly skilled employees that monitor and remedy security issues full time, protecting the complete infrastructure against all possible attacks. These types of end-to-end solutions can be very well secured, according to Smits, because the complete IIoT ecosystem, including hardware, connectivity and cloud infrastructure, is controlled by the cloud provider.
Smart Factories are Adopting More As-a-Service Models
The utilization of the industrial internet of things has made it possible for smart factory operators to take advantage of various new as-a-service models to increase productivity.
More companies have started offering new “as-a-service” business models for the manufacturing sector. Increased adoption of the industrial internet of things (IIoT) and cloud technologies are giving manufacturers the ability to combat challenges like unplanned downtime and deferring upfront costs. Loses from unplanned downtime can cost manufacturers millions of dollars. Utilizing new applications enabled through IIoT can help overcome challenges such as this. IHS Markit estimates IIoT solutions can reduce unplanned downtime by around a 30 percent.
Many companies have started or plan to offer new service models, such as maintenance as a service or product as a service. These business models are empowered by IIoT platforms by sending alerts if a product requires maintenance or attention, among others.
Maintenance as a Service
Collecting large amounts of maintenance data has been made possible by the Internet of Things (IoT) and IIoT. The collection and analysis of this data have led to a new business model, maintenance as a service (MaaS). This service model gives smart factory operators and manufacturers the ability to remotely monitor machinery, create a smarter workforce and provide insight into the lifecycle of equipment.
Utilizing MaaS can help smart factories deal with the problems brought on by unplanned downtime. Furthermore, the information can be used to determine when maintenance should be scheduled before a breakdown occurs. By doing this, smart factory operators can shift from a preventative maintenance approach to a predictive maintenance approach.
Product as a Service
One factor hindering the growth of smart factories and IIoT solutions is the cost of equipment. The product-as-a-service (PaaS) business model allows smart factory operators to pay for processes and operations instead of purchasing the equipment outright. This takes the stress off manufacturers when it comes to maintenance expenses, product failures and ensures they will not be stuck with obsolete equipment when it comes time for upgrades.
The current market for PaaS is still pretty new, but the continued expansion of IIoT solutions and smart factories should propel development. For now, some PaaS providers are delivering value-added services to machines already owned by manufacturers to help ease the transition. In this case, PaaS providers could add performance monitors such as sensors and controllers to existing equipment. The data collected could then be used to improve efficiency and even the product itself.
Automation as a Service
The global automation-as-a-service (AaaS) market is expected to reach US$6.2 billion by 2022, according to a report by MarketsandMarkets. Growth is attributed to the increasing demand for automation and the increasing adoption of cloud technology. In the manufacturing sector, AaaS allows manufacturers to shift from slow manual processes to faster automated ones. It is being increasingly adopted for various workflows, such as vendor management, purchase order management, request for quotation and inventory management, according to MarketsandMarkets. Using AaaS increases productivity and reduces operational cost by eliminating routine manual and clerical tasks, and minimizing the manufacturing lead time.
Future of As-a-Service Models in Manufacturing
More as-a-service models are sure to emerge as the need for efficiency, productivity and cost savings continues. Already models for IoT as a service and IIoT as a service exist and will likely continue to grow.
All of these as-a-service models, though, require the collection, sharing and processing of data. Concerns about data security and data ownership could pose challenges to adoption. However, the proper education, training and cooperation between all related parties on how to handle and secure data will ensure it is used to the advantage of manufacturing and not against it.
