How Industrial IoT Enables the Factory of the Future ??????

Trillion-dollar projections on the expanding size of the market are urging companies to capitalize on the Industrial IoT [IIoT].

For many, however, it remains unclear how industries should apply IIoT to begin making the hyper-efficient and agile factory of the future a reality.

As the?Fourth Industrial Revolution?transforms manufacturing, logistics, and agriculture, enterprises continue to look for ways to?create value from?converging technologies. But what are the steps that companies need to take to put together an effective agenda of action?

It is essential that the?implementation of the industrial internet?is incorporated into the?company’s strategy?and?business development?activities.

In other words, chief executives must embrace change. To advance?decision-making?to the correct level,?CEOs?must be included from the very beginning, possibly as the?initiative’s main sponsors. IT/OT officers alone cannot effectively drive real digital transformation.

Manufacturers should initiate the transformation by defining a?specific set of goals, to be assessed and validated initially with a?PoC?focusing, for example, a single non-critical production line/asset,?before the implementation at scale of an end-to-end Industrial IoT solution. Being successful, the next step will be to deploy an?industrial internet pilot?in one facility, which will be used as a case study for learning how IoT works in this whole industrial environment. The pilot facility is then adjusted and developed according to observations. After the test phase, it is easy for a company to apply the same principles, with proper adjustments,?at scale/in production to other plants.

The concept of flexible infrastructure refers to how transformation can be simpler in certain contexts. It is easier to justify?large investments?in industrial internet in environments where industrial internet is incorporated into production by transitioning directly to?automated, advanced IIoT environments. The transition phase is less complicated when the existing infrastructure is light because there are fewer things that must be accounted for in applying new solutions.

Industrial internet in practice

Applications of Industrial IoT are already a reality. There are tenths of different use cases of IIoT in enterprises. Companies are already?developing IoT applications that work, and they have started making a difference, and more important of all, getting actual results, and a ROI in months, not years!

For example,?transportation?and?warehousing?benefit from?automated vehicles?and?asset tracking and tracing. In?manufacturing,?predictive maintenance?[PdM] and?asset performance management?[APM] are key areas where industrial internet boosts value creation.

Predictive/prescriptive maintenance keeps assets up and running, decreasing operational costs, and saving companies millions of dollars.?Data?from IIoT-enabled systems – sensors, cameras, and?data?analytics?enabled by powerful artificial intelligence (AI) or machine learning (ML) algorithms – helps to better plan maintenance, allowing manufacturers to service equipment well before problems occur. Data streaming from sensors and devices can be used to quickly assess current conditions (CBM), recognize warning signs, deliver alerts, and automatically trigger appropriate maintenance processes (PdM).?IIoT coupled with AI or ML thus turns maintenance into a dynamic, rapid, and automated task.

Other potential advantages include?increased equipment lifetime, increased plant?safety?and fewer accidents with a positive impact on the environment, according to?ESG?directives.

The importance of edge analytics

Companies have been proactive in moving the processing of IIoT to?cloud?services. However, in my opinion, it is not necessarily a wise move to have everything in the cloud. During critical stages of the manufacturing process, it is crucial that decisions can be made instantaneously. Here, manufacturers can benefit from?edge analytics.

Edge computing enables?real-time analytics, and -?in terms of milliseconds?– automated actions. Edge analytics is an approach to data collection and analysis where automated analytical computation is performed on data at a sensor, network switch or another device (Edge) instead of waiting for the data to be sent back to a centralized data store. IIoT can be supplemented with?open-source computer hardware and software applications?that allow some of the processing to take place on site, at the edge of the network and near the source of the data.

Edge computing?helps ensure that the right processing takes place at the right time, in the right place, triggering the right response on time to avoid critical failures, which could cost millions!

Edge computing is also a preferable option for the cloud in terms of?security, as proprietary data is kept within the company firewall. Moreover, edge computing becomes vital when you need?real-time analysis?and?automated action?to save?critical-mission?production lines or facilities from potential heavy damages.

Creating value with Industrial IoT

There’s no?value?in data?without advanced algorithms of?machine learning.

Value can be created in surprisingly simple ways by putting data to work. As an example of enhancing safety and efficiency in?fleet management, I can refer to how?Fleet Complete, a leading global provider of mission-critical connected technologies for fleet, asset, and mobile workforce-based companies,?uses?AWS?advanced analytics based on AI/ML to fuel innovation and generate deeper insights from?IoT data.

This case study illustrates how IIoT is already creating value. Fleet Complete uses AWS to help fleet owners?cut costs and reduce vehicle downtime, as well as expand its business faster by supporting more than?50 million requests daily.

The company provides?fleet,?asset, and?mobile workforce?management solutions in the?connected commercial vehicle?space. As an example, when a container comes to a port in Los Angeles and the freight is ultimately delivered to a doorstep in Toronto, each leg of the movement of that freight requires constant visibility. To that, Fleet Complete adds?vehicle?diagnostics?and?prognostic?information and analysis,?preventive maintenance?(PdM) content, and?video telematics.

By layering all these different types of data, Fleet Complete’s customers can determine things like how?driving behavior?affects vehicle brake pads, or how?poor roads?impact vehicle components and lifespan.

Augury, an Industrial IoT company, worked with?Colgate-Palmolive?to use its?AI-driven Health-Machine?predictive/prescriptive maintenance (PdM) end-to-end solution, and they saved 2.8 million tubes of toothpaste. They also worked with?PepsiCo Frito-Lay, and they saved a million pounds of product.

“We figure the savings at 192 hours of downtime and an output of 2.8M tubes of toothpaste, plus $12,000 for a new motor and $27,000 in variable conversion costs.”

It still takes courage to adopt innovations like this. However, getting started quickly by?building a case study of industrial internet?and then working towards expanding IIoT to cover more and more of the industrial realm is strongly recommended.

Companies should start seeing emerging technology like?Industrial IoT?not as a threat but as?the only way to survive?in a matter of a few years. That’s two or three years if you are an optimist, five to ten if you are more conservative.

In my view, the simple capacity of devices to seize data is?not?what the Industrial Internet of Things is essentially about. Even if you have all the infrastructure and the technology to get the data – sensors, Wi-Fi, the gateway, the cloud – and the capacity of analyzing the data,?there’s no real value in it without AI, more specifically?advanced algorithms of machine learning (ML).

IIoT?is all about?AI?or?ML?analyzing data in?real time,?to?make decisions?and?act, most of the time several days or even?weeks before a potential issue. This process results in?actual business outcomes.?Prescriptive analytics?react autonomously, real-time: In a mission-critical situation, a prescriptive system will autonomously decide what to do. This is where?edge analytics is imperative.

My point is:?You can’t consider industrial internet standalone. The?real value?comes from how companies use?AI and ML-enabled IIoT solutions?in analyzing and processing data, obtaining - by doing so - in real time insights/alerts, which enable efficient data-based decision making.

Source:?https://www.dhirubhai.net/posts/fabiobottacci_how-industrial-iot-enables-the-factory-of-activity-7031999968609546240-2Obv

By Fabio Bottacci | February 2023

Bio:?Fabio Bottacci?is a relationship builder, creative problem solver and strategic thinker. Senior industrial executive, he acquired a solid background in large multinational organizations across Brazil, US, and Western Europe. He is known for his ability to deliver results despite ambiguity and obstacles, to build bridges between people and to manage conflict and negotiations.

He began his career at?Accenture Italia, strategy practice, while attending MBA courses. He then moved to Brazil, where he consistently proved, during more than 20 years of professional experience, strong clients network, industry knowledge and business development expertise in the oil and gas, automotive and energy/utilities verticals.

Since 2015, he has been the founder & CEO of?VINCI Digital - Industrial IoT Strategic Advisory, being recognized internationally as a thought leader by well-known organization, such as the?World Economic Forum,?IoT Solution World Congress,?BNDES, etc, and helping startups, SME, and big corporations to thrive within the actual digital transformation environment, by developing new business models, and delivering actual results/ROI in months, not years.