A client places an order for a custom-designed car. The order process has hardly been concluded, but production has already begun. The manufacturing process is being carried out by intelligent, autonomous machines that communicate with each other in real time and that coordinate the entire production process by themselves. Sounds like a vision of the future? Actually, it isn't. Welcome to the Industrial Internet of Things!
The current status of the Industrial Internet of Things
The full potential of this emerging development has by no means been reached. But one thing is clear, thanks to today's information and communications technologies, the fourth industrial revolution, as it is also known, is well and truly underway. New IT infrastructures have made it possible to interconnect production facilities, components and devices as never before. High-performance sensors can now retrieve and exchange data in real time. The result? Production processes are becoming much more agile and efficient.
And it is not just the production process that is changing. The Industrial Internet of Things is revolutionising the very way that businesses and stakeholders connect with each other. Staff members, clients, external personnel and partners will all have direct access to the production system. This itself presents one of the biggest challenges as different kinds of data from a diverse range of areas, hitherto kept separate from each other, need to be made compatible so that systems can communicate with each other. It goes without saying that data management has a very important role to play when it comes to achieving this.
The significance of the Industrial Internet of Things for maintenance personnel
The Industrial Internet of Things will introduce many new tasks to existing areas of work. It also gives companies better tools to develop themselves as businesses, optimise their processes and increase their efficiency. The area of maintenance provides an excellent example. A production facility that has been brought to a standstill due to malfunctioning or damaged equipment is the nightmare of every maintenance technician. However, such downtime could soon become a thing of the past. If elements of a production line are capable of registering when they are in need of maintenance or when they need to be replaced, and error patterns can be identified using the vast quantities of data now available, then predictive maintenance has been achieved. Predictive maintenance and maintenance of facilities has not only revolutionised the work environment of today's maintenance personnel, it is also radically changing their job description. We will now take a deeper look at this and other trends related to the Industrial Internet of Things.
Implementing smart maintenance means that your maintenance work has been transformed from being corrective to predictive. In order to recognise indicators of malfunctions or defects, however, a large quantity of different types of data needs to be extracted, collected and analysed.
Achieving this not only presents a real challenge for existing IT infrastructures, it also carries within itself new potential sources of error. It is only possible to carry out predictive action correctly when the data itself is accurate.
What happens if data is corrupted or goes missing? When such instances occur, the source of error needs to be quickly detected, monitored, and normal operations need to be restored with the minimum possible loss of data. Needless to say, complete documentation, robust version control, and automated backups are a must when it comes to enabling smooth disaster recovery. Clearly a job for today's cutting-edge data management.
Webcast series - free of charge
Version Control and Change Management for Automated Food & Beverage Production
In our 45-minutes webcast we will give you an overview on how food and beverage manufacturers can benefit from version control and change management software. We will show you how versiondog enables you to meet legal requirements for food safety and cybersecurity as well as how to reduce production downtime and manual work while improving process quality.