January 2021 Driving Force Blog
01 January 2021

IIoT & Industry 4.0:
Predictive Analytics can Prevent Costly Shutdowns and Repairs at Industrial Facilities

It’s no secret that the digital age has allowed rapid growth of the possibilities within the manufacturing industry. Advanced machines and people connected by a vast network which can give real-time analytics, collect and exchange information, and monitor processes like never before. This is called the Industrial Internet of Things (IIoT); a term coined by the industrial giant, GE, in late 2012. Not to be confused with Internet of Things, or IoT, the IIoT connects machinery and devices especially in industries where system failures can result in significant downtime, high-risk or life-threatening situations. The main purpose of connecting these machines together is to improve efficiency, health, or safety.

History of IIoT

The concept of IIoT stems through what is called the Industry 4.0 Vision, which originates from the German manufacturing industry. The thought is that this vision is a series of recommendations that companies can do to become more competitive and exploded into a global phenomenon. Also often called the “fourth industrial revolution”, the Industry 4.0 vision is generally characterized with the following schools of thought: the use of extensive automation, a shift from central industrial control systems to product-defined production steps, closed-loop data models, personalization/customization of products, and of course, bridging the physical and digital world through cyber-physical systems (enabled by IIoT). The predictive approach that IIoT allows helps to deliver safety, performance, customer experience, capacity, cost efficiency, and sustainability of key business assets.

Using Analytics

With the plethora of new information that is availableunderstanding and identifying patterns in data is a necessity for any manufacturing operation to maintain a “well oiled machine” status. This is where an asset condition monitoring tool is useful.Similar to how humans go to the doctor for preventative and diagnostic testing, these types of apparatuses do the same diagnostics for machines. Often, even E-mail and/or text alerts can be set up to notify the maintenance or plant personnel of potential problems with the equipment. This  can prevent future machine failure and allows for scheduled maintenance or repairsreducing unnecessary and unplanned downtime. The data gathered is presented in a clean visual portal for an efficient user experience.

Additional Business Use Case

The IIoT allows for efficient decision making, even from a top level, during business management. Data that comes from sensors within the network of machines could potentially open up new revenue streams. Depending on your industry, there are several options for this, but they all boil down to a common thread – a premium service for your end consumer. For example, those in the transport industry might find freight monitoring and fleet management analytics to be useful for their own operations along with allowing a charge to be able to access this data. Accessing this data would provide information on shipments and foresight into potential bottlenecks.

Unsurprisingly, a Genpact research study showed that almost 81% of organizations globally believed that the successful adaption of IIoT is critical for future success. This is especially true when we talk about high-tech and large enterprise companies. Having smart monitoring, predictive maintenance, and being able to make intelligent decisions all from your smart phone or tablet is the way of the future for industrial manufacturing facilities.