We’re in the midst of a fourth industrial revolution driven by emerging tech like big data and analytics, autonomous robots, Industrial Internet of Things (IIoT) and the Cloud. These technologies actively transform the way manufacturers make and distribute products today—with massive potential to increase productivity in the near future. At the center of this industry-wide transformation: Artificial intelligence (AI).
A recent Forbes survey on AI found that 44 percent of respondents from the automotive and manufacturing sectors classified AI as “highly important” to their work in the next five years, while 49 percent said it was “absolutely critical to success.” Meanwhile, MIT and the Boston Consulting Group found that a gap exists between organizations’ AI ambitions and their ability to execute—with only one in five companies utilizing AI solutions in their work today. Despite the potential that AI holds for the manufacturing industry, many companies are slow to adopt the technology.
While oftentimes they understand the importance of adoption and the potential benefits, the transition is often too large a hurdle. The hurdle is more than just a financial and physical undertaking. McKinsey found that “many business leaders are uncertain about what exactly AI can do for them, where to obtain AI-powered applications, how to integrate them into their companies, and how to assess the return on an investment in the technology.” That said, manufacturing leaders shouldn’t submit to the complexity and opacity of AI—the technology’s benefits are numerous, decipherable, and will save businesses time and money.
AI Helps Lower Maintenance Costs and Increase Revenues
Unplanned downtime costs in manufacturing amount to around $50 billion annually, according to recent studies. However, as more manufacturers turn to AI and its predictive maintenance capabilities, that $50 billion in losses has the potential to be eliminated. Further, manufacturers now have the ability to monitor equipment and alert businesses of deviations from expected behavior by coupling machine sensors with AI and machine learning. This allows for early warning of any equipment and supply chain issues, saving businesses both time and money.
With AI-powered IoT systems, manufacturers can have real-time insight into how their products are doing. These systems can also alert manufacturers when they need to fix or replace equipment, allowing businesses and their customers to operate more proactively. When the AI tech predicts a failure may occur, maintenance requests will be automatically sent out. Technology-generated alerts can include anything from information on where the failure is, to how much time manufacturers have to remedy the issue.
Predictive maintenance has the ability to both reduce unplanned downtime saving businesses lots of money as well as extending the Remaining Useful Life (RUL) of their equipment. In fact, a recent McKinsey report found that AI-enhanced predictive maintenance of industrial equipment will lead to a 10 percent reduction in annual maintenance costs, up to 20 percent reduction in downtime, and 25 percent reduction in inspection costs.
AI Streamlines Manufacturing Processes and Increases Efficiency
In addition to enabling manufacturers to identify and fix maintenance issues, AI technologies can also streamline current processes and help manufacturers become significantly more efficient. Each year, manufacturers spend exorbitant amounts of money testing goods for quality—and scrapping batches that are deemed subpar. With AI, manufacturers can conduct root-cause analysis, reducing both testing and scrapping rates. Moreover, AI tech can collect and monitor products and machine data, helping companies detect problems faster and predict quality patterns. For manufacturers, this drives down costs, saves time, and reduces waste.
AI algorithms can also help manage factory floors, enabling manufacturers to find the most efficient path to move materials—minimizing both energy consumption and the need for quality reviews. AI can also be used for predictive scrapping of parts in assembly lines and scrapping defective parts as early as possible to avoid unnecessary work. As products and their shop environments change, AI technologies are able to analyze floor space availability and help plan future locations for crucial tools like production machines and inspection stations—ultimately helping manufacturers boost their bottom line.
Another challenge manufacturers face today is anticipating shifts in consumer demand. With AI, manufacturers can adjust their strategies and production to better meet demand for irregularly-demanded items, brand new products and sales promotions. As manufacturers incorporate AI into their strategies, they will be able to use the massive amounts of production data to better predict buying behaviors using real-time analytics and respond to customer demand.
The Time for Adoption Is Now
In order to stay competitive in today’s manufacturing industry, companies will need to take the plunge and invest in AI technologies sooner rather than later (read: now). The benefits of AI will only continue to grow from here, and will continue to transform every aspect of manufacturing—from design and production, to supply chain management and administration. The adoption and implementation of AI-driven systems will transform manufacturing into an industry built on data-driven strategies and proactive decisions, improving the way manufacturers operate, boost productivity, keep costs reasonable and ultimately, produce goods that improve customers’ lives.
Nicole Hardin is the Director of Product Management at Sage Software.