Despite the many indisputable advantages that information technology can bring to manufacturing processes, the sector has traditionally been slow to innovate. However, technologies ranging from artificial intelligence (AI) to advanced robotics and the internet of things (IoT) are starting to make an impact. We’re quickly heading towards an autonomous industry propelled by digital transformation.
While that might sound like science fiction, those manufacturing firms at the bleeding edge of innovation have already been running largely autonomous factories for well over a decade. In fact, there are now entire factories that are unmanned most of the time. Aside from the more obvious benefit of cutting costs, manufacturing firms are embracing information technology to boost quality and efficiency and improve conditions for their employees.
Resource planning and sourcing
Traditionally, factories have generated an enormous amount of waste. Once product designs have been finalized, producing goods at scale used to require a great deal of guesswork. Too many raw materials and you end up with excess waste. Too few, and you end up being unable to satisfy the increasing demands of your customers.
Today, everyone’s talking about lean manufacturing, in which parts and raw materials arrive as fast as they’re used. By adding data analytics and modern project management tools into the mix, manufacturing firms can now forecast future needs with greater accuracy than ever before. That means efficient sourcing and reduced manufacturing waste.
Continuous improvement through data analytics
Digital data is the driving force behind every informed business decision. Since every digital activity generates data, the sheer amount of information available to today’s organizations is skyrocketing. Data-driven insights can be used to improve operational efficiencies in every stage of the manufacturing process, from resource planning to assembly and delivery to the shop floor. By providing real-time information, data analytics foster a process and culture of continuous improvement, thereby saving costs, reducing the environmental impact, and boosting customer satisfaction.
Reducing human error with automation
People will always make mistakes, some of which include data entry errors, missed deadlines, and poor cybersecurity practices. Automation allows manufacturing firms to reduce human error by eliminating the need to carry out many of the more tedious, repetitive tasks that lead to burnout and decreased morale. Happier employees aren’t just more productive — they’re less likely to make mistakes and are freed up to take on more valuable tasks that require creative problem-solving.
Augmenting your workforce
New technologies can actually help improve workplace efficiency and safety. Rather than being about replacing employees with robots, it’s about establishing a synergy between the two in which technology empowers employees.
To that end, we can expect to see a dramatic rise in the use of augmented and virtual reality on the factory floor in the coming years. Augmented reality, for example, can help employees work with complicated machine environments that they wouldn’t ordinarily have the necessary skill sets to operate. Other wearable devices will help improve safety, and is fast heading towards becoming standard in more hazardous workplaces.
Improving research and development (R&D)
Mass production of any kind relies on complex planning, which is the most crucial stage of the manufacturing process. Although data analytics can provide enormous benefits in R&D, this is one stage where people retain a highly important role and will continue to do so for the foreseeable future. In fact, due to the specialized nature of R&D, the necessary skill sets can be hard to come by.
Fortunately, technology also has an answer to this problem in the form of online collaboration platforms, like Office 365, that enable R&D departments to connect with talent from around the world. Another technology that’s making an impact on R&D is 3D printing, which firms use for accelerating product development, optimizing resource usage, and determining what future products look like.