Banner Makes IIoT Simple and Accessible

The Industrial Internet of Things (IIoT) is defined as sensors, machines, tools and autonomous devices connected together to collect real-time data for industrial applications. For automated and semi-automated factory production, IIoT provides key insights to increase productivity, improve efficiency and reduce costs. This collected device data can be analyzed in the cloud or on edge computing platforms, allowing users to take actions with directly measurable value:

• optimizing production
• increasing operational efficiency
• reallocation of resources
• implement predictive maintenance
• reduction of energy consumption
• improving error prevention
• minimizing downtime
• managing costs

IIoT forms part of a complete technology ecosystem that benefits factory automation, assembly lines, logistics, transportation, distribution and other key elements of today’s manufacturing. At its core, it is a subset of the Internet of Things (IoT) – meaning physical devices and digital tools built to communicate with each other online – but with a particular focus on industry and the business benefits that can be achieved.

IIoT networks rely on online connections, cloud servers and software, but the hardware components of these systems should not be overlooked. Fortunately, Banner Engineering makes it possible not only to design customized IIoT-enabled automation systems, but also to upgrade existing manufacturing infrastructure for comprehensive IIoT implementation.

IoT is a key component of Industry 4.0 or the Fourth Industrial Revolution. It is a concept for modern manufacturing that harnesses the power of networked systems and data analytics to enable companies to make strategic, insight-driven business decisions. In essence, IIoT is what transforms factories into “smart” factories. The data captured can be used to accelerate and scale existing operations or even redefine business models to better serve customers and outpace competitors. The term also implies a certain urgency: if companies are too slow to adopt IIoT technology, they could find themselves left behind in the competitive global marketplace.

Meanwhile, a company that continuously collects and interprets data from its equipment can gain a distinct competitive advantage. It can monitor the speeds of automated processes to identify problems such as production bottlenecks, make relevant adjustments and fine-tune machine performance to eliminate inefficiencies and increase throughput. The data makes it easier to manage raw material quantities – a necessity, especially at a time when supply chains are disrupted – and can be used to determine more cost-effective logistics for packaging and distribution of finished products.

The benefits of IIoT integration range from advanced technology enhancements to discreet time savings. For example, robots equipped with sensors can collect information about themselves and their surroundings and then communicate that data. Also, tools or parts on inventory lists can be tracked online, reducing the time operators would normally spend searching for them(¹),

“According to Oxford Economics, the Industrial Internet of Things (IIoT) could impact sectors that account for 62% of GDP in G20 countries,” says Spanish multinational electricity company Iberdrola. “The application of IIoT in industry promises to be the biggest driver of productivity and innovation over the next decade. “(²), And of course, companies around the world are taking IIoT technology seriously and investing heavily in implementation. Over $300 billion was invested globally in manufacturing, transportation and energy applications in 2019, and this figure is expected to double by 2025.(³)

Another compelling argument for incorporating IIoT technology is that it allows companies to move beyond traditional planned preventive maintenance and instead implement informed predictive maintenance. By installing machine sensors to monitor factors such as vibration and temperature, factory operators can catch indicators that a key mechanism such as an engine may be showing signs of impending exhaustion or failure. If a failure occurs at the wrong time, it can cause a catastrophic loss in production time and expected revenue. Sensor data that identifies parts that require imminent maintenance is an extremely valuable insight because it gives the company the opportunity to plan the repair or replacement of these parts before they fail. The financial impact of predictive maintenance can be measured. McKinsey Global Institute reports the following:

We estimate that predictive maintenance can reduce maintenance costs of factory equipment by 10 to 40 percent. … Furthermore, better predictive maintenance using IoT can extend the useful life of machines, reducing equipment downtime by up to 50 percent and reducing equipment capital investment by 3 to 5 percent. These savings in manufacturing have a potential economic impact of around $630 billion per year in 2025.(⁴)

Sensors are now so commonplace in production automation that it is hard to imagine a factory without them. Most factories use many different types of sensors to count product quantities, schedule steps in an automated process or ensure optimal production conditions, but by their very nature, the electronic signals that sensors already transmit can be collected for insightful data analysis. Even a simple binary pulse from a sensor is a potential source of data that can be monitored to streamline operations. How often a photoelectric beam is interrupted (by products on a conveyor, for example) can be captured and recorded to calculate operating speeds, which can be adjusted to maximize productivity as part of a larger manufacturing process.

The types of data that sensors can capture are practically limitless. They can record quantities, volumes, distances, weights, dimensions, shapes, colors, positioning, temperatures, thermal activity, vibration, reflectivity, curvature, surface variations, material composition, response to sound waves, proximity to physical obstacles, visual or auditory information, texture patterns, steps in a programmed sequence and almost anything else. Any value a sensor can observe can be a data point, and any data point can be measured over time.

In this way, the whole philosophy of IIoT is part of the trend towards “Big Data” analytics to make insight-driven business decisions. Simply put, the more data manufacturers collect from their installed sensors, the more they understand about the capabilities of their own systems. They can leverage this “actionable” data to improve processes at any level of production. And these improvements can lead to leaner, more productive results, giving them a distinct fulfillment advantage over competitors.

IIoT and Industry 4.0 represent a major shift in manufacturing, and factories that delay development will likely face major competitive challenges in the future. Fortunately, adapting manufacturing to collect insightful machine data doesn’t have to be too difficult or costly. Whether you are revitalizing your existing plant or designing new factory processes from scratch, Banner is here to support you. It continues to build device solutions that enable you to transform your traditional manufacturing operation into a leaner and more productive IIoT-enabled smart factory. All with an agile, scalable and practical approach.