IoT in Industry

Industry IoT

IoT is part of the reason the term industry 4.0 is no longer a buzz word. Operation managers can reap the major benefits by streamlining crucial processes when it comes to predicting the arrival of materials, effectively locating and using power tools, predicting maintenance of these tools, and automatically checking the quality of final products.

The applications mentioned below may revolutionize specific processes within manufacturing, logistics, and retail. While some of these solutions are already viable for a small-scale operation, they are particularly beneficial to incorporate at a larger scale, as they often take human labor out of the equation, which improves consistency, reliability, and productivity. It saves human resources from spending time on mundane, repetitive tasks.

Streamlining quality management

Manufacturing is highly competitive. To keep up with the customer’s ever-increasing demand, faster, smarter, and flexible production lines may become the gold standard.

However, scaling up or streamlining quality control has always remained a challenge, and it has often remained the weakest (slowest) link in the production chain. These days, manufacturing plants are looking to automate manual inspection, which would greatly reduce human labor costs.

IoT-enabled devices play a crucial role in automatically determining whether there is an intolerable deviation from predetermined quality parameters. Combining different systems, such as high-definition camera vision systems with acoustic sensors and a powerful image processing software could be used to identify defects automatically.

Long term, AI could be applied to learn from all the feedback produced by these systems in order to adjust and improve the production process. These vision systems are already being actively used by manufacturers producing electronics (particularly smartphones), metal parts, and other consumer goods.

IoT-enabled power tools to improve the operator’s productivity and safety

Even a relatively small-scale manufacturing plant may contain hundreds of different tools and machines that need to be handled manually and are constantly being used.

Locating all these drills, torque wrenches, hammers, welders, and shears is always a challenge for factory managers, especially at a larger scale. With the use of IoT-sensors, we cannot only instantly locate every single tool, but also make sure the tools only function within preset parameters tailored towards the upcoming task. This drastically improves the productivity of operators, as they do not have to waste precious time locating or reconfiguring their tools.

Bosch and Airbus, two companies that heavily rely on efficient manufacturing, have pioneered the implementation of IoT into their operator tools with their Factory of the Future-Project.

The concepts of connected measuring, drilling and tightening tools can be applied across most steps of the manufacturing process. Airbus believes there is huge potential for improving their productivity by using “smart hand tools”.

Another aviation company, GE Aviation (a subsidiary of General Electric supplying engines to commercial aircraft) has recorded massive improvements in operator productivity through their Skylight on Glass project.

They developed a WiFi-enabled torque wrench that can be used to tighten bolts for routine maintenance and assembly tasks optimally. As such, errors during critical stages in the assembly process of engines can be eliminated.

A side-by-side study also demonstrated that mechanics were 8-11 % more productive during a routine assembly. The study team believes that the mechanics would become even more efficient once they have passed the learning curve for using such devices.

Optimizing existing supply chains

Events across a supply chain can be monitored in real-time using IoT-enabled devices, tracking different inputs and products. RFID tags and so-called beacons can be used to track a company’s inventory as it moves across the supply chain. Sensors could even detect harmful handling of parcels by measuring temperature, humidity, static discharge, or shock exposure.

Manufacturers gain more transparency and useful insights into their inventory and can set more realistic timelines for material availability. Using these large data-sets, manufacturers can pinpoint interdependencies, which can be used to optimize the manufacturing schedule.

A prime example of this technology is the cryptocurrency project, known as Waltonchain. It was launched to combat the challenges faced by supply chain management. Waltonchain wants to use RFID tags to provide transparency to various industries.

The ecosystem of this solution is being supported by the economy of the Waltonchain (WTC) coin. The project has already partnered with several large logistics companies and developed its own chip technology, thus decreasing its dependency on other companies.

Autonomous vehicles

While many people think of Tesla’s Model S when they read about autonomous vehicles, the benefits of this new technological milestone will extend far beyond the end-consumer.

The industrial applications of unmanned vehicles may seem endless: Whether it’s drones to survey construction sites, autonomous trucks to transport minerals from mine to port, or delivery vehicles that will never need a break.

The widespread adoption and efficacy of self-driving vehicles cannot be stopped and is already being extensively tested by many companies. The logistics sector is going to reap the benefits by integrating these solutions into their day-to-day business.

Autonomous vehicles will have IoT-devices installed at any corner, and as you may notice from other IoT applications that have an AI component: Smart integration of IoT-devices is the bread and butter of any smart analytics system (in this case, the car’s AI).

The real challenge of autonomous vehicles is not the gathering of datasets through IoT devices, but the correct interpretation of this data in order to make smart, safe and efficient decisions on the road. Ideally, this will minimize the risk of accidents, reduce operating costs, and help make road traffic more efficient and predictable.

Off the public road-grid, autonomous vehicles are already actively being used by some companies. In Norway, autonomous trucks made by Volvo are currently transporting limestone from an open-pit mine to a port five kilometers away.

Predictive maintenance

IoT sensors installed on machines can provide relevant maintenance data that informs the operation manager about a machine’s health and potential impending malfunction.

Tracking metrics, such as overall equipment effectiveness and overall process effectiveness, allows manufacturers to identify and face issues that may cause an unplanned downtime in the near future.

Realtime data about voltages, currents, temperatures, etc. allows operators to precisely evaluate the current condition of their machines. Thus the need for maintenance can be accurately predicted before a malfunction takes place, which helps to avoid disruptions in the production chain.