Production challenges do not wait on IT developments, and getting to the root of a problem, or identifying the conditions that hinder smooth operation, does not always have to be rocket science.
Effective industrial data collection, aggregation and visualisation software has made it possible for manufacturers to gain insights into their processes.
With many industrial data strategies falling short, can industrial businesses achieve an effective data strategy?
COVID-19 has revolutionised all our lives. The next big challenge that the manufacturing sector faces is getting employees back to work, safely, and kick-starting production.
alk of Industry 4.0 has been useful in helping businesses understand the value of industrial automation and connectivity. But a lot of it is just hype, and many of the technologies are not being adopted as broadly or effectively as they could be.
This theme of increased data collection has become fossilised by modern automation, as well as health and safety standards, both of which rely on complete data handling to operate robotics and keep workers safe respectively.
Historian software systems, combined with thoroughly implemented monitoring equipment, collect data from every available variable on a production line.
There are many ways that unplanned downtime can negatively impact a business. In continuous process industries downtime causes produce to be lost. The costs of this further impact the bottom line, beyond just lost profits.
With an estimated seven billion IoT devices in the world, it’s not surprising that companies can generate overwhelming amounts of operational and environmental data, bringing with it the potential for substantial process improvement.
It’s no secret that data collection is important for generating valuable insight that helps plant managers improve efficiency in industrial systems. However, what seems unknown to many in the industry is the importance of understanding the context of the data being analysed
In the age of the industrial internet of things (IIoT), the speed of data analysis is key to effective operation. Edge computing accelerates this process, allowing for industrial data analysis to be performed at the point of collection.
Data is the most important raw material in industry. Yet few understand who owns it after it is created, or what rights they have while storing it. A lot of the issues that data ownership presents are not what they seem at first glance. We explain who owns what with regards to industrial data and explains what risks can arise and how to protect your business from them.
Novotek was part of the team of companies that initiated PC-based SCADA back in the 1980s. While it was revolutionary in the automation industry, plants have changed enormously since then, so SCADA systems must reflect this. The rise of the Internet of Things (IoT) means that there are far more connected devices around the plant, all of which need monitoring by SCADA systems.
When we think of virtual reality (VR), many of us still think back to the bulky, unflattering headsets found in video game arcades in the 1980s and 1990s. However, modern VR and augmented reality (AR) technology is more than a quirky arcade attraction, with it offering a wealth of benefits to food and beverage maintenance engineers.
NASA developed the first digital twinning project in the early days of space exploration to operate and maintain systems that were out of physical proximity. Digital twinning has advanced exponentially since then, with factories now able to duplicate their machines for better monitoring.
Throughout history and mythology, twins have been represented as counterparts; mirror images highlighted as having unique relationships and even their
While initially concerned at the impact of remote work mandated as part of COVID-19 safe working practices, many industrial leaders