The Industrial Internet of Things (IIoT) is one of the greatest resources managers and operators can count on to boost plant performance and safety in manufacturing. How does this inciting technology work? How can you rip off its benefits? Continue reading below! I will share the insights you want to know to boost Operations & Maintenance performance.
Key Developments in the Manufacturing Industry
Before diving into our main topic, let’s have a quick stop to overview the evolution steps leaping to today’s industrial landscape. Always a valuable precedent to go through before addressing IIoT.
Thus far, industrial transformation within manufacturing splits into four main periods:
- Industry 1.0: The beginning! Manufacturing started in 1760. At that time, mechanization through water and steam power raised the first flag towards industrialization.
- Industry 2.0: Over a century went by for a new era to begin. Mass production! Assembly lines get powered by electricity, bringing new unforeseen capabilities for the industry.
- Industry 3.0: In 1969, a third wall arrived! The addition of computers, automation, and robotics elements to the production lines changed the scope.
- Industry 4.0: The beginning of the 21st century brought new layers to manufacturing development. Enhanced machine involvement through digitization is at the steering wheel. Data and analytics offer new insights on how to make industries more effective and productive.
The integration of computerized and robotics to assembly lines and escalating tech development is accelerating the entry to new stages. The effect is such that a transition to Industry 5.0 is already gearing up to approach mass customization. Nevertheless, at this opportunity we are keeping the focus on Industry 4.0. It is the stage that better contextualizes our topic of interest, IIoT.
How Is Industry 4.0 Serving the Manufacturing Industry?
As mentioned earlier, big data and analytics influence today’s operations with unique pragmatism. Hence, their implantation marked the beginning of the fourth industrial revolution (industry 4.0).
Industry 4.0 introduce the deployment of smart, self-sufficient devices and fit-for-purpose technologies to help teams add more value to their processes through:
- Agile and informed decision making,
- Increased productivity, safety and profitability, and
- Better maintenance performance.
All of these enhancements can be capitalized like never before with addition of IIoT tech to the operations. So, what exactly is IIoT? Let’s talk about it!
What Is IIoT? How Is It Different from IoT?
IIoT is an extension of the Internet of Things (IoT). A tech developed to enhance manufacturing through the disposition of smart sensors and actuators across industrial assets. Much like IoT, the industrial internet of things is a communication ecosystem for cloud-based processes fed by data exchanges. Despite the common ground shared by IoT and IIoT, they are different technologies that don’t overlap and are easily differentiated.
To better illustrate the disparities, picture the contrast between climate control devices for homes and industrial applications:
- Thermostats, adjustable lighting, smoke detectors, and smart locks are the standard go-to products for any home with enabled climate control. Homeowners monitor or adapt the climate conditions using Wi-Fi, Bluetooth, or a smartphone app. Sometimes, an SMS is enough.
- In an industrial complex, the settings are not as linear, and one type of solution doesn’t fit all. The kind of sensors used depends on the specific process. Requirements for climate control could imply the measure of different parameters such as emissions, noise, and vibrations. Operators watch over happenings through an HMI screen or an app. Stakes are high at industrial applications. Failed reads could threaten the health of workers and nearby communities. Reliability and 24/7 availability are a must!
In IIoT, devices engage in a Machine-to-Machine (M2M) communication protocol. Throughout, big data sharing and sophisticated machine learning tech come into place to analyze large datasets, identify patterns, and alert on uprising conditions. In return, engineers are more informed about their facilities and can adopt a proactive approach to solve issues timely and measuredly.
Technologies Enabling IIoT
- Artificial intelligence/machine learning: Both are brands of computer science. AI uses data and algorithms to learn how humans respond to specific scenarios. ML also happens to be a field of AI. It is developed to predict accurate outcomes without programming.
- Cyber security: A platform to secure the physical and communication path between connected and disconnected assets.
- Cloud computing: An IT system equipped with the infrastructure needed to perform accurate and real-time computing services, i.e., servers, software, databases, storage, and network, among others.
- Edge computing: It refers to the practice of capturing, storing, processing, and analyzing data close to the location where the data is generated, opposed to a centralized data-processing warehouse.
- Data mining and analytics: Convey the process of uncovering patterns and extracting actionable insights from the large pool of datasets stored by the enterprise.
These cutting edge techs work together as a seamless system to unleash new information and calls for action aimed at driving processing value and sparing losses.
- Enhanced productivity and scrap reduction: Access to a more detailed process visualization and clear statistical insights enable teams to manage facilities with agility and run predictive models that lower the defect rate through a proactive approach. So was the experience of this manufacturer, achieving a 21% scrap reduction.
- Better maintenance performance: Autonomous operations and process optimizations free teams to engage in better maintenance practices, deploying predictive models that lead to fewer incidents and a decrease in unplanned downtime. An example is Metso’s case study of mine operations.
- High efficiency and sustainability: Fully integrated assets under a single source of truth, real-time data, and AI analytics open the door to grander operational effectiveness empowered by better decision making and capacity to detect anomalies early, sparing production losses and harmful consequences. Read how cement manufacturer Holcim takes business to a new level.
The benefits, in their own way, drive savings and better profitability across enterprises. Just to put it into context, a Ball Mill mining application is currently seeing 5M euros in savings per site through the deployment of software apps, AI engines, and “soft sensor” technology that allows mining operation staff to access process variables and KPIs in near real-time. Regarding payback and implementation times, both were achieved under six months.
Contact Verdusco Consulting
- Email: Raul@VerduscoConsulting.com.
- Phone Number: 248-622-2850.