Industrial Internet of Things (IIoT) Challenges


The advent of the Industrial Internet of Things (IIoT) is being dubbed as Industry 4.0 or the 4th industrial revolution. According to a McKinsey report, this revolution is well underway, with an anticipation that the percentage of factories adopting IIoT will reach 65%-90% in advanced economies and 50%-70% in developing economies by 2025. The economic benefits are projected to be in trillions of dollars with a large percentage of those coming from improvements in Operations Optimization, Predictive Maintenance and Inventory Management.

The IIoT revolution is enabled by the advances in electronics hardware, network connectivity, data storage, analytics and cloud infrastructure. Cheaper and more powerful hardware is empowering smart sensors, wireless networks and gateways. Ability to carry large data volumes over local or remote networks for storage and processing has enabled analytics. Analytics from diverse data sets in real-time as well as offline, in turn, has opened newer business models and more efficient work-flows. Getting all these ingredients to work together is what makes the whole greater than the sum of the parts.

The overall IIoT adoption started gradually and seems to be accelerating now. Just like all other revolutions, the 4th industrial revolution is also not without its own resistance and challenges from Luddites who would oppose it for various reasons. There are a variety of factors behind its slower than expected adoption rate, ranging from technical to human aspects. Some of the most significant are:

Security and safety concerns: For the entire end-to-end deployment and at each stage and interfaces in between, including physical security of the deployment, data security, and safeguards

Integration difficulties: Legacy hardware, lack of interoperability, a mix of the multitude of technologies and protocols, lack of IT infrastructure on the shop floor

Infrastructure requirements: Reliable and consistent network connectivity, storage space and analytical processing power required to handle very large data volumes

Business-related challenges: Complexity of deployments, Initial investment, not very attractive RoI (Return on Investment) unless full potential is realized using analytics, system downtime and testing for deployments

Human/Social issues: Lack of trained resources with technology and domain skills, worker concerns about job security, reluctance for change, retraining

Ecosystem issues: Too many platforms and vendors to choose from, lack of Inter-operability and accepted standards

Apart from these, all industrial deployments must adhere to the established standards related to confidentiality, availability, integrity and safety as well as typical enterprise IT security practices. It is important not to forget that IIoT deals with cyber-physical systems where the physical world (devices, machines, infrastructure, etc.) could be impacted remotely over the internet, that is, from the cyberspace. The recent past has ample examples of criminals, state-actors and hackers manipulating such systems with devastating and scary outcomes. Add to these amateur hackers, buggy software with unintended side-effects, improperly implemented network barriers, etc., and suddenly IIoT becomes a worrisome business!

The next 2 installments of this 3-part series will discuss some of these issues in more details.

Recent Posts

Start typing and press Enter to search