How the earth can be sustained is at the forefront of many discussions. It is also the reason many manufacturing companies are taking steps to help do their part with sustainable manufacturing practices. The U.S. Department of Commerce defines sustainable manufacturing as “the creation of manufactured products that use processes that minimize negative environmental impacts, conserve energy and natural resources, are safe for employees, communities, and consumers and are economically sound.”

A manufacturing operation will see benefits from implementing best practices for a sustainable manufacturing initiative. For example, the sustainable manufacturing practice of using materials that are non-hazardous or able to be recycled would lead to safe disposal. This would lower or eliminate containment fees, fines and penalties and would lead to reduced spending.

The next benefit is the positive environmental impact that sustainable manufacturing has. The sustainable manufacturing practice of using less energy, water and packaging will not only reduce waste generated but also preserve the environment.

In today’s world, social media makes it is easier than ever for customers to connect with businesses. Because of this, it is important for companies to maintain a positive brand image. Through transparency regarding sustainable manufacturing practices, the public can see a sustainable manufacturing company adopting environmental sustainability. This transparency enhances brand image for a company.

Using materials and inputs that are non-hazardous doesn’t just have a positive impact on a company’s cost spending. It also has a positive impact on the environment. The same can be said for the use of renewable energy. Energy efficient lighting lasts longer and requires less electricity to operate. With less electricity use, a company will cut spending on energy.

Sustainable manufacturing has many benefits for a company. It has proven practices and benefits that more and more companies have been embracing and implementing.

The manufacturing sector has typically been among the first to benefit from technological innovation, particularly in the field of robotics and automation. Traditional industrial robotic systems usually require the use of peripheral safety equipment for the safety of human co-workers. However, the features designed to protect human workers tend to increase cost and space requirements. It falls on manufacturers to find a solution that not only addresses these problems but also the need to provide solutions for customer needs quickly.

Collaborative robots (or cobots) help address existing challenges in work and manufacturing tasks by enabling human-robot collaboration (HRC) within the same workflow and common workspace. The HRC model combines the human ability to judge, react, and plan with a robot’s strength and repeatability of actions.

The use of collaborative robots in manufacturing provides the following benefits:

• Cobots can be reprogrammed during manufacturing changeovers using human-machine interfaces (HMIs).
• Cobots can handle repetitive, physically taxing and high-risk tasks.
• Cobots promote safety on the manufacturing floor.
• Cobots are more affordable and easier to operate and maintain.
• Cobots can detect nonstandard activity within their immediate work environment.
• Cobots are usually lightweight, making them easy to move where needed.
• Cobots help manufacturing companies achieve greater productivity.
• Cobots reduce strain on production employees.
• Cobots can help reduce costs and waste.

Collaborative robots in manufacturing function as assistants to workers. As robots handle repetitive and dangerous tasks, their human counterparts can focus on being creative and improving manufacturing processes. This arrangement also results in better attendance and performance as workers are happier and less stressed.

HRC is not about robots replacing humans. It’s a matter of realigning who does what. Cobots can work on automated processes, while their human partners can focus on analytical work and innovation. It’s an excellent formula that can substantially benefit manufacturing industries.

In today’s society, there aren’t many places to go to escape technology. It is a never-ending evolution. This is evident in how technological advancements have changed businesses operations. Digitalization, artificial intelligence and augmented reality are all trends that are affecting automation as they grow and evolve.

With digitalization comes the ability to convert information into digital form. This ability has allowed businesses to increase efficiency, reduce operational cost, and eliminate human error. Digitalization can be an extension of automation. Everything digitalization provides is in some way a form of automation.

With easier communication and more accessibility from digitalization, businesses have been able to expand and develop relationships across the globe. Companies can now have multiple locations in multiple states, or even locations in other countries. This allows companies to stay in touch and keep up to date with company protocols.

Artificial Intelligence is becoming more prevalent. Cell phones are in pockets, Alexa is in homes, and robotics are at work. Smart phones have given humans the ability to explore the internet, play a videogame, send emails, or make a phone call all on one device. Robots are placed on assembly lines to aid the creation of products. All these examples show how helpful and useful AI is to the human world.

Augmented Reality is another form of technology coming to the forefront to aid automation and businesses. Augmented reality transforms a physical environment into a captive and interactive virtual world.

The future of technology goes hand in hand with the future of automation. Technology makes things easier for humans. Why not take advantage of it? The future of automation is as bright as the future of technology. The more technology progresses the more automation will progress.

You may not realize it, but your interactions on the internet are being leveraged as the information sources used to make decisions in a variety of very clever software-based systems. Leading tech firms – such as Google and Netflix – regularly leverage user-specific search and activity data to feed algorithms that ultimately streamline and enhance customer deliverables. The result being that you gain an online experience customized to your tastes.

Interestingly, if we replace ‘user-specific data’ with ‘machine/process-specific data’ it quickly becomes clear that the same Big Data approach – coupled to machine learning – has the potential to revolutionize industry. The problem is that even simple manufacturing cells can generate huge amounts of data. So how do you make sense of it all and – more importantly – then use it to your advantage?

This is where AI and machine learning will step in. By distinguishing relevant data from noise, defining logical connections and correlations and removing any non-connectable data, AI can quickly provide pertinent information upon which decisions can be made. Feed it even more historical data and it will make even better decisions.

This isn’t a pipe dream either. AI and machine learning can be catered for, now, by any company running any solution. Indeed, adding data-gathering capabilities to even the ‘dumbest’ manufacturing operation is relatively straightforward and can be achieved with a very palatable financial outlay. In the very near future this data will (more than likely) be fed to subscription-based services that will securely collect, collate, translate and deploy solutions and answers that will not only allow users to make better decisions, but will also create the next industrial paradigm.

Luckily Big Data does not need big pockets. At RS Components, we already have many initiatives in place to both cater for the demands and exploit the benefits of the Big Data-driven manufacturing economy. Even the most basic manufacturing data – especially when leveraged intelligently – can make a huge difference and the path to adoption is already wide open and incredibly well supported for applications of any size, and at a sensible budget.

Editor's note: This is a sponsored blog post from RS Components.

Super temporal resolution microscopy (STReM), which uses a rotating phase mask to encode fast dynamics in each camera frame, allows scientists to view and gather useful information about fluorescing molecules at a frame rate 20x faster than typical lab cameras allow.

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