Increasingly, artificial intelligence (AI) predictive analytics is transforming the way the manufacturing industry operates. Its impact is being felt not just by the employees who work on factory floors but also by the executives in the enterprise’s C-suites.

AI predictive analytics is ushering in a new era of smart manufacturing, thanks to the convergence of an array of digital technologies such as low-cost sensors, advanced robotics, high-speed networks, real-time analytics, and embedded systems. This new age of futuristic factories has been termed Industry 4.0 as it’s the fourth major disruption in modern manufacturing.

Industry 4.0 is expected to cause massive upheavals in various manufacturing sectors. Some companies will embrace cognitive manufacturing and flourish. Others will be slow to adapt and lag behind.

Building the factory of the future

Manufacturers’ interest in AI analytics is rapidly increasing, with the availability of open source tools and a proliferation of cloud-based, AI-powered data analytics.

A Forbes Insights survey on AI found that 44 percent of respondents from the manufacturing and automotive industries said AI is “highly important” to their manufacturing function in the next five years. Moreover, nearly half of the respondents said AI is “absolutely critical to success1.”

Here are three ways manufacturers are revolutionizing their production processes:

Quality control

Large factories routinely employ hundreds or thousands of workers to spot defects in products, even in very small parts. An AI-powered machine equipped with a highly sensitive camera can spot the same defects as well as microscopic ones that are not visible to the human eye.

Using machine learning, these machine-vision tools are trained on a small set of samples and learn from what they observe. When the machine-vision tools notice a defect or problem, they send an alert. They can detect variations in raw materials, changes in machine behavior, and deviations from recipes, all of which helps improve quality control.

These increases in quality control translate into more efficient day-to-day operations. This in turn leads to fewer product returns and ultimately improvement in customer satisfaction and brand image.

Predictive maintenance

Unplanned maintenance costs manufacturers an estimated $50 billion each year, according to research2. Asset failure is responsible for 42 percent of this unwanted downtime.

Now, thanks to commodity sensors, digital twins (virtual versions of a physical machine), and AI predictive analytics, smart machines can produce real-time reports on their performance, enabling factory staff to perform proactive maintenance before a part, machine, or system falls into disrepair.

As a result, smart manufacturers can save valuable time and resources, especially labor costs and costs to repair or even replace mission-critical equipment. Plus, keeping your equipment properly maintained means you avoid potentially disruptive, and costly, downtime.

Supply chain optimization

AI analytics is improving how manufacturers manage their supply chain operations, from the factory floor to the trucks that deliver the goods, by making the entire process more seamless and efficient.

On a strategic level, AI predictive analytics is enabling executives to better understand the many factors that affect their supply chain and adjust their business operations accordingly. AI algorithms can help the C-suite develop data-based estimates of market demand by analyzing patterns that involve consumer behavior, socioeconomic factors, weather trends, political stability, and more.

As a result, manufacturers can adjust their staffing, inventory, and supply of raw materials to realize unprecedented levels of efficiency.

Get the help you need

One of the keys to a successful AI analytics strategy is effectively managing and controlling your factory equipment. Sprint Business’ Automation and Control solutions enable you to automatically keep track of your property, assets, and inventory around the clock, thanks to wireless sensor monitoring solutions.

Sensor technology and portal design such as that provided by Sprint deliver continual access to connected sensors on your equipment, enabling you to remotely manage and configure them from any internet-enabled mobile device.

1https://www.forbes.com/sites/insights-intelai/2018/07/17/how-ai-builds-a-better-manufacturing-process/#4564a8c11e84

2https://partners.wsj.com/emerson/unlocking-performance/how-manufacturers-can-achieve-top-quartile-performance/