In the current context of Industry 4.0, improving efficiency is
Thanks to the Internet of Things (IoT), companies can collect more and more data. What we do with this data is what allows us to create efficiencies and improve productivity.
The Relationship Between IoT and Efficiency in the Industrial Sector
IoT allows us to collect reliable and safe real-time data and transform it into very useful information for businesses. This helps to reduce the consumption of resources to improve our efficiency and productivity.
In this sense, the Industrial Internet of Things (IIoT) is gaining a more solid position as it evolves, connecting machines and devices in strategic industries like agriculture, the manufacturing industry, logistics or energy production. In these sectors, continuous improvement and optimization of industrial processes are crucial. To achieve this, companies must maximize the knowledge they have at each of the points of their different processes. Thus, they can detect when inefficiencies, bottlenecks or excessive resource consumption are taking place. Thanks to this information, businesses can make reasoned business-driven decisions.
The Processes IoT Affects
Although it’s true that processes differ from one company to another, there is a series of common patterns in the industrial sector. In this article, we’re focusing on the processes corresponding to inventory management, manufacturing, and distribution. Through sensors located in warehouses, vehicles, machinery, premises, etc., the following data may be obtained:
- Data for inventory management. Collecting data on the internal location of the products and the kilometers traveled by the operators allows companies to reach an intelligent warehouse design. It may also be relevant to gather data on temperature, humidity, or solar exposure, as well as energy consumption in the warehouse to ensure efficient management of resources and prevention from damages in products. Also, companies will be able to plan orders and make accurate predictions based on stock levels and their analysis.
- Data on manufacturing. Having information about the manufacturing time implies knowing how long it takes the machines to start, how long they are in operation and how often production interruptions occur because of problems in the machinery. This allows companies to know and plan better the manufacturing, and to be able to serve faster and better to customers. When, in addition, we measure the number of defects produced by each volume of manufacture, we can save costs thanks to the possibility of implementing corrective measures and predictive maintenance. Also, if we quantify the energy consumption in the plant or the amount of waste produced in manufacturing, we can be more sustainable, which is key to achieve efficiency.
- Data for logistics management. If what we want is to optimize the logistics function, especially in freight transport functions, it will be necessary to obtain data from delivery vehicles, such as their GPS location, their cargo volume, and their downtime and delivery times. If in addition to this we add the data on the warehouse as the internal location of the products, the kilometers traveled by the operators and the number of orders, we’ll also have an integrated and efficient logistics management.
Once this data is collected and converted into information, companies can act in areas such as the following:
- Asset maintenance. Through maintenance alerts based on the predictions about the average time it takes for a machine or piece to fail. (This is what is known as predictive maintenance)
- Workforce management. Thanks to the information gathered, decisions can be made on how the personnel in the plant should be organized, the breaks they should make, etc.
- Plant organization. By rearranging goods and products in the warehouse, companies can reduce or optimize as much as possible the kilometers traveled by the workers or vehicles.
- Energy savings. By activating the lights only in those areas where it is necessary, controlling temperature and ventilation, etc.
- Logistics optimization. By having more information about routes, downtimes, number of orders, etc. Decisions on the number of vehicles that must be in operation at each moment, as well as their maintenance can be made.
These four areas are examples of how data obtained through sensors located at all points of the value chain can help create efficiencies to companies. However, the possibilities offered by IoT in the industrial sector are endless.
To explore these possibilities and exploit them to the fullest, companies cannot forget about taking care of cybersecurity. It’s necessary to have an IoT provider that can extract all this data reliably and safely, and thus avoid possible security failures, which would generate huge losses for the business.