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People are doing what they can to help the environment. However, creating an impact takes more than installing a solar panel or swapping to energy efficient light bulbs. Manufacturers should consider how making small, impactful changes in their facility can actually make a difference in the environment. 

Where do your products come from? Sometimes we only consider how far a product travelled from the warehouse to our front door. However, the journey from raw material to production, storage and delivery can cover several countries and continents, increasing carbon emissions and causing environmental issues.

When an obsolete component breaks, manufacturers might struggle to find a replacement. This is especially true in highly regulated sectors like pharmaceuticals or food processing, where like-for-like replacements are not an option and the exact same part has to be sourced. Second-hand parts might seem like a great solution, but they come with a variety of risks.

Evidence shows that components obsolescence is increasing rapidly. According to recent research by IHS Technology, in the year 2000 alone, component manufacturers issued 1,164 end-of-life (EOL) or product discontinuance notices, and the figure spiked to 5,506 by 2014. Though IHS forecasts that the number of such notices is going to decline, it’s always best to be prepared.

In the film Minority Report, the foreknowledge of three psychics is used to predict crimes and apprehend the future offenders, stopping the crimes before they occur. Predictive maintenance strategies are not too dissimilar to this, in that they stop problems before they arise, saving both time and money for the company.

In the classic film series Back to the Future, the risks and rewards of acting based on the knowledge of future events are explored through the adventures of Michael J. Fox’s Marty McFly.  Manufacturers can reap the rewards of predicting the future by using machine learning to implement a predictive maintenance strategy and save substantial amounts of time and money.

Unplanned machine downtime costs the world’s manufacturers over $50 billion a year, with a major cause of this being unexpected equipment failure. How can modern sensor networks reduce unplanned machine downtime in the manufacturing industry?

According to the 2019 Official Annual Cybercrime Report, a business falls victim to a ransomware attack every 14 seconds. As manufacturers connect more equipment to the Internet of Things, ransomware and other security breaches pose a more serious threat to productivity.

According to a study by the Ponemon Institute, UK companies lose an average of nearly £3 million for every data breach they experience. While manufacturers often struggle to guard against cybersecurity threats, automation can help them protect themselves by making processes more robust.

Until now, typically the worst threat that manufacturers faced from ransomware was the inconvenience of downtime and lost production while the company worked to get its systems back online using backups. Cyber attackers played a numbers game, relying on a small number of victims to pay the ransom. However, a new trend sees attackers leak the sensitive data if victims don’t pay.

To reduce their reliance on fossil fuels and minimise their carbon footprint, an increasing number of companies are implementing low-carbon microgrids. Just like traditional microgrids, low-carbon ones can help firms meet their energy demands without depending solely on the national grid. Unlike traditional solutions, however, these eco-friendly microgrids are almost zero-emission.

Some manufacturers are still recovering from the repercussions of the 2008 crisis, but economists predict that another global recession could impact industry in 2020. Meanwhile, natural disasters and global warming are proving that we need to do more to preserve our resources. In times of economic instability and environmental concerns, the idea of turning production scrap into usable energy is appealing to many manufacturers.

History teaches that energy transitions are not easy. For decades, whale oil was considered indispensable for a variety of applications, until it was gradually replaced by the cheaper and more efficient kerosene. This transition led to the extinction of industrial whaling, one of the world’s first multinational businesses.

There is rarely, if ever, a one-size-fits-all approach to manufacturing. It is important that site managers know what considerations to make when choosing an industrial robot to automate their processes.

To most people, man and machine seamlessly working hand-in-hand is like something out of a science fiction film. However, it is steadily becoming commonplace in the modern manufacturing facility. Here we examine the rise of collaborative robots in the manufacturing industry and considerations site managers must make when adopting them into their facility.

Over the last decade, manufacturers debated the pros and cons of traditional robots and cobots; often struggling to decide which to adopt in their facilities. Here we explore how the lines between the two will fade in the new decade, as each evolves and gains the benefit of the other.

The Condor Cluster was a supercomputer built out of 1,760 Sony PlayStation 3s running on the Linux operating system. Built to analyse high definition satellite imagery, the Condor Cluster was in operation for just a few months before Sony disabled the use of Linux on the PS3, leaving no means to procure functioning Linux replacement units.

Concorde was certainly ahead of its time, but some of the problems its designers encountered still exist today, such as those encountered when using commercial off-the-shelf products.